Preprints in Motion: Tracking Changes Between Posting And
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What Is Biomath?
What is Biomath? Summary Biomathematics covers a wide range of activities at the interface between the mathematical and biological sciences. Depending on who you talk to, it might have a different name, including mathematical biology, systems biology, quantitative biology or theoretical biology. The focus of our biomathematics program is on building and using mathematical models to describe and analyze biological systems. Often this involves the analysis of biological data, which typically means using statistical approaches together with the models. In many cases, our models are mechanistic, meaning that their components represent biological processes, although many of us also use models that are more statistical in nature. More In-Depth Biomathematics is the use of mathematical models to help understand phenomena in biology. Modern experimental biology is very good at taking biological systems apart (at all levels of organization, from genome to global nutrient cycling), into components simple enough that their structure and function can be studied in isolation. Dynamic models are a way to put the pieces back together, with equations that represent the system’s components, processes, and the structure of their interactions. Mathematical models are important tools in basic scientific research in many areas of biology, including physiology, cellular biology, developmental biology, ecology, evolution, toxicology, epidemiology, immunology, natural resource management, and conservation biology. The results obtained from analysis and simulation -
Ten Simple Rules to Consider Regarding Preprint Submission
EDITORIAL Ten simple rules to consider regarding preprint submission Philip E. Bourne1*, Jessica K. Polka2, Ronald D. Vale3, Robert Kiley4 1 Office of the Director, The National Institutes of Health, Bethesda, Maryland, United States of America, 2 Whitehead Institute, Cambridge, Massachusetts, United States of America, 3 Department of Cellular and Molecular Pharmacology and the Howard Hughes Medical Institute, University of California San Francisco, San Francisco, California, United States of America, 4 Wellcome Library, The Wellcome Trust, London, United Kingdom * [email protected] For the purposes of these rules, a preprint is defined as a complete written description of a body of scientific work that has yet to be published in a journal. Typically, a preprint is a research article, editorial, review, etc. that is ready to be submitted to a journal for peer review or is under review. It could also be a commentary, a report of negative results, a large data set and its description, and more. Finally, it could also be a paper that has been peer reviewed and either is awaiting formal publication by a journal or was rejected, but the authors are willing to make the content public. In short, a preprint is a research output that has not completed a typi- cal publication pipeline but is of value to the community and deserving of being easily discov- ered and accessed. We also note that the term preprint is an anomaly, since there may not be a a1111111111 print version at all. The rules that follow relate to all these preprint types unless otherwise a1111111111 noted. -
1 the Challenges Facing Genomic Informatics
1 The Challenges Facing Genomic Informatics Temple F. Smith What are these areas of intense research labeled bioinformatics and functional genomics? If we take literally much of the recently published "news and views," it seems that the often stated claim that the last century was the century of physics, whereas the twenty-first will be the century of biology, rests significantly on these new research areas. We might therefore ask: What is new about them? After all, compu- tational or mathematical biology has been around for a long time. Surely much of bioinformatics, particularly that associated with evolution and genetic analyses, does not appear very new. In fact, the related work of researchers like R. A. Fisher, J. B. S. Haldane, and SewellWright dates nearly to the beginning of the 1900s. The modem analytical approaches to genetics, evolution, and ecology rest directly on their and similar work. Even genetic mapping easily dates to the 1930s, with the work of T. S. Painter and his students of Drosophila (still earlier if you include T. H. Morgan's work on X-linked markers in the fly). Thus a short historical review might provide a useful perspective on this anticipated century of biology and allow us to view the future from a firmer foundation. First of all, it should be helpful to recognize that it was very early in the so-called century of physics that modem biology began, with a paper read by Hermann Muller at a 1921meeting in Toronto. Muller, a student of Morgan's, stated that although of submicroscopic size, the gene was clearly a physical particle of complex structure, not just a working construct! Muller noted that the gene is unique from its product, and that it is normally duplicated unchanged, but once mutated, the new form is in turn duplicated faithfully. -
Estimated Costs of Implementing an Open Access Policy at a Private Foundation
bioRxiv preprint doi: https://doi.org/10.1101/128413; this version posted August 17, 2017. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. Estimated costs of implementing an open access policy at a private foundation 1 2 Carly Strasser and Eesha Khare 1 Gordon and Betty Moore Foundation, Palo Alto, California, USA 2 Harvard University, Cambridge, Massachusetts, USA Corresponding author: Carly Strasser1 Email address: [email protected] 1 bioRxiv preprint doi: https://doi.org/10.1101/128413; this version posted August 17, 2017. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. Abstract Background: The Gordon and Betty Moore Foundation (GBMF) was interested in understanding the potential effects of a policy requiring open access to peer-reviewed publications resulting from the research the foundation funds. Methods: We collected data on more than 2000 publications in over 500 journals that were generated by GBMF grantees since 2001. We then examined the journal policies to establish how two possible open -
Catalyzed Synthesis of Zinc Clays by Prebiotic Central Metabolites
bioRxiv preprint doi: https://doi.org/10.1101/075176; this version posted September 14, 2016. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license. Catalyzed Synthesis of Zinc Clays by Prebiotic Central Metabolites Ruixin Zhoua, Kaustuv Basub, Hyman Hartmanc, Christopher J. Matochad, S. Kelly Searsb, Hojatollah Valib,e, and Marcelo I. Guzman*,a *Corresponding Author: [email protected] aDepartment of Chemistry, University of Kentucky, Lexington, KY, 40506, USA; bFacility for Electron Microscopy Research, McGill University, 3640 University Street, Montreal, Quebec H3A 0C7, Canada; cEarth, Atmosphere, and Planetary Science Department, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; dDepartment of Plant and Soil Sciences, University of Kentucky, Lexington, KY, 40546, USA; eDepartment of Anatomy & Cell Biology, 3640 University Street, Montreal H3A 0C7, Canada The authors declare no competing financial interest. Number of text pages: 20 Number of Figures: 9 Number of Tables: 0 bioRxiv preprint doi: https://doi.org/10.1101/075176; this version posted September 14, 2016. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license. Abstract How primordial metabolic networks such as the reverse tricarboxylic acid (rTCA) cycle and clay mineral catalysts coevolved remains a mystery in the puzzle to understand the origin of life. -
Downloads Presented on the Abstract Page
bioRxiv preprint doi: https://doi.org/10.1101/2020.04.27.063578; this version posted April 28, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY 4.0 International license. A systematic examination of preprint platforms for use in the medical and biomedical sciences setting Jamie J Kirkham1*, Naomi Penfold2, Fiona Murphy3, Isabelle Boutron4, John PA Ioannidis5, Jessica K Polka2, David Moher6,7 1Centre for Biostatistics, Manchester Academic Health Science Centre, University of Manchester, Manchester, United Kingdom. 2ASAPbio, San Francisco, CA, USA. 3Murphy Mitchell Consulting Ltd. 4Université de Paris, Centre of Research in Epidemiology and Statistics (CRESS), Inserm, Paris, F-75004 France. 5Meta-Research Innovation Center at Stanford (METRICS) and Departments of Medicine, of Epidemiology and Population Health, of Biomedical Data Science, and of Statistics, Stanford University, Stanford, CA, USA. 6Centre for Journalology, Clinical Epidemiology Program, Ottawa Hospital Research Institute, Ottawa, Canada. 7School of Epidemiology and Public Health, Faculty of Medicine, University of Ottawa, Ottawa, Canada. *Corresponding Author: Professor Jamie Kirkham Centre for Biostatistics Faculty of Biology, Medicine and Health The University of Manchester Jean McFarlane Building Oxford Road Manchester, M13 9PL, UK Email: [email protected] Tel: +44 (0)161 275 1135 bioRxiv preprint doi: https://doi.org/10.1101/2020.04.27.063578; this version posted April 28, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. -
Systems Biology Behind Immunoprotection of Both Sheep and Goats After 2 Sungri/96 PPRV Vaccination
bioRxiv preprint doi: https://doi.org/10.1101/2020.08.14.252056; this version posted August 15, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY 4.0 International license. 1 Systems Biology behind immunoprotection of both Sheep and Goats after 2 Sungri/96 PPRV vaccination 3 Sajad Ahmad Wani1,2#, Manas Ranjan Praharaj3#, Amit R Sahu1, Raja Ishaq Nabi 4 Khan1, Kaushal Kishor Rajak1, Dhanavelu Muthuchelvan4, Aditya Sahoo5, Bina 5 Mishra1, R. K. Singh1*, Bishnu Prasad Mishra1* and Ravi Kumar Gandham3* 6 1 ICAR-Indian Veterinary Research Institute (IVRI), Bareilly, India 7 2 The Ohio State University, Columbus, OH, United States 8 3 DBT-National Institute of Animal Biotechnology, Hyderabad, India 9 4 ICAR-Indian Veterinary Research Institute (IVRI), Mukteswar, India 10 5 ICAR- Directorate of Foot and Mouth Disease, Mukteswar, India 11 # Equal Contributors 12 * Corresponding Authors: Ravi Kumar Gandham, [email protected] 13 Bishnu Prasad Mishra, [email protected] 14 Raj Kumar Singh, [email protected] 15 16 Abstract 17 Immune response is a highly coordinated cascade involving all the subsets of 18 PBMCs. In this study, RNA-Seq analysis of PBMC subsets - CD4+, CD8+, CD14+, 19 CD21+ and CD335+ cells from day 0 and day 5 of Sungri/96 Peste des Petits 20 Ruminants vaccinated sheep and goats was done to delineate the systems biology 21 behind immune - protection of the vaccine in sheep and goats. Assessment of the 22 immune response processes enriched by the differentially expressed genes in all the 23 subsets suggested a strong dysregulation towards development of early inflammatory 24 microenvironment, which is very much required for differentiation of monocytes to 25 macrophages, and for activation and migration of dendritic cells into the draining lymph 26 nodes. -
Publication Rate and Citation Counts for Preprints Released During the COVID-19 Pandemic: the Good, the Bad and the Ugly
Publication rate and citation counts for preprints released during the COVID-19 pandemic: the good, the bad and the ugly Diego Añazco1,*, Bryan Nicolalde1,*, Isabel Espinosa1, Jose Camacho2, Mariam Mushtaq1, Jimena Gimenez1 and Enrique Teran1 1 Colegio de Ciencias de la Salud, Universidad San Francisco de Quito, Quito, Ecuador 2 Colegio de Ciencias e Ingenieria, Universidad San Francisco de Quito, Quito, Ecuador * These authors contributed equally to this work. ABSTRACT Background: Preprints are preliminary reports that have not been peer-reviewed. In December 2019, a novel coronavirus appeared in China, and since then, scientific production, including preprints, has drastically increased. In this study, we intend to evaluate how often preprints about COVID-19 were published in scholarly journals and cited. Methods: We searched the iSearch COVID-19 portfolio to identify all preprints related to COVID-19 posted on bioRxiv, medRxiv, and Research Square from January 1, 2020, to May 31, 2020. We used a custom-designed program to obtain metadata using the Crossref public API. After that, we determined the publication rate and made comparisons based on citation counts using non-parametric methods. Also, we compared the publication rate, citation counts, and time interval from posting on a preprint server to publication in a scholarly journal among the three different preprint servers. Results: Our sample included 5,061 preprints, out of which 288 were published in scholarly journals and 4,773 remained unpublished (publication rate of 5.7%). We found that articles published in scholarly journals had a significantly higher total citation count than unpublished preprints within our sample (p < 0.001), and that preprints that were eventually published had a higher citation count as preprints Submitted 25 September 2020 20 January 2021 when compared to unpublished preprints (p < 0.001). -
QUANTITATIVE BIOLOGY This Interdiscplinary Major Bridges the Space Between Biology, Chemistry, Data Science, and Engineering
QUANTITATIVE BIOLOGY This interdiscplinary major bridges the space between biology, chemistry, data science, and engineering. It allows students interested in studying the life sciences to achieve a fuller background in the quantitative sciences such as computer science and statistics that are essential for modern data-driven biological science. The Quantitative Biology major is designed to train students to be both high-level biologists and high-level data analysts. Students will take an introductory seminar, participate in undergraduate research, and write an honors thesis. BACHELOR OF SCIENCE (BS) GENERAL OVERVIEW Seven lower division courses: One advanced biology course. Examples include: General Biology — Organismal Biology and Evolution Evolution and Population Genetics General Biology — Cell Biology and Physiology Molecular Biology Introduction to Quantitative Biology Seminar General Chemistry A At least two upper division courses. Examples include: Introduction to Programming Cellular and Molecular Neuroscience Data Structures and Object Oriented Design Mathematics of Machine Learning Calculus I Fundamentals of Physics I Choose one Capstone course from the following: Choose five courses from the following areas: Computational Genome Analysis Structural Bioinformatics: From Atoms to Cells Physics Chemistry Research Experience: Mathematics Students are required to enroll in directed Computer Science research in a lab approved by the Quantitative Biology Executive Committee or assigned faculty adviser EXPERIENTIAL OPPORTUNITIES Freshman -
Tracking the Popularity and Outcomes of All Biorxiv Preprints
1 Meta-Research: Tracking the popularity and outcomes of all bioRxiv 2 preprints 3 Richard J. Abdill1 and Ran Blekhman1,2 4 1 – Department of Genetics, Cell Biology, and Development, University of Minnesota, 5 Minneapolis, MN 6 2 – Department of Ecology, Evolution, and Behavior, University of Minnesota, St. Paul, 7 MN 8 9 ORCID iDs 10 RJA: 0000-0001-9565-5832 11 RB: 0000-0003-3218-613X 12 13 Correspondence 14 Ran Blekhman, PhD 15 University of Minnesota 16 MCB 6-126 17 420 Washington Avenue SE 18 Minneapolis, MN 55455 19 Email: [email protected] 1 20 Abstract 21 The growth of preprints in the life sciences has been reported widely and is 22 driving policy changes for journals and funders, but little quantitative information has 23 been published about preprint usage. Here, we report how we collected and analyzed 24 data on all 37,648 preprints uploaded to bioRxiv.org, the largest biology-focused preprint 25 server, in its first five years. The rate of preprint uploads to bioRxiv continues to grow 26 (exceeding 2,100 in October 2018), as does the number of downloads (1.1 million in 27 October 2018). We also find that two-thirds of preprints posted before 2017 were later 28 published in peer-reviewed journals, and find a relationship between the number of 29 downloads a preprint has received and the impact factor of the journal in which it is 30 published. We also describe Rxivist.org, a web application that provides multiple ways 31 to interact with preprint metadata. 32 Introduction 33 In the 30 days of September 2018, four leading biology journals – The Journal of 34 Biochemistry, PLOS Biology, Genetics and Cell – published 85 full-length research 35 articles. -
Gender Disparity in Computational Biology Research Publications
bioRxiv preprint doi: https://doi.org/10.1101/070631; this version posted August 26, 2016. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY 4.0 International license. Gender disparity in computational biology research publications Kevin S. Bonham and Melanie I. Stefan 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 positions, 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. Intro There is ample literature on the underrepresentation of women in STEM fields and the biases contributing to it. Those biases, though often subtle, are pervasive in several ways: they are often held and perpetuated by both men and women, and they are apparent across all aspects of academic and scientific practice. -
Preprinting Microbiology
bioRxiv preprint doi: https://doi.org/10.1101/110858; this version posted April 21, 2017. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY 4.0 International license. Preprinting Microbiology Patrick D. Schloss† † To whom correspondence should be addressed: [email protected]; Department of Microbiology and Immunology, University of Michigan, Ann Arbor, MI Format: Perspective Counts: ~5600 words plus 50 references, 1 figure, and a 150 word abstract 1 bioRxiv preprint doi: https://doi.org/10.1101/110858; this version posted April 21, 2017. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY 4.0 International license. 1 Abstract 2 The field of microbiology has experienced significant growth due to transformative advances in 3 technology and the influx of scientists driven by a curiosity to understand how microbes sustain 4 myriad biochemical processes that maintain the Earth. With this explosion in scientific output, a 5 significant bottleneck has been the ability to rapidly disseminate new knowledge to peers and the 6 public. Preprints have emerged as a tool that a growing number of microbiologists are using to 7 overcome this bottleneck. Posting preprints can help to transparently recruit a more diverse pool 8 of reviewers prior to submitting to a journal for formal peer-review. Although use of preprints is 9 still limited in the biological sciences, early indications are that preprints are a robust tool that can 10 complement and enhance peer-reviewed publications.