ACM BCB 2014 Program
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Proquest Dissertations
Automated learning of protein involvement in pathogenesis using integrated queries Eithon Cadag A dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy University of Washington 2009 Program Authorized to Offer Degree: Department of Medical Education and Biomedical Informatics UMI Number: 3394276 All rights reserved INFORMATION TO ALL USERS The quality of this reproduction is dependent upon the quality of the copy submitted. In the unlikely event that the author did not send a complete manuscript and there are missing pages, these will be noted. Also, if material had to be removed, a note will indicate the deletion. UMI Dissertation Publishing UMI 3394276 Copyright 2010 by ProQuest LLC. All rights reserved. This edition of the work is protected against unauthorized copying under Title 17, United States Code. uest ProQuest LLC 789 East Eisenhower Parkway P.O. Box 1346 Ann Arbor, Ml 48106-1346 University of Washington Graduate School This is to certify that I have examined this copy of a doctoral dissertation by Eithon Cadag and have found that it is complete and satisfactory in all respects, and that any and all revisions required by the final examining committee have been made. Chair of the Supervisory Committee: Reading Committee: (SjLt KJ. £U*t~ Peter Tgffczy-Hornoch In presenting this dissertation in partial fulfillment of the requirements for the doctoral degree at the University of Washington, I agree that the Library shall make its copies freely available for inspection. I further agree that extensive copying of this dissertation is allowable only for scholarly purposes, consistent with "fair use" as prescribed in the U.S. -
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. -
Methodology for Predicting Semantic Annotations of Protein Sequences by Feature Extraction Derived of Statistical Contact Potentials and Continuous Wavelet Transform
Universidad Nacional de Colombia Sede Manizales Master’s Thesis Methodology for predicting semantic annotations of protein sequences by feature extraction derived of statistical contact potentials and continuous wavelet transform Author: Supervisor: Gustavo Alonso Arango Dr. Cesar German Argoty Castellanos Dominguez A thesis submitted in fulfillment of the requirements for the degree of Master’s on Engineering - Industrial Automation in the Department of Electronic, Electric Engineering and Computation Signal Processing and Recognition Group June 2014 Universidad Nacional de Colombia Sede Manizales Tesis de Maestr´ıa Metodolog´ıapara predecir la anotaci´on sem´antica de prote´ınaspor medio de extracci´on de caracter´ısticas derivadas de potenciales de contacto y transformada wavelet continua Autor: Tutor: Gustavo Alonso Arango Dr. Cesar German Argoty Castellanos Dominguez Tesis presentada en cumplimiento a los requerimientos necesarios para obtener el grado de Maestr´ıaen Ingenier´ıaen Automatizaci´onIndustrial en el Departamento de Ingenier´ıaEl´ectrica,Electr´onicay Computaci´on Grupo de Procesamiento Digital de Senales Enero 2014 UNIVERSIDAD NACIONAL DE COLOMBIA Abstract Faculty of Engineering and Architecture Department of Electronic, Electric Engineering and Computation Master’s on Engineering - Industrial Automation Methodology for predicting semantic annotations of protein sequences by feature extraction derived of statistical contact potentials and continuous wavelet transform by Gustavo Alonso Arango Argoty In this thesis, a method to predict semantic annotations of the proteins from its primary structure is proposed. The main contribution of this thesis lies in the implementation of a novel protein feature representation, which makes use of the pairwise statistical contact potentials describing the protein interactions and geometry at the atomic level. -
BMC Bioinformatics Biomed Central
BMC Bioinformatics BioMed Central Proceedings Open Access NIPS workshop on New Problems and Methods in Computational Biology Gal Chechik*1, Christina Leslie2, William Stafford Noble3, Gunnar Rätsch4, Quaid Morris5 and Koji Tsuda6 Address: 1Computer Science Department, Stanford University, 353 Serra Mall, Stanford University, Stanford, CA 94305, USA, 2Computational Biology Program, Memorial Sloan-Kettering Cancer Center, 1275 York Ave, Box 460, New York, NY 10065, USA, 3Department of Genome Sciences, University of Washington, 1705 NE Pacific St, Seattle, WA 98109, USA, 4Friedrich Miescher Laboratory of the Max Planck Society, Spemannstr. 39, 72076 Tübingen, Germany, 5Terrence Donnelley Centre for Cellular and Biomolecular Research, University of Toronto, 160 College Street, Toronto, Ontario, M5S 3E1, Canada and 6Max Planck Institute for Biological Cybernetics, Spemannstr. 38, 72076 Tübingen, Germany Email: Gal Chechik* - [email protected]; Christina Leslie - [email protected]; William Stafford Noble - [email protected]; Gunnar Rätsch - [email protected]; Quaid Morris - [email protected]; Koji Tsuda - [email protected] * Corresponding author from NIPS workshop on New Problems and Methods in Computational Biology Whistler, Canada. 8 December 2006 Published: 21 December 2007 BMC Bioinformatics 2007, 8(Suppl 10):S1 doi:10.1186/1471-2105-8-S10-S1 <supplement> <title> <p>Neural Information Processing Systems (NIPS) workshop on New Problems and Methods in Computational Biology</p> </title> <editor>Gal Chechik, Christina Leslie, William Stafford Noble, Gunnar Rätsch, Quiad Morris and Koji Tsuda</editor> <note>Proceedings</note> <url>http://www.biomedcentral.com/content/pdf/1471-2105-8-S10-info.pdf</url> </supplement> This article is available from: http://www.biomedcentral.com/1471-2105/8/S10/S1 © 2007 Chechik et al; licensee BioMed Central Ltd. -
UC San Diego UC San Diego Electronic Theses and Dissertations
UC San Diego UC San Diego Electronic Theses and Dissertations Title Analysis and applications of conserved sequence patterns in proteins Permalink https://escholarship.org/uc/item/5kh9z3fr Author Ie, Tze Way Eugene Publication Date 2007 Peer reviewed|Thesis/dissertation eScholarship.org Powered by the California Digital Library University of California UNIVERSITY OF CALIFORNIA, SAN DIEGO Analysis and Applications of Conserved Sequence Patterns in Proteins A dissertation submitted in partial satisfaction of the requirements for the degree Doctor of Philosophy in Computer Science by Tze Way Eugene Ie Committee in charge: Professor Yoav Freund, Chair Professor Sanjoy Dasgupta Professor Charles Elkan Professor Terry Gaasterland Professor Philip Papadopoulos Professor Pavel Pevzner 2007 Copyright Tze Way Eugene Ie, 2007 All rights reserved. The dissertation of Tze Way Eugene Ie is ap- proved, and it is acceptable in quality and form for publication on microfilm: Chair University of California, San Diego 2007 iii DEDICATION This dissertation is dedicated in memory of my beloved father, Ie It Sim (1951–1997). iv TABLE OF CONTENTS Signature Page . iii Dedication . iv Table of Contents . v List of Figures . viii List of Tables . x Acknowledgements . xi Vita, Publications, and Fields of Study . xiii Abstract of the Dissertation . xv 1 Introduction . 1 1.1 Protein Homology Search . 1 1.2 Sequence Comparison Methods . 2 1.3 Statistical Analysis of Protein Motifs . 4 1.4 Motif Finding using Random Projections . 5 1.5 Microbial Gene Finding without Assembly . 7 2 Multi-Class Protein Classification using Adaptive Codes . 9 2.1 Profile-based Protein Classifiers . 14 2.2 Embedding Base Classifiers in Code Space . -
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. -
The Pan-NLR'ome of Arabidopsis Thaliana
The pan-NLR’ome of Arabidopsis thaliana Dissertation der Mathematisch-Naturwissenschaftlichen Fakultät der Eberhard Karls Universität Tübingen zur Erlangung des Grades eines Doktors der Naturwissenschaften (Dr. rer. nat.) vorgelegt von Anna-Lena Van de Weyer aus Bad Kissingen Tübingen 2019 Gedruckt mit Genehmigung der Mathematisch-Naturwissenschaftlichen Fakultät der Eberhard Karls Universität Tübingen. Tag der mündlichen Qualifikation: 25.03.2019 Dekan: Prof. Dr. Wolfgang Rosenstiel 1. Berichterstatter: Prof. Dr. Detlef Weigel 2. Berichterstatter: Prof. Dr. Thorsten Nürnberger Acknowledgements I would like to thank my thesis advisors Prof. Detlef Weigel and Prof. Thorsten Nürnberger for not only their continuous support during my PhD studies but also for their critical questions and helpful ideas that shaped and developed my project. Fur- thermore, I would like to thank Dr. Felicity Jones for being part of my Thesis Advisory Committee, for fruitful discussions and for her elaborate questions. I would like to express my sincere gratitude to Dr. Felix Bemm, who worked closely with me during the last years, who continuously challenged and promoted me and with- out whom I would not be where and who I am now. In the mindmap for my acknowl- edgement I wrote down ’Felix: thanks for everything’. That says it all. Further thanks goes to my collaborators Dr. Freddy Monteiro and Dr. Oliver Furzer for their essential contributions to experiments and analyses during all stages of my PhD. Their sheer endless knowledge of NLR biology amplified my curiosity and enthusiasm to learn. Freddy deserves a special thank you for his awesome collaborative spirit and for answering all my NLR related newbie questions. -
Supplementary Materials For
1 Supplementary Materials for 2 3 Aishwarya Korgaonkar, Clair Han, Andrew L. Lemire, Igor Siwanowicz, Djawed Bennouna, 4 Rachel Kopec, Peter Andolfatto, Shuji Shigenobu, David L. Stern 5 6 Correspondence to: [email protected] 7 8 9 This PDF file includes: 10 11 Materials and Methods 12 Supplementary Text 13 Figs. S1 to S16 14 Tables S1 to S11 15 16 Other Supplementary Materials for this manuscript include the following: 17 18 Movie S1 19 20 1 21 Materials and Methods 22 23 Imaging of leaves and fundatrices inside developing galls 24 25 Young Hamamelis virginiana (witch hazel) leaves or leaves with early stage galls of 26 Hormaphis cornu were fixed in Phosphate Buffered Saline (PBS: 137 mM NaCl, 2.7 mM KCl, 27 10 mM Na2HPO4, 1.8 mM KH2PO4, pH 7.4) containing 0.1% Triton X-100, 2% 28 paraformaldehyde and 0.5% glutaraldehyde (paraformaldehyde and glutaraldehyde were EM 29 grade from Electron Microscopy Services) at room temperature for two hours without agitation 30 to prevent the disruption of the aphid stylet inserted into leaf tissue. Fixed leaves or galls were 31 washed in PBS containing 0.1% Triton X-100, hand cut into small sections (~10 mm2), and 32 embedded in 7% agarose for subsequent sectioning into 0.3 mm thick sections using a Leica 33 Vibratome (VT1000s). Sectioned plant tissue was stained with Calcofluor White (0.1 mg/mL, 34 Sigma-Aldrich, F3543) and Congo Red (0.25 mg/mL, Sigma-Aldrich, C6767) in PBS 35 containing 0.1% Triton X-100 with 0.5% DMSO and Escin (0.05 mg/mL, Sigma-Aldrich, 36 E1378) at room temperature with gentle agitation for 2 days. -
Proceedings of the Eighteenth International Conference on Machine Learning., 282 – 289
Abstracts of papers, posters and talks presented at the 2008 Joint RECOMB Satellite Conference on REGULATORYREGULATORY GENOMICS GENOMICS - SYSTEMS BIOLOGY - DREAM3 Oct 29-Nov 2, 2008 MIT / Broad Institute / CSAIL BMP follicle cells signaling EGFR signaling floor cells roof cells Organized by Manolis Kellis, MIT Andrea Califano, Columbia Gustavo Stolovitzky, IBM Abstracts of papers, posters and talks presented at the 2008 Joint RECOMB Satellite Conference on REGULATORYREGULATORY GENOMICS GENOMICS - SYSTEMS BIOLOGY - DREAM3 Oct 29-Nov 2, 2008 MIT / Broad Institute / CSAIL Organized by Manolis Kellis, MIT Andrea Califano, Columbia Gustavo Stolovitzky, IBM Conference Chairs: Manolis Kellis .................................................................................. Associate Professor, MIT Andrea Califano ..................................................................... Professor, Columbia University Gustavo Stolovitzky....................................................................Systems Biology Group, IBM In partnership with: Genome Research ..............................................................................editor: Hillary Sussman Nature Molecular Systems Biology ............................................... editor: Thomas Lemberger Journal of Computational Biology ...............................................................editor: Sorin Istrail Organizing committee: Eleazar Eskin Trey Ideker Eran Segal Nir Friedman Douglas Lauffenburger Ron Shamir Leroy Hood Satoru Miyano Program Committee: Regulatory Genomics: -
Table of Contents
January 10-14, 2015 PLANT & ANIMAL GENOME XXIII Town & Country Hotel THE INTERNATIONAL CONFERENCE San Diego, CA ON THE STATUS OF PLANT & ANIMAL GENOME RESEARCH FINAL PROGRAM, ABSTRACT & EXHIBIT GUIDE Organizing Committee Chairman: Stephen R. Heller, NIST (USA) A PLANT CO-ORGANIZERS A ABSTRACT & WEBSITE Dave Clements, Johns Hopkins University, COORDINATORS USA Victoria Carollo Blake, USDA/ARS/WRRC, Catherine Feuillet, Bayer CropScience, USA USA David Grant, USDA/ARS/CICGR, USA J. Perry Gustafson, University of Missouri, Gerard Lazo, USDA/ARS/WRRC, USA (Retired ), USA Jerome P. Miksche, Emeritus Director, A TRAVEL GRANTS COORDINATOR USDA, Plant Genome Program, USA Douglas Bigwood, Diogenix, USA Graham Moore, John Innes Centre, UK Tom Blake, Montana State University Susan R. Wessler, University of California, (Retired), USA Riverside, USA Rod A. Wing, University of Arizona, USA A SPECIAL DUTY COORDINATORS Hans Cheng, USDA/ARS, USA A ANIMAL CO-ORGANIZERS Max Rothschild, Iowa State University, Ernie Bailey, University of Kentucky, USA USA Daniel Ciobanu, University of Nebraska, USA Kwan-Suk Kim, Chungbuk National University, South Korea Stephen White, USDA/ARS, USA Sponsors and Supporters ORGANIZER Scherago International A USDA, Agricultural Research Service 111 Town Square Place A USDA, National Agricultural Library Suite 1208 USDA, National Institute of Food and Agriculture A Jersey City, NJ 07310 A John Innes Centre Phone: (201) 653-4777 Fax: (201) 653-5705 Cover artwork provided by Applied Biosystems. Originally developed for the company’s -
Classifying Peroxiredoxin Subgroups and Identifying
CLASSIFYING PEROXIREDOXIN SUBGROUPS AND IDENTIFYING DISCRIMINATING MOTIFS VIA MACHINE LEARNING BY JIAJIE XIAO A Thesis Submitted to the Graduate Faculty of WAKE FOREST UNIVERSITY GRADUATE SCHOOL OF ARTS AND SCIENCES in Partial Fulfillment of the Requirements for the Degree of MASTER OF SCIENCE Computer Science May, 2018 Winston-Salem, North Carolina Approved By: William Turkett, Jr., Ph.D., Advisor David John, Ph.D., Chair Grey Ballard, Ph.D. James Pease, Ph.D. Dedication This work is dedicated to my parents, Mingfu Xiao and Lizhu Xu, my sister, Wanling Xiao. Because of their hard work, I get to be exactly who I want to be. ii Acknowledgments First, I would like to show my gratitude towards the Center for Molecular Communication and Signaling for supporting me as a Research Fellow for the fall semester in 2017-2018 academic year. The extra time and focus has helped me expand my research project in directions I would not have been able to explore otherwise. I would also like to thank the Department of Computer Science at Wake Forest University. I appreciate all of the resources and support that the department has provided me with in order to complete my thesis. I would also like to thank the professors who have been very helpful and welcoming during coursework, seminars, and hallway passings. I want to thank Dr. John, Dr. Ballard, and Dr. Pease for being on my committee. I appreciate your input and the time you are taking to help me complete my thesis. I want to thank Dr. Poole for the interactions in the Prx subgroup classification project. -
Probabilistic Protein Engineering
Probabilistic Protein Engineering Thesis by Kevin Kaichuang Yang In Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy in Chemical Engineering CALIFORNIA INSTITUTE OF TECHNOLOGY Pasadena, California 2019 Defended 14 Dec 2018 ii © 2019 Kevin Kaichuang Yang ORCID: 0000-0001-9045-6826 Some rights reserved. This thesis is distributed under a Creative Commons Attribution-NonCommercial-ShareAlike License iii ACKNOWLEDGEMENTS First, I’d like to thank my advisor Frances Arnold for her support and guidance throughout my PhD. I applied to Caltech because I wanted to work for Frances, and she has not disappointed. Even as I took a detour to teach high school, she welcomed me into her lab first for a summer, and then for my PhD. Frances has a keen eye for important but tractable scientific problems and gave me the freedom to pursue them past the boundaries of her discipline. Frances has pushed me to be a better scientist, and her lessons are the foundation for the rest of my career. One thing Frances has done very well is to build a world-class research group. I would like to specifically thank several group members. During my first stint in the lab, Sabine Brinkmann-Chen, John McIntosh, and Chris Farwell taught me to perform directed evolution. Sabine also keeps us all safe, happy, and productive. When I rejoined the lab, Lukas Herwig reacquainted me with molecular biology. It was a joy to work with Claire Bedbrook and Austin Rice on my first three papers. Thank you for collecting my data for me. Zachary Wu has been a great co-belligerent for the cause of machine learning in the Arnold lab.