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RECENT ADVANCES in BIOLOGY, BIOPHYSICS, BIOENGINEERING and COMPUTATIONAL CHEMISTRY
RECENT ADVANCES in BIOLOGY, BIOPHYSICS, BIOENGINEERING and COMPUTATIONAL CHEMISTRY Proceedings of the 5th WSEAS International Conference on CELLULAR and MOLECULAR BIOLOGY, BIOPHYSICS and BIOENGINEERING (BIO '09) Proceedings of the 3rd WSEAS International Conference on COMPUTATIONAL CHEMISTRY (COMPUCHEM '09) Puerto De La Cruz, Tenerife, Canary Islands, Spain December 14-16, 2009 Recent Advances in Biology and Biomedicine A Series of Reference Books and Textbooks Published by WSEAS Press ISSN: 1790-5125 www.wseas.org ISBN: 978-960-474-141-0 RECENT ADVANCES in BIOLOGY, BIOPHYSICS, BIOENGINEERING and COMPUTATIONAL CHEMISTRY Proceedings of the 5th WSEAS International Conference on CELLULAR and MOLECULAR BIOLOGY, BIOPHYSICS and BIOENGINEERING (BIO '09) Proceedings of the 3rd WSEAS International Conference on COMPUTATIONAL CHEMISTRY (COMPUCHEM '09) Puerto De La Cruz, Tenerife, Canary Islands, Spain December 14-16, 2009 Recent Advances in Biology and Biomedicine A Series of Reference Books and Textbooks Published by WSEAS Press www.wseas.org Copyright © 2009, by WSEAS Press All the copyright of the present book belongs to the World Scientific and Engineering Academy and Society Press. All rights reserved. No part of this publication may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, electronic, mechanical, photocopying, recording, or otherwise, without the prior written permission of the Editor of World Scientific and Engineering Academy and Society Press. All papers of the present volume were peer reviewed -
Applied Category Theory for Genomics – an Initiative
Applied Category Theory for Genomics { An Initiative Yanying Wu1,2 1Centre for Neural Circuits and Behaviour, University of Oxford, UK 2Department of Physiology, Anatomy and Genetics, University of Oxford, UK 06 Sept, 2020 Abstract The ultimate secret of all lives on earth is hidden in their genomes { a totality of DNA sequences. We currently know the whole genome sequence of many organisms, while our understanding of the genome architecture on a systematic level remains rudimentary. Applied category theory opens a promising way to integrate the humongous amount of heterogeneous informations in genomics, to advance our knowledge regarding genome organization, and to provide us with a deep and holistic view of our own genomes. In this work we explain why applied category theory carries such a hope, and we move on to show how it could actually do so, albeit in baby steps. The manuscript intends to be readable to both mathematicians and biologists, therefore no prior knowledge is required from either side. arXiv:2009.02822v1 [q-bio.GN] 6 Sep 2020 1 Introduction DNA, the genetic material of all living beings on this planet, holds the secret of life. The complete set of DNA sequences in an organism constitutes its genome { the blueprint and instruction manual of that organism, be it a human or fly [1]. Therefore, genomics, which studies the contents and meaning of genomes, has been standing in the central stage of scientific research since its birth. The twentieth century witnessed three milestones of genomics research [1]. It began with the discovery of Mendel's laws of inheritance [2], sparked a climax in the middle with the reveal of DNA double helix structure [3], and ended with the accomplishment of a first draft of complete human genome sequences [4]. -
ISMB 2008 Toronto
ISMB 2008 Toronto The Harvard community has made this article openly available. Please share how this access benefits you. Your story matters Citation Linial, Michal, Jill P. Mesirov, B. J. Morrison McKay, and Burkhard Rost. 2008. ISMB 2008 Toronto. PLoS Computational Biology 4(6): e1000094. Published Version doi:10.1371/journal.pcbi.1000094 Citable link http://nrs.harvard.edu/urn-3:HUL.InstRepos:11213310 Terms of Use This article was downloaded from Harvard University’s DASH repository, and is made available under the terms and conditions applicable to Other Posted Material, as set forth at http:// nrs.harvard.edu/urn-3:HUL.InstRepos:dash.current.terms-of- use#LAA Message from ISCB ISMB 2008 Toronto Michal Linial1,2, Jill P. Mesirov1,3, BJ Morrison McKay1*, Burkhard Rost1,4 1 International Society for Computational Biology (ISCB), University of California San Diego, La Jolla, California, United States of America, 2 Sudarsky Center, The Hebrew University of Jerusalem, Jerusalem, Israel, 3 Broad Institute of MIT and Harvard, Cambridge, Massachusetts, United States of America, 4 Department of Biochemistry and Molecular Biophysics, Columbia University, New York, New York, United States of America the integration of students, and for the of ISMB. One meeting in South Asia support of young leaders in the field. (InCoB; http://incob.binfo.org.tw/) has ISMB has also become a forum for already been sponsored by ISCB, and reviewing the state of the art in the many another one in North Asia is going to fields of this growing discipline, for follow. ISMB itself has also been held in introducing new directions, and for an- Australia (2003) and Brazil (2006). -
Microblogging the ISMB: a New Approach to Conference Reporting
Message from ISCB Microblogging the ISMB: A New Approach to Conference Reporting Neil Saunders1*, Pedro Beltra˜o2, Lars Jensen3, Daniel Jurczak4, Roland Krause5, Michael Kuhn6, Shirley Wu7 1 School of Molecular and Microbial Sciences, University of Queensland, St. Lucia, Brisbane, Queensland, Australia, 2 Department of Cellular and Molecular Pharmacology, University of California San Francisco, San Francisco, California, United States of America, 3 Novo Nordisk Foundation Center for Protein Research, Panum Institute, Copenhagen, Denmark, 4 Department of Bioinformatics, University of Applied Sciences, Hagenberg, Freistadt, Austria, 5 Max-Planck-Institute for Molecular Genetics, Berlin, Germany, 6 European Molecular Biology Laboratory, Heidelberg, Germany, 7 Stanford Medical Informatics, Stanford University, Stanford, California, United States of America Cameron Neylon entitled FriendFeed for Claire Fraser-Liggett opened the meeting Scientists: What, Why, and How? (http:// with a review of metagenomics and an blog.openwetware.org/scienceintheopen/ introduction to the human microbiome 2008/06/12/friendfeed-for-scientists-what- project (http://friendfeed.com/search?q = why-and-how/) for an introduction. room%3Aismb-2008+microbiome+OR+ We—a group of science bloggers, most fraser). The subsequent Q&A session of whom met in person for the first time at covered many of the exciting challenges The International Conference on Intel- ISMB 2008—found FriendFeed a remark- for those working in this field. Clearly, ligent Systems for Molecular Biology -
2015 Wattiezm Memoire
Institutional Repository - Research Portal Dépôt Institutionnel - Portail de la Recherche University of Namurresearchportal.unamur.be THESIS / THÈSE MASTER IN COMPUTER SCIENCE Design of a support system for modelling gene regulatory networks Author(s) - Auteur(s) : Wattiez, Morgan Award date: 2015 Awarding institution: University of Namur Supervisor - Co-Supervisor / Promoteur - Co-Promoteur : Link to publication Publication date - Date de publication : Permanent link - Permalien : Rights / License - Licence de droit d’auteur : General rights Copyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright owners and it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights. • Users may download and print one copy of any publication from the public portal for the purpose of private study or research. • You may not further distribute the material or use it for any profit-making activity or commercial gain • You may freely distribute the URL identifying the publication in the public portal ? Take down policy If you believe that this document breaches copyright please contact us providing details, and we will remove access to the work immediately and investigate your claim. BibliothèqueDownload date: Universitaire 04. oct.. 2021 Moretus Plantin University of Namur Faculty of Computer Science Academic Year 2014{2015 Design of a support system for modelling gene regulatory networks Morgan WATTIEZ Supervisor: (Signed for Release Approval Jean-Marie JACQUET Study Rules art. 40) Thesis submitted in partial fulfillment of the requirements for the degree of Master in Computer Science at the University of Namur Abstract The understanding of gene regulatory networks depends upon the solving of ques- tions related to the interactions in those networks. -
The Basic Units of Life How Cell Atlases Can Shed Light on Disease Mechanisms with Remarkable Accuracy
Press Information, July 28, 2021 Cells: The Basic Units of Life How cell atlases can shed light on disease mechanisms with remarkable accuracy The Schering Stiftung awards the Ernst Schering Prize 2021 to Aviv Regev. A pioneer in the field of single-cell analysis, she successfully combines approaches from biology and computer science and thus revolutionizes the field of precision medicine. Aviv Regev is considered a pioneer in the field of single-cell biology and has broken new ground by combining the disciplines of biology, computation, and genetic engineering. She has uniquely succeeded in combining and refining some of the most important experimental and analytical tools in such a way that she can analyze the genome of hundreds of thousands of single cells simultaneously. This single-cell genome analysis makes it possible to map and characterize a large number of individual tissue cells. Aviv Regev was the first to apply these single-cell technologies to solid tumors and to successfully identify those cells and genes that influence tumor growth and resistance to treatment. In addition, she discovered rare cell types that are involved in cystic fibrosis and ulcerative colitis. Last but not least, together with international research groups, and her colleague Sarah Teichmann she built the Human Cell Atlas and inspired Prof. Aviv Regev, PhD scientists all over the world to use these tools to create a Photo: Casey Atkins comprehensive atlas of all cell types in the human body. These cell atlases of parts of the human body illuminate disease mechanisms with remarkable accuracy and have recently also been used successfully to study disease progression in COVID-19. -
CV Aviv Regev
AVIV REGEV Curriculum Vitae Education and training Ph.D., Computational Biology, Tel Aviv University, Tel Aviv, Israel, 1998-2002 Advisor: Prof. Eva Jablonka (Tel Aviv University) Advisor: Prof. Ehud Shapiro (Computer Science, Weizmann Institute) M.Sc. (direct, Summa cum laude) Tel Aviv University, Tel Aviv, Israel, 1992-1997 Advisor: Prof. Sara Lavi A student in the Adi Lautman Interdisciplinary Program for the Fostering of Excellence (studies mostly in Biology, Computer Science and Mathematics) Post Training Positions Executive Vice President and Global Head, Genentech Research and Early Development, Genentech/Roche, 2020 - Current HHMI Investigator, 2014-2020 Chair of the Faculty (Executive Leadership Team), Broad Institute, 2015 – 2020 Professor, Department of Biology, MIT, 2015-Current (on leave) Founding Director, Klarman Cell Observatory, Broad Institute, 2012-2020 Director, Cell Circuits Program, Broad Institute, 2013 - 2020 Associate Professor with Tenure, Department of Biology, MIT, 2011-2015 Early Career Scientist, Howard Hughes Medical Institute, 2009-2014 Core Member, Broad Institute of MIT and Harvard, 2006-Current (on leave) Assistant Professor, Department of Biology, MIT, 2006-2011 Bauer Fellow, Center for Genomics Research, Harvard University, 2003-2006 International Service Founding Co-Chair, Human Cell Atlas, 2016-Current Honors Vanderbilt Prize, 2021 AACR Academy, Elected Fellow, 2021 AACR-Irving Weinstein Foundation Distinguished Lecturer, 2021 James Prize in Science and Technology Integration, National Academy of -
Modeling and Analysis of RNA-Seq Data: a Review from a Statistical Perspective
Modeling and analysis of RNA-seq data: a review from a statistical perspective Wei Vivian Li 1 and Jingyi Jessica Li 1;2;∗ Abstract Background: Since the invention of next-generation RNA sequencing (RNA-seq) technolo- gies, they have become a powerful tool to study the presence and quantity of RNA molecules in biological samples and have revolutionized transcriptomic studies. The analysis of RNA-seq data at four different levels (samples, genes, transcripts, and exons) involve multiple statistical and computational questions, some of which remain challenging up to date. Results: We review RNA-seq analysis tools at the sample, gene, transcript, and exon levels from a statistical perspective. We also highlight the biological and statistical questions of most practical considerations. Conclusion: The development of statistical and computational methods for analyzing RNA- seq data has made significant advances in the past decade. However, methods developed to answer the same biological question often rely on diverse statical models and exhibit dif- ferent performance under different scenarios. This review discusses and compares multiple commonly used statistical models regarding their assumptions, in the hope of helping users select appropriate methods as needed, as well as assisting developers for future method development. 1 Introduction RNA sequencing (RNA-seq) uses the next generation sequencing (NGS) technologies to reveal arXiv:1804.06050v3 [q-bio.GN] 1 May 2018 the presence and quantity of RNA molecules in biological samples. Since its invention, RNA- seq has revolutionized transcriptome analysis in biological research. RNA-seq does not require any prior knowledge on RNA sequences, and its high-throughput manner allows for genome-wide profiling of transcriptome landscapes [1,2]. -
BIOINFORMATICS Doi:10.1093/Bioinformatics/Btq499
Vol. 26 ECCB 2010, pages i409–i411 BIOINFORMATICS doi:10.1093/bioinformatics/btq499 ECCB 2010 Organization CONFERENCE CHAIR B. Comparative Genomics, Phylogeny, and Evolution Yves Moreau, Katholieke Universiteit Leuven, Belgium Martijn Huynen, Radboud University Nijmegen Medical Centre, The Netherlands PROCEEDINGS CHAIR Yves Van de Peer, Ghent University & VIB, Belgium Jaap Heringa, Free University of Amsterdam, The Netherlands C. Protein and Nucleotide Structure LOCAL ORGANIZING COMMITTEE Anna Tramontano, University of Rome ‘La Sapienza’, Italy Jan Gorodkin, University of Copenhagen, Denmark Yves Moreau, Katholieke Universiteit Leuven, Belgium Jaap Heringa, Free University of Amsterdam, The Netherlands D. Annotation and Prediction of Molecular Function Gert Vriend, Radboud University, Nijmegen, The Netherlands Yves Van de Peer, University of Ghent & VIB, Belgium Nir Ben-Tal, Tel-Aviv University, Israel Kathleen Marchal, Katholieke Universiteit Leuven, Belgium Fritz Roth, Harvard Medical School, USA Jacques van Helden, Université Libre de Bruxelles, Belgium Louis Wehenkel, Université de Liège, Belgium E. Gene Regulation and Transcriptomics Antoine van Kampen, University of Amsterdam & Netherlands Jaak Vilo, University of Tartu, Estonia Bioinformatics Center (NBIC) Zohar Yakhini, Agilent Laboratories, Tel-Aviv & the Tech-nion, Peter van der Spek, Erasmus MC, Rotterdam, The Netherlands Haifa, Israel STEERING COMMITTEE F. Text Mining, Ontologies, and Databases Michal Linial (Chair), Hebrew University, Jerusalem, Israel Alfonso Valencia, National -
Using Bayesian Networks to Analyze Expression Data
JOURNAL OFCOMPUTATIONAL BIOLOGY Volume7, Numbers 3/4,2000 MaryAnn Liebert,Inc. Pp. 601–620 Using Bayesian Networks to Analyze Expression Data NIR FRIEDMAN, 1 MICHAL LINIAL, 2 IFTACH NACHMAN, 3 andDANA PE’ER 1 ABSTRACT DNAhybridization arrayssimultaneously measurethe expression level forthousands of genes.These measurementsprovide a “snapshot”of transcription levels within the cell. Ama- jorchallenge in computationalbiology is touncover ,fromsuch measurements,gene/ protein interactions andkey biological features ofcellular systems. In this paper,wepropose a new frameworkfor discovering interactions betweengenes based onmultiple expression mea- surements. This frameworkbuilds onthe use of Bayesian networks forrepresenting statistical dependencies. ABayesiannetwork is agraph-basedmodel of joint multivariateprobability distributions thatcaptures properties ofconditional independence betweenvariables. Such models areattractive for their ability todescribe complexstochastic processes andbecause theyprovide a clear methodologyfor learning from(noisy) observations.We start byshowing howBayesian networks can describe interactions betweengenes. W ethen describe amethod forrecovering gene interactions frommicroarray data using tools forlearning Bayesiannet- works.Finally, we demonstratethis methodon the S.cerevisiae cell-cycle measurementsof Spellman et al. (1998). Key words: geneexpression, microarrays, Bayesian methods. 1.INTRODUCTION centralgoal of molecularbiology isto understand the regulation of protein synthesis and its Areactionsto external -
The 4Th Bologna Winter School: Hot Topics in Structural Genomics†
Comparative and Functional Genomics Comp Funct Genom 2003; 4: 394–396. Published online in Wiley InterScience (www.interscience.wiley.com). DOI: 10.1002/cfg.314 Conference Report The 4th Bologna Winter School: hot topics in structural genomics† Rita Casadio* Department of Biology/CIRB, University of Bologna, Via Irnerio 42, 40126 Bologna, Italy *Correspondence to: Abstract Rita Casadio, Department of Biology/CIRB, University of The 4th Bologna Winter School on Biotechnologies was held on 9–15 February Bologna, Via Irnerio 42, 40126 2003 at the University of Bologna, Italy, with the specific aim of discussing recent Bologna, Italy. developments in bioinformatics. The school provided an opportunity for students E-mail: [email protected] and scientists to debate current problems in computational biology and possible solutions. The course, co-supported (as last year) by the European Science Foundation program on Functional Genomics, focused mainly on hot topics in structural genomics, including recent CASP and CAPRI results, recent and promising genome- Received: 3 June 2003 wide predictions, protein–protein and protein–DNA interaction predictions and Revised: 5 June 2003 genome functional annotation. The topics were organized into four main sections Accepted: 5 June 2003 (http://www.biocomp.unibo.it). Published in 2003 by John Wiley & Sons, Ltd. Predictive methods in structural Predictive methods in functional genomics genomics • Contemporary challenges in structure prediction • Prediction of protein function (Arthur Lesk, and the CASP5 experiment (John Moult, Uni- University of Cambridge, Cambridge, UK). versity of Maryland, Rockville, MD, USA). • Microarray data analysis and mining (Raf- • Contemporary challenges in structure prediction faele Calogero, University of Torino, Torino, (Anna Tramontano, University ‘La Sapienza’, Italy). -
Biological Pathways Exchange Language Level 3, Release Version 1 Documentation
BioPAX – Biological Pathways Exchange Language Level 3, Release Version 1 Documentation BioPAX Release, July 2010. The BioPAX data exchange format is the joint work of the BioPAX workgroup and Level 3 builds on the work of Level 2 and Level 1. BioPAX Level 3 input from: Mirit Aladjem, Ozgun Babur, Gary D. Bader, Michael Blinov, Burk Braun, Michelle Carrillo, Michael P. Cary, Kei-Hoi Cheung, Julio Collado-Vides, Dan Corwin, Emek Demir, Peter D'Eustachio, Ken Fukuda, Marc Gillespie, Li Gong, Gopal Gopinathrao, Nan Guo, Peter Hornbeck, Michael Hucka, Olivier Hubaut, Geeta Joshi- Tope, Peter Karp, Shiva Krupa, Christian Lemer, Joanne Luciano, Irma Martinez-Flores, Zheng Li, David Merberg, Huaiyu Mi, Ion Moraru, Nicolas Le Novere, Elgar Pichler, Suzanne Paley, Monica Penaloza- Spinola, Victoria Petri, Elgar Pichler, Alex Pico, Harsha Rajasimha, Ranjani Ramakrishnan, Dean Ravenscroft, Jonathan Rees, Liya Ren, Oliver Ruebenacker, Alan Ruttenberg, Matthias Samwald, Chris Sander, Frank Schacherer, Carl Schaefer, James Schaff, Nigam Shah, Andrea Splendiani, Paul Thomas, Imre Vastrik, Ryan Whaley, Edgar Wingender, Guanming Wu, Jeremy Zucker BioPAX Level 2 input from: Mirit Aladjem, Gary D. Bader, Ewan Birney, Michael P. Cary, Dan Corwin, Kam Dahlquist, Emek Demir, Peter D'Eustachio, Ken Fukuda, Frank Gibbons, Marc Gillespie, Michael Hucka, Geeta Joshi-Tope, David Kane, Peter Karp, Christian Lemer, Joanne Luciano, Elgar Pichler, Eric Neumann, Suzanne Paley, Harsha Rajasimha, Jonathan Rees, Alan Ruttenberg, Andrey Rzhetsky, Chris Sander, Frank Schacherer,