Women in Bioinformatics Panelists
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BIOINFORMATICS Doi:10.1093/Bioinformatics/Bti144
Vol. 00 no. 0 2004, pages 1–11 BIOINFORMATICS doi:10.1093/bioinformatics/bti144 Solving and analyzing side-chain positioning problems using linear and integer programming Carleton L. Kingsford, Bernard Chazelle and Mona Singh∗ Department of Computer Science, Lewis-Sigler Institute for Integrative Genomics, Princeton University, 35, Olden Street, Princeton, NJ 08544, USA Received on August 1, 2004; revised on October 10, 2004; accepted on November 8, 2004 Advance Access publication … ABSTRACT set of possible rotamer choices (Ponder and Richards, 1987; Motivation: Side-chain positioning is a central component of Dunbrack and Karplus, 1993) for each Cα position on the homology modeling and protein design. In a common for- backbone. The goal is to choose a rotamer for each position mulation of the problem, the backbone is fixed, side-chain so that the total energy of the molecule is minimized. This conformations come from a rotamer library, and a pairwise formulation of SCP has been the basis of some of the more energy function is optimized. It is NP-complete to find even a successful methods for homology modeling (e.g. Petrey et al., reasonable approximate solution to this problem. We seek to 2003; Xiang and Honig, 2001; Jones and Kleywegt, 1999; put this hardness result into practical context. Bower et al., 1997) and protein design (e.g. Dahiyat and Mayo, Results: We present an integer linear programming (ILP) 1997; Malakauskas and Mayo, 1998; Looger et al., 2003). In formulation of side-chain positioning that allows us to tackle homology modeling, the goal is to predict the structure for a large problem sizes. -
Algorithms for Computational Biology 8Th International Conference, Alcob 2021 Missoula, MT, USA, June 7–11, 2021 Proceedings
Lecture Notes in Bioinformatics 12715 Subseries of Lecture Notes in Computer Science Series Editors Sorin Istrail Brown University, Providence, RI, USA Pavel Pevzner University of California, San Diego, CA, USA Michael Waterman University of Southern California, Los Angeles, CA, USA Editorial Board Members Søren Brunak Technical University of Denmark, Kongens Lyngby, Denmark Mikhail S. Gelfand IITP, Research and Training Center on Bioinformatics, Moscow, Russia Thomas Lengauer Max Planck Institute for Informatics, Saarbrücken, Germany Satoru Miyano University of Tokyo, Tokyo, Japan Eugene Myers Max Planck Institute of Molecular Cell Biology and Genetics, Dresden, Germany Marie-France Sagot Université Lyon 1, Villeurbanne, France David Sankoff University of Ottawa, Ottawa, Canada Ron Shamir Tel Aviv University, Ramat Aviv, Tel Aviv, Israel Terry Speed Walter and Eliza Hall Institute of Medical Research, Melbourne, VIC, Australia Martin Vingron Max Planck Institute for Molecular Genetics, Berlin, Germany W. Eric Wong University of Texas at Dallas, Richardson, TX, USA More information about this subseries at http://www.springer.com/series/5381 Carlos Martín-Vide • Miguel A. Vega-Rodríguez • Travis Wheeler (Eds.) Algorithms for Computational Biology 8th International Conference, AlCoB 2021 Missoula, MT, USA, June 7–11, 2021 Proceedings 123 Editors Carlos Martín-Vide Miguel A. Vega-Rodríguez Rovira i Virgili University University of Extremadura Tarragona, Spain Cáceres, Spain Travis Wheeler University of Montana Missoula, MT, USA ISSN 0302-9743 ISSN 1611-3349 (electronic) Lecture Notes in Bioinformatics ISBN 978-3-030-74431-1 ISBN 978-3-030-74432-8 (eBook) https://doi.org/10.1007/978-3-030-74432-8 LNCS Sublibrary: SL8 – Bioinformatics © Springer Nature Switzerland AG 2021 This work is subject to copyright. -
BIOGRAPHICAL SKETCH NAME: Berger
BIOGRAPHICAL SKETCH NAME: Berger, Bonnie eRA COMMONS USER NAME (credential, e.g., agency login): BABERGER POSITION TITLE: Simons Professor of Mathematics and Professor of Electrical Engineering and Computer Science EDUCATION/TRAINING (Begin with baccalaureate or other initial professional education, such as nursing, include postdoctoral training and residency training if applicable. Add/delete rows as necessary.) EDUCATION/TRAINING DEGREE Completion (if Date FIELD OF STUDY INSTITUTION AND LOCATION applicable) MM/YYYY Brandeis University, Waltham, MA AB 06/1983 Computer Science Massachusetts Institute of Technology SM 01/1986 Computer Science Massachusetts Institute of Technology Ph.D. 06/1990 Computer Science Massachusetts Institute of Technology Postdoc 06/1992 Applied Mathematics A. Personal Statement Advances in modern biology revolve around automated data collection and sharing of the large resulting datasets. I am considered a pioneer in the area of bringing computer algorithms to the study of biological data, and a founder in this community that I have witnessed grow so profoundly over the last 26 years. I have made major contributions to many areas of computational biology and biomedicine, largely, though not exclusively through algorithmic innovations, as demonstrated by nearly twenty thousand citations to my scientific papers and widely-used software. In recognition of my success, I have just been elected to the National Academy of Sciences and in 2019 received the ISCB Senior Scientist Award, the pinnacle award in computational biology. My research group works on diverse challenges, including Computational Genomics, High-throughput Technology Analysis and Design, Biological Networks, Structural Bioinformatics, Population Genetics and Biomedical Privacy. I spearheaded research on analyzing large and complex biological data sets through topological and machine learning approaches; e.g. -
Are Profile Hidden Markov Models Identifiable?
Are Profile Hidden Markov Models Identifiable? Srilakshmi Pattabiraman Tandy Warnow Department of Electrical and Computer Engineering Department of Computer Science University of Illinois at Urbana-Champaign University of Illinois at Urbana-Champaign Urbana, Illinois Urbana, Illinois [email protected] [email protected] ABSTRACT 1 INTRODUCTION Profile Hidden Markov Models (HMMs) are graphical models that Profile Hidden Markov Models (HMMs) are arguably themost can be used to produce finite length sequences from a distribution. common statistical models in bioinformatics. Originally introduced In fact, although they were only introduced for bioinformatics 25 by Haussler and colleagues in [10, 12], and then expanded later years ago (by Haussler et al., Hawaii International Conference on in many subsequent texts [4–6, 9, 11, 21, 25], profile HMMs are Systems Science 1993), they are arguably the most commonly used now used in many analytical steps in biological sequence analysis statistical model in bioinformatics, with multiple applications, in- [15, 17–19, 22]. cluding protein structure and function prediction, classifications Profile Hidden Markov models are graphical models with match of novel proteins into existing protein families and superfamilies, states, insertion states, and deletion states; and the match and in- metagenomics, and multiple sequence alignment. The standard use sertion states emit letters from an underlying alphabet Σ (i.e., Σ of profile HMMs in bioinformatics has two steps: first a profile may be the 20 amino acids, the four nucleotides, or some other HMM is built for a collection of molecular sequences (which may set of symbols). In the standard form presented in [4] (widely in not be in a multiple sequence alignment), and then the profile HMM use in bioinformatics applications), each profile Hidden Markov is used in some subsequent analysis of new molecular sequences. -
Computational Biology and Bioinformatics
Vol. 30 ISMB 2014, pages i1–i2 BIOINFORMATICS EDITORIAL doi:10.1093/bioinformatics/btu304 Editorial This special issue of Bioinformatics serves as the proceedings of The conference used a two-tier review system, a continuation the 22nd annual meeting of Intelligent Systems for Molecular and refinement of a process begun with ISMB 2013 in an effort Biology (ISMB), which took place in Boston, MA, July 11–15, to better ensure thorough and fair reviewing. Under the revised 2014 (http://www.iscb.org/ismbeccb2014). The official confer- process, each of the 191 submissions was first reviewed by at least ence of the International Society for Computational Biology three expert referees, with a subset receiving between four and (http://www.iscb.org/), ISMB, was accompanied by 12 Special eight reviews, as needed. These formal reviews were frequently Interest Group meetings of one or two days each, two satellite supplemented by online discussion among reviewers and Area meetings, a High School Teachers Workshop and two half-day Chairs to resolve points of dispute and reach a consensus on tutorials. Since its inception, ISMB has grown to be the largest each paper. Among the 191 submissions, 29 were conditionally international conference in computational biology and bioinfor- accepted for publication directly from the first round review Downloaded from matics. It is expected to be the premiere forum in the field for based on an assessment of the reviewers that the paper was presenting new research results, disseminating methods and tech- clearly above par for the conference. A subset of 16 papers niques and facilitating discussions among leading researchers, were viewed as potentially in the top tier but raised significant practitioners and students in the field. -
ABSTRACT HISTORICAL GRAPH DATA MANAGEMENT Udayan
ABSTRACT Title of dissertation: HISTORICAL GRAPH DATA MANAGEMENT Udayan Khurana, Doctor of Philosophy, 2015 Dissertation directed by: Professor Amol Deshpande Department of Computer Science Over the last decade, we have witnessed an increasing interest in temporal analysis of information networks such as social networks or citation networks. Finding temporal interaction patterns, visualizing the evolution of graph properties, or even simply com- paring them across time, has proven to add significant value in reasoning over networks. However, because of the lack of underlying data management support, much of the work on large-scale graph analytics to date has largely focused on the study of static properties of graph snapshots. Unfortunately, a static view of interactions between entities is often an oversimplification of several complex phenomena like the spread of epidemics, informa- tion diffusion, formation of online communities, and so on. In the absence of appropriate support, an analyst today has to manually navigate the added temporal complexity of large evolving graphs, making the process cumbersome and ineffective. In this dissertation, I address the key challenges in storing, retrieving, and analyzing large historical graphs. In the first part, I present DeltaGraph, a novel, extensible, highly tunable, and distributed hierarchical index structure that enables compact recording of the historical information, and that supports efficient retrieval of historical graph snapshots. I present analytical models for estimating required storage space and snapshot retrieval times which aid in choosing the right parameters for a specific scenario. I also present optimizations such as partial materialization and columnar storage to speed up snapshot retrieval. In the second part, I present Temporal Graph Index that builds upon DeltaGraph to support version-centric retrieval such as a node’s 1-hop neighborhood history, along with snapshot reconstruction. -
John Anthony Capra
John Anthony Capra Contact Vanderbilt University e-mail: tony.capra-at-vanderbilt.edu Information Dept. of Biological Sciences www: http://www.capralab.org/ VU Station B, Box 35-1634 office: U5221 BSB/MRB III Nashville, TN 37235-1634 phone: (615) 343-3671 Research • Applying computational methods to problems in genetics, evolution, and biomedicine. Interests • Integrating genome-scale data to understand the functional effects of genetic differences between individuals and species. • Modeling evolutionary processes that drive the creation of lineage-specific traits and diseases. Academic Vanderbilt University, Nashville, Tennessee USA Employment Assistant Professor, Department of Biological Sciences August 2014 { Present Assistant Professor, Department of Biomedical Informatics February 2013 { Present Investigator, Center for Human Genetics Research Education And Gladstone Institutes, University of California, San Francisco, CA USA Training Postdoctoral Fellow, October 2009 { December 2012 • Advisor: Katherine Pollard Princeton University, Princeton, New Jersey USA Ph.D., Computer Science, June 2009 • Advisor: Mona Singh • Thesis: Algorithms for the Identification of Functional Sites in Proteins M.A., Computer Science, October 2006 Columbia College, Columbia University, New York, New York USA B.A., Computer Science, May 2004 B.A., Mathematics, May 2004 Pembroke College, Oxford University, Oxford, UK Columbia University Oxford Scholar, October 2002 { June 2003 • Subject: Mathematics Honors and Gladstone Institutes Award for Excellence in Scientific Leadership 2012 Awards Society for Molecular Biology and Evolution (SMBE) Travel Award 2012 PhRMA Foundation Postdoctoral Fellowship in Informatics 2011 { 2013 Princeton University Wu Graduate Fellowship 2004 { 2008 Columbia University Oxford Scholar 2002 { 2003 Publications Capra JA* and Kostka D*. Modeling DNA methylation dynamics with approaches from phyloge- netics. -
Research News
Computing Research News COMPUTING RESEARCH ASSOCIATION, CELEBRATING 40 YEARS OF SERVICE TO THE COMPUTING RESEARCH COMMUNITY JUNE 2013 Vol. 25 / No. 6 Announcements 2 Coalition for National Science Funding 2 CRA Announces Outstanding Undergraduate Researcher Award Winners 3 Computing Research in Action 5 CERP Infographic 6 NSF Funding Opportunity 6 CRA Recognizes Participants 7 CRA Board Members 16 CRA Board Officers 16 CRA Staff 16 Professional Opportunities 17 COMPUTING RESEARCH NEWS, JUNE 2013 Vol. 25 / No. 6 Announcements 2012 Taulbee Report Updated May 15, 2013 Corrected Table F6 Click here to download updated version CRA Releases Latest Research Issue Report New Technology-based Models for Postsecondary Learning: Conceptual Frameworks and Research Agendas The report details the findings of a National Science Foundation-Sponsored Computing Research Association Workshop held at MIT on January 9-11, 2013. From the report: “Advances in technology and in knowledge about expertise, learning, and assessment have the potential to reshape the many forms of education and training past matriculation from high school. In the next decade, higher education, military and workplace training, and professional development must all transform to exploit the opportunities of a new era, leveraging emerging technology-based models that can make learning more efficient and possibly improve student support, all at lower cost for a broader range of learners.” The report is now available as a pdf at http://cra.org/resources/research-issues/. Slides from the presentation at NSF on April 19, 2013 are also available. Investments in STEM Research and Education: Fueling American Innovation On May 7, at the Rayburn House Office Building in Brett Bode from the National Center for Supercomputing Washington, DC, the Coalition for National Science Funding Applications at University of Illinois Urbana-Champaign were (CNSF) held its 19th annual exhibition and reception, on hand to talk about the “Blue Waters” project. -
Graduation 2019
Department of Graduation Computer Science Celebration & Awards Dinner 2019 Evening Schedule 6:00pm Social Time 7:00pm Welcome Dr. Sanjeev Setia, Chair Department of Computer Science 7:10pm Dinner 8:00pm Presentation of Awards Dr. Sanjeev Setia, Chair Department of Computer Science Doctor of Philosophy Computer Science Indranil Banerjee Dissertation Title: Problems on Sorting, Sets and Graphs Major Professor: Dana Richards, PhD Arda Gumusalan Dissertation Title: Dynamic Modulation Scaling Enabled Real Time Transmission Scheduling For Wireless Sensor Networks Major Professor: Robert Simon, PhD Yun Guo Dissertation Title: Towards Automatically Localizing and Repairing SQL Faults Major Professors: Jeff Offut, PhD & Amihai Motro, PhD Mohan Krishnamoorthy Dissertation Title: Stochastic Optimization based on White-box Deterministic Approximations: Models, Algorithms and Application to Service Networks Major Professors: Alexander Brodsky, PhD & Daniel Menascé, PhD Arsalan Mousavian Dissertation Title: Semantic and 3D Understanding of a Scene for Robot Perception Major Professor : Jana Kosecka, PhD Zhiyun Ren Dissertation Title: Academic Performance Prediction with Machine Learning Techniques Major Professor : Huzefa Rangwala, PhD Md A. Reza Dissertation Title: Scene Understanding for Robotic Applications Major Professor : Jana Kosecka, PhD Venkateshwar Tadakamalla Dissertation Title: Analysis and Autonomic Elasticity Control for Multi-Server/Queues Under Traffic Surges in Cloud Environments Major Professor : Daniel A. Menascé, PhD Jianchao Tan -
I S C B N E W S L E T T
ISCB NEWSLETTER FOCUS ISSUE {contents} President’s Letter 2 Member Involvement Encouraged Register for ISMB 2002 3 Registration and Tutorial Update Host ISMB 2004 or 2005 3 David Baker 4 2002 Overton Prize Recipient Overton Endowment 4 ISMB 2002 Committees 4 ISMB 2002 Opportunities 5 Sponsor and Exhibitor Benefits Best Paper Award by SGI 5 ISMB 2002 SIGs 6 New Program for 2002 ISMB Goes Down Under 7 Planning Underway for 2003 Hot Jobs! Top Companies! 8 ISMB 2002 Job Fair ISCB Board Nominations 8 Bioinformatics Pioneers 9 ISMB 2002 Keynote Speakers Invited Editorial 10 Anna Tramontano: Bioinformatics in Europe Software Recommendations11 ISCB Software Statement volume 5. issue 2. summer 2002 Community Development 12 ISCB’s Regional Affiliates Program ISCB Staff Introduction 12 Fellowship Recipients 13 Awardees at RECOMB 2002 Events and Opportunities 14 Bioinformatics events world wide INTERNATIONAL SOCIETY FOR COMPUTATIONAL BIOLOGY A NOTE FROM ISCB PRESIDENT This newsletter is packed with information on development and dissemination of bioinfor- the ISMB2002 conference. With over 200 matics. Issues arise from recommendations paper submissions and over 500 poster submis- made by the Society’s committees, Board of sions, the conference promises to be a scientific Directors, and membership at large. Important feast. On behalf of the ISCB’s Directors, staff, issues are defined as motions and are discussed EXECUTIVE COMMITTEE and membership, I would like to thank the by the Board of Directors on a bi-monthly Philip E. Bourne, Ph.D., President organizing committee, local organizing com- teleconference. Motions that pass are enacted Michael Gribskov, Ph.D., mittee, and program committee for their hard by the Executive Committee which also serves Vice President work preparing for the conference. -
Emerging Topics in Biological Networks and Systems Biology Symposium at the Swedish Collegium for Advanced Study (Scas), Uppsala 9-11 October, 2017
Emerging Topics in Biological Networks and Systems Biology Symposium at the Swedish Collegium for Advanced Study (scas), Uppsala 9-11 October, 2017 mona singh, Princeton University, usa Network-based Methods for Identifying Cancer Genes Abstract: A central goal in cancer genomics is to identify the somatic alterations that underpin tumor initiation and progression. While commonly mutated cancer genes are readily identifiable, those that are rarely mutated across samples are difficult to distinguish from the large numbers of other infrequently mutated genes. Molecular interactions and networks provide a powerful frame- work with which to tackle some of the difficulties arising from the diverse somatic mutational landscapes of cancers. In this talk, I will first demonstrate that cancer genes can be discovered by identifying genes whose interaction interfaces are enriched in somatic mutations. Next, I will show how to leverage per-individual mutational profiles within the context of protein-protein interaction networks in order to identify small connected subnetworks of genes that, while not individually frequently mutated, comprise pathways that are altered across (i.e., “cover”) a large fraction of individuals. Overall, these two approaches recapitulate known cancer driver genes, and discover novel, and sometimes rarely-mutated, genes with likely roles in cancer. About: Mona Singh obtained her AB and SM degrees at Harvard University, and her PhD at MIT, all three in Computer Science. She did postdoctoral work at the Whitehead Institute for Biomedical Research. She has been on the faculty at Princeton since 1999, and currently she is Professor of Computer Science in the computer science department and the Lewis-Sigler Institute for Integrative Genomics. -
Curriculum Vitae
Curriculum Vitae Tandy Warnow Grainger Distinguished Chair in Engineering 1 Contact Information Department of Computer Science The University of Illinois at Urbana-Champaign Email: [email protected] Homepage: http://tandy.cs.illinois.edu 2 Research Interests Phylogenetic tree inference in biology and historical linguistics, multiple sequence alignment, metage- nomic analysis, big data, statistical inference, probabilistic analysis of algorithms, machine learning, combinatorial and graph-theoretic algorithms, and experimental performance studies of algorithms. 3 Professional Appointments • Co-chief scientist, C3.ai Digital Transformation Institute, 2020-present • Grainger Distinguished Chair in Engineering, 2020-present • Associate Head for Computer Science, 2019-present • Special advisor to the Head of the Department of Computer Science, 2016-present • Associate Head for the Department of Computer Science, 2017-2018. • Founder Professor of Computer Science, the University of Illinois at Urbana-Champaign, 2014- 2019 • Member, Carl R. Woese Institute for Genomic Biology. Affiliate of the National Center for Supercomputing Applications (NCSA), Coordinated Sciences Laboratory, and the Unit for Criticism and Interpretive Theory. Affiliate faculty member in the Departments of Mathe- matics, Electrical and Computer Engineering, Bioengineering, Statistics, Entomology, Plant Biology, and Evolution, Ecology, and Behavior, 2014-present. • National Science Foundation, Program Director for Big Data, July 2012-July 2013. • Member, Big Data Senior Steering Group of NITRD (The Networking and Information Tech- nology Research and Development Program), subcomittee of the National Technology Council (coordinating federal agencies), 2012-2013 • Departmental Scholar, Institute for Pure and Applied Mathematics, UCLA, Fall 2011 • Visiting Researcher, University of Maryland, Spring and Summer 2011. 1 • Visiting Researcher, Smithsonian Institute, Spring and Summer 2011. • Professeur Invit´e,Ecole Polytechnique F´ed´erale de Lausanne (EPFL), Summer 2010.