6 results
Search Results
2. 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
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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
- Full Text
- View/download PDF
3. The life history of learning: Demographic structure changes cultural outcomes.
- Author
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Fogarty, Laurel, Creanza, Nicole, and Feldman, Marcus W.
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LEARNING , *CULTURAL pluralism , *POPULATION , *DEMOGRAPHIC characteristics , *SOCIAL evolution - Abstract
Human populations show rich cultural diversity. Underpinning this diversity of tools, rituals, and cultural norms are complex interactions between cultural evolutionary and demographic processes. Most models of cultural change assume that individuals use the same learning modes and methods throughout their lives. However, empirical data on ‘learning life histories’—the balance of dominant modes of learning (for example, learning from parents, peers, or unrelated elders) throughout an individual’s lifetime—suggest that age structure may play a crucial role in determining learning modes and cultural evolutionary trajectories. Thus, studied in isolation, demographic and cultural evolutionary models show only part of the picture. This paper describes a mathematical and computational framework that combines demographic and cultural evolutionary methods. Using this general framework, we examine interactions between the ways in which culture is spread throughout an individual’s lifetime and cultural change across generations. We show that including demographic structure alongside cultural dynamics can help to explain domain-specific patterns of cultural evolution that are a persistent feature of cultural data, and can shed new light on rare but significant demographic events. [ABSTRACT FROM AUTHOR]
- Published
- 2019
- Full Text
- View/download PDF
4. Ten simple rules for organizing a bioinformatics training course in low- and middle-income countries
- Author
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Patricia Carvajal-López, Piraveen Gopalasingam, Amel Ghouila, Sarah L. Morgan, Guilherme Oliveira, Verena Ras, Paballo Abel Chauke, Alice Matimba, Alejandro Reyes, Selene L. Fernandez-Valverde, Nicola Mulder, Marco Cristancho, Javier De Las Rivas, Fatma Z. Guerfali, Victoria Dominguez Del Angel, Benjamin Moore, Wellcome Trust, National Institutes of Health (US), Biotechnology and Biological Sciences Research Council (UK), Global Challenges Research Fund, Instituto de Salud Carlos III, Consejo Superior de Investigaciones Científicas (España), Universidad de Salamanca, and Instituto Nacional de Bioinformática (España)
- Subjects
Budgets ,Financial Management ,Economics ,Computer science ,Social Sciences ,Economic Geography ,Database and Informatics Methods ,Learning and Memory ,0302 clinical medicine ,Sociology ,Simple (abstract algebra) ,Psychology ,Biology (General) ,0303 health sciences ,Geography ,Ecology ,4. Education ,Software Engineering ,ComputingMilieux_GENERAL ,Professions ,Interdisciplinary Placement ,Editorial ,Computational Theory and Mathematics ,Modeling and Simulation ,Low and Middle Income Countries ,Educational Status ,Engineering and Technology ,Workshops ,Curriculum ,Human learning ,Computer and Information Sciences ,Coronavirus disease 2019 (COVID-19) ,Bioinformatics ,QH301-705.5 ,Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) ,Training course ,MEDLINE ,Research and Analysis Methods ,Education ,Computer Software ,Human Learning ,03 medical and health sciences ,Cellular and Molecular Neuroscience ,Genetics ,Learning ,Animals ,Humans ,Molecular Biology ,Developing Countries ,Ecology, Evolution, Behavior and Systematics ,030304 developmental biology ,Cognitive Psychology ,Sustainability science ,Biology and Life Sciences ,Computational Biology ,Data science ,Trainees ,Low and middle income countries ,Instructors ,People and Places ,Earth Sciences ,Cognitive Science ,Population Groupings ,Finance ,030217 neurology & neurosurgery ,Neuroscience - Abstract
© 2021 Moore et al., Bioinformatics training is required at every stage of a scientist’s research career. Continual bioinformatics training allows exposure to an ever-changing and growing repertoire of techniques and databases, and so biologists, computational scientists, and healthcare practitioners are all seeking learning opportunities in the use of computational resources and tools designed for data storage, retrieval, and analysis. There are abundant opportunities for accessing bioinformatics training for scientists in high-income countries (HICs), with well-equipped facilities and participants and trainers requiring minimal travel and financial costs alongside a range of general advice for developing short bioinformatics training courses [1–3]. However, regionally targeted bioinformatics training in low- and middle-income countries (LMICs) often requires more extensive local and external support, organization, and travel. Due to the limited expertise in bioinformatics in LMICs in general, most bioinformatics training requires a fair amount of collaboration with experts beyond the local community, country, or region. A common model of training, used as the basis of this article, includes a local host collaborating with local, regional, and international experts gathering to train local or regional participants. Recently, there has been a growth of capacity strengthening initiatives in LMICs, such as the Pan African Bioinformatics Network for Human Heredity and Health in Africa (H3ABioNet) Initiative [4–6], the Capacity Building for Bioinformatics in Latin America (CABANA) Project [7], the Asia Pacific BioInformatics Network (APBioNet) [8], and the Wellcome Connecting Science Courses and Conferences program [9]. One of the important strands of these initiatives is a drive to organize and deliver valuable bioinformatics training, but organizing and delivering short bioinformatics training workshops in an LMIC present a unique set of challenges. This paper attempts to build upon the sage advice for organizing bioinformatics workshops with specific guidance for organizing and delivering them in LMICs. It describes the processes to follow in organizing courses taking into consideration the low-resource setting. We should also note that LMICs are not a monolithic group and that setting, context, temporality, and specific location matters. LMICs are a complex regional grouping [10] and should be treated as such; however, we will present some common lessons that we hope will help organizers and trainers of bioinformatics training events in LMICs to navigate the often different, challenging, and rewarding experience., The authors who contributed to this manuscript are funded as follows: BM receives salary support from Wellcome Trust grants [WT108749/Z/15/Z, WT108749/Z/15/A], PC, VR, NM, AG’s salaries are funded in whole, or in part, by the NIH Common Fund H3ABioNet grant [U24HG006941], MC, SLFV, AR, PG, PCL’s salaries were partly funded by the UKRI-BBSRC ‘Capacity building for bioinformatics in Latin America’ (CABANA) grant, on behalf of the Global Challenges Research Fund [BB/P027849/1], JDLR is funded by ISCiii AES [ref. PI18/00591] at the CSIC/USAL (Spain) and by CYTED, RIABIO (Red Iberoamericana 521RT0118), AM’s salary is funded by [WT206194/Z/17/Z], GO is funded by the CABANA grant and SM is funded by the EMBL-EBI.
- Published
- 2021
5. Ten simple rules for partnering with K-12 teachers to support broader impact goals
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Louise S. Mead, Kristin M. Bass, Alexa Warwick, Frieda Reichsman, and Angela Kolonich
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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
6. Ten quick tips for delivering programming lessons
- Author
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Greg Wilson
- Subjects
0301 basic medicine ,Computer and Information Sciences ,QH301-705.5 ,Computer science ,Social Sciences ,computer.software_genre ,Education ,Craft ,Computer Software ,03 medical and health sciences ,Cellular and Molecular Neuroscience ,Human Learning ,0302 clinical medicine ,Learning and Memory ,Cognition ,Sociology ,Memory ,Computer software ,Genetics ,Learning ,Psychology ,Humans ,Biology (General) ,Molecular Biology ,Ecology, Evolution, Behavior and Systematics ,Language ,Ecology ,Recall ,Multimedia ,Teaching ,Cognitive Psychology ,Biology and Life Sciences ,Teachers ,Professions ,030104 developmental biology ,Computational Theory and Mathematics ,Modeling and Simulation ,Instructors ,People and Places ,Memory Recall ,Cognitive Science ,Population Groupings ,Workshops ,computer ,Value (mathematics) ,030217 neurology & neurosurgery ,Human learning ,Neuroscience - Abstract
Teaching well is a craft like any other, and success often comes from an accumulation of small improvements rather than from any single large change. This paper describes 10 practices you can use when teaching programming (and other subjects). All are easy to adopt and have proven their value in institutional classrooms, intensive workshops, and other settings.
- Published
- 2019
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