Research in Computational Molecular Biology
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Current Topics in Computational Molecular Biology Edited by Tao Jiang Ying Xu Michael Q. Zhang a Bradford Book the MIT Press
Current Topics in Computational Molecular Biology edited by Tao Jiang Ying Xu Michael Q. Zhang A Bradford Book The MIT Press Cambridge, Massachusetts London, England Contents Preface vii I INTRODUCTION 1 1 The Challenges Facing Genomic Informatics 3 Temple F. Smith H COMPARATIVE SEQUENCE AND GENOME ANALYSIS 9 2 Bayesian Modeling and Computation in Bioinformatics Research 11 Jun S. Liu 3 Bio-Sequence Comparison and Applications 45 Xiaoqiu Huang 4 Algorithmic Methods for Multiple Sequence Alignment 71 Tao Jiang and Lusheng Wang 5 Phylogenetics and the Quartet Method 111 Paul Kearney 6 Genome Rearrangement 135 David Sankoff and Nadia El-Mabrouk 7 Compressing DNA Sequences 157 Ming Li HI DATA MINING AND PATTERN DISCOVERY 173 8 Linkage Analysis of Quantitative Traits 175 Shizhong Xu , 9 Finding Genes by Computer: Probabilistic and Discriminative Approaches 201 Victor V. Solovyev 10 Computational Methods for Promoter Recognition 249 Michael Q. Zhang 11 Algorithmic Approaches to Clustering Gene Expression Data 269 Ron Shamir and Roded Sharan 12 KEGG for Computational Genomics 301 Minoru Kanehisa and Susumu Goto vi Contents 13 Datamining: Discovering Information from Bio-Data 317 Limsoon Wong IV COMPUTATIONAL STRUCTURAL BIOLOGY 343 14 RNA Secondary Structure Prediction 345 Zhuozhi Wang and Kaizhong Zhang 15 Properties and Prediction of Protein Secondary Structure 365 Victor V. Solovyev and Ilya N. Shindyalov 16 Computational Methods for Protein Folding: Scaling a Hierarchy of Complexities 403 Hue Sun Chan, Huseyin Kaya, and Seishi Shimizu 17 Protein Structure Prediction by Comparison: Homology-Based Modeling 449 Manuel C. Peitsch, Torsten Schwede, Alexander Diemand, and Nicolas Guex 18 Protein Structure Prediction by Protein Threading and Partial Experimental Data 467 Ying Xu and Dong Xu 19 Computational Methods for Docking and Applications to Drug Design: Functional Epitopes and Combinatorial Libraries 503 Ruth Nussinov, Buyong Ma, and Haim J. -
Bonnie Berger Named ISCB 2019 ISCB Accomplishments by a Senior
F1000Research 2019, 8(ISCB Comm J):721 Last updated: 09 APR 2020 EDITORIAL Bonnie Berger named ISCB 2019 ISCB Accomplishments by a Senior Scientist Award recipient [version 1; peer review: not peer reviewed] Diane Kovats 1, Ron Shamir1,2, Christiana Fogg3 1International Society for Computational Biology, Leesburg, VA, USA 2Blavatnik School of Computer Science, Tel Aviv University, Tel Aviv, Israel 3Freelance Writer, Kensington, USA First published: 23 May 2019, 8(ISCB Comm J):721 ( Not Peer Reviewed v1 https://doi.org/10.12688/f1000research.19219.1) Latest published: 23 May 2019, 8(ISCB Comm J):721 ( This article is an Editorial and has not been subject https://doi.org/10.12688/f1000research.19219.1) to external peer review. Abstract Any comments on the article can be found at the The International Society for Computational Biology (ISCB) honors a leader in the fields of computational biology and bioinformatics each year with the end of the article. Accomplishments by a Senior Scientist Award. This award is the highest honor conferred by ISCB to a scientist who is recognized for significant research, education, and service contributions. Bonnie Berger, Simons Professor of Mathematics and Professor of Electrical Engineering and Computer Science at the Massachusetts Institute of Technology (MIT) is the 2019 recipient of the Accomplishments by a Senior Scientist Award. She is receiving her award and presenting a keynote address at the 2019 Joint International Conference on Intelligent Systems for Molecular Biology/European Conference on Computational Biology in Basel, Switzerland on July 21-25, 2019. Keywords ISCB, Bonnie Berger, Award This article is included in the International Society for Computational Biology Community Journal gateway. -
120421-24Recombschedule FINAL.Xlsx
Friday 20 April 18:00 20:00 REGISTRATION OPENS in Fira Palace 20:00 21:30 WELCOME RECEPTION in CaixaForum (access map) Saturday 21 April 8:00 8:50 REGISTRATION 8:50 9:00 Opening Remarks (Roderic GUIGÓ and Benny CHOR) Session 1. Chair: Roderic GUIGÓ (CRG, Barcelona ES) 9:00 10:00 Richard DURBIN The Wellcome Trust Sanger Institute, Hinxton UK "Computational analysis of population genome sequencing data" 10:00 10:20 44 Yaw-Ling Lin, Charles Ward and Steven Skiena Synthetic Sequence Design for Signal Location Search 10:20 10:40 62 Kai Song, Jie Ren, Zhiyuan Zhai, Xuemei Liu, Minghua Deng and Fengzhu Sun Alignment-Free Sequence Comparison Based on Next Generation Sequencing Reads 10:40 11:00 178 Yang Li, Hong-Mei Li, Paul Burns, Mark Borodovsky, Gene Robinson and Jian Ma TrueSight: Self-training Algorithm for Splice Junction Detection using RNA-seq 11:00 11:30 coffee break Session 2. Chair: Bonnie BERGER (MIT, Cambrige US) 11:30 11:50 139 Son Pham, Dmitry Antipov, Alexander Sirotkin, Glenn Tesler, Pavel Pevzner and Max Alekseyev PATH-SETS: A Novel Approach for Comprehensive Utilization of Mate-Pairs in Genome Assembly 11:50 12:10 171 Yan Huang, Yin Hu and Jinze Liu A Robust Method for Transcript Quantification with RNA-seq Data 12:10 12:30 120 Zhanyong Wang, Farhad Hormozdiari, Wen-Yun Yang, Eran Halperin and Eleazar Eskin CNVeM: Copy Number Variation detection Using Uncertainty of Read Mapping 12:30 12:50 205 Dmitri Pervouchine Evidence for widespread association of mammalian splicing and conserved long range RNA structures 12:50 13:10 169 Melissa Gymrek, David Golan, Saharon Rosset and Yaniv Erlich lobSTR: A Novel Pipeline for Short Tandem Repeats Profiling in Personal Genomes 13:10 13:30 217 Rory Stark Differential oestrogen receptor binding is associated with clinical outcome in breast cancer 13:30 15:00 lunch break Session 3. -
ISMB 99 August 6 – 10, 1999 Heidelberg, Germany the Seventh
______________________________________ Welcome to ISMB 99 August 6 – 10, 1999 Heidelberg, Germany The Seventh International Conference on Intelligent Systems for Molecular Biology ______________________________________ Final Program and Detailed Schedule Friday, August 6, 1999 Tutorial Day The tutorials will take place in the following rooms: 8:30 – 12:30 (Coffee break around 10:30) Tutorial #1 Trübnersaal Piere Baldi Probabilistic graphical models Tutorial #2 Robert-Schumann-Zimmer Douglas L. Brutlag Bioinformatics and Molecular Biology Tutorial #3 Ballsaal Martin Reese The challenge of annotating a complete eukaryotic genome: A case study in Drosophila melanogaster Tutorial #4 Gustav-Mahler-Zimmer Tandy Warnow Computational and statistical Junhyong Kim challenges involved in reconstructing evolutionary trees Tutorial #5 Sebastian-Münster-Saal Thomas Werner The biology and bioinformatics of regulatory regions in genomes Lunch (on this day served in "Grosser Saal" on the ground floor) 13:30 – 17:30 (Coffee break around 15:30) Tutorial #6 Sebastian-Münster-Saal Rob Miller EST Clustering Alan Christoffels Winston Hide Tutorial #7 Trübnersaal Kevin Karplus Getting the most out of hidden Markov Melissa Cline models Christian Barrett Tutorial #8 Robert-Schumann-Zimmer Arthur Lesk Sequence-structure relationships and evolutionary structure changes in proteins Tutorial #9 Gustav-Mahler-Zimmer David States PERL abstractions for databases and Brian Dunford distributed computing Shore Tutorial # 10 Ballsaal Zoltan Szallasi Genetic network analysis -
Extrachromosomal and Other Mechanisms of Oncogene Amplification in Cancer
Title: Extrachromosomal and other mechanisms of oncogene amplification in cancer Abstract: Increase in the number of copies of tumor promoting (onco-) genes is a hallmark of many cancers, and cancers with copy number amplifications are often associated with poor outcomes. Despite their importance, the mechanisms causing these amplifications are incompletely understood. In this talk, we describe our recent results suggesting that a large faction of amplification is due to formation of extrachromosomal DNA (ecDNA). EcDNA play a critical role in tumor heterogeneity, accelerated cancer evolution, and drug resistance through their unique mechanism of non-chromosomal inheritance. While predominant, ecDNA are not the only mechanism to cause amplification. We also describe recent algorithmic methods required to distinguish ecDNA from other mechanisms including Breakage Fusion Bridge formation, Chromothripsis, and simpler events such as tandem duplications and translocations. The talk is a mix of published and unpublished work, largely in collaboration with Paul Mischel's lab at UCSD. EcDNA was recently recognized as one of the grand challenges of cancer research by Cancer Research UK and the National Cancer Institute. Reading Luebeck, 2020, Verhaak 2019 Biography Vineet Bafna, Ph.D., joined the Computer Science faculty at the University of California, San Diego in 2003, after seven years in the biosciences industry. He received his Ph.D. in computer science from The Pennsylvania State University in 1994 and was an NSF postdoctoral researcher at the Center for Discrete Mathematics and Theoretical Computer Science for two years. From 1996-99, Bafna was a senior investigator at SmithKline Beecham, conducting research on DNA signaling, target discovery and EST assembly. -
UC San Diego Electronic Theses and Dissertations
UC San Diego UC San Diego Electronic Theses and Dissertations Title Computational methods for genome-wide non-coding RNA discovery and analysis Permalink https://escholarship.org/uc/item/5qc2h8tf Author Zhang, Shaojie Publication Date 2007 Peer reviewed|Thesis/dissertation eScholarship.org Powered by the California Digital Library University of California UNIVERSITY OF CALIFORNIA, SAN DIEGO Computational Methods for Genome-Wide Non-Coding RNA Discovery and Analysis A dissertation submitted in partial satisfaction of the requirements for the degree Doctor of Philosophy in Computer Science by Shaojie Zhang Committee in charge: Professor Vineet Bafna, Chair Professor Sanjoy Dasgupta Professor Pavel Pevzner Professor Glenn Tesler Professor Steven Wasserman 2007 . Copyright Shaojie Zhang, 2007 All rights reserved. The dissertation of Shaojie Zhang is approved, and it is acceptable in quality and form for publication on micro- ¯lm: Chair University of California, San Diego 2007 iii To my parents. iv TABLE OF CONTENTS Signature Page . iii Dedication . iv Table of Contents . v List of Figures . vii List of Tables . viii Acknowledgements . ix Vita, Publications, and Fields of Study . xi Abstract . xiii 1 Introduction . 1 1.1 Non-coding RNAs . 1 1.2 RNA secondary structure . 4 1.3 The Challenge of ncRNA Discovery and Analysis . 6 1.3.1 RNA Homolog Search . 7 1.3.2 RNA Consensus Folding for ncRNA Discovery . 8 1.4 Dissertation Outline . 9 2 FastR: Fast RNA Search Using Structure-based Filters . 11 2.1 Introduction . 11 2.2 Methods . 14 2.2.1 Strucutre-based Filters . 14 2.2.2 Structure-based Filter Design . 17 2.2.3 Optimal Structure-based Filter Design . -
Call for Papers (Page 1)
CALL FOR PAPERS IEEE Computational Systems Bioinformatics Conference Stanford, CA • August 8-11, 2005 You are invited to submit papers to the 2005 IEEE Computational Systems Bioinformatics Conference (CSB2005). The conference’s goal is to facilitate exchange of ideas and collaborations between computer scientists and biologists by presenting cutting-edge computational biology research findings. Such research has an interdisciplinary character. Computer science and mathematical modeling papers must contain a concise description of the biological problem being solved, and biology papers should show how computation or analysis affects the results. Topics of interest include (but are not limited to): • Microarray Data Analysis • Mathematical and Quantitative Models • MicroRNA and RNAi of Cellular and Multicellular Systems • Pathways, Networks, Systems Biology • Synthetic Biological Systems • Biomedical Applications • Sequence Alignment • Biological Data Visualization • Evolution and Phylogenetics • Protein Structures and Complexes • Functional Genomics • Biological Data Mining • High Performance Bio-computing • Pattern Recognition • Comparative Genomics • Microbial Community Analysis • SNPs and Haplotyping • Promoter Analysis and Discovery Full papers are limited to 12 pages, single-spaced, in 12-point type, including title, abstract (250 words or less), figures, tables, text, and bibliography. The first page should give keywords, authors’ postal and electronic mailing addresses. Papers must not have been previously published and must not be currently under consideration for publication elsewhere. Papers will be submitted electronically in MS Word, postscript or PDF format. This year, the conference will also accept short papers, limited to four pages. These papers should describe new research activity in which a complete set of results may not yet be available. Full and short papers will have 25 and 15 minutes, respectively, of presentation time. -
Parallelization of Dynamic Programming Recurrences in Computational Biology Arpith Jacob Washington University in St
Washington University in St. Louis Washington University Open Scholarship All Theses and Dissertations (ETDs) January 2010 Parallelization of dynamic programming recurrences in computational biology Arpith Jacob Washington University in St. Louis Follow this and additional works at: https://openscholarship.wustl.edu/etd Recommended Citation Jacob, Arpith, "Parallelization of dynamic programming recurrences in computational biology" (2010). All Theses and Dissertations (ETDs). 169. https://openscholarship.wustl.edu/etd/169 This Dissertation is brought to you for free and open access by Washington University Open Scholarship. It has been accepted for inclusion in All Theses and Dissertations (ETDs) by an authorized administrator of Washington University Open Scholarship. For more information, please contact [email protected]. WASHINGTON UNIVERSITY IN ST. LOUIS School of Engineering and Applied Science Department of Computer Science and Engineering Thesis Examination Committee: Jeremy Buhler, Chair Michael Brent Ron Cytron Mark Franklin Robert Morley Bill Smart David Taylor PARALLELIZATION OF DYNAMIC PROGRAMMING RECURRENCES IN COMPUTATIONAL BIOLOGY by Arpith Chacko Jacob A dissertation presented to the Graduate School of Arts and Sciences of Washington University in partial fulfillment of the requirements for the degree of DOCTOR OF PHILOSOPHY December 2010 Saint Louis, Missouri copyright by Arpith Chacko Jacob 2010 ABSTRACT OF THE THESIS Parallelization of dynamic programming recurrences in computational biology by Arpith Chacko Jacob Doctor of Philosophy in Computer Science Washington University in St. Louis, 2010 Research Advisor: Professor Jeremy Buhler The rapid growth of biosequence databases over the last decade has led to a per- formance bottleneck in the applications analyzing them. In particular, over the last five years DNA sequencing capacity of next-generation sequencers has been doubling every six months as costs have plummeted. -
PLOS Computational Biology Associate Editor Handbook Second Edition Version 2.6
PLOS Computational Biology Associate Editor Handbook Second Edition Version 2.6 Welcome and thank you for your support of PLOS Computational Biology and the Open Access movement. PLOS Computational Biology is one of the four community run, Open Access journals published by the Public Library of Science. The journal features works of exceptional significance that further our understanding of living systems at all scales—from molecules and cells, to patient populations and ecosystems—through the application of computational methods. Readers include life and computational scientists, who can take the important findings presented here to the next level of discovery. Since its launch in 2005, PLOS Computational Biology has grown not only in the number of papers published, but also in recognition as a quality publication and community resource. We have every reason to expect that this trend will continue and our team of Associate Editors play an invaluable role in this process. Associate Editors oversee the peer review process for the journal, including evaluating submissions, selecting reviewers, assessing reviewer comments, and making editorial decisions. Together with fellow Editorial Board members and the PLOS CB Team, Associate Editors uphold journal policies and ethical standards and work to promote the PLOS mission to provide free public access to scientific research. PLOS Computational Biology is one of a suite of influential journals published by PLOS. Information about the other journals, the PLOS business model, PLOS innovations in scientific publishing, and Open Access copyright and licensure can be found in Appendix IX. Table of Contents PLOS Computational Biology Editorial Board Membership ................................................................................... 2 Manuscript Evaluation ..................................................................................................................................... -
Computational Discovery of Splicing Events from High-Throughput Omics Data
COMPUTATIONAL DISCOVERY OF SPLICING EVENTS FROM HIGH-THROUGHPUT OMICS DATA by Yen-Yi Lin M.Sc., National Taiwan University, 2008 B.Sc., National Taiwan University, 2003 Thesis Submitted in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy in the School of Computing Sciences Faculty of Applied Sciences c Yen-Yi Lin 2017 SIMON FRASER UNIVERSITY Summer 2017 Copyright in this work rests with the author. Please ensure that any reproduction or re-use is done in accordance with the relevant national copyright legislation. Approval Name: Yen-Yi Lin Degree: Doctor of Philosophy (Computing Sciences) Title: COMPUTATIONAL DISCOVERY OF SPLICING EVENTS FROM HIGH-THROUGHPUT OMICS DATA Examining Committee: Chair: Faraz Hach University Research Associate Cenk Sahinalp Senior Supervisor Professor Martin Ester Senior Supervisor Professor Peter Unrau Supervisor Professor Dept. of Molecular Biology and Biochemistry Leonid Chindelevitch Internal Examiner Assistant Professor Vineet Bafna External Examiner Professor Computer Science and Engineering University of California, San Diego Date Defended: July 18, 2017 ii Abstract The splicing mechanism, the process of forming mature messenger RNA (mRNA) by only concatenating exons and removing introns, is an essential step in gene expression. It allows a single gene to have multiple RNA isoforms which potentially code different proteins. In addition, aberrant transcripts generated from non-canonical splicing events (e.g. gene fusions) are believed to be potential drivers in many tumor types and human diseases. Thus, identification and quantification of expressed RNAs from RNA-Seq data become fundamental steps in many clinical studies. For that reason, number of methods have been developed. Most popular computational methods designed for these high-throughput omics data start by analyzing the datasets based on existing gene annotations. -
Predicting RNA Binding Proteins Using Discriminative Methods
Predicting RNA binding proteins using discriminative methods by Shweta Bhandare M.S. Department of Interdisciplinary Telecommunications, University of Colorado at Boulder 2003 B.E., College of Engineering, University of Goa, 1995 A thesis submitted to the Faculty of the Graduate School of the University of Colorado in partial fulfillment of the requirements for the degree of Doctor of Philosophy Department of Computer Science 2017 This thesis entitled: Predicting RNA binding proteins using discriminative methods written by Shweta Bhandare has been approved for the Department of Computer Science Prof. Robin Dowell Dr. Debra S. Goldberg Prof. Larry E. Hunter Dr. Daniel Weaver Date The final copy of this thesis has been examined by the signatories, and we find that both the content and the form meet acceptable presentation standards of scholarly work in the above mentioned discipline. iii Bhandare, Shweta (Ph.D., Computer Science) Predicting RNA binding proteins using discriminative methods Thesis directed by Prof. Robin Dowell and Dr. Debra S. Goldberg This thesis examines the role of computational methods in identifying the motifs utilized by RNA-binding proteins (RBPs). RBPs play an important role in post-transcriptional regulation and identify their targets in a highly specific fashion through recognition of primary sequence and/or secondary structure hence making the prediction a complex problem. I applied the existing k-spectrum kernel method to a support vector machine and verified the published binding sites of two RBPs: Human antigen R (HuR) and Tristetraprolin (TTP). These RBPs exhibit opposing effects to the bound messenger RNA (mRNA) transcript but have simi- lar binding preferences. -
Front Matter
Cambridge University Press 978-1-107-01146-5 - Bioinformatics for Biologists Edited by Pavel Pevzner and Ron Shamir Frontmatter More information BIOINFORMATICS FOR BIOLOGISTS The computational education of biologists is changing to prepare students for facing the complex data sets of today’s life science research. In this concise textbook, the authors’ fresh pedagogical approaches lead biology students from first principles towards computational thinking. A team of renowned bioinformaticians take innovative routes to introduce computational ideas in the context of real biological problems. Intuitive explanations promote deep understanding, using little mathematical formalism. Self-contained chapters show how computational procedures are developed and applied to central topics in bioinformatics and genomics, such as the genetic basis of disease, genome evolution, or the tree of life concept. Using bioinformatic resources requires a basic understanding of what bioinformatics is and what it can do. Rather than just presenting tools, the authors – each a leading scientist – engage the students’ problem-solving skills, preparing them to meet the computational challenges of their life science careers. PAVEL PEVZNER is Ronald R. Taylor Professor of Computer Science and Director of the Bioinformatics and Systems Biology Program at the University of California, San Diego. He was named a Howard Hughes Medical Institute Professor in 2006. RON SHAMIR is Raymond and Beverly Sackler Professor of Bioinformatics and head of the Edmond J. Safra Bioinformatics