Automated Function Prediction SIG Program
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ISCB Ebola Award for Important Future Research on the Computational Biology of Ebola Virus
ISCB Ebola Award for Important Future Research on the Computational Biology of Ebola Virus Journal Information Article/Issue Information Journal ID (nlm-ta): F1000Res Self URI: f1000research-4-6464.pdf Journal ID (iso-abbrev): F1000Res Date accepted: 13 January 2015 Journal ID (pmc): F1000Research Publication date (electronic): 15 January 2015 Title: F1000Research Publication date (collection): 2015 ISSN (electronic): 2046-1402 Volume: 4 Publisher: F1000Research (London, UK) Electronic Location Identifier: 12 Article Id (accession): PMC4457108 Article Id (pmcid): PMC4457108 Article Id (pmc-uid): 4457108 PubMed ID: 26097686 DOI: 10.12688/f1000research.6038.1 Funding: The author(s) declared that no grants were involved in supporting this work. Categories Subject: Editorial Categories Subject: Articles Subject: Bioinformatics Subject: Theory & Simulation Subject: Tropical & Travel-Associated Diseases Subject: Viral Infections (without HIV) Subject: Virology ISCB Ebola Award for Important Future Research on the Computational Biology of Ebola Virus v1; ref status: not peer reviewed Peter D. Karp Bonnie Berger Diane Kovats Thomas Lengauer Michal Linial Pardis Sabeti Winston Hide Burkhard Rost 1 1International Society for Computational Biology, La Jolla, CA, USA 2 2SRI International, Menlo Park, CA, USA 3 3Department of Mathematics, Massachusetts Institute of Technology, Cambridge, MA, USA 4 4Computational Biology and Applied Algorithmics, Max Planck Institute for Informatics, Saarbruecken, Germany 5 5Hebrew University & Institute of Advanced -
EYAL AKIVA, Phd
Eyal Akiva CV, Nov. 2017 EYAL AKIVA, PhD Department of Bioengineering and Therapeutic Sciences Phone +1-650-504-9008 University of California at San Francisco Email [email protected] 1700 4th street, San Francisco, Web www.babbittlab.ucsf.edu/eakiva CA, USA EDUCATION 2012-2017 Post-doctoral fellowship at UCSF, Dept. Of Bioengineering and Therapeutic Sciences. Host: Prof. Patricia Babbitt. 2010-2012 Post-doctoral fellowship at UCSF, Dept. Of Bioengineering and Therapeutic Sciences. Host: Prof. Tanja Kortemme. 2004-2010 PhD at The Hebrew University of Jerusalem (Israel), bioinformatics. Host: Prof. Hanah Margalit. “Various Aspects of Modularity in Protein-Protein Interaction". 2001-2004 MSc at The Hebrew University of Jerusalem (Israel), bioinformatics and human genetics. Host: Prof. Muli Ben-Sasson. “Exploiting the Exploiters: Identification of Virus-Host Pep- tide Mimicry as a Source for Modules of Functional Significance”. MAGNA CUM LAUDE. 1997-2000 BSc at Bar-Ilan University (Israel), biology (major) and computer science (minor). Final project advisor: Prof. Ramit Mehr “Modeling the Evolution of the Immune System: a Sim- ulation of the Evolution of Genes that Encode the Variable Regions of Immunoglobulins”. MAGNA CUM LAUDE. 1996-1997 First year of "Industrial Engineering and Management" studies, Tel-Aviv University, Israel. OTHER WORK EXPERIENCE 2000-01 ‘Do-coop technologies’: Team leader and chemistry/microbiology researcher; development of biological applications and manufacture of proprietary nanoparticles (Or Yehuda, Israel and Tel-Aviv University (Prof. Eshel Ben-Jacob’s lab at the school of physics)). FUNDING, HONORS AND AWARDS 2017 Grant: Co-PI, “Utilizing metagenomic sequences for enzyme function prediction”, Joint Genome Institute (US Department of Energy) (http://jgi.doe.gov/doe-user-facilities-ficus- join-forces-to-tackle-biology-big-data/). -
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 -
Download Link at Figshare.Com/Articles/Bint Fishmovie32 100 Mat/5009840)
Distribution Agreement In presenting this thesis or dissertation as a partial fulfillment of the requirements for an advanced degree from Emory University, I hereby grant to Emory University and its agents the non-exclusive license to archive, make accessible, and display my thesis or dissertation in whole or in part in all forms of media, now or hereafter known, including display on the world wide web. I understand that I may select some access restrictions as part of the online submission of this thesis or dissertation. I retain all ownership rights to the copyright of the thesis or dissertation. I also retain the right to use in future works (such as articles or books) all or part of this thesis or dissertation. Signature: Joseph L. Natale Date Inference, Dynamics, and Coarse-Graining of Large-Scale Biological Networks By Joseph L. Natale Doctor of Philosophy Physics Ilya Nemenman, Ph.D. Advisor Gordon Berman, Ph.D. Committee Member Avani Gadani, Ph.D. Committee Member H. George E. Hentschel, Ph.D. Committee Member Daniel Weissman, Ph.D. Committee Member Accepted: Lisa A. Tedesco, Ph.D. Dean of the James T. Laney School of Graduate Studies Date Inference, Dynamics, and Coarse-Graining of Large-Scale Biological Networks By Joseph L. Natale B.S., Stevens Institute of Technology, NJ, 2012 M.S., Stevens Institute of Technology, NJ, 2013 Advisor: Ilya Nemenman, Ph.D. An abstract of A dissertation submitted to the Faculty of the James T. Laney School of Graduate Studies of Emory University in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Physics 2020 Inference, Dynamics, and Coarse-Graining of Large-Scale Biological Networks By Joseph L. -
Dear Delegates,History of Productive Scientific Discussions of New Challenging Ideas and Participants Contributing from a Wide Range of Interdisciplinary fields
3rd IS CB S t u d ent Co u ncil S ymp os ium Welcome To The 3rd ISCB Student Council Symposium! Welcome to the Student Council Symposium 3 (SCS3) in Vienna. The ISCB Student Council's mis- sion is to develop the next generation of computa- tional biologists. We would like to thank and ac- knowledge our sponsors and the ISCB organisers for their crucial support. The SCS3 provides an ex- citing environment for active scientific discussions and the opportunity to learn vital soft skills for a successful scientific career. In addition, the SCS3 is the biggest international event targeted to students in the field of Computational Biology. We would like to thank our hosts and participants for making this event educative and fun at the same time. Student Council meetings have had a rich Dear Delegates,history of productive scientific discussions of new challenging ideas and participants contributing from a wide range of interdisciplinary fields. Such meet- We are very happy to welcomeings have you proved all touseful the in ISCBproviding Student students Council and postdocs Symposium innovative inputsin Vienna. and an Afterincreased the network suc- cessful symposiums at ECCBof potential 2005 collaborators. in Madrid and at ISMB 2006 in Fortaleza we are determined to con- tinue our efforts to provide an event for students and young researchers in the Computational Biology community. Like in previousWe ar yearse extremely our excitedintention to have is toyou crhereatee and an the opportunity vibrant city of Vforienna students welcomes to you meet to our their SCS3 event. peers from all over the world for exchange of ideas and networking. -
Annual Scientific Report 2011 Annual Scientific Report 2011 Designed and Produced by Pickeringhutchins Ltd
European Bioinformatics Institute EMBL-EBI Annual Scientific Report 2011 Annual Scientific Report 2011 Designed and Produced by PickeringHutchins Ltd www.pickeringhutchins.com EMBL member states: Austria, Croatia, Denmark, Finland, France, Germany, Greece, Iceland, Ireland, Israel, Italy, Luxembourg, the Netherlands, Norway, Portugal, Spain, Sweden, Switzerland, United Kingdom. Associate member state: Australia EMBL-EBI is a part of the European Molecular Biology Laboratory (EMBL) EMBL-EBI EMBL-EBI EMBL-EBI EMBL-European Bioinformatics Institute Wellcome Trust Genome Campus, Hinxton Cambridge CB10 1SD United Kingdom Tel. +44 (0)1223 494 444, Fax +44 (0)1223 494 468 www.ebi.ac.uk EMBL Heidelberg Meyerhofstraße 1 69117 Heidelberg Germany Tel. +49 (0)6221 3870, Fax +49 (0)6221 387 8306 www.embl.org [email protected] EMBL Grenoble 6, rue Jules Horowitz, BP181 38042 Grenoble, Cedex 9 France Tel. +33 (0)476 20 7269, Fax +33 (0)476 20 2199 EMBL Hamburg c/o DESY Notkestraße 85 22603 Hamburg Germany Tel. +49 (0)4089 902 110, Fax +49 (0)4089 902 149 EMBL Monterotondo Adriano Buzzati-Traverso Campus Via Ramarini, 32 00015 Monterotondo (Rome) Italy Tel. +39 (0)6900 91402, Fax +39 (0)6900 91406 © 2012 EMBL-European Bioinformatics Institute All texts written by EBI-EMBL Group and Team Leaders. This publication was produced by the EBI’s Outreach and Training Programme. Contents Introduction Foreword 2 Major Achievements 2011 4 Services Rolf Apweiler and Ewan Birney: Protein and nucleotide data 10 Guy Cochrane: The European Nucleotide Archive 14 Paul Flicek: -
Ribonucleotide Reductase Genes Influence The
RIBONUCLEOTIDE REDUCTASE GENES INFLUENCE THE BIOLOGY AND ECOLOGY OF MARINE VIRUSES by Amelia O. Harrison A thesis submitted to the Faculty of the University of Delaware in partial fulfillment of the requirements for the degree of Master of Science in Marine Studies Fall 2019 c 2019 Amelia O. Harrison All Rights Reserved RIBONUCLEOTIDE REDUCTASE GENES INFLUENCE THE BIOLOGY AND ECOLOGY OF MARINE VIRUSES by Amelia O. Harrison Approved: K. Eric Wommack, Ph.D. Professor in charge of thesis on behalf of the Advisory Committee Approved: Mark A. Moline, Ph.D. Director of the School of Marine Science and Policy Approved: Estella A. Atekwana, Ph.D. Dean of the College of Earth, Ocean, and Environment Approved: Douglas J. Doren, Ph.D. Interim Vice Provost for Graduate and Professional Education and Dean of the Graduate College ACKNOWLEDGMENTS First, I would like to thank my advisor, Eric Wommack, for taking a chance on me as a freshman undergrad and again as a masters student. It has been a privilege to work with someone so passionate and excited about science. I would also like to thank Shawn Polson, who has also supported me and helped foster my love for research over the past six years. I would like to thank the final member of my committee, Jennifer Biddle, for her insight and general awesomeness. I am deeply thankful for all of my past and current labmates. Barb Ferrell who somehow always has time for everyone. Prasanna Joglekar, for always making me laugh. Rachel Marine, who took me on as an intern despite not having the time. -
Methods for Global Organization of All Known Protein Sequences
Metho ds for Global Organization of all Known Protein Sequences Thesis submitted for the degree \Do ctor of Philosophy" Golan Yona Submitted to the Senate of the Hebrew University in the year 1999 1 This work was carried out under the sup ervision of Prof. Nathan Linial, Prof. Naftali Tishby and Dr. Michal Linial. 2 Acknowledgments First, I would like to thank my advisors: Nati Linial and Tali Tishby of the computer science department and Michal Linial of the life science department at the Hebrew University. Within the last ve years we have come a long way together, and I'm grateful for their guidance, supp ort, warmth and generous help all these years. I would like to thank my colleagues and friends in the machine learning lab, with whom I sp ent most of the last ve years: Itay Gat, Lidror Troyansky, Elad Schneidman, Shlomo Dubnov, Shai Fine, Noam Slonim, Ofer Neiman and Ran El-Yaniv, for all their help and for b eing great company. A sp ecial thanks to Ran El-Yaniv, a dear friend who encouraged me to keep b elieving in myself. I very much enjoyed working with Gill Bejerano, with whom I am still working on fascinating new directions. I would next like to thank all of my colleagues and friends in the molecular genetics and biotechnology lab headed by Hanah Margalit: Ora Schueler, Eyal Nadir, Iddo Friedb erg, Yael Mandel and Yael Altuvia, for the great time I had every Thursday in our journal club group meetings. Besides the many pap ers I had in my bag after each such meeting, it was also great fun. -
Shsearch: a Method for Fast Remote Homology Detection Baddar M
SHsearch: a method for fast remote homology detection Baddar M. Faculty of Engineering, Alexandria University , Egypt Abstract—Remote homology detection is the problem of detecting homology in cases of low sequence similarity. It is a hard computational problem with no approach that works well in all cases. Methods based on profile hidden Markov models (HMM) often exhibit relatively higher sensitivity for detecting remote homologies than commonly used approaches. However, calculating similarity scores in profile HMM methods is computationally intensive as they use dynamic programming algorithms. In this paper we introduce SHsearch: a new method for remote protein homology detection. Our method is implemented as a modification of HHsearch: a remote protein homology detection method based on comparing two profile HMMs. The motivation for modification was to reduce the run time of HHsearch significantly with minimal sensitivity loss. SHsearch focuses on comparing the important submodels of the query and database HMMs instead of comparing the complete models. Hence, SHsearch achieves a significant speedup over HHsearch with minimal loss in sensitivity. On SCOP 1.63, SHsearch achieved 88X speedup with 8.2% loss in sensitivity with respect to HHsearch at error rate of 10%, which deemed to be an acceptable tradeoff. Index Terms—biological sequence classification, hidden Markov models —————————— ◆ —————————— 1 INTRODUCTION Analysis of large scale sequence data has become an important task in computational biology and comparative genomics, inspired in part by numerous scientific and technological applications such as the biomedical literature analysis or the analysis of biological sequences. Protein homology detection has attracted particular interest due to its critical role in many biological applications. -
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ISCB Ebola Award for Important Future Research on the Computational Biology of Ebola Virus The Harvard community has made this article openly available. Please share how this access benefits you. Your story matters Citation Karp, Peter D., Bonnie Berger, Diane Kovats, Thomas Lengauer, Michal Linial, Pardis Sabeti, Winston Hide, and Burkhard Rost. 2015. “ISCB Ebola Award for Important Future Research on the Computational Biology of Ebola Virus.” PLoS Computational Biology 11 (1): e1004087. doi:10.1371/journal.pcbi.1004087. http:// dx.doi.org/10.1371/journal.pcbi.1004087. Published Version doi:10.1371/journal.pcbi.1004087 Citable link http://nrs.harvard.edu/urn-3:HUL.InstRepos:14065320 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 ISCB Ebola Award for Important Future Research on the Computational Biology of Ebola Virus Peter D. Karp1,2, Bonnie Berger1,3, Diane Kovats1*, Thomas Lengauer1,4, Michal Linial1,5, Pardis Sabeti6,7,8, Winston Hide9, Burkhard Rost1,10,11* 1 International Society for Computational Biology, La Jolla, California, United States of America, 2 SRI International, Menlo Park, California, United States of America, 3 Department of Mathematics, Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts, United States of America, 4 Computational Biology and Applied Algorithmics, -
Automated Function Prediction SIG Meeting July 20Th 2013, Berlin, Germany ISMB/ECCB 2013
Automated Function Prediction SIG Meeting July 20th 2013, Berlin, Germany ISMB/ECCB 2013 Keynote Speakers Alex Bateman European Bioinformatics Institute, UK. Using protein domains and families for functional prediction Patricia Babbitt University of California, San Francisco, USA. Protein similarity networks: Identification of functional trends from the context of sequence similarity Anna Tramontano University of Rome, “La Sapienza”, Italy. CASP: aging or growing up? Keith Dunker Indiana University, USA. Functions of Intrinsically Disordered Proteins Automated Function Prediction SIG 2013 Programme 08:30 Welcome from the organisers 08:45 Keynote – Keith Dunker, Indiana University, USA. Functions of Intrinsically Disordered Proteins 09:15 Giorgio Valentini, Università degli Studi di Milano, Italy. Scalable Network-based Learning Methods for Automated Function Prediction based on the Neo4j Graph-database 09:35 Joachim Bargsten, Wageningen University, The Netherlands. Integrated network- and sequence-based protein function prediction across the plant kingdom 09:55 Christos Ouzounis, Institute of Applied Biosciences, Greece. We still haz a job: genome annotashuns 10:15 Coffee break 10:45 Keynote – Patricia Babbitt, University of California, San Francisco, USA. Protein similarity networks: Identification of functional trends from the context of sequence similarity 11:15 Rachael Huntley, European Bioinformatics Institute, UK. The Gene Ontology Resource – Common Misconceptions 11:35 Nives Skunca, ETH Zurich, Switzerland. Assessing protein function predictions in light of the Open World Assumption 11:55 Noah Youngs, New York University, USA. Negative Example Selection in Protein Function Prediction 12:15 Lunch 13:30 Keynote – Anna Tramontano, University of Rome “La Sapienza”, Italy. CASP: aging or growing up? 14:00 Indika Kahanda, Colorado State University, USA. -
CV Burkhard Rost
Burkhard Rost CV BURKHARD ROST TUM Informatics/Bioinformatics i12 Boltzmannstrasse 3 (Rm 01.09.052) 85748 Garching/München, Germany & Dept. Biochemistry & Molecular Biophysics Columbia University New York, USA Email [email protected] Tel +49-89-289-17-811 Photo: © Eckert & Heddergott, TUM Web www.rostlab.org Fax +49-89-289-19-414 Document: CV Burkhard Rost TU München Affiliation: Columbia University TOC: • Tabulated curriculum vitae • Grants • List of publications Highlights by numbers: • 186 invited talks in 29 countries (incl. TedX) • 250 publications (187 peer-review, 168 first/last author) • Google Scholar 2016/01: 30,502 citations, h-index=80, i10=179 • PredictProtein 1st Internet server in mol. biol. (since 1992) • 8 years ISCB President (International Society for Computational Biology) • 143 trained (29% female, 50% foreigners from 32 nations on 6 continents) Brief narrative: Burkhard Rost obtained his doctoral degree (Dr. rer. nat.) from the Univ. of Heidelberg (Germany) in the field of theoretical physics. He began his research working on the thermo-dynamical properties of spin glasses and brain-like artificial neural networks. A short project on peace/arms control research sketched a simple, non-intrusive sensor networks to monitor aircraft (1988-1990). He entered the field of molecular biology at the European Molecular Biology Laboratory (EMBL, Heidelberg, Germany, 1990-1995), spent a year at the European Bioinformatics Institute (EBI, Hinxton, Cambridgshire, England, 1995), returned to the EMBL (1996-1998), joined the company LION Biosciences for a brief interim (1998), became faculty in the Medical School of Columbia University in 1998, and joined the TUM Munich to become an Alexander von Humboldt professor in 2009.