56 results
Search Results
2. Ten simple rules for reading a scientific paper
- Author
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William A. Petri, Kevin L Steiner, and Maureen A. Carey
- Subjects
Science and Technology Workforce ,Economics ,Social Sciences ,Scientific literature ,Careers in Research ,Key (music) ,Habits ,Learning and Memory ,Sociology ,Reading (process) ,Psychology ,Biology (General) ,media_common ,Simple (philosophy) ,Textbooks ,Ecology ,Library card ,Careers ,Publications ,Research Assessment ,Professions ,Editorial ,Computational Theory and Mathematics ,Modeling and Simulation ,Research Reporting Guidelines ,Educational Status ,Periodicals as Topic ,Employment ,QH301-705.5 ,Science Policy ,media_common.quotation_subject ,Research and Analysis Methods ,Education ,Cellular and Molecular Neuroscience ,Level of Effort ,Human Learning ,Genetics ,Mathematics education ,Learning ,Early career ,Molecular Biology ,Ecology, Evolution, Behavior and Systematics ,Publishing ,Behavior ,Research ,Cognitive Psychology ,Biology and Life Sciences ,Advice (programming) ,Reading ,Labor Economics ,People and Places ,Scientists ,Cognitive Science ,Population Groupings ,Undergraduates ,Neuroscience - Abstract
“There is no problem that a library card can't solve” according to author Eleanor Brown [1]. This advice is sound, probably for both life and science, but even the best tool (like the library) is most effective when accompanied by instructions and a basic understanding of how and when to use it. For many budding scientists, the first day in a new lab setting often involves a stack of papers, an email full of links to pertinent articles, or some promise of a richer understanding so long as one reads enough of the scientific literature. However, the purpose and approach to reading a scientific article is unlike that of reading a news story, novel, or even a textbook and can initially seem unapproachable. Having good habits for reading scientific literature is key to setting oneself up for success, identifying new research questions, and filling in the gaps in one’s current understanding; developing these good habits is the first crucial step. Advice typically centers around two main tips: read actively and read often. However, active reading, or reading with an intent to understand, is both a learned skill and a level of effort. Although there is no one best way to do this, we present 10 simple rules, relevant to novices and seasoned scientists alike, to teach our strategy for active reading based on our experience as readers and as mentors of undergraduate and graduate researchers, medical students, fellows, and early career faculty. Rules 1–5 are big picture recommendations. Rules 6–8 relate to philosophy of reading. Rules 9–10 guide the “now what?” questions one should ask after reading and how to integrate what was learned into one’s own science.
- Published
- 2020
3. Women are underrepresented in computational biology: An analysis of the scholarly literature in biology, computer science and computational biology.
- Author
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Bonham, Kevin S. and Stefan, Melanie I.
- Subjects
STEM education ,COMPUTATIONAL biology ,BIBLIOMETRICS ,SCIENCE publishing ,SCIENCE & state - Abstract
While women are generally underrepresented in STEM fields, there are noticeable differences between fields. For instance, the gender ratio in biology is more balanced than in computer science. We were interested in how this difference is reflected in the interdisciplinary field of computational/quantitative biology. To this end, we examined the proportion of female authors in publications from the PubMed and arXiv databases. There are fewer female authors on research papers in computational biology, as compared to biology in general. This is true across authorship position, year, and journal impact factor. A comparison with arXiv shows that quantitative biology papers have a higher ratio of female authors than computer science papers, placing computational biology in between its two parent fields in terms of gender representation. Both in biology and in computational biology, a female last author increases the probability of other authors on the paper being female, pointing to a potential role of female PIs in influencing the gender balance. [ABSTRACT FROM AUTHOR]
- Published
- 2017
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4. Ten Simple Rules for Writing a Literature Review.
- Author
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Pautasso, Marco
- Subjects
LITERATURE reviews ,BIBLIOGRAPHICAL citations ,RESEARCH ,PUBLISHING ,LITERARY research - Abstract
The author reflects on the simple rules for writing a literature review in scientific fields. He suggests the importance for scientists to rely on regular summaries of the recent literature as they cannot be expected to examine in detail every single new paper relevant to their interests. He cites the characteristics of a topic that are likely to lead to a literature review. He also advises the need to search and re-search the literature.
- Published
- 2013
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5. Ten simple rules for developing good reading habits during graduate school and beyond.
- Author
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Méndez, Marcos
- Subjects
READING ,HABIT formation ,COMPREHENSION ,HISTORY ,PERIODICALS ,BIBLIOGRAPHICAL citations - Abstract
The author talks about several rules that a person can follow to develop good reading habits in graduate school and beyond. Topics discussed include the importance of developing the habit of reading on a daily basis; the need to develop comprehension skills; and the need to study the history of one's discipline. Also mentioned are the importance of creating a list of relevant journals, the need to read books, and the benefits of using a reference manager.
- Published
- 2018
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6. Chemical features mining provides new descriptive structure-odor relationships.
- Author
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Licon, Carmen C., Bosc, Guillaume, Sabri, Mohammed, Mantel, Marylou, Fournel, Arnaud, Bushdid, Caroline, Golebiowski, Jerome, Robardet, Celine, Plantevit, Marc, Kaytoue, Mehdi, and Bensafi, Moustafa
- Subjects
ODORS ,COLOR vision ,PREDICTION models ,BIOLOGY ,ALGORITHMS - Abstract
An important goal in researching the biology of olfaction is to link the perception of smells to the chemistry of odorants. In other words, why do some odorants smell like fruits and others like flowers? While the so-called stimulus-percept issue was resolved in the field of color vision some time ago, the relationship between the chemistry and psycho-biology of odors remains unclear up to the present day. Although a series of investigations have demonstrated that this relationship exists, the descriptive and explicative aspects of the proposed models that are currently in use require greater sophistication. One reason for this is that the algorithms of current models do not consistently consider the possibility that multiple chemical rules can describe a single quality despite the fact that this is the case in reality, whereby two very different molecules can evoke a similar odor. Moreover, the available datasets are often large and heterogeneous, thus rendering the generation of multiple rules without any use of a computational approach overly complex. We considered these two issues in the present paper. First, we built a new database containing 1689 odorants characterized by physicochemical properties and olfactory qualities. Second, we developed a computational method based on a subgroup discovery algorithm that discriminated perceptual qualities of smells on the basis of physicochemical properties. Third, we ran a series of experiments on 74 distinct olfactory qualities and showed that the generation and validation of rules linking chemistry to odor perception was possible. Taken together, our findings provide significant new insights into the relationship between stimulus and percept in olfaction. In addition, by automatically extracting new knowledge linking chemistry of odorants and psychology of smells, our results provide a new computational framework of analysis enabling scientists in the field to test original hypotheses using descriptive or predictive modeling. [ABSTRACT FROM AUTHOR]
- Published
- 2019
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7. Ten simple rules for scientists: Improving your writing productivity.
- Author
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Peterson, Todd C., Kleppner, Sofie R., and Botham, Crystal M.
- Subjects
WORK environment ,SELF-talk - Abstract
An introduction to the journal is presented in which the editor discusses various reports in the issue on the topics including the importance of writing in science research, developing a working environment in workplace, and managing self talk about writing.
- Published
- 2018
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8. Ten simple rules for responsible referencing.
- Author
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Penders, Bart
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CITATION indexes ,CROSS references (Information retrieval) ,BIBLIOGRAPHICAL citations ,TRUTHFULNESS & falsehood ,CITATION analysis - Abstract
The author discusses 10 simple rules for responsible referencing. Topics discussed include citations for content of the publication and reading the publications of citations for quality and credibility of work; importance of self-citation in discussions of citations and evaluations of citation-based metrics; and evaluating citations in their rhetorical context and accepting differences in citation cultures across boundaries.
- Published
- 2018
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9. Ten simple rules for giving an effective academic job talk.
- Author
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Sura, Shayna A., Smith, Lauren L., Ambrose, Monique R., Amorim, C. Eduardo Guerra, Beichman, Annabel C., Gomez, Ana C. R., Juhn, Mark, Kandlikar, Gaurav S., Miller, Julie S., Mooney, Jazlyn, Mummah, Riley O., Lohmueller, Kirk E., and Lloyd-Smith, James O.
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JOB applications ,CAREER development ,EMPLOYMENT interviewing ,CONVERSATION ,RESEARCH grants ,JOB hunting - Published
- 2019
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10. Ten simple rules when considering retirement.
- Author
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Bourne, Philip E.
- Subjects
RETIREMENT ,COMPUTATIONAL biology ,BIOCOMPATIBILITY ,STEM education ,AUTOBIOGRAPHY - Abstract
The article presents author's comments on the rules that should be considered during retirement. It focuses on the retirement in computational biology. It offers information on autobiographical perspective on biomedical data. It focuses on the need for expertise in science, technology, engineering, and medicine (STEM).
- Published
- 2018
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11. Ten simple rules for drawing scientific comics.
- Author
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McDermott, Jason E., Partridge, Matthew, and Bromberg, Yana
- Subjects
COMIC books, strips, etc. ,SCIENTIFIC terminology ,SCIENTIFIC communication ,SCIENCE journalism ,SCIENTIFIC community - Abstract
The article presents guidelines for drawing scientific comics for efficient communication of difficult ideas. Suggestions mentioned include finding the right shapes for use in conveying the appropriate message one is trying to make, making one's comics simple to convey a complicated idea easier to understand, and taking time to ensure that the details in one's comics are right.
- Published
- 2018
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12. Ten simple rules for successfully completing a graduate degree in Latin America.
- Author
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Ruelas Inzunza, Ernesto, Salazar-Rivera, Gabriela I., Láinez, Magdiel, Ruiz-Gómez, María Guadalupe, Domínguez-Eusebio, Carlo A., Cristóbal-Sánchez, Griselda, Teodosio Faustino, Issaac A., Pérez-López, Edel, Campbell, Meagan L., Merfa, Marcus Vinicius, Latorre Beltrán, Ivonne Tatiana, Armas, Fernanda, and Mota-Vargas, Claudio
- Subjects
GRADUATE education ,LIFE science education ,LIFE sciences ,SCHOLARSHIPS ,EDUCATION - Abstract
This article offers tips for students to complete a graduate degree in biological sciences in Latin America. Topics discussed include the features that underlie the performance of graduate programs around the world, the importance of investigating the graduate program and the adviser, scholarship programs for graduate students, and the need to follow administrative procedures from admission to graduation.
- Published
- 2017
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13. Ten simple rules for getting the most out of a summer laboratory internship.
- Author
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Aicher, Toby P., Barabási, Dániel L., Harris, Benjamin D., Nadig, Ajay, and Williams, Kaitlin L.
- Subjects
INTERNSHIP programs ,LEARNING ,COMMUNICATION ,MENTORS ,SOCIAL interaction - Abstract
The author offers rules for getting the most out of a summer laboratory internship. The rules discussed include summer internships afford no such luxury which is important to optimize learning by working diligently and efficiently, productive stream of communication with mentor and internship has a programming course which can start learning computational skills. It mentions satisfying project, a supportive group, and unique social interactions.
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- 2017
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14. bigPint: A Bioconductor visualization package that makes big data pint-sized
- Author
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Dianne Cook and Lindsay Rutter
- Subjects
Big Data ,0301 basic medicine ,Science and Technology Workforce ,Source code ,Computer science ,Big data ,Datasets as Topic ,Gene Expression ,Molecular biology assays and analysis techniques ,Careers in Research ,Bioconductor ,Mathematical and Statistical Techniques ,0302 clinical medicine ,Computer graphics (images) ,Cluster Analysis ,Graphics ,Biology (General) ,Pseudocode ,media_common ,Nucleic acid analysis ,Ecology ,Software Engineering ,Genomics ,Research Assessment ,RNA analysis ,Reproducibility ,Professions ,Computational Theory and Mathematics ,Modeling and Simulation ,Engineering and Technology ,Research Article ,Computer and Information Sciences ,Science Policy ,QH301-705.5 ,media_common.quotation_subject ,Research and Analysis Methods ,03 medical and health sciences ,Cellular and Molecular Neuroscience ,Data visualization ,Interactivity ,Computer Graphics ,Genetics ,Hierarchical Clustering ,Molecular Biology ,Ecology, Evolution, Behavior and Systematics ,Sequence Analysis, RNA ,Software Tools ,business.industry ,Data Visualization ,Computational Biology ,Biology and Life Sciences ,Genome Analysis ,Visualization ,Molecular biology techniques ,030104 developmental biology ,People and Places ,Scientists ,Population Groupings ,business ,Software ,030217 neurology & neurosurgery - Abstract
Interactive data visualization is imperative in the biological sciences. The development of independent layers of interactivity has been in pursuit in the visualization community. We developed bigPint, a data visualization package available on Bioconductor under the GPL-3 license (https://bioconductor.org/packages/release/bioc/html/bigPint.html). Our software introduces new visualization technology that enables independent layers of interactivity using Plotly in R, which aids in the exploration of large biological datasets. The bigPint package presents modernized versions of scatterplot matrices, volcano plots, and litre plots through the implementation of layered interactivity. These graphics have detected normalization issues, differential expression designation problems, and common analysis errors in public RNA-sequencing datasets. Researchers can apply bigPint graphics to their data by following recommended pipelines written in reproducible code in the user manual. In this paper, we explain how we achieved the independent layers of interactivity that are behind bigPint graphics. Pseudocode and source code are provided. Computational scientists can leverage our open-source code to expand upon our layered interactive technology and/or apply it in new ways toward other computational biology tasks., Author summary Biological disciplines face the challenge of increasingly large and complex data. One necessary approach toward eliciting information is data visualization. Newer visualization tools incorporate interactive capabilities that allow scientists to extract information more efficiently than static counterparts. In this paper, we introduce technology that allows multiple independent layers of interactive visualization written in open-source code. This technology can be repurposed across various biological problems. Here, we apply this technology to RNA-sequencing data, a popular next-generation sequencing approach that provides snapshots of RNA quantity in biological samples at given moments in time. It can be used to investigate cellular differences between health and disease, cellular changes in response to external stimuli, and additional biological inquiries. RNA-sequencing data is large, noisy, and biased. It requires sophisticated normalization. The most popular open-source RNA-sequencing data analysis software focuses on models, with little emphasis on integrating effective visualization tools. This is despite sound evidence that RNA-sequencing data is most effectively explored using graphical and numerical approaches in a complementary fashion. The software we introduce can make it easier for researchers to use models and visuals in an integrated fashion during RNA-sequencing data analysis.
- Published
- 2020
15. IL6-mediated HCoV-host interactome regulatory network and GO/Pathway enrichment analysis
- Author
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Alfredo Benso and Gianfranco Politano
- Subjects
RNA viruses ,Proteomics ,0301 basic medicine ,Science and Technology Workforce ,Genes, Viral ,Coronaviruses ,Interaction Networks ,Ontology (information science) ,Betacoronavirus ,Coronavirus Infections ,Humans ,Interleukin-6 ,Pandemics ,Pneumonia, Viral ,Viral Proteins ,Gene Ontology ,Host-Pathogen Interactions ,Careers in Research ,Biochemistry ,Interactome ,0302 clinical medicine ,Medicine and Health Sciences ,Drug Interactions ,Viral ,Biology (General) ,Pathology and laboratory medicine ,Ecology ,Gene Ontologies ,Genomics ,Medical microbiology ,Nucleic acids ,Professions ,Computational Theory and Mathematics ,Modeling and Simulation ,Viruses ,Protein Interaction Networks ,SARS CoV 2 ,Pathogens ,Host (network) ,Network Analysis ,Research Article ,Computer and Information Sciences ,SARS coronavirus ,Coronavirus disease 2019 (COVID-19) ,Science Policy ,QH301-705.5 ,Systems biology ,Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) ,Computational biology ,Biology ,Research and Analysis Methods ,Microbiology ,03 medical and health sciences ,Cellular and Molecular Neuroscience ,Genetics ,Molecular Biology Techniques ,Non-coding RNA ,Molecular Biology ,Ecology, Evolution, Behavior and Systematics ,Life Scientists ,Pharmacology ,Natural antisense transcripts ,SARS-CoV-2 ,Gene Mapping ,Organisms ,Viral pathogens ,COVID-19 ,Biology and Life Sciences ,Computational Biology ,Pneumonia ,Pathway enrichment ,Genome Analysis ,Gene regulation ,Microbial pathogens ,MicroRNAs ,030104 developmental biology ,Genes ,People and Places ,RNA ,Scientists ,Population Groupings ,Gene expression ,030217 neurology & neurosurgery - Abstract
During these days of global emergency for the COVID-19 disease outbreak, there is an urgency to share reliable information able to help worldwide life scientists to get better insights and make sense of the large amount of data currently available. In this study we used the results presented in [1] to perform two different Systems Biology analyses on the HCoV-host interactome. In the first one, we reconstructed the interactome of the HCoV-host proteins, integrating it with highly reliable miRNA and drug interactions information. We then added the IL-6 gene, identified in recent publications [2] as heavily involved in the COVID-19 progression and, interestingly, we identified several interactions with the reconstructed interactome. In the second analysis, we performed a Gene Ontology and a Pathways enrichment analysis on the full set of the HCoV-host interactome proteins and on the ones belonging to a significantly dense cluster of interacting proteins identified in the first analysis. Results of the two analyses provide a compact but comprehensive glance on some of the current state-of-the-art regulations, GO, and pathways involved in the HCoV-host interactome, and that could support all scientists currently focusing on SARS-CoV-2 research., Author summary In this paper we provide data about the HCoV-host interactome that can be extracted from the integration of several public available databases. We used the initial interactome published by Zhou et al. and analyzed if there are already known and validated interactions. We also looked into possible known miRNAs and drugs interactions to suggest possible biomarker candidates and treatment options. We also performed a Gene Ontology and a Pathways enrichment analysis to understand which are the pathways most likely involved in the proteins targeted by SARS-CoV-2. This paper not only provides a set of validated and reliable data that could help researchers in their fight against the COVID-19 disease outbreak, but also demonstrates how Systems Biology can be effectively used to quickly gather preliminary but still significant data without resorting only to expensive lab experiments.
- Published
- 2020
16. Wisdom of crowds in computational biology.
- Author
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Papin, Jason A. and Mac Gabhann, Feilim
- Subjects
MEDICAL publishing ,MACHINE learning ,ARTIFICIAL intelligence in medicine ,COMPUTATIONAL biology ,INDIVIDUALIZED medicine - Abstract
The authors comment on the breadth of research published in the journal at the intersection of machine learning and health and biology. Topics covered include the application of machine learning to health and biology, the hope that data-driven strategies will lead to a richer understanding of biological mechanisms, and cross-journal initiatives aimed at exploring how disciplines can be brought together to tackle problems in computational biology and precision medicine.
- Published
- 2019
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17. Ten simple rules for providing optimal administrative support to research teams.
- Author
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Garrido, Romina, Trowbridge, Casandra A., and Tamura, Nana
- Subjects
RESEARCH teams ,ADMINISTRATIVE assistants ,SOCIAL learning ,PROFESSIONAL relationships ,SCIENTIFIC community ,CULTURAL pluralism ,HEBBIAN memory ,BUSINESS communication - Abstract
You can help your principal investigator on the oversight of grant rules and procedures, keeping protocols up to date, writing reports, and fulfilling requests from the Institutional Review Board (IRB). Regardless, what is important is for the administrator to be curious about science and make the effort to get a basic familiarity with the scientific discipline and academic working environment they are supporting. Although human resources, principal investigators, and lab managers are a large part of the onboarding process for a new employee, administrative staff are typically involved in the process as well. [Extracted from the article]
- Published
- 2019
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18. EMULSION: Transparent and flexible multiscale stochastic models in human, animal and plant epidemiology.
- Author
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Picault, Sébastien, Huang, Yu-Lin, Sicard, Vianney, Arnoux, Sandie, Beaunée, Gaël, and Ezanno, Pauline
- Subjects
PLANT epidemiology ,FOOD emulsions ,MULTISCALE modeling ,STOCHASTIC models ,EMULSIONS ,KNOWLEDGE representation (Information theory) ,PLANT capacity - Abstract
Stochastic mechanistic epidemiological models largely contribute to better understand pathogen emergence and spread, and assess control strategies at various scales (from within-host to transnational scale). However, developing realistic models which involve multi-disciplinary knowledge integration faces three major challenges in predictive epidemiology: lack of readability once translated into simulation code, low reproducibility and reusability, and long development time compared to outbreak time scale. We introduce here EMULSION, an artificial intelligence-based software intended to address those issues and help modellers focus on model design rather than programming. EMULSION defines a domain-specific language to make all components of an epidemiological model (structure, processes, parameters…) explicit as a structured text file. This file is readable by scientists from other fields (epidemiologists, biologists, economists), who can contribute to validate or revise assumptions at any stage of model development. It is then automatically processed by EMULSION generic simulation engine, preventing any discrepancy between model description and implementation. The modelling language and simulation architecture both rely on the combination of advanced artificial intelligence methods (knowledge representation and multi-level agent-based simulation), allowing several modelling paradigms (from compartment- to individual-based models) at several scales (up to metapopulation). The flexibility of EMULSION and its capability to support iterative modelling are illustrated here through examples of progressive complexity, including late revisions of core model assumptions. EMULSION is also currently used to model the spread of several diseases in real pathosystems. EMULSION provides a command-line tool for checking models, producing model diagrams, running simulations, and plotting outputs. Written in Python 3, EMULSION runs on Linux, MacOS, and Windows. It is released under Apache-2.0 license. A comprehensive documentation with installation instructions, a tutorial and many examples are available from: . [ABSTRACT FROM AUTHOR]
- Published
- 2019
- Full Text
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19. Perspective: Dimensions of the scientific method.
- Author
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Voit, Eberhard O.
- Subjects
SCIENTIFIC method ,SCIENTISTS ,SCIENCE & state ,MATHEMATICAL models ,KNOWLEDGE acquisition (Expert systems) ,GEOMETRIC shapes - Abstract
The scientific method has been guiding biological research for a long time. It not only prescribes the order and types of activities that give a scientific study validity and a stamp of approval but also has substantially shaped how we collectively think about the endeavor of investigating nature. The advent of high-throughput data generation, data mining, and advanced computational modeling has thrown the formerly undisputed, monolithic status of the scientific method into turmoil. On the one hand, the new approaches are clearly successful and expect the same acceptance as the traditional methods, but on the other hand, they replace much of the hypothesis-driven reasoning with inductive argumentation, which philosophers of science consider problematic. Intrigued by the enormous wealth of data and the power of machine learning, some scientists have even argued that significant correlations within datasets could make the entire quest for causation obsolete. Many of these issues have been passionately debated during the past two decades, often with scant agreement. It is proffered here that hypothesis-driven, data-mining–inspired, and “allochthonous” knowledge acquisition, based on mathematical and computational models, are vectors spanning a 3D space of an expanded scientific method. The combination of methods within this space will most certainly shape our thinking about nature, with implications for experimental design, peer review and funding, sharing of result, education, medical diagnostics, and even questions of litigation. [ABSTRACT FROM AUTHOR]
- Published
- 2019
- Full Text
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20. Bioinformatics in Jordan: Status, challenges, and future directions.
- Author
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Bani Baker, Qanita and Nuser, Maryam S.
- Subjects
BIOINFORMATICS ,COMPUTATIONAL biology ,SEQUENCE alignment ,EDUCATION research ,SCIENCE & state - Abstract
Bioinformatics plays a key role in supporting the life sciences. In this work, we examine bioinformatics in Jordan, beginning with the current status of bioinformatics education and research, then exploring the challenges of advancing bioinformatics, and finally looking to the future for how Jordanian bioinformatics research may develop. [ABSTRACT FROM AUTHOR]
- Published
- 2019
- Full Text
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21. Information-theoretic analysis of multivariate single-cell signaling responses.
- Author
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Jetka, Tomasz, Nienałtowski, Karol, Winarski, Tomasz, Błoński, Sławomir, and Komorowski, Michał
- Abstract
Mathematical methods of information theory appear to provide a useful language to describe how stimuli are encoded in activities of signaling effectors. Exploring the information-theoretic perspective, however, remains conceptually, experimentally and computationally challenging. Specifically, existing computational tools enable efficient analysis of relatively simple systems, usually with one input and output only. Moreover, their robust and readily applicable implementations are missing. Here, we propose a novel algorithm, SLEMI—statistical learning based estimation of mutual information, to analyze signaling systems with high-dimensional outputs and a large number of input values. Our approach is efficient in terms of computational time as well as sample size needed for accurate estimation. Analysis of the NF-κB single—cell signaling responses to TNF-α reveals that NF-κB signaling dynamics improves discrimination of high concentrations of TNF-α with a relatively modest impact on discrimination of low concentrations. Provided R-package allows the approach to be used by computational biologists with only elementary knowledge of information theory. [ABSTRACT FROM AUTHOR]
- Published
- 2019
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22. Think: Theory for Africa.
- Author
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Currin, Christopher B., Khoza, Phumlani N., Antrobus, Alexander D., Latham, Peter E., Vogels, Tim P., and Raimondo, Joseph V.
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SCIENTIFIC knowledge ,SOCIAL sciences education ,TECHNOLOGY ,COMPUTATIONAL neuroscience ,SCIENCE & state - Abstract
The article offers information on the challenging scientific problems faced by humanity. Topics discussed include information on the efforts to empower Africans to join the global neuroscience community; discussions on the BRAIN initiative in the U.S. and the Human Brain Project in Europe; and the information on the limiting factor for computational neuroscience development in Africa.
- Published
- 2019
- Full Text
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23. Models that learn how humans learn: The case of decision-making and its disorders.
- Author
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Dezfouli, Amir, Griffiths, Kristi, Ramos, Fabio, Dayan, Peter, and Balleine, Bernard W.
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DECISION making ,RECURRENT neural networks ,REINFORCEMENT learning ,MENTAL health ,PREDICTION models ,COMPUTER simulation - Abstract
Popular computational models of decision-making make specific assumptions about learning processes that may cause them to underfit observed behaviours. Here we suggest an alternative method using recurrent neural networks (RNNs) to generate a flexible family of models that have sufficient capacity to represent the complex learning and decision- making strategies used by humans. In this approach, an RNN is trained to predict the next action that a subject will take in a decision-making task and, in this way, learns to imitate the processes underlying subjects’ choices and their learning abilities. We demonstrate the benefits of this approach using a new dataset drawn from patients with either unipolar (n = 34) or bipolar (n = 33) depression and matched healthy controls (n = 34) making decisions on a two-armed bandit task. The results indicate that this new approach is better than baseline reinforcement-learning methods in terms of overall performance and its capacity to predict subjects’ choices. We show that the model can be interpreted using off-policy simulations and thereby provides a novel clustering of subjects’ learning processes—something that often eludes traditional approaches to modelling and behavioural analysis. [ABSTRACT FROM AUTHOR]
- Published
- 2019
- Full Text
- View/download PDF
24. Ten simple rules for providing a meaningful research experience to high school students.
- Author
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Lescak, Emily A., O’Neill, Kate M., Collu, Giovanna M., and Das, Subhamoy
- Subjects
RESEARCH ,HIGH school students ,MENTORING ,STEM education ,STEM occupations - Abstract
An editorial is presented on rules for providing a meaningful research experience to high school students. Topics discussed include ten rules for becoming an effective research mentor for high school students and their training, research opportunities as undergraduates and career consideration in science, technology, engineering, and mathematics and bridging the gap between scientists and the general public on scientific research.
- Published
- 2019
- Full Text
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25. Ten simple rules towards healthier research labs.
- Author
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Maestre, Fernando T.
- Subjects
SCHOLARS ,HEALTH ,PRIVATE investigators ,SCIENTISTS ,SCIENCE - Abstract
The negative effects of extremely competitive academic and research environments on the performance and health of researchers are well known and common worldwide. The prevalence of these effects, particularly among early career researchers, calls for a more humane and people-centered way of working within research labs. Although there is growing concern about the urgent need for a better life–work balance when doing science, there are not many examples about how this could be achieved in practice. In this article, I introduce 10 simple rules to make the working environment of research labs more nurturing, collaborative, and people-centered. These rules are directed towards existing and future principal investigators (PIs) but will be of interest to anyone working in a research lab and/or dealing with how to improve working conditions for scientists. [ABSTRACT FROM AUTHOR]
- Published
- 2019
- Full Text
- View/download PDF
26. Ten simple rules for organizing a webinar series.
- Author
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Fadlelmola, Faisal M., Panji, Sumir, Ahmed, Azza E., Ghouila, Amel, Akurugu, Wisdom A., Entfellner, Jean-Baka Domelevo, Souiai, Oussema, Mulder, Nicola, and null, null
- Subjects
WEBINARS ,COMMUNITIES ,AUDIENCES ,EMAIL ,SOCIAL media - Abstract
The article presents ten simple rules for hosting a regular webinar series with particular emphasis on resource-constrained communities like many in Africa. Topics include aligning a webinar theme to the expectations of the audience; settling on a convenient and user friendly webinar platform; and announcing webinars through mailing lists and social media platform.
- Published
- 2019
- Full Text
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27. Strategies and opportunities for promoting bioinformatics in Zimbabwe.
- Author
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Shoko, Ryman, Manasa, Justen, Maphosa, Mcebisi, Mbanga, Joshua, Mudziwapasi, Reagan, Nembaware, Victoria, Sanyika, Walter T., Tinago, Tawanda, Chikwambi, Zedias, Mawere, Cephas, Matimba, Alice, Mugumbate, Grace, Mufandaedza, Jonathan, Mulder, Nicola, and Patterton, Hugh
- Subjects
BIOINFORMATICS ,LIFE sciences ,HIV infections ,AIDS ,TUBERCULOSIS - Abstract
The article reviews progress made by scientists in bioinformatics and propose strategies for boosting bioinformatics capacity. It mentions information on Eastern Africa Network for Bioinformatics Training (EANBiT), which aims at developing practitioners who can develop and use bioinformatics approaches to biosciences. It presents use of biosciences in treating infectious diseases such as the human immunodeficiency virus/acquired immunodeficiency syndrome (HIV/AIDS), and tuberculosis (TB).
- Published
- 2018
- Full Text
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28. Wrangling distributed computing for high-throughput environmental science: An introduction to HTCondor.
- Author
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Erickson, Richard A., Fienen, Michael N., McCalla, S. Grace, Weiser, Emily L., Bower, Melvin L., Knudson, Jonathan M., and Thain, Greg
- Subjects
DISTRIBUTED computing ,BIOLOGISTS ,CLOUD computing ,OPEN source software ,COMPUTATIONAL biology - Abstract
Biologists and environmental scientists now routinely solve computational problems that were unimaginable a generation ago. Examples include processing geospatial data, analyzing -omics data, and running large-scale simulations. Conventional desktop computing cannot handle these tasks when they are large, and high-performance computing is not always available nor the most appropriate solution for all computationally intense problems. High-throughput computing (HTC) is one method for handling computationally intense research. In contrast to high-performance computing, which uses a single "supercomputer," HTC can distribute tasks over many computers (e.g., idle desktop computers, dedicated servers, or cloud-based resources). HTC facilities exist at many academic and government institutes and are relatively easy to create from commodity hardware. Additionally, consortia such as Open Science Grid facilitate HTC, and commercial entities sell cloud-based solutions for researchers who lack HTC at their institution. We provide an introduction to HTC for biologists and environmental scientists. Our examples from biology and the environmental sciences use HTCondor, an open source HTC system. [ABSTRACT FROM AUTHOR]
- Published
- 2018
- Full Text
- View/download PDF
29. Ten simple rules for writing a literature review
- Author
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Marco Pautasso
- Subjects
Science and Technology Workforce ,Web of science ,Computer science ,Science Policy ,Writing ,MEDLINE ,Guidelines as Topic ,Careers in Research ,Cellular and Molecular Neuroscience ,Citation analysis ,Genetics ,Molecular Biology ,lcsh:QH301-705.5 ,Ecology, Evolution, Behavior and Systematics ,Simple (philosophy) ,Ecology ,Research Assessment ,Data science ,Review Literature as Topic ,Systematic review ,Editorial ,Computational Theory and Mathematics ,Critical thinking ,lcsh:Biology (General) ,Science Education ,Modeling and Simulation ,Citation ,Publication Practices ,Primary research - Abstract
Literature reviews are in great demand in most scientific fields. Their need stems from the ever-increasing output of scientific publications [1]. For example, compared to 1991, in 2008 three, eight, and forty times more papers were indexed in Web of Science on malaria, obesity, and biodiversity, respectively [2]. Given such mountains of papers, scientists cannot be expected to examine in detail every single new paper relevant to their interests [3]. Thus, it is both advantageous and necessary to rely on regular summaries of the recent literature. Although recognition for scientists mainly comes from primary research, timely literature reviews can lead to new synthetic insights and are often widely read [4]. For such summaries to be useful, however, they need to be compiled in a professional way [5]. When starting from scratch, reviewing the literature can require a titanic amount of work. That is why researchers who have spent their career working on a certain research issue are in a perfect position to review that literature. Some graduate schools are now offering courses in reviewing the literature, given that most research students start their project by producing an overview of what has already been done on their research issue [6]. However, it is likely that most scientists have not thought in detail about how to approach and carry out a literature review. Reviewing the literature requires the ability to juggle multiple tasks, from finding and evaluating relevant material to synthesising information from various sources, from critical thinking to paraphrasing, evaluating, and citation skills [7]. In this contribution, I share ten simple rules I learned working on about 25 literature reviews as a PhD and postdoctoral student. Ideas and insights also come from discussions with coauthors and colleagues, as well as feedback from reviewers and editors.
- Published
- 2013
30. 2018 ISCB Overton Prize awarded to Cole Trapnell.
- Author
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Fogg, Christiana N., Kovats, Diane E., and Shamir, Ron
- Subjects
AWARD winners ,COMPUTATIONAL biology ,BIOLOGICAL societies - Abstract
The article announces that Dr. Cole Trapnell of University of Washington has received the Overton Prize from the International Society for Computational Biology (ISCB).
- Published
- 2018
- Full Text
- View/download PDF
31. Submit a Topic Page to PLOS Computational Biology and Wikipedia.
- Author
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Mietchen, Daniel, Wodak, Shoshana, Wasik, Szymon, Szostak, Natalia, and Dessimoz, Christophe
- Subjects
COMPUTATIONAL biology ,AUTHORS ,READERSHIP ,ORIGIN of life - Abstract
The article offers information on the periodical's `Topic Pages' project as a way to help fill important gaps in Wikipedia's coverage of computational biology content and to credit authors for their contributions. It mentions that hypercycle theory is now more accessible not only for advanced readers, but also for ordinary people who seek knowledge on the computational aspects of the origins of life.
- Published
- 2018
- Full Text
- View/download PDF
32. Eleven quick tips for running an interdisciplinary short course for new graduate students.
- Author
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Saunders, Timothy E., He, Cynthia Y., Koehl, Patrice, Ong, L. L. Sharon, and So, Peter T. C.
- Subjects
INTERDISCIPLINARY education ,GRADUATE students ,REASONING ,LIFE science education - Abstract
Quantitative reasoning and techniques are increasingly ubiquitous across the life sciences. However, new graduate researchers with a biology background are often not equipped with the skills that are required to utilize such techniques correctly and efficiently. In parallel, there are increasing numbers of engineers, mathematicians, and physical scientists interested in studying problems in biology with only basic knowledge of this field. Students from such varied backgrounds can struggle to engage proactively together to tackle problems in biology. There is therefore a need to establish bridges between those disciplines. It is our proposal that the beginning of graduate school is the appropriate time to initiate those bridges through an interdisciplinary short course. We have instigated an intensive 10-day course that brought together new graduate students in the life sciences from across departments within the National University of Singapore. The course aimed at introducing biological problems as well as some of the quantitative approaches commonly used when tackling those problems. We have run the course for three years with over 100 students attending. Building on this experience, we share 11 quick tips on how to run such an effective, interdisciplinary short course for new graduate students in the biosciences. [ABSTRACT FROM AUTHOR]
- Published
- 2018
- Full Text
- View/download PDF
33. Eleven quick tips for architecting biomedical informatics workflows with cloud computing.
- Author
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Cole, Brian S. and Moore, Jason H.
- Subjects
BIOINFORMATICS ,CLOUD computing ,MEDICAL research ,COMPUTER networks ,INFORMATION science - Abstract
Cloud computing has revolutionized the development and operations of hardware and software across diverse technological arenas, yet academic biomedical research has lagged behind despite the numerous and weighty advantages that cloud computing offers. Biomedical researchers who embrace cloud computing can reap rewards in cost reduction, decreased development and maintenance workload, increased reproducibility, ease of sharing data and software, enhanced security, horizontal and vertical scalability, high availability, a thriving technology partner ecosystem, and much more. Despite these advantages that cloud-based workflows offer, the majority of scientific software developed in academia does not utilize cloud computing and must be migrated to the cloud by the user. In this article, we present 11 quick tips for architecting biomedical informatics workflows on compute clouds, distilling knowledge gained from experience developing, operating, maintaining, and distributing software and virtualized appliances on the world’s largest cloud. Researchers who follow these tips stand to benefit immediately by migrating their workflows to cloud computing and embracing the paradigm of abstraction. [ABSTRACT FROM AUTHOR]
- Published
- 2018
- Full Text
- View/download PDF
34. Ten simple rules to create a serious game, illustrated with examples from structural biology.
- Author
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Baaden, Marc, Delalande, Olivier, Ferey, Nicolas, Pasquali, Samuela, Waldispühl, Jérôme, and Taly, Antoine
- Subjects
VIDEO games ,SCIENCE ,RULES ,TEACHING ,GAMES - Abstract
The article presents simple rules for developing serious scientific videogames. One rule is that the goal of the game should be defined in a clear way in terms of science and teaching. Another rule is that equilibrium has to be created between scientific accuracy and player accessibility. Another rule is that one should let the players interact with scientific data.
- Published
- 2018
- Full Text
- View/download PDF
35. The development and application of bioinformatics core competencies to improve bioinformatics training and education.
- Author
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Mulder, Nicola, Schwartz, Russell, Brazas, Michelle D., Brooksbank, Cath, Gaeta, Bruno, Morgan, Sarah L., Pauley, Mark A., Rosenwald, Anne, Rustici, Gabriella, Sierk, Michael, Warnow, Tandy, and Welch, Lonnie
- Subjects
BIOINFORMATICS ,SYSTEMS biology ,COMPUTATIONAL biology ,CORE competencies ,OCCUPATIONAL training - Abstract
Bioinformatics is recognized as part of the essential knowledge base of numerous career paths in biomedical research and healthcare. However, there is little agreement in the field over what that knowledge entails or how best to provide it. These disagreements are compounded by the wide range of populations in need of bioinformatics training, with divergent prior backgrounds and intended application areas. The Curriculum Task Force of the International Society of Computational Biology (ISCB) Education Committee has sought to provide a framework for training needs and curricula in terms of a set of bioinformatics core competencies that cut across many user personas and training programs. The initial competencies developed based on surveys of employers and training programs have since been refined through a multiyear process of community engagement. This report describes the current status of the competencies and presents a series of use cases illustrating how they are being applied in diverse training contexts. These use cases are intended to demonstrate how others can make use of the competencies and engage in the process of their continuing refinement and application. The report concludes with a consideration of remaining challenges and future plans. [ABSTRACT FROM AUTHOR]
- Published
- 2018
- Full Text
- View/download PDF
36. Assessing an effective undergraduate module teaching applied bioinformatics to biology students.
- Author
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Madlung, Andreas
- Subjects
BIOINFORMATICS ,BIOLOGY education ,BIOLOGY students ,BIOLOGY teachers ,TEACHING methods ,BIG data ,DATA analysis ,EDUCATION - Abstract
Applied bioinformatics skills are becoming ever more indispensable for biologists, yet incorporation of these skills into the undergraduate biology curriculum is lagging behind, in part due to a lack of instructors willing and able to teach basic bioinformatics in classes that don’t specifically focus on quantitative skill development, such as statistics or computer sciences. To help undergraduate course instructors who themselves did not learn bioinformatics as part of their own education and are hesitant to plunge into teaching big data analysis, a module was developed that is written in plain-enough language, using publicly available computing tools and data, to allow novice instructors to teach next-generation sequence analysis to upper-level undergraduate students. To determine if the module allowed students to develop a better understanding of and appreciation for applied bioinformatics, various tools were developed and employed to assess the impact of the module. This article describes both the module and its assessment. Students found the activity valuable for their education and, in focus group discussions, emphasized that they saw a need for more and earlier instruction of big data analysis as part of the undergraduate biology curriculum. [ABSTRACT FROM AUTHOR]
- Published
- 2018
- Full Text
- View/download PDF
37. Ten simple rules for biologists learning to program.
- Author
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Carey, Maureen A. and Papin, Jason A.
- Subjects
BIOLOGISTS ,COMPUTERS in biology ,SCIENTIFIC computing ,PROGRAMMING languages ,COMPUTER programmers - Abstract
The article discusses the rules for biologists to acquire a computational skill set. These include selecting the programming language that suits one's goals, applying critical thinking and problem solving skills in each task, as well as asking for technical support from a community of programmers for a certain scientific application.
- Published
- 2018
- Full Text
- View/download PDF
38. MAGPIE: Simplifying access and execution of computational models in the life sciences.
- Author
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Baldow, Christoph, Salentin, Sebastian, Schroeder, Michael, Roeder, Ingo, and Glauche, Ingmar
- Subjects
LIFE sciences ,COMPUTER simulation ,SYSTEMS biology ,COMPUTATIONAL biology ,VIRTUAL machine systems - Abstract
Over the past decades, quantitative methods linking theory and observation became increasingly important in many areas of life science. Subsequently, a large number of mathematical and computational models has been developed. The BioModels database alone lists more than 140,000 Systems Biology Markup Language (SBML) models. However, while the exchange within specific models classes has been supported by standardisation and database efforts, the generic application and especially the re-use of models is still limited by practical issues such as easy and straight forward model execution. MAGPIE, a odeling and nalysis eneric latform with ntegrated valuation, closes this gap by providing a software platform for both, publishing and executing computational models without restrictions on the programming language, thereby combining a maximum on flexibility for programmers with easy handling for non-technical users. MAGPIE goes beyond classical SBML platforms by including all models, independent of the underlying programming language, ranging from simple script models to complex data integration and computations. We demonstrate the versatility of MAGPIE using four prototypic example cases. We also outline the potential of MAGPIE to improve transparency and reproducibility of computational models in life sciences. A demo server is available at magpie.imb.medizin.tu-dresden.de. [ABSTRACT FROM AUTHOR]
- Published
- 2017
- Full Text
- View/download PDF
39. Ten simple rules for writing a career development award proposal.
- Author
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Botham, Crystal M., Arribere, Joshua A., Brubaker, Sky W., and Beier, Kevin T.
- Subjects
GRANT writing ,CAREER development ,GRANTS (Money) ,AUTHORSHIP ,MENTORING in the professions ,MENTORING - Abstract
The article presents rules for writing a proposal for a career development grant. Applicants are advised to have three months of full-time effort for completing the application, to use the review criteria as a guide for writing a proposal and to write a clear and concise proposal. The importance of having a mentoring team during the proposed funding program is discussed.
- Published
- 2017
- Full Text
- View/download PDF
40. Machine learning to design integral membrane channelrhodopsins for efficient eukaryotic expression and plasma membrane localization.
- Author
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Bedbrook, Claire N., Yang, Kevin K., Rice, Austin J., Gradinaru, Viviana, and Arnold, Frances H.
- Subjects
MACHINE learning ,EUKARYOTIC cells ,CELL membranes ,MEMBRANE proteins ,PROTEIN expression ,CHIMERISM ,PROTEIN structure ,GAUSSIAN processes - Abstract
There is growing interest in studying and engineering integral membrane proteins (MPs) that play key roles in sensing and regulating cellular response to diverse external signals. A MP must be expressed, correctly inserted and folded in a lipid bilayer, and trafficked to the proper cellular location in order to function. The sequence and structural determinants of these processes are complex and highly constrained. Here we describe a predictive, machine-learning approach that captures this complexity to facilitate successful MP engineering and design. Machine learning on carefully-chosen training sequences made by structure-guided SCHEMA recombination has enabled us to accurately predict the rare sequences in a diverse library of channelrhodopsins (ChRs) that express and localize to the plasma membrane of mammalian cells. These light-gated channel proteins of microbial origin are of interest for neuroscience applications, where expression and localization to the plasma membrane is a prerequisite for function. We trained Gaussian process (GP) classification and regression models with expression and localization data from 218 ChR chimeras chosen from a 118,098-variant library designed by SCHEMA recombination of three parent ChRs. We use these GP models to identify ChRs that express and localize well and show that our models can elucidate sequence and structure elements important for these processes. We also used the predictive models to convert a naturally occurring ChR incapable of mammalian localization into one that localizes well. [ABSTRACT FROM AUTHOR]
- Published
- 2017
- Full Text
- View/download PDF
41. Unmet needs for analyzing biological big data: A survey of 704 NSF principal investigators.
- Author
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Barone, Lindsay, Williams, Jason, and Micklos, David
- Subjects
BIG data ,DATA analysis ,LIFE sciences ,BIOINFORMATICS ,HIGH performance computing ,DATA integration ,INFORMATION resources management - Abstract
In a 2016 survey of 704 National Science Foundation (NSF) Biological Sciences Directorate principal investigators (BIO PIs), nearly 90% indicated they are currently or will soon be analyzing large data sets. BIO PIs considered a range of computational needs important to their work, including high performance computing (HPC), bioinformatics support, multistep workflows, updated analysis software, and the ability to store, share, and publish data. Previous studies in the United States and Canada emphasized infrastructure needs. However, BIO PIs said the most pressing unmet needs are training in data integration, data management, and scaling analyses for HPC—acknowledging that data science skills will be required to build a deeper understanding of life. This portends a growing data knowledge gap in biology and challenges institutions and funding agencies to redouble their support for computational training in biology. [ABSTRACT FROM AUTHOR]
- Published
- 2017
- Full Text
- View/download PDF
42. Ten simple rules in considering a career in academia versus government.
- Author
-
Bourne, Philip E.
- Subjects
ACADEMIC employment ,CIVIL service positions ,VOCATIONAL guidance ,VOCATIONAL interests ,DECISION making - Abstract
The author reflects on rules to be followed while making a career decision, which includes selection of career between academic research based career and the non-research government career. He states that both the work environments have a very large scope if chosen as career. The similarities and differences between the two fields is presented from the author's point of view.
- Published
- 2017
- Full Text
- View/download PDF
43. Ten simple rules to make the most out of your undergraduate research career.
- Author
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Yu, Megan and Kuo, Yu-Min
- Subjects
RESEARCH ,UNDERGRADUATES ,CAREER development ,MASSIVE open online courses ,RESEARCH personnel - Abstract
The article discusses several rules for undergraduates to help them intellectually enrich their research experiences, in view of benefits of research in undergraduate education, and their struggle in understanding purpose of work. Topics include need for undergraduates to start early to explore research interests and goals for career; having a background knowledge in the research area using resources like Massive Open Online Courses; and having positive relationships with research colleagues.
- Published
- 2017
- Full Text
- View/download PDF
44. Ten Simple Rules for Developing a Successful Research Proposal in Brazil.
- Author
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de Oliveira, Dyoni M., Buckeridge, Marcos S., and dos Santos, Wanderley D.
- Subjects
RESEARCH grants ,FEDERAL aid to research ,ACADEMIC degrees ,DOCTORAL degree ,SCHOLARSHIPS - Abstract
The article describes the ten rules for the development of a successful research grant proposal and MSc and PhD degree fellowships. Topics include defining the problem clearly, formulating falsifiable hypotheses and including preliminary data, and establishing clear objectives. Also suggested is carefully estimating the duration and requirements of experimental procedures.
- Published
- 2017
- Full Text
- View/download PDF
45. Continuing Education Workshops in Bioinformatics Positively Impact Research and Careers.
- Author
-
Brazas, Michelle D. and Ouellette, B. F. Francis
- Subjects
BIOINFORMATICS ,INFORMATION science ,COMPUTERS in biology ,CONTINUING education ,ADULT education workshops - Abstract
Bioinformatics.ca has been hosting continuing education programs in introductory and advanced bioinformatics topics in Canada since 1999 and has trained more than 2,000 participants to date. These workshops have been adapted over the years to keep pace with advances in both science and technology as well as the changing landscape in available learning modalities and the bioinformatics training needs of our audience. Post-workshop surveys have been a mandatory component of each workshop and are used to ensure appropriate adjustments are made to workshops to maximize learning. However, neither bioinformatics.ca nor others offering similar training programs have explored the long-term impact of bioinformatics continuing education training. Bioinformatics.ca recently initiated a look back on the impact its workshops have had on the career trajectories, research outcomes, publications, and collaborations of its participants. Using an anonymous online survey, bioinformatics.ca analyzed responses from those surveyed and discovered its workshops have had a positive impact on collaborations, research, publications, and career progression. [ABSTRACT FROM AUTHOR]
- Published
- 2016
- Full Text
- View/download PDF
46. Principles for data analysis workflows
- Author
-
Váleri N. Vásquez, Ciera C. Martinez, and Sara Stoudt
- Subjects
FOS: Computer and information sciences ,Data Analysis ,0301 basic medicine ,Science and Technology Workforce ,Economics ,Computer science ,Social Sciences ,Design elements and principles ,Careers in Research ,Workflow ,Computer Science - Computers and Society ,0302 clinical medicine ,Biology (General) ,Data Management ,Careers ,Ecology ,Software Development ,Software Engineering ,Research Assessment ,Reproducibility ,Professions ,Computational Theory and Mathematics ,Modeling and Simulation ,Engineering and Technology ,Raw data ,Employment ,Computer and Information Sciences ,Science Policy ,Process (engineering) ,QH301-705.5 ,Research and Analysis Methods ,Phase (combat) ,Education ,Computer Software ,03 medical and health sciences ,Cellular and Molecular Neuroscience ,Computers and Society (cs.CY) ,Genetics ,Humans ,Molecular Biology ,Ecology, Evolution, Behavior and Systematics ,Software Tools ,business.industry ,Data Science ,Software development ,Computational Biology ,Data science ,030104 developmental biology ,Labor Economics ,People and Places ,Scientists ,Population Groupings ,business ,Software ,030217 neurology & neurosurgery - Abstract
A systematic and reproducible “workflow”—the process that moves a scientific investigation from raw data to coherent research question to insightful contribution—should be a fundamental part of academic data-intensive research practice. In this paper, we elaborate basic principles of a reproducible data analysis workflow by defining 3 phases: the Explore, Refine, and Produce Phases. Each phase is roughly centered around the audience to whom research decisions, methodologies, and results are being immediately communicated. Importantly, each phase can also give rise to a number of research products beyond traditional academic publications. Where relevant, we draw analogies between design principles and established practice in software development. The guidance provided here is not intended to be a strict rulebook; rather, the suggestions for practices and tools to advance reproducible, sound data-intensive analysis may furnish support for both students new to research and current researchers who are new to data-intensive work.
- Published
- 2021
47. 2018 outstanding contributions to ISCB award: Russ Altman.
- Author
-
Fogg, Christiana N., Kovats, Diane E., and Shamir, Ron
- Subjects
MOLECULAR biology ,COMPUTATIONAL biology ,AWARDS ,BIOLOGICAL societies - Abstract
The article announces that Professor Russ Altman is the 2018 winner of the Outstanding Contributions to International Society for Computational Biology (ISCB) Award and will be recognized at the 2018 Intelligent Systems for Molecular Biology (ISMB) meeting in Chicago, Illinois in July 208.
- Published
- 2018
- Full Text
- View/download PDF
48. Ten simple rules for partnering with K-12 teachers to support broader impact goals
- Author
-
Louise S. Mead, Kristin M. Bass, Alexa Warwick, Frieda Reichsman, and Angela Kolonich
- Subjects
0301 basic medicine ,Evolutionary Genetics ,Science and Technology Workforce ,Biomedical Research ,Social Sciences ,Careers in Research ,Science education ,0302 clinical medicine ,Learning and Memory ,Sociology ,ComputingMilieux_COMPUTERSANDEDUCATION ,Psychology ,Cooperative Behavior ,Biology (General) ,Grade level ,Simple (philosophy) ,Schools ,Ecology ,Professional development ,Research Personnel ,Professions ,Science research ,Editorial ,Computational Theory and Mathematics ,Modeling and Simulation ,Physical Sciences ,Educational Status ,Engineering ethics ,Human learning ,Science Policy ,QH301-705.5 ,Science ,Materials Science ,Schoolchildren ,Biology ,Education ,03 medical and health sciences ,Cellular and Molecular Neuroscience ,Human Learning ,Genetics ,Humans ,Learning ,Molecular Biology ,Ecology, Evolution, Behavior and Systematics ,Evolutionary Biology ,Cognitive Psychology ,Biology and Life Sciences ,Teachers ,030104 developmental biology ,Science Education ,People and Places ,Cognitive Science ,Scientists ,Population Groupings ,School Teachers ,030217 neurology & neurosurgery ,Professional expertise ,Neuroscience - Abstract
Contributing to broader impacts is an important aspect of scientific research. Engaging practicing K-12 teachers as part of a research project can be an effective approach for addressing broader impacts requirements of grants, while also advancing researcher and teacher professional growth. Our focus is on leveraging teachers' professional expertise to develop science education materials grounded in emerging scientific research. In this paper, we describe ten simple rules for planning, implementing, and evaluating teacher engagement to support the broader impact goals of your research project. These collaborations can lead to the development of instructional materials or activities for students in the classroom or provide science research opportunities for teachers. We share our successes and lessons learned while collaborating with high school biology teachers to create technology-based, instructional materials developed from basic biological research. The rules we describe are applicable across teacher partnerships at any grade level in that they emphasize eliciting and respecting teachers' professionalism and expertise.
- Published
- 2020
49. Ten simple rules for giving an effective academic job talk
- Author
-
Lauren L. Smith, Ana C. R. Gomez, Gaurav S. Kandlikar, Shayna A. Sura, Julie S. Miller, Monique Ambrose, Mark Juhn, Jazlyn A. Mooney, James O. Lloyd-Smith, Annabel C. Beichman, Kirk E. Lohmueller, C. Eduardo Guerra Amorim, and Riley O. Mummah
- Subjects
0301 basic medicine ,Science and Technology Workforce ,Economics ,Social Sciences ,Careers in Research ,Graduates ,0302 clinical medicine ,Simple (abstract algebra) ,Reading (process) ,Biology (General) ,Workplace ,media_common ,Careers ,Ecology ,4. Education ,Biological Evolution ,Faculty ,Los Angeles ,Test (assessment) ,Professions ,Editorial ,Computational Theory and Mathematics ,Research Design ,Modeling and Simulation ,Educational Status ,Psychology ,Employment ,Process (engineering) ,QH301-705.5 ,Science Policy ,media_common.quotation_subject ,Research Grants ,Jobs ,Research and Analysis Methods ,Job market ,Research Funding ,03 medical and health sciences ,Cellular and Molecular Neuroscience ,Genetics ,Humans ,Education, Graduate ,Students ,Molecular Biology ,Ecology, Evolution, Behavior and Systematics ,Medical education ,Evolutionary Biology ,ComputingMilieux_THECOMPUTINGPROFESSION ,Biology and Life Sciences ,Computational Biology ,Variety (linguistics) ,Work Engagement ,030104 developmental biology ,Labor Economics ,People and Places ,Job Application ,Position (finance) ,Scientists ,Population Groupings ,030217 neurology & neurosurgery ,Strengths and weaknesses - Abstract
You’ve finally completed your dissertation research and have your PhD in hand—yay! Maybe you’re also in the middle of a postdoctoral position. If you’re reading this article, chances are you are actively searching for and applying for faculty positions. (Check out reference [1] if you’re early in the application process and [2] for additional advice!) Unfortunately, many graduate students and postdocs are not taught the skills necessary for acquiring a faculty position after passing the “looks good on paper” part of the application and securing an on-campus interview. One of the last crucial steps in earning a faculty position is your academic job talk. No matter how great of a scientist you are, if you cannot give a compelling job talk, chances are low that you will be hired. Yet many candidates receive little guidance on how to ace this unique and vital test. To help address this gap, we have put together these ten simple rules that will help you give an effective job talk. To be clear, these are rules developed for the academic job talk in a research-heavy department, which is typically in a seminar format. These rules are not targeted toward other formats such as chalk talks or teaching demonstrations, although some pointers may still apply. We are a group primarily composed of University of California, Los Angeles (UCLA) faculty, postdocs, and graduate students who participated in two recent job searches in the Ecology and Evolutionary Biology Department. We evaluated ten job talks over the span of 2 months and discussed their strengths and weaknesses in a weekly seminar course. These ten rules are based on our discussions of what worked (and what didn’t) across the variety of job talks we observed, as well as our various experiences on the job market and search committees over the years.
- Published
- 2019
50. Ten simple rules for hosting artists in a scientific lab
- Author
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Karine Bonneval, India Mansour, Matthias C. Rillig, Johannes Lehmann, Saša Spačal, Regine Rapp, Christian de Lutz, and Vera Meyer
- Subjects
0301 basic medicine ,Science and Technology Workforce ,Biomedical Research ,Culture ,Social Sciences ,Mindset ,Human learning ,Careers in Research ,The arts ,Creativity ,Learning and Memory ,0302 clinical medicine ,Sociology ,Realm ,Psychology ,Biology (General) ,Language ,media_common ,Career Choice ,Ecology ,Appreciative listening ,Personal development ,Professions ,Editorial ,Computational Theory and Mathematics ,Modeling and Simulation ,Engineering ethics ,Art ,Computer and Information Sciences ,Science Policy ,QH301-705.5 ,Science ,media_common.quotation_subject ,Context (language use) ,03 medical and health sciences ,Cellular and Molecular Neuroscience ,ddc:570 ,Genetics ,Openness to experience ,Learning ,Humans ,Molecular Biology ,Ecology, Evolution, Behavior and Systematics ,Computers ,business.industry ,Government funding of science ,Cognitive Psychology ,Biology and Life Sciences ,500 Naturwissenschaften und Mathematik::570 Biowissenschaften ,Biologie::570 Biowissenschaften ,Biologie ,Research funding ,030104 developmental biology ,People and Places ,Cognitive Science ,Scientists ,Population Groupings ,Interdisciplinary Communication ,business ,030217 neurology & neurosurgery ,Neuroscience - Abstract
Hosting an artist in a scientific lab is likely a new experience for many scientists in the natural and engineering sciences, and perhaps also for many artists, yet it can be a very beneficial experience for both parties [1]. “Art and science are in a tension that is most fruitful when these disciplines observe and penetrate each other and experience how much of the other they themselves still contain” [2]. During our science and art collaborations in the last years, we have learned what connects and what separates our disciplines, how different yet common our worlds of working and thinking are, and how stimulating such collaborations can be. Although scientists and artists belong to two different cultural worlds, many share research as a congruent method to explore and understand the world around us. Often, scientific and artistic work spaces are indistinguishable as they are full of equipment, materials, tools, and computers to run experiments and analyze data [3,4]. Science and art are fundamentally connected through their focus on creativity [5]. Also, both scientists and artists deliberately venture into the public realm in the spirit of Hannah Arendt: “Humanity is never won in loneliness and never by handing one’s work over to the public. Only if you take your life and person[ality] into the venture of the public realm, will you reach [humanity]” [6]. At the most fundamental level, science and art both try to understand the world around us and to guide society to recognize and solve problems. Artistic and scientific research may also have much more in common than one expects at first sight: They both involve years of schools and personal development, they both involve trial and error, and the sharing of results with different communities. However, transdisciplinary cooperation requires openness, a willingness to take risks, the ability for self-reflection, respect, and esteem for the other culture as well as a lot of appreciative listening from both parties [7,8]. Our paper thus intends to serve as a practical guide for both, artists-in-residence and the hosting scientific lab to easier cross borders, to better collaborate, to better learn from each other, and to sustainably bridge the different cultures of science and the arts. Our discussion starts at the point where a decision for such an interaction has already taken place. Still wondering if this is for you? There is much to gain for both sides. For the scientists, for example, this interaction can be a source of new ideas and questions, offering new points of view. Some of us also felt that this interaction offered training in explaining research in clear, simple language, and provided opportunities for interfacing with the science-curious public in a curated context. For the artists, this can be about learning new tools, methods, and approaches and about the specific topics on which a lab works. Some of the following 10 “rules” apply more to the artist, some more to the hosting science lab, and some to both (Fig 1). Open in a separate window Fig 1 Summary of the 10 rules, arrayed from intellectual/philosophical to practical/logistical and divided into rules more applicable to the hosting science lab and rules relevant for both the hosting lab and the artist. Rule 1: Be open The basic mindset and attitude required for both scientists and artists is openness. Openness to new input, willingness to share ideas, and a sharing attitude. It is not at all required to have an artistic “inclination” on the part of the hosting scientist, but nothing can replace an open attitude. Be open to accept that research can be both: scientific research and artistic research (for a definition of artistic research, see [9]).
- Published
- 2021
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