11,615 results
Search Results
2. 2021 Bioinformatics and Translational Informatics Best Papers.
- Author
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Benton ML and McGrath SP
- Subjects
- Humans, Machine Learning, Precision Medicine, Electronic Health Records, Computational Biology, Informatics
- Abstract
Objectives: To identify and summarize the top bioinformatics and translational informatics papers published in 2021 for the IMIA Yearbook., Methods: We performed a broad literature search to retrieve Bioinformatics and Translational Informatics (BTI) papers and coupled this with a series of editorial and peer reviews to identity the top papers in the area., Results: We identified a final candidate list of 15 BTI papers for peer-review; from these candidates, the top three papers were chosen to highlight in this synopsis. These papers expand the integration of multi-omics data with electronic health records and use advanced machine learning approaches to tailor models to individual patients. In addition, our honorable mention paper foreshadows the growing impact of BTI research on precision medicine through the continued development of large clinical consortia., Conclusion: In the top BTI papers this year, we observed several important trends, including the use of deep-learning approaches to analyse diverse data types, the development of integrative and web-accessible bioinformatics pipelines, and a continued focus on the power of individual genome sequencing for precision health., Competing Interests: Disclosure The authors report no conflicts of interest in this work., (IMIA and Thieme. This is an open access article published by Thieme under the terms of the Creative Commons Attribution-NonDerivative-NonCommercial License, permitting copying and reproduction so long as the original work is given appropriate credit. Contents may not be used for commercial purposes, or adapted, remixed, transformed or built upon. (https://creativecommons.org/licenses/by-nc-nd/4.0/).)
- Published
- 2022
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3. Machine learning methods for prediction of cancer driver genes: a survey paper.
- Author
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Andrades R and Recamonde-Mendoza M
- Subjects
- Algorithms, Humans, Machine Learning, Mutation, Oncogenes, Computational Biology methods, Neoplasms diagnosis, Neoplasms genetics, Neoplasms pathology
- Abstract
Identifying the genes and mutations that drive the emergence of tumors is a critical step to improving our understanding of cancer and identifying new directions for disease diagnosis and treatment. Despite the large volume of genomics data, the precise detection of driver mutations and their carrying genes, known as cancer driver genes, from the millions of possible somatic mutations remains a challenge. Computational methods play an increasingly important role in discovering genomic patterns associated with cancer drivers and developing predictive models to identify these elements. Machine learning (ML), including deep learning, has been the engine behind many of these efforts and provides excellent opportunities for tackling remaining gaps in the field. Thus, this survey aims to perform a comprehensive analysis of ML-based computational approaches to identify cancer driver mutations and genes, providing an integrated, panoramic view of the broad data and algorithmic landscape within this scientific problem. We discuss how the interactions among data types and ML algorithms have been explored in previous solutions and outline current analytical limitations that deserve further attention from the scientific community. We hope that by helping readers become more familiar with significant developments in the field brought by ML, we may inspire new researchers to address open problems and advance our knowledge towards cancer driver discovery., (© The Author(s) 2022. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.)
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- 2022
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4. The molecular basis of socially mediated phenotypic plasticity in a eusocial paper wasp.
- Author
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Taylor BA, Cini A, Wyatt CDR, Reuter M, and Sumner S
- Subjects
- Algorithms, Animals, Female, Gene Ontology, Gene Regulatory Networks, Humans, Machine Learning, Phenotype, Adaptation, Physiological genetics, Computational Biology methods, Gene Expression Profiling methods, Social Behavior, Transcriptome genetics, Wasps genetics
- Abstract
Phenotypic plasticity, the ability to produce multiple phenotypes from a single genotype, represents an excellent model with which to examine the relationship between gene expression and phenotypes. Analyses of the molecular foundations of phenotypic plasticity are challenging, however, especially in the case of complex social phenotypes. Here we apply a machine learning approach to tackle this challenge by analyzing individual-level gene expression profiles of Polistes dominula paper wasps following the loss of a queen. We find that caste-associated gene expression profiles respond strongly to queen loss, and that this change is partly explained by attributes such as age but occurs even in individuals that appear phenotypically unaffected. These results demonstrate that large changes in gene expression may occur in the absence of outwardly detectable phenotypic changes, resulting here in a socially mediated de-differentiation of individuals at the transcriptomic level but not at the levels of ovarian development or behavior.
- Published
- 2021
- Full Text
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5. Introduction to the JBCB Special Issue on Selected Papers from BICOB-2020.
- Author
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Eulenstein O, Ding Q, and Al-Mubaid H
- Subjects
- Congresses as Topic, Humans, Neoplasms genetics, Proteins chemistry, Computational Biology
- Published
- 2021
- Full Text
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6. Machine learning approaches and databases for prediction of drug-target interaction: a survey paper.
- Author
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Bagherian M, Sabeti E, Wang K, Sartor MA, Nikolovska-Coleska Z, and Najarian K
- Subjects
- Databases, Factual, Humans, Computational Biology methods, Drug Discovery methods, Machine Learning
- Abstract
The task of predicting the interactions between drugs and targets plays a key role in the process of drug discovery. There is a need to develop novel and efficient prediction approaches in order to avoid costly and laborious yet not-always-deterministic experiments to determine drug-target interactions (DTIs) by experiments alone. These approaches should be capable of identifying the potential DTIs in a timely manner. In this article, we describe the data required for the task of DTI prediction followed by a comprehensive catalog consisting of machine learning methods and databases, which have been proposed and utilized to predict DTIs. The advantages and disadvantages of each set of methods are also briefly discussed. Lastly, the challenges one may face in prediction of DTI using machine learning approaches are highlighted and we conclude by shedding some lights on important future research directions., (© The Author(s) 2020. Published by Oxford University Press.)
- Published
- 2021
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7. Ten simple rules for writing a paper about scientific software.
- Author
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Romano JD and Moore JH
- Subjects
- Humans, Internet, Research Personnel, Writing, Computational Biology, Publishing, Software
- Abstract
Papers describing software are an important part of computational fields of scientific research. These "software papers" are unique in a number of ways, and they require special consideration to improve their impact on the scientific community and their efficacy at conveying important information. Here, we discuss 10 specific rules for writing software papers, covering some of the different scenarios and publication types that might be encountered, and important questions from which all computational researchers would benefit by asking along the way., Competing Interests: The authors have declared that no competing interests exist.
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- 2020
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8. Special Issue "Selected Papers from the 8th Asia-Pacific NMR (APNMR) Symposium: Recent Advances in NMR Spectroscopy".
- Author
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Bhattacharjya S, Yang D, and Yoon HS
- Subjects
- Asia, Humans, Pacific Islands, Computational Biology methods, Magnetic Resonance Imaging methods, Magnetic Resonance Spectroscopy methods, Periodicals as Topic
- Abstract
Asia-Pacific NMR (APNMR) has been an important scientific event in the region, engaging a large number of NMR scientists from academia and industries [...].
- Published
- 2020
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9. Reply to the paper: Misunderstood parameters of NCBI BLAST impacts the correctness of bioinformatics workflows.
- Author
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Madden TL, Busby B, and Ye J
- Subjects
- Leukocytes, Sequence Alignment, Software, Computational Biology, Workflow
- Published
- 2019
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10. Selected Papers from the International Workshop on Cancer Bioinformatics and Intelligent Medicine (CBIM2018).
- Author
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Chu YW and Lee YH
- Subjects
- Congresses as Topic, Humans, Periodicals as Topic, Computational Biology, Neoplasms genetics
- Published
- 2019
- Full Text
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11. Selected Papers from the Workshop on Computational Biology: Joint with the International Joint Conference on Artificial Intelligence and the International Conference on Machine Learning, 2018.
- Author
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Diallo AB, Nguifo EM, Dhifli W, Azizi E, Prabhakaran S, and Tansey W
- Subjects
- Artificial Intelligence, Congresses as Topic, Machine Learning, Publications, Computational Biology methods
- Published
- 2019
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12. Position Paper Computational Cardiology.
- Author
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Athanasiou L, Nezami FR, and Edelman ER
- Subjects
- Cardiology organization & administration, Cardiology statistics & numerical data, Cardiovascular Diseases diagnostic imaging, Humans, Machine Learning, Publications statistics & numerical data, Cardiac Imaging Techniques, Computational Biology, Medical Informatics
- Abstract
Computational cardiology is the scientific field devoted to the development of methodologies that enhance our mechanistic understanding, diagnosis and treatment of cardiovascular disease. In this regard, the field embraces the extraordinary pace of discovery in imaging, computational modeling, and cardiovascular informatics at the intersection of atherogenesis and vascular biology. This paper highlights existing methods, practices, and computational models and proposes new strategies to support a multidisciplinary effort in this space. We focus on the means by that to leverage and coalesce these multiple disciplines to advance translational science and computational cardiology. Analyzing the scientific trends and understanding the current needs we present our perspective for the future of cardiovascular treatment.
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- 2019
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13. Introduction to Selected Papers from GIW2018.
- Author
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Li J, Nakai K, Zheng Y, Sato K, and Wong L
- Subjects
- Congresses as Topic, Drug Interactions, Epistasis, Genetic, Influenza A virus physiology, RNA chemistry, Sequence Alignment methods, Viral Tropism, Computational Biology methods, Genomics methods
- Published
- 2018
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14. Introduction to Selected Papers from GIW2017.
- Author
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Sael L
- Subjects
- Genomics, Proteins chemistry, Computational Biology, Drug Design
- Published
- 2018
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15. Introduction to Papers Selected from MCCMB'17.
- Author
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Gelfand M
- Subjects
- Proteins chemistry, Proteins genetics, Computational Biology, Genomics, Systems Biology
- Published
- 2018
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16. Selected Papers from the 16th International Conference on Bioinformatics (InCoB 2017).
- Author
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Akutsu T
- Subjects
- Algorithms, Bone Marrow diagnostic imaging, Congresses as Topic, Humans, Protein Processing, Post-Translational, Computational Biology methods, Data Mining methods
- Published
- 2017
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17. Honored papers 2016.
- Author
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Ciaccio EJ
- Subjects
- Humans, Publishing, Computational Biology
- Published
- 2017
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18. Introduction to selected papers from the 8th International Conference on Bioinformatics and Computational Biology (BICOB 2016).
- Author
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Haspel N, Ioerger T, and Al-Mubaid H
- Subjects
- Cloud Computing, Congresses as Topic, Genome, Microbial, Computational Biology methods, Systems Biology methods
- Published
- 2017
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19. Language models for biological research: a primer.
- Author
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Simon E, Swanson K, and Zou J
- Subjects
- Humans, Natural Language Processing, Programming Languages, Artificial Intelligence, Computational Biology methods
- Abstract
Language models are playing an increasingly important role in many areas of artificial intelligence (AI) and computational biology. In this primer, we discuss the ways in which language models, both those based on natural language and those based on biological sequences, can be applied to biological research. This primer is primarily intended for biologists interested in using these cutting-edge AI technologies in their applications. We provide guidance on best practices and key resources for adapting language models for biology., (© 2024. Springer Nature America, Inc.)
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- 2024
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20. Applying interpretable machine learning in computational biology-pitfalls, recommendations and opportunities for new developments.
- Author
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Chen V, Yang M, Cui W, Kim JS, Talwalkar A, and Ma J
- Subjects
- Humans, Algorithms, Machine Learning, Computational Biology methods
- Abstract
Recent advances in machine learning have enabled the development of next-generation predictive models for complex computational biology problems, thereby spurring the use of interpretable machine learning (IML) to unveil biological insights. However, guidelines for using IML in computational biology are generally underdeveloped. We provide an overview of IML methods and evaluation techniques and discuss common pitfalls encountered when applying IML methods to computational biology problems. We also highlight open questions, especially in the era of large language models, and call for collaboration between IML and computational biology researchers., (© 2024. Springer Nature America, Inc.)
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- 2024
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21. Bioinformatics programs are 31-fold over-represented among the highest impact scientific papers of the past two decades.
- Author
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Wren JD
- Subjects
- Humans, Periodicals as Topic, Publishing, Computational Biology trends, Publications trends, Software
- Abstract
Motivation: To analyze the relative proportion of bioinformatics papers and their non-bioinformatics counterparts in the top 20 most cited papers annually for the past two decades., Results: When defining bioinformatics papers as encompassing both those that provide software for data analysis or methods underlying data analysis software, we find that over the past two decades, more than a third (34%) of the most cited papers in science were bioinformatics papers, which is approximately a 31-fold enrichment relative to the total number of bioinformatics papers published. More than half of the most cited papers during this span were bioinformatics papers. Yet, the average 5-year JIF of top 20 bioinformatics papers was 7.7, whereas the average JIF for top 20 non-bioinformatics papers was 25.8, significantly higher (P < 4.5 × 10(-29)). The 20-year trend in the average JIF between the two groups suggests the gap does not appear to be significantly narrowing. For a sampling of the journals producing top papers, bioinformatics journals tended to have higher Gini coefficients, suggesting that development of novel bioinformatics resources may be somewhat 'hit or miss'. That is, relative to other fields, bioinformatics produces some programs that are extremely widely adopted and cited, yet there are fewer of intermediate success., Contact: jdwren@gmail.com, Supplementary Information: Supplementary data are available at Bioinformatics online., (© The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.)
- Published
- 2016
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22. Preface to selected papers from the 6th International Conference on Computational Systems-Biology and Bioinformatics (CSBio2015).
- Author
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Kittichotirat W, Engchuan W, Vongsangnak W, and Meechai A
- Subjects
- Algorithms, Animals, Cell Cycle, Congresses as Topic, Mammals, Molecular Sequence Annotation, Computational Biology methods, Genomics methods, Systems Biology methods
- Published
- 2016
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23. The papers presented at 7th Young Scientists School "Systems Biology and Bioinformatics" (SBB'15): Introductory Note. Introduction.
- Author
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Baranova AV and Orlov YL
- Subjects
- Computational Biology, Genomics, Systems Biology
- Published
- 2016
- Full Text
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24. Introduction to selected papers from GIW/InCoB 2015.
- Author
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Horton P, Schönbach C, Ranganathan S, and Yiu SM
- Subjects
- Genomics, Humans, Computational Biology
- Published
- 2015
- Full Text
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25. Introduction. These two issues contain a selected subset of the papers presented at RECOMB 2014.
- Author
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Sharan R
- Subjects
- Computational Biology instrumentation, Computational Biology methods, Humans, Computational Biology trends
- Published
- 2015
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26. Letter to the editor: On reviews and papers on new methods.
- Author
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Boulesteix AL
- Subjects
- Humans, Publishing, Review Literature as Topic, Computational Biology methods
- Published
- 2015
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27. Guest Editors’ Introduction: Selected Papers from ACM-BCB 2013.
- Author
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Aluru S and Slonim DK
- Subjects
- Humans, Computational Biology
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- 2015
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28. Foreword to the special issue on selected papers from the 6th International Conference on Bioinformatics and Computational Biology (BICoB 2014).
- Author
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Saeed F, Al-Mubaid H, and Dasgupta B
- Subjects
- Algorithms, Databases, Protein, Evolution, Molecular, Systems Biology, Computational Biology
- Published
- 2014
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29. Closing the loop: from paper to protein annotation using supervised Gene Ontology classification.
- Author
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Gobeill J, Pasche E, Vishnyakova D, and Ruch P
- Subjects
- Proteins chemistry, Proteins classification, Software, Computational Biology methods, Data Curation methods, Gene Ontology, Molecular Sequence Annotation methods
- Abstract
Gene function curation of the literature with Gene Ontology (GO) concepts is one particularly time-consuming task in genomics, and the help from bioinformatics is highly requested to keep up with the flow of publications. In 2004, the first BioCreative challenge already designed a task of automatic GO concepts assignment from a full text. At this time, results were judged far from reaching the performances required by real curation workflows. In particular, supervised approaches produced the most disappointing results because of lack of training data. Ten years later, the available curation data have massively grown. In 2013, the BioCreative IV GO task revisited the automatic GO assignment task. For this issue, we investigated the power of our supervised classifier, GOCat. GOCat computes similarities between an input text and already curated instances contained in a knowledge base to infer GO concepts. The subtask A consisted in selecting GO evidence sentences for a relevant gene in a full text. For this, we designed a state-of-the-art supervised statistical approach, using a naïve Bayes classifier and the official training set, and obtained fair results. The subtask B consisted in predicting GO concepts from the previous output. For this, we applied GOCat and reached leading results, up to 65% for hierarchical recall in the top 20 outputted concepts. Contrary to previous competitions, machine learning has this time outperformed standard dictionary-based approaches. Thanks to BioCreative IV, we were able to design a complete workflow for curation: given a gene name and a full text, this system is able to select evidence sentences for curation and to deliver highly relevant GO concepts. Contrary to previous competitions, machine learning this time outperformed dictionary-based systems. Observed performances are sufficient for being used in a real semiautomatic curation workflow. GOCat is available at http://eagl.unige.ch/GOCat/., Database Url: http://eagl.unige.ch/GOCat4FT/., (© The Author(s) 2014. Published by Oxford University Press.)
- Published
- 2014
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30. Leveraging transformers-based language models in proteome bioinformatics.
- Author
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Le NQK
- Subjects
- Data Mining, Machine Learning, Natural Language Processing, Proteome, Computational Biology
- Abstract
In recent years, the rapid growth of biological data has increased interest in using bioinformatics to analyze and interpret this data. Proteomics, which studies the structure, function, and interactions of proteins, is a crucial area of bioinformatics. Using natural language processing (NLP) techniques in proteomics is an emerging field that combines machine learning and text mining to analyze biological data. Recently, transformer-based NLP models have gained significant attention for their ability to process variable-length input sequences in parallel, using self-attention mechanisms to capture long-range dependencies. In this review paper, we discuss the recent advancements in transformer-based NLP models in proteome bioinformatics and examine their advantages, limitations, and potential applications to improve the accuracy and efficiency of various tasks. Additionally, we highlight the challenges and future directions of using these models in proteome bioinformatics research. Overall, this review provides valuable insights into the potential of transformer-based NLP models to revolutionize proteome bioinformatics., (© 2023 Wiley-VCH GmbH.)
- Published
- 2023
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31. Establishing African genomics and bioinformatics programs through annual regional workshops.
- Author
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Sharaf A, Nesengani LT, Hayah I, Kuja JO, Mdyogolo S, Omotoriogun TC, Odogwu BA, Beedessee G, Smith RM, Barakat A, Moila AM, El Hamouchi A, Benkahla A, Boukteb A, Elmouhtadi A, Mafwila AL, Abushady AM, Elsherif AK, Ahmed B, Wairuri C, Ndiribe CC, Ebuzome C, Kinnear CJ, Ndlovu DF, Iraqi D, El Fahime E, Assefa E, Ouardi F, Belharfi FZ, Tmimi FZ, Markey FB, Radouani F, Zeukeng F, Mvumbi GL, Ganesan H, Hanachi M, Nigussie H, Charoute H, Benamri I, Mkedder I, Haddadi I, Meftah-Kadmiri I, Mubiru JF, Domelevo Entfellner JK, Rokani JB, Ogwang J, Daiga JB, Omumbo J, Ideozu JE, Errafii K, Labuschagne K, Komi KK, Tonfack LB, Hadjeras L, Ramantswana M, Chaisi M, Botes MW, Kilian M, Kvas M, Melloul M, Chaouch M, Khyatti M, Abdo M, Phasha-Muchemenye M, Hijri M, Mediouni MR, Hassan MA, Piro M, Mwale M, Maaloum M, Mavhunga M, Olivier NA, Aminou O, Arbani O, Souiai O, Djocgoue PF, Mentag R, Zipfel RD, Tata RB, Megnekou R, Muzemil S, Paez S, Salifu SP, Kagame SP, Selka S, Edwards S, Gaouar SBS, Reda SRA, Fellahi S, Khayi S, Ayed S, Madisha T, Sahil T, Udensi OU, Ras V, Ezebuiro V, Duru VC, David X, Geberemichael Y, Tchiechoua YH, Mungloo-Dilmohamud Z, Chen Z, Happi C, Kariuki T, Ziyomo C, Djikeng A, Badaoui B, Mapholi N, Muigai A, Osuji JO, and Ebenezer TE
- Subjects
- Africa, Humans, Biodiversity, Genomics education, Computational Biology methods, Computational Biology education
- Abstract
The African BioGenome Project (AfricaBP) Open Institute for Genomics and Bioinformatics aims to overcome barriers to capacity building through its distributed African regional workshops and prioritizes the exchange of grassroots knowledge and innovation in biodiversity genomics and bioinformatics. In 2023, we implemented 28 workshops on biodiversity genomics and bioinformatics, covering 11 African countries across the 5 African geographical regions. These regional workshops trained 408 African scientists in hands-on molecular biology, genomics and bioinformatics techniques as well as the ethical, legal and social issues associated with acquiring genetic resources. Here, we discuss the implementation of transformative strategies, such as expanding the regional workshop model of AfricaBP to involve multiple countries, institutions and partners, including the proposed creation of an African digital database with sequence information relating to both biodiversity and agriculture. This will ultimately help create a critical mass of skilled genomics and bioinformatics scientists across Africa., (© 2024. Springer Nature America, Inc.)
- Published
- 2024
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32. Exploiting protein language models for the precise classification of ion channels and ion transporters.
- Author
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Ghazikhani H and Butler G
- Subjects
- Humans, Databases, Protein, Software, Membrane Proteins chemistry, Membrane Proteins metabolism, Membrane Proteins classification, Ion Transport, Algorithms, Ion Channels metabolism, Ion Channels chemistry, Ion Channels classification, Computational Biology methods, Deep Learning
- Abstract
This study introduces TooT-PLM-ionCT, a comprehensive framework that consolidates three distinct systems, each meticulously tailored for one of the following tasks: distinguishing ion channels (ICs) from membrane proteins (MPs), segregating ion transporters (ITs) from MPs, and differentiating ICs from ITs. Drawing upon the strengths of six Protein Language Models (PLMs)-ProtBERT, ProtBERT-BFD, ESM-1b, ESM-2 (650M parameters), and ESM-2 (15B parameters), TooT-PLM-ionCT employs a combination of traditional classifiers and deep learning models for nuanced protein classification. Originally validated on an existing dataset by previous researchers, our systems demonstrated superior performance in identifying ITs from MPs and distinguishing ICs from ITs, with the IC-MP discrimination achieving state-of-the-art results. In light of recommendations for additional validation, we introduced a new dataset, significantly enhancing the robustness and generalization of our models across bioinformatics challenges. This new evaluation underscored the effectiveness of TooT-PLM-ionCT in adapting to novel data while maintaining high classification accuracy. Furthermore, this study explores critical factors affecting classification accuracy, such as dataset balancing, the impact of using frozen versus fine-tuned PLM representations, and the variance between half and full precision in floating-point computations. To facilitate broader application and accessibility, a web server (https://tootsuite.encs.concordia.ca/service/TooT-PLM-ionCT) has been developed, allowing users to evaluate unknown protein sequences through our specialized systems for IC-MP, IT-MP, and IC-IT classification tasks., (© 2024 The Authors. Proteins: Structure, Function, and Bioinformatics published by Wiley Periodicals LLC.)
- Published
- 2024
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33. Whole genome sequence of Vibrio cholerae directly from dried spotted filter paper.
- Author
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Bénard, Angèle H. M., Guenou, Etienne, Fookes, Maria, Ateudjieu, Jerome, Kasambara, Watipaso, Siever, Matthew, Rebaudet, Stanislas, Boncy, Jacques, Adrien, Paul, Piarroux, Renaud, Sack, David A., Thomson, Nicholas, and Debes, Amanda K.
- Subjects
CHOLERA ,TREPONEMA pallidum ,FILTER paper ,VIBRIO cholerae ,NUCLEOTIDE sequencing ,HEALTH facilities ,CHOLERA toxin - Abstract
Background: Global estimates for cholera annually approximate 4 million cases worldwide with 95,000 deaths. Recent outbreaks, including Haiti and Yemen, are reminders that cholera is still a global health concern. Cholera outbreaks can rapidly induce high death tolls by overwhelming the capacity of health facilities, especially in remote areas or areas of civil unrest. Recent studies demonstrated that stool specimens preserved on filter paper facilitate molecular analysis of Vibrio cholerae in resource limited settings. Specimens preserved in a rapid, low-cost, safe and sustainable manner for sequencing provides previously unavailable data about circulating cholera strains. This may ultimately provide new information to shape public policy response on cholera control and elimination. Methodology/Principal findings: Whole genome sequencing (WGS) recovered close to a complete sequence of the V. cholerae O1 genome with satisfactory genome coverage from stool specimens enriched in alkaline peptone water (APW) and V. cholerae culture isolates, both spotted on filter paper. The minimum concentration of V. cholerae DNA sufficient to produce quality genomic information was 0.02 ng/μL. The genomic data confirmed the presence or absence of genes of epidemiological interest, including cholera toxin and pilus loci. WGS identified a variety of diarrheal pathogens from APW-enriched specimen spotted filter paper, highlighting the potential for this technique to explore the gut microbiome, potentially identifying co-infections, which may impact the severity of disease. WGS demonstrated that these specimens fit within the current global cholera phylogenetic tree, identifying the strains as the 7
th pandemic El Tor. Conclusions: WGS results allowed for mapping of short reads from APW-enriched specimen and culture isolate spotted filter papers this provided valuable molecular epidemiological sequence information on V. cholerae strains from remote, low-resource settings. These results identified the presence of co-infecting pathogens while providing rare insight into the specific V. cholerae strains causing outbreaks in cholera-endemic areas. [ABSTRACT FROM AUTHOR]- Published
- 2019
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34. The molecular basis of socially mediated phenotypic plasticity in a eusocial paper wasp
- Author
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Max Reuter, Benjamin A. Taylor, Seirian Sumner, Alessandro Cini, and Christopher D. R. Wyatt
- Subjects
0106 biological sciences ,0301 basic medicine ,Bioinformatics ,Science ,Wasps ,education ,Gene regulatory network ,General Physics and Astronomy ,Polistes dominula ,010603 evolutionary biology ,01 natural sciences ,Article ,General Biochemistry, Genetics and Molecular Biology ,Machine Learning ,03 medical and health sciences ,Gene expression ,Animals ,Humans ,Gene Regulatory Networks ,Social Behavior ,Paper wasp ,Phenotypic plasticity ,Multidisciplinary ,biology ,Gene Expression Profiling ,Computational Biology ,General Chemistry ,Animal behaviour ,biology.organism_classification ,Adaptation, Physiological ,Phenotype ,Eusociality ,Gene Ontology ,030104 developmental biology ,Evolutionary biology ,Female ,Adaptation ,Transcriptome ,Entomology ,Algorithms - Abstract
Phenotypic plasticity, the ability to produce multiple phenotypes from a single genotype, represents an excellent model with which to examine the relationship between gene expression and phenotypes. Analyses of the molecular foundations of phenotypic plasticity are challenging, however, especially in the case of complex social phenotypes. Here we apply a machine learning approach to tackle this challenge by analyzing individual-level gene expression profiles of Polistes dominula paper wasps following the loss of a queen. We find that caste-associated gene expression profiles respond strongly to queen loss, and that this change is partly explained by attributes such as age but occurs even in individuals that appear phenotypically unaffected. These results demonstrate that large changes in gene expression may occur in the absence of outwardly detectable phenotypic changes, resulting here in a socially mediated de-differentiation of individuals at the transcriptomic level but not at the levels of ovarian development or behavior., Connecting genotypes to complex social behaviour is challenging. Taylor et al. use machine learning to show a strong response of caste-associated gene expression to queen loss, wherein individual wasp’s expression profiles become intermediate between queen and worker states, even in the absence of behavioural changes.
- Published
- 2021
35. Paper-based microfluidics for DNA diagnostics of malaria in low resource underserved rural communities
- Author
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Edridah M. Tukahebwa, Julien Reboud, Zhugen Yang, Jonathan M. Cooper, Alice Garrett, Candia Rowell, Gaolian Xu, and Moses Adriko
- Subjects
Paper ,Rural Population ,Adolescent ,Low resource ,Computer science ,low-resource settings ,Point-of-care testing ,Microfluidics ,Loop-mediated isothermal amplification ,malaria ,Medically Underserved Area ,02 engineering and technology ,Computational biology ,01 natural sciences ,Biochemistry ,Polymerase Chain Reaction ,law.invention ,Engineering ,nucleic acid-based tests ,law ,medicine ,Humans ,Medical diagnosis ,Malaria, Falciparum ,Child ,Polymerase chain reaction ,Multidisciplinary ,010401 analytical chemistry ,Reproducibility of Results ,Biological Sciences ,DNA, Protozoan ,021001 nanoscience & nanotechnology ,medicine.disease ,3. Good health ,0104 chemical sciences ,Diagnosis of malaria ,PNAS Plus ,Molecular Diagnostic Techniques ,Physical Sciences ,Health Resources ,paper microfluidics ,0210 nano-technology ,point-of-care diagnostics ,Malaria - Abstract
Significance Populations living in remote rural communities would benefit from rapid, highly sensitive molecular, DNA-based diagnostics to inform the correct and timely treatment of infectious diseases. Such information is also becoming increasingly relevant in global efforts for disease elimination, where the testing of asymptomatic patients is now seen as being important for the identification of disease reservoirs. However, healthcare workers face practical and logistical problems in the implementation of such tests, which often involve complex instrumentation and centralized laboratories. Here we describe innovations in paper microfluidics that enable low-cost, multiplexed DNA-based diagnostics for malaria, delivered, in a first-in-human study, in schools in rural Uganda., Rapid, low-cost, species-specific diagnosis, based upon DNA testing, is becoming important in the treatment of patients with infectious diseases. Here, we demonstrate an innovation that uses origami to enable multiplexed, sensitive assays that rival polymerase chain reactions (PCR) laboratory assays and provide high-quality, fast precision diagnostics for malaria. The paper-based microfluidic technology proposed here combines vertical flow sample-processing steps, including paper folding for whole-blood sample preparation, with an isothermal amplification and a lateral flow detection, incorporating a simple visualization system. Studies were performed in village schools in Uganda with individual diagnoses being completed in
- Published
- 2019
36. Paper-Based Biosensors: Frontiers in Point-of-Care Detection of COVID-19 Disease
- Author
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Riccarda Antiochia
- Subjects
Paper ,Coronavirus disease 2019 (COVID-19) ,Point-of-Care Systems ,Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) ,viruses ,paper-based microfluidics ,lcsh:Biotechnology ,Clinical Biochemistry ,paper-based-biosensor ,COVID-19 ,POC diagnostics ,lateral flow immunoassay ,nucleic acid later flow assay ,Review ,Biosensing Techniques ,02 engineering and technology ,Disease ,Viral antigen ,Computational biology ,01 natural sciences ,Viral gene ,lcsh:TP248.13-248.65 ,Humans ,Medicine ,Antigens, Viral ,Point of care ,Immunoassay ,SARS-CoV-2 ,business.industry ,010401 analytical chemistry ,General Medicine ,Paper based ,021001 nanoscience & nanotechnology ,0104 chemical sciences ,RNA, Viral ,CRISPR-Cas Systems ,0210 nano-technology ,business ,Antibody detection - Abstract
This review summarizes the state of the art of paper-based biosensors (PBBs) for coronavirus disease 2019 (COVID-19) detection. Three categories of PBB are currently being been used for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) diagnostics, namely for viral gene, viral antigen and antibody detection. The characteristics, the analytical performance, the advantages and drawbacks of each type of biosensor are highlighted and compared with traditional methods. It is hoped that this review will be useful for scientists for the development of novel PBB platforms with enhanced performance for helping to contain the COVID-19 outbreak, by allowing early diagnosis at the point of care (POC).
- Published
- 2021
37. Inferring Interaction Networks from Transcriptomic Data: Methods and Applications.
- Author
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Singh V and Singh V
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- Humans, Bayes Theorem, Protein Interaction Mapping methods, Protein Interaction Maps genetics, Computational Biology methods, Gene Expression Profiling methods, Gene Regulatory Networks, Transcriptome
- Abstract
Transcriptomic data is a treasure trove in modern molecular biology, as it offers a comprehensive viewpoint into the intricate nuances of gene expression dynamics underlying biological systems. This genetic information must be utilized to infer biomolecular interaction networks that can provide insights into the complex regulatory mechanisms underpinning the dynamic cellular processes. Gene regulatory networks and protein-protein interaction networks are two major classes of such networks. This chapter thoroughly investigates the wide range of methodologies used for distilling insightful revelations from transcriptomic data that include association-based methods (based on correlation among expression vectors), probabilistic models (using Bayesian and Gaussian models), and interologous methods. We reviewed different approaches for evaluating the significance of interactions based on the network topology and biological functions of the interacting molecules and discuss various strategies for the identification of functional modules. The chapter concludes with highlighting network-based techniques of prioritizing key genes, outlining the centrality-based, diffusion- based, and subgraph-based methods. The chapter provides a meticulous framework for investigating transcriptomic data to uncover assembly of complex molecular networks for their adaptable analyses across a broad spectrum of biological domains., (© 2024. The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature.)
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- 2024
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38. Vox Sanguinis Best Paper 2023.
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- *
TERTIARY structure , *COMPUTATIONAL biology , *CONFERENCES & conventions , *BLOOD transfusion - Abstract
Dr. Rocío Trueba‐Gómez and her team from Mexico City, Mexico, have been awarded the Vox Sanguinis Best Paper Prize 2023 for their paper titled "Use of computational biology to compare the theoretical tertiary structures of the most common forms of RhCE and RhD." This prestigious prize is given annually for the best original paper published in Vox Sanguinis the previous year and includes a certificate and a cash prize of 5000 Euros. The authors will receive the award during the opening ceremony of the 38th International Congress of the International Society of Blood Transfusion in Barcelona. Congratulations to the authors on their achievement. [Extracted from the article]
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- 2024
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39. Advances and opportunities in RNA structure experimental determination and computational modeling.
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Zhang J, Fei Y, Sun L, and Zhang QC
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- Artificial Intelligence, Computer Simulation, Models, Molecular, Nucleic Acid Conformation, Computational Biology methods, RNA chemistry, RNA genetics
- Abstract
Beyond transferring genetic information, RNAs are molecules with diverse functions that include catalyzing biochemical reactions and regulating gene expression. Most of these activities depend on RNAs' specific structures. Therefore, accurately determining RNA structure is integral to advancing our understanding of RNA functions. Here, we summarize the state-of-the-art experimental and computational technologies developed to evaluate RNA secondary and tertiary structures. We also highlight how the rapid increase of experimental data facilitates the integrative modeling approaches for better resolving RNA structures. Finally, we provide our thoughts on the latest advances and challenges in RNA structure determination methods, as well as on future directions for both experimental approaches and artificial intelligence-based computational tools to model RNA structure. Ultimately, we hope the technological advances will deepen our understanding of RNA biology and facilitate RNA structure-based biomedical research such as designing specific RNA structures for therapeutics and deploying RNA-targeting small-molecule drugs., (© 2022. Springer Nature America, Inc.)
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- 2022
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40. The people behind the papers - Jian Xing, Agnieszka Lukomska, Bruce Rheaume and Ephraim Trakhtenberg.
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Rheaume, Bruce, Jian Xing, Trakhtenberg, Ephraim, and Lukomska, Agnieszka
- Subjects
- *
AXONS , *BIOLOGICAL systems , *CENTRAL nervous system , *NEURAL circuitry , *COMPUTATIONAL biology - Published
- 2023
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- View/download PDF
41. Phenotypically distinguishing ESBL-producing pathogens using paper-based surface enhanced Raman sensors
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Ian M. White, Shannon H. Hilton, Hieu T. Nguyen, Connor Hall, Philip DeShong, and Micaela L. Everitt
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Esbl production ,Antimicrobial susceptibility ,Single sample ,02 engineering and technology ,Computational biology ,Microbial Sensitivity Tests ,Barcode ,01 natural sciences ,Biochemistry ,Article ,beta-Lactamases ,Analytical Chemistry ,law.invention ,law ,Escherichia coli ,Environmental Chemistry ,Humans ,Instrumentation (computer programming) ,Spectroscopy ,Escherichia coli Infections ,Chemistry ,010401 analytical chemistry ,Treatment options ,Paper based ,Surface-enhanced Raman spectroscopy ,021001 nanoscience & nanotechnology ,0104 chemical sciences ,Anti-Bacterial Agents ,0210 nano-technology - Abstract
Antimicrobial stewardship practices are critical in preventing the further erosion of treatment options for bacterial infections. Yet, at the same time, determination of an infection’s antimicrobial susceptibility requires multiple rounds of culture and expensive lab automation systems. In this work, we report the use of paper-based surface enhanced Raman spectroscopy (SERS) sensors and portable instrumentation to phenotypically discriminate multi-drug resistance with fewer culture steps than conventional clinical microbiology. Specifically, we demonstrate the identification of resistance to varying generations of β-lactam antibiotics by detecting the activity of particular β-lactamase enzymes in a multiplexed assay. The method utilizes molecular reporters that consist of β-lactams with SERS barcodes. Hydrolysis of the β-lactam by β-lactamase enzymes in the sample expels the barcode; the released sulfur-containing barcode is then detected via SERS. Using this approach, we demonstrate the differentiation of E. coli strains with (1) extended spectrum β-lactamase (ESBL), (2) narrow-spectrum β-lactamase, and (3) no resistance, using only a single measurement on a single sample. In addition, we experimentally validate an approach to expand the library of reporters through the simple chemical synthesis of new barcoded β-lactams. Importantly, the reported method determines the susceptibility based on phenotypic β-lactamase activity, which is aligned with current microbiology lab standards. This new method will enable the precise selection of effective β-lactam antibiotics (as opposed to defaulting to drugs of last resort) faster than current methods while using simple steps and low-cost portable instrumentation.
- Published
- 2020
42. Genetic testing in inherited endocrine disorders: joint position paper of the European reference network on rare endocrine conditions (Endo-ERN)
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Eggermann T., Elbracht M., Kurth I., Juul A., Johannsen T. H., Netchine I., Mastorakos G., Johannsson G., Musholt T. J., Zenker M., Prawitt D., Pereira A. M., Hiort O., Stefan Riedl, Birgit Rami-Merhar, Greisa Vila, Sabina Baumgartner-Parzner, Walter Bonfig, Claudine Heinrichs, Dominique Maiter, Inge Gies, Martine Cools, Kristina Casteels, Albert Beckers, Sabina Zacharieva, Violeta Iotova, Tomislav Jukic, Dario Rahelic, Vassos Neocleous, Leonidas Phylactou, Michal Krsek, Jan Lebl, Claus Gravholt, Anders Juul, Vallo Tillmann, Vallo Volke, Tapani Ebeling, Thierry Brue, Patrice Rodien, Jérôme Bertherat, Christine Poitou Bernert, Philippe Touraine, Philippe Chanson, Michel Polak, Maithe Tauber, Thomas Eggermann, Joachim Spranger, Dagmar Fuhrer, Thomas Danne, Olaf Hiort, Klaus Mohnike, Dirk Prawitt, Markus Luster, Nicole Reisch, Martin Reincke, Julia Rohayem, Martin Fassnacht, Miklós Tóth, Alessandra Cassio, Sonia Toni, Csilla Krausz, Barbara Piccini, Diego Ferone, Gianni Russo, Luca Persani, Annamaria Colao, Mariacarolina Salerno, Marco Boscaro, Carla Scaroni, Ferruccio Santini, Giovanni Ceccarini, Ezio Ghigo, Iveta Dzivite-Krisane, Vita Rovite, Lauma Janozola, Rasa Verkauskiene, Michael Witsch, James Clark, Johannes Romijn, Thera Links, Nienke Biermasz, Sabine Hannema, Bas Havekes, Hedi Claahsen-van der Grinten, Henri Timmers, Robin Peeters, Gerlof Valk, A A Verrijn Stuart, Harm Haak, Eystein Husebye, Jens Bollerslev, Barbara Jarzab, Agnieszka 'Szypowska, João-Filipe Raposo, Dana Craiu, Doina Piciu, Ludmila Kostalova, Jarmila Vojtková, Tadej Battelino, Roque Cardona-Hernandez, Diego Yeste, Sonia Gaztambide, Anna Nordenström, Neil Gittoes, Trevor Cole, Elizabeth Crowne, Faisal Ahmed, Mohammed Didi, Marta Korbonits, Mehul Dattani, Peter Clayton, Justin Davies, Eggermann, T., Elbracht, M., Kurth, I., Juul, A., Johannsen, T. H., Netchine, I., Mastorakos, G., Johannsson, G., Musholt, T. J., Zenker, M., Prawitt, D., Pereira, A. M., Hiort, O, Salerno, M, Clinical sciences, Growth and Development, Pediatrics, Eggermann T., Elbracht M., Kurth I., Juul A., Johannsen T.H., Netchine I., Mastorakos G., Johannsson G., Musholt T.J., Zenker M., Prawitt D., Pereira A.M., and Hiort O., Stefan Riedl, Birgit Rami-Merhar, Greisa Vila, Sabina Baumgartner-Parzner, Walter Bonfig, Claudine Heinrichs, Dominique Maiter, Inge Gies, Martine Cools, Kristina Casteels, Albert Beckers, Sabina Zacharieva, Violeta Iotova, Tomislav Jukic, Dario Rahelic, Vassos Neocleous, Leonidas Phylactou, Michal Krsek, Jan Lebl, Claus Gravholt, Anders Juul, Vallo Tillmann, Vallo Volke, Tapani Ebeling, Thierry Brue, Patrice Rodien, Jérôme Bertherat, Christine Poitou Bernert, Philippe Touraine, Philippe Chanson, Michel Polak, Maithe Tauber, Thomas Eggermann, Joachim Spranger, Dagmar Fuhrer, Thomas Danne, Olaf Hiort, Klaus Mohnike, Dirk Prawitt, Markus Luster, Nicole Reisch, Martin Reincke, Julia Rohayem, Martin Fassnacht, Miklós Tóth, Alessandra Cassio, Sonia Toni, Csilla Krausz, Barbara Piccini, Diego Ferone, Gianni Russo, Luca Persani, Annamaria Colao, Mariacarolina Salerno, Marco Boscaro, Carla Scaroni, Ferruccio Santini, Giovanni Ceccarini, Ezio Ghigo, Iveta Dzivite-Krisane, Vita Rovite, Lauma Janozola, Rasa Verkauskiene, Michael Witsch, James Clark, Johannes Romijn, Thera Links, Nienke Biermasz, Sabine Hannema, Bas Havekes, Hedi Claahsen-van der Grinten, Henri Timmers, Robin Peeters, Gerlof Valk, A A Verrijn Stuart, Harm Haak, Eystein Husebye, Jens Bollerslev, Barbara Jarzab, Agnieszka 'Szypowska, João-Filipe Raposo, Dana Craiu, Doina Piciu, Ludmila Kostalova, Jarmila Vojtková, Tadej Battelino, Roque Cardona-Hernandez, Diego Yeste, Sonia Gaztambide, Anna Nordenström, Neil Gittoes, Trevor Cole, Elizabeth Crowne, Faisal Ahmed, Mohammed Didi, Marta Korbonits, Mehul Dattani, Peter Clayton, Justin Davies
- Subjects
0301 basic medicine ,Genetic testing ,disorders of sex development ,PREDICTION ,lcsh:Medicine ,CHILDREN ,Review ,VARIANTS ,Hypogonadotropic hypogonadism ,Imprinting disorder ,0302 clinical medicine ,Pharmacology (medical) ,Genetics (clinical) ,Imprinting disorders ,Rare endocrine conditions ,Short stature - glucose and insulin homeostasis - Hypogonadotropic hypogonadism - differences/disorders of sex development ,Medicine(all) ,RISK ,medicine.diagnostic_test ,CHALLENGES ,differences ,High-Throughput Nucleotide Sequencing ,General Medicine ,genetic testing, Imprinting disorders, Rare endocrine conditions, Short stature, glucose and insulin homeostasis, Hypogonadotropic hypogonadism, disorders of sex development ,Mutation (genetic algorithm) ,Rare endocrine condition ,Identification (biology) ,Genetic counseling ,030209 endocrinology & metabolism ,Computational biology ,DIAGNOSIS ,Endocrine System Diseases ,differences/disorders of sex development ,03 medical and health sciences ,Rare Diseases ,BECKWITH-WIEDEMANN SYNDROME ,medicine ,MANAGEMENT ,Endocrine system ,Humans ,business.industry ,Network on ,lcsh:R ,glucose and insulin homeostasis ,Human genetics ,Short stature ,030104 developmental biology ,Mutation ,Position paper ,business ,Short stature - glucose and insulin homeostasis - Abstract
Orphanet journal of rare diseases: OJRD 15(1), 144 (2020). doi:10.1186/s13023-020-01420-w, Published by BioMed Central, London
- Published
- 2020
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43. Whole genome sequence of Vibrio cholerae directly from dried spotted filter paper
- Author
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Paul Adrien, Maria Fookes, Nicholas R. Thomson, Jerome Ateudjieu, Jacques Boncy, Etienne Guenou, Matthew Siever, Stanislas Rebaudet, David A. Sack, Amanda K. Debes, Watipaso Kasambara, Angèle Bénard, Renaud Piarroux, The Wellcome Trust Sanger Institute [Cambridge], University of Buéa, Université de Dschang, Johns Hopkins Bloomberg School of Public Health [Baltimore], Johns Hopkins University (JHU), Assistance Publique - Hôpitaux de Marseille (APHM), Hôpital Européen [Fondation Ambroise Paré - Marseille], Institut Pierre Louis d'Epidémiologie et de Santé Publique (iPLESP), Sorbonne Université (SU)-Institut National de la Santé et de la Recherche Médicale (INSERM), Sorbonne Université (SU), CHU Pitié-Salpêtrière [AP-HP], Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP), Gestionnaire, Hal Sorbonne Université, Institut National de la Santé et de la Recherche Médicale (INSERM)-Sorbonne Université (SU), and Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)
- Subjects
Bacterial Diseases ,0301 basic medicine ,Molecular biology ,[SDV]Life Sciences [q-bio] ,RC955-962 ,Pathology and Laboratory Medicine ,medicine.disease_cause ,El Tor ,Genome ,0302 clinical medicine ,Filter Paper ,Cholera ,Arctic medicine. Tropical medicine ,Medicine and Health Sciences ,DNA extraction ,Vibrio cholerae ,Phylogeny ,Data Management ,Genetics ,biology ,Database and informatics methods ,Cholera toxin ,Sequence analysis ,1. No poverty ,Phylogenetic Analysis ,Genomics ,Bacterial Pathogens ,3. Good health ,Laboratory Equipment ,Phylogenetics ,[SDV] Life Sciences [q-bio] ,Infectious Diseases ,Medical Microbiology ,Engineering and Technology ,Pathogens ,Public aspects of medicine ,RA1-1270 ,Research Article ,Neglected Tropical Diseases ,Paper ,Computer and Information Sciences ,Bioinformatics ,030231 tropical medicine ,Equipment ,Biomolecular isolation ,Microbiology ,03 medical and health sciences ,Extraction techniques ,medicine ,Humans ,Evolutionary Systematics ,Microbial Pathogens ,DNA sequence analysis ,Vibrio ,Taxonomy ,Whole genome sequencing ,Evolutionary Biology ,Sequence Assembly Tools ,Bacteria ,Whole Genome Sequencing ,Organisms ,Public Health, Environmental and Occupational Health ,Biology and Life Sciences ,Computational Biology ,Outbreak ,Tropical Diseases ,Genome Analysis ,medicine.disease ,biology.organism_classification ,DNA isolation ,Research and analysis methods ,Molecular biology techniques ,030104 developmental biology ,13. Climate action ,Genome, Bacterial - Abstract
Background Global estimates for cholera annually approximate 4 million cases worldwide with 95,000 deaths. Recent outbreaks, including Haiti and Yemen, are reminders that cholera is still a global health concern. Cholera outbreaks can rapidly induce high death tolls by overwhelming the capacity of health facilities, especially in remote areas or areas of civil unrest. Recent studies demonstrated that stool specimens preserved on filter paper facilitate molecular analysis of Vibrio cholerae in resource limited settings. Specimens preserved in a rapid, low-cost, safe and sustainable manner for sequencing provides previously unavailable data about circulating cholera strains. This may ultimately contribute new information to shape public policy response on cholera control and elimination. Methodology/Principal findings Whole genome sequencing (WGS) recovered close to a complete sequence of the V. cholerae O1 genome with satisfactory genome coverage from stool specimens enriched in alkaline peptone water (APW) and V. cholerae culture isolates, both spotted on filter paper. The minimum concentration of V. cholerae DNA sufficient to produce quality genomic information was 0.02 ng/μL. The genomic data confirmed the presence or absence of genes of epidemiological interest, including cholera toxin and pilus loci. WGS identified a variety of diarrheal pathogens from APW-enriched specimen spotted filter paper, highlighting the potential for this technique to explore the gut microbiome, potentially identifying co-infections, which may impact the severity of disease. WGS demonstrated that these specimens fit within the current global cholera phylogenetic tree, identifying the strains as the 7th pandemic El Tor. Conclusions WGS results allowed for mapping of short reads from APW-enriched specimen and culture isolate spotted filter papers. This provided valuable molecular epidemiological sequence information on V. cholerae strains from remote, low-resource settings. These results identified the presence of co-infecting pathogens while providing rare insight into the specific V. cholerae strains causing outbreaks in cholera-endemic areas., Author summary Cholera affects more than 4 million people globally every year; people predominantly living in poverty or in resource-constrained conditions including political crises or natural disasters. Cholera’s typical presentation is characterized by rapid onset of acute watery diarrhea and vomiting which can progress from watery stool to shock in as little as four hours. Laboratory conditions needed for culture confirmation and strain preservation are rarely to never present in these affected areas. In fact, many cholera endemic areas in Sub-Saharan African are so remote that even treatment response alone is often challenging. Here we present the genomic analysis of DNA extracted from dried filter paper, which is a low-cost, low-tech and sustainable method. Previously this method has facilitated cholera confirmation by PCR, but we demonstrate that this method is also suitable for whole genome sequencing and subsequent strain characterization by presenting the analysis of samples from an outbreak in a remote area of Cameroon. This method will facilitate the understanding of the molecular epidemiology in cholera-prone areas, which were previously too challenging to attempt. It also introduces a method that can be used on a broader scale for diarrheal disease surveillance, including providing a window into co-infection and microbiome analyses.
- Published
- 2019
44. Fully Dried Two-Dimensional Paper Network for Enzymatically Enhanced Detection of Nucleic Acid Amplicons
- Author
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Kristin M. Byers, Jacqueline C. Linnes, HyunDae D. Cho, and Anna R. Bird
- Subjects
Chemistry ,General Chemical Engineering ,010401 analytical chemistry ,02 engineering and technology ,General Chemistry ,Computational biology ,Amplicon ,021001 nanoscience & nanotechnology ,01 natural sciences ,Article ,0104 chemical sciences ,Nucleic acid ,0210 nano-technology ,QD1-999 - Abstract
Two-dimensional paper networks (2DPNs) have enabled the use of paper-based platforms to perform multistep immunoassays for detection of pathogenic diseases at the point-of-care. To date, however, detection has required the user to provide multiple signal enhancement solutions and been limited to protein targets. We solve these challenges by using mathematical equations to guide the device design of a novel 2DPN, which leverages multiple fluidic inputs to apply fully dried solutions of hydrogen peroxide, diaminobenzidine, and horseradish peroxidase signal enhancement reagents to enhance the limit-of-detection of numerous nucleic acid products. Upon rehydration in our unique 2DPN design, the dried signal enhancement solution reduces the limit-of-detection (LOD) of the device to 5 × 1011 nucleic acid copies/mL without increasing false positive detection. Our easy-to-use device retains activity after 28 days of dry storage and produces reliable signal enhancement 40 min after sample application. The fully integrated device demonstrated versatility in its ability to detect double-stranded and single-stranded DNA samples, as well as peptide nucleic acids.
- Published
- 2020
45. Bioinformatics of genome regulation and structure – 2020 papers collection
- Author
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Yuriy L. Orlov, Ralf Hofestädt, Oxana B. Dobrovolskaya, and Ming Chen
- Subjects
Structure (mathematical logic) ,Editorial ,Genome regulation ,General Medicine ,Computational biology ,Biology ,TP248.13-248.65 ,Biotechnology - Published
- 2020
46. Next-generation sequencing for BCR-ABL1 kinase domain mutation testing in patients with chronic myeloid leukemia: a position paper
- Author
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Sara Galimberti, Fabio Stagno, Patrizia Pregno, Monica Bocchia, Mario Tiribelli, Elisabetta Abruzzese, Giuseppe Saglio, Luigiana Luciano, Alessandra Iurlo, Gianantonio Rosti, Giovanni Barosi, Massimiliano Bonifacio, Massimo Breccia, Antonella Gozzini, Simona Soverini, Paolo Vigneri, Soverini S., Abruzzese E., Bocchia M., Bonifacio M., Galimberti S., Gozzini A., Iurlo A., Luciano L., Pregno P., Rosti G., Saglio G., Stagno F., Tiribelli M., Vigneri P., Barosi G., and Breccia M.
- Subjects
Cancer Research ,medicine.medical_specialty ,Sanger sequencing ,DNA Mutational Analysis ,Fusion Proteins, bcr-abl ,Computational biology ,Review ,lcsh:RC254-282 ,DNA sequencing ,symbols.namesake ,Internal medicine ,Leukemia, Myelogenous, Chronic, BCR-ABL Positive ,hemic and lymphatic diseases ,Medicine ,Humans ,Molecular Biology ,Protein Kinase Inhibitors ,Hematology ,business.industry ,lcsh:RC633-647.5 ,Patient Selection ,Chronic myeloid leukemia ,Myeloid leukemia ,High-Throughput Nucleotide Sequencing ,BCR-ABL1 mutation ,lcsh:Diseases of the blood and blood-forming organs ,Protein-Tyrosine Kinases ,lcsh:Neoplasms. Tumors. Oncology. Including cancer and carcinogens ,Oncology ,Protein kinase domain ,Mutation (genetic algorithm) ,Mutation ,symbols ,Mutation testing ,Next-generation sequencing ,Position paper ,business - Abstract
BCR-ABL1 kinase domain (KD) mutation status is considered to be an important element of clinical decision algorithms for chronic myeloid leukemia (CML) patients who do not achieve an optimal response to tyrosine kinase inhibitors (TKIs). Conventional Sanger sequencing is the method currently recommended to test BCR-ABL1 KD mutations. However, Sanger sequencing has limited sensitivity and cannot always discriminate between polyclonal and compound mutations. The use of next-generation sequencing (NGS) is increasingly widespread in diagnostic laboratories and represents an attractive alternative. Currently available data on the clinical impact of NGS-based mutational testing in CML patients do not allow recommendations with a high grade of evidence to be prepared. This article reports the results of a group discussion among an ad hoc expert panel with the objective of producing recommendations on the appropriateness of clinical decisions about the indication for NGS, the performance characteristics of NGS platforms, and the therapeutic changes that could be applied based on the use of NGS in CML. Overall, these recommendations might be employed to inform clinicians about the practical use of NGS in CML.
- Published
- 2019
47. Autonomous Lab-on-Paper for Multiplexed, CRISPR-based Diagnostics of SARS-CoV-2
- Author
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Enrique Ballesteros, Changchun Liu, Ziyue Li, Maroun M. Sfeir, Xiong Ding, and Kun Yin
- Subjects
Biomedical Engineering ,Recombinase Polymerase Amplification ,Bioengineering ,Computational biology ,Biology ,medicine.disease_cause ,Biochemistry ,Sensitivity and Specificity ,Virus ,Article ,03 medical and health sciences ,0302 clinical medicine ,medicine ,CRISPR ,Humans ,Multiplex ,Clustered Regularly Interspaced Short Palindromic Repeats ,030212 general & internal medicine ,Pandemics ,030304 developmental biology ,Coronavirus ,0303 health sciences ,SARS-CoV-2 ,COVID-19 ,General Chemistry ,Nucleic acid amplification technique ,Molecular diagnostics ,Reverse transcriptase ,RNA, Viral ,CRISPR-Cas Systems ,Nucleic Acid Amplification Techniques - Abstract
The COVID-19 pandemic, caused by severe acute respiratory coronavirus 2 (SARS-CoV-2), has become a public health emergency and widely spread around the world. Rapid, accurate and early diagnosis of COVID-19 infection plays a crucial role in breaking this pandemic. However, the detection accuracy is limited for current single-gene diagnosis of SARS-CoV-2. Herein, we develop an autonomous lab-on-paper platform for multiplex gene diagnosis of SARS-CoV-2 by combining reverse transcription recombinase polymerase amplification (RT-RPA) and CRISPR-Cas12a detection. The autonomous lab-on-paper is capable of simultaneously detecting nucleoprotein (N) gene and spike (S) gene of SARS-CoV-2 virus as well as Human housekeeping RNAse P gene (an internal control) in a single clinical sample. With the developed platform, 10(2) copies viral RNA per test can be detected within one hour. Also, the lab-on-paper platform has been used to detect 21 swab clinical samples and obtains a comparable performance to the conventional RT-PCR method. Thus, the developed lab-on-paper platform holds great potential for rapid, sensitive, reliable, multiple molecular diagnostics of COVID-19 and other infectious diseases in resource-limited settings.
- Published
- 2021
48. Awarded papers focus on solving basic algorithmic problems, with applications in bioinformatics
- Subjects
Computational biology ,RNA ,College teachers ,Algorithms ,Algorithm ,Business ,Health ,Health care industry - Abstract
2022 NOV 13 (NewsRx) -- By a News Reporter-Staff News Editor at Medical Letter on the CDC & FDA -- The prize for the best research article of the Workshop [...]
- Published
- 2022
49. FnCas9-based CRISPR diagnostic for rapid and accurate detection of major SARS-CoV-2 variants on a paper strip
- Author
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Ranjeet Maurya, Aparna S, Debojyoti Chakraborty, Souvik Maiti, Rhythm Phutela, Janani Srinivasa Vasudevan, Sundaram Acharya, Asgar Hussain Ansari, Akshay Kanakan, Sneha Gulati, Manoj Kumar, Mohd Azhar, Poorti Kathpalia, Jayaram Murthy, and Rajesh Pandey
- Subjects
0301 basic medicine ,Pregnancy test ,QH301-705.5 ,Science ,Computational biology ,Biology ,medicine.disease_cause ,General Biochemistry, Genetics and Molecular Biology ,Virus ,Lateral flow test ,03 medical and health sciences ,chemistry.chemical_compound ,0302 clinical medicine ,medicine ,CRISPR ,Humans ,Clustered Regularly Interspaced Short Palindromic Repeats ,N501Y ,Biology (General) ,Mutation ,variants ,General Immunology and Microbiology ,SARS-CoV-2 ,General Neuroscience ,Nucleic acid sequence ,COVID-19 ,General Medicine ,FnCas9 ,Tools and Resources ,030104 developmental biology ,Epidemiology and Global Health ,chemistry ,FELUDA ,COVID-19 Nucleic Acid Testing ,Nucleic acid ,Medicine ,CRISPR-Cas Systems ,030217 neurology & neurosurgery ,DNA ,CRISPRDx - Abstract
The COVID-19 pandemic originating in the Wuhan province of China in late 2019 has impacted global health, causing increased mortality among elderly patients and individuals with comorbid conditions. During the passage of the virus through affected populations, it has undergone mutations, some of which have recently been linked with increased viral load and prognostic complexities. Several of these variants are point mutations that are difficult to diagnose using the gold standard quantitative real-time PCR (qRT-PCR) method and necessitates widespread sequencing which is expensive, has long turn-around times, and requires high viral load for calling mutations accurately. Here, we repurpose the high specificity of Francisella novicida Cas9 (FnCas9) to identify mismatches in the target for developing a lateral flow assay that can be successfully adapted for the simultaneous detection of SARS-CoV-2 infection as well as for detecting point mutations in the sequence of the virus obtained from patient samples. We report the detection of the S gene mutation N501Y (present across multiple variant lineages of SARS-CoV-2) within an hour using lateral flow paper strip chemistry. The results were corroborated using deep sequencing on multiple wild-type (n = 37) and mutant (n = 22) virus infected patient samples with a sensitivity of 87% and specificity of 97%. The design principle can be rapidly adapted for other mutations (as shown also for E484K and T716I) highlighting the advantages of quick optimization and roll-out of CRISPR diagnostics (CRISPRDx) for disease surveillance even beyond COVID-19. This study was funded by Council for Scientific and Industrial Research, India., eLife digest SARS-CoV-2, the virus responsible for COVID-19, has a genome made of RNA (a nucleic acid similar to DNA) that can mutate, potentially making the disease more transmissible, and more lethal. Most countries have monitored the rise of mutated strains using a technique called next generation sequencing (NGS), which is time-consuming, expensive and requires skilled personnel. Sometimes the mutations to the virus are so small that they can only be detected using NGS. Finding cheaper, simpler and faster SARS-CoV-2 tests that can reliably detect mutated forms of the virus is crucial for public health authorities to monitor and manage the spread of the virus. Lateral flow tests (the same technology used in many pregnancy tests) are typically cheap, fast and simple to use. Typically, lateral flow assay strips have a band of immobilised antibodies that bind to a specific protein (or antigen). If a sample contains antigen molecules, these will bind to the immobilised antibodies, causing a chemical reaction that changes the colour of the strip and giving a positive result. However, lateral flow tests that use antibodies cannot easily detect nucleic acids, such as DNA or RNA, let alone mutations in them. To overcome this limitation, lateral flow assays can be used to detect a protein called Cas9, which, in turn, is able to bind to nucleic acids with specific sequences. Small changes in the target sequence change how well Cas9 binds to it, meaning that, in theory, this approach could be used to detect small mutations in the SARS-CoV-2 virus. Kumar et al. made a lateral flow test that could detect a Cas9 protein that binds to a nucleic acid sequence found in a specific mutant strain of SARS-CoV-2. This Cas9 was highly sensitive to changes in its target sequence, so a small mutation in the target nucleic acid led to the protein binding less strongly, and the signal from the lateral flow test being lost. This meant that the lateral flow test designed by Kumar et al. could detect mutations in the SARS-CoV-2 virus at a fraction of the price of NGS approaches if used only for diagnosis. The lateral flow test was capable of detecting mutant viruses in patient samples too, generating a colour signal within an hour of a positive sample being run through the assay. The test developed by Kumar et al. could offer public health authorities a quick and cheap method to monitor the spread of mutant SARS-CoV-2 strains; as well as a way to determine vaccine efficacy against new strains.
- Published
- 2021
50. Machine learning methods for prediction of cancer driver genes: a survey paper
- Author
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Renan Andrades and Mariana Recamonde-Mendoza
- Subjects
Genomics (q-bio.GN) ,FOS: Computer and information sciences ,Computer Science - Machine Learning ,J.3 ,Computational Biology ,Oncogenes ,Machine Learning (cs.LG) ,Machine Learning ,Neoplasms ,FOS: Biological sciences ,Mutation ,Humans ,Quantitative Biology - Genomics ,Molecular Biology ,Algorithms ,Information Systems - Abstract
Identifying the genes and mutations that drive the emergence of tumors is a critical step to improving our understanding of cancer and identifying new directions for disease diagnosis and treatment. Despite the large volume of genomics data, the precise detection of driver mutations and their carrying genes, known as cancer driver genes, from the millions of possible somatic mutations remains a challenge. Computational methods play an increasingly important role in discovering genomic patterns associated with cancer drivers and developing predictive models to identify these elements. Machine learning (ML), including deep learning, has been the engine behind many of these efforts and provides excellent opportunities for tackling remaining gaps in the field. Thus, this survey aims to perform a comprehensive analysis of ML-based computational approaches to identify cancer driver mutations and genes, providing an integrated, panoramic view of the broad data and algorithmic landscape within this scientific problem. We discuss how the interactions among data types and ML algorithms have been explored in previous solutions and outline current analytical limitations that deserve further attention from the scientific community. We hope that by helping readers become more familiar with significant developments in the field brought by ML, we may inspire new researchers to address open problems and advance our knowledge towards cancer driver discovery.
- Published
- 2021
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