REGULATORY GENOMICS - REGULATORYSYSTEMS BIOLOGY GENOMICS - DREAM4 Wed Dec 2-Sun Dec 6, 2009

Total Page:16

File Type:pdf, Size:1020Kb

REGULATORY GENOMICS - REGULATORYSYSTEMS BIOLOGY GENOMICS - DREAM4 Wed Dec 2-Sun Dec 6, 2009 Abstracts of papers, posters and talks presented at the 2009 Joint RECOMB Satellite Conference on REGULATORY GENOMICS - REGULATORYSYSTEMS BIOLOGY GENOMICS - DREAM4 Wed Dec 2-Sun Dec 6, 2009 YDL051W YKR057W MIT / Broad Institute / CSAIL YNL232W YLR179C YER060WA YNL277W YPL206C YJR139C YJR010W YPR167C YNR051C YDR502C YFR030W YDR253C YOR038C YPL038W YIR017C YNL103W YER114C YOL064C YJR138W YER092W YOR344C YJR137C YGR204W YLR157C YAL012W YBR144C YER091C YLR158C YLR303W YJR060W Asparagine catabolism Cysteine biosynthetic process Methionine metabolism Sulfur acid metabolism YLR155C YBR145W Other or unknown function Conference Chairs: Manolis Kellis, MIT Ziv Bar-Joseph, CMU Andrea Califano, Columbia Gustavo Stolovitzky, IBM REGULATORY GENOMICS - SYSTEMS BIOLOGY - DREAM4 2009 Abstracts of papers, posters and talks presented at the 2009 Joint RECOMB Satellite Conference on REGULATORY GENOMICS - REGULATORYSYSTEMS BIOLOGY GENOMICS - DREAM4 Wed Dec 2-Sun Dec 6, 2009 MIT / Broad Institute / CSAIL Conference Chairs: Manolis Kellis, MIT Ziv Bar-Joseph, CMU Andrea Califano, Columbia Gustavo Stolovitzky, IBM Conference Chairs: Manolis Kellis ..................................................... Associate Professor, MIT Ziv Bar-Joseph ................................................ Associate Professor, CMU Andrea Califano ........................................ Professor, Columbia University Gustavo Stolovitzky.......................................Systems Biology Group, IBM In Partnership With: PLoS Computational Biology .........................editor: Catherine Nancarrow PLos ONE .................................................................. editor: Peter Binfield Associate Editor, PLoS Computational Biology Uwe Ohler Session Chairs: Regulatory Genomics: DREAM4: Systems Biology: Nitin Baliga Fritz Roth Diego di Bernardo Panayiotis (Takis) Benos Peter Sorger James Collins Michael Brent Yuval Kluger Christina Leslie Avi Ma'ayan Uwe Ohler Franziska Michor Ron Shamir Roded Sharan Pablo Tamayo Dennis Vitkup Program Committee: Regulatory Genomics: Hao Li Eleazar Eskin Manolis Kellis, chair Eran Segal Igor Jurisica Ziv Bar-Joseph, chair Ron Shamir Pascal Kahlem Orly Alter Saurabh Sinha Andre Levchenko Nitin S Baliga Mona Singh Avi Ma'ayan Panayiotis (Takis) Christopher Workman Adam Margolin Benos Satoru Miyano Mathieu Blanchette Systems Biology and Dana Pe'er Michael R. Brent DREAM: Theodore Perkins Albert Erives Andrea Califano, chair Timothy Ravasi Eleazar Eskin Gustavo Stolovitzky, Frederick Roth Ernest Fraenkel chair Michael Samoilov Nir Friedman M. Madan Babu Roded Sharan Mikhail Gelfand Gary Bader Mona Singh Sridhar Hannenhalli Joel Bader Pavel Sumazin Tim Hughes Diego di Bernardo Denis Thieffry Uri Keich Jim Collins Ioannis Xenarios Christina Leslie Joaquin Dopazo Local Organization and Student Volunteers: Local organization Matt Edwards CMU Monica Concepcion Chuck Epstein Anthony Gitter Sally Lee Sudeshna Fisch Peter Huggins Pia Handsom Taran Gujral Hai-Son Le Karen Shirer Christina Harview Henry Lin Eliana Hechter Shan Zhong Local Volunteers: Yan Meng Guy Zinman Loyal Goff Michal Rabani Charlie Frogner Erroll Rueckert Other Patrycja Missiuro Mark Sevecka Betty Chang Yang Ding Tal Shay Antonina Mitrofanova Mary Addonizio Eboney Smith Yeison Rodriguez Adam Callahan Li Wang Cover art credit: Yeast functional modules in amino-acid metabolism, Daniel Marbach Gene expression atlas for Drosophila Blastoderm. Fowlkes, DePace, Malik. Human membrane receptor interactions, Yanjun Qi, Judith Klein-Seetharaman. Special thanks for booklet assembly to: Michelle Martin Online material: All talks will be videotaped and shared freely online with presenter’s permission. All papers accepted and published will be available freely online from PLoS. All videos of accepted papers will be linked to the papers through the PLoS site. Photos from the meeting will be made available through the conference website. All invited talks will be sync’ed with slides in an interactive site by the New York Academy of Sciences. All these materials can be accessed at any time from: http://compbio.mit.edu/recombsat/ For any inquiries, please contact the conference chairs at: [email protected] Industry and Government Sponsors: The organizers wish to thank the following industrial and government sponsors for their generous support of this conference. The NIH National Centers for Biomedical Computing and the MAGNet Center at Columbia University The New York Academy of Sciences IBM Research Scientific Partners The organizers also wish to thank the following journals for their invaluable support in publishing conference manuscripts. PLoS Computational Biology PLoS ONE Local Hosts and Organization Many thanks also go to our local hosts for making this meeting possible. Massachusetts Broad Institute of Computer Science Institute of MIT and Harvard and Artificial Technology Intelligence Lab Wednesday December 2nd, 2009 Dear attendees, Welcome to the 6th Annual RECOMB Satellite on Regulatory Genomics, the 5th Annual RECOMB Satellite on Systems Biology, and the 4th Annual DREAM reverse engineering challenges. The goal of this meeting is to bring together computational and experimental scientists in the area of regulatory genomics and systems biology, to discuss current research directions, latest findings, and establish new collaborations towards a systems-level understanding of activities in the cell. The next 5 days will consist of keynote presentations, oral presentations selected from submitted full length papers and 1-page abstracts, and posters presentations also selected from submitted abstracts. But most importantly, it’s an opportunity to connect, discuss, exchange ideas, think together, and plan ahead. For the second year in a row this meeting has been sold out, this year more than a month in advance. We have also received a record number of more than 50 full length papers and more than 250 abstracts, resulting in a scientific program of outmost quality. All submitted full length papers were fully reviewed by the program committee and 17 were accepted to the conference and by our partner journals, with 8 papers going to PLoS Computational Biology and 9 papers to PLoS ONE. These papers should appear online by the time the meeting starts, and will be ultimately linked together with the corresponding talks on the PLoS website, providing a new means for science dissemination. All abstracts were reviewed by the conference chairs and 16 additional session chairs, resulting in 50 abstracts selected for oral presentation, and most remaining abstracts for poster presentation. Welcome to Boston, for what promises to be a very exciting meeting! The conference chairs: Regulatory Genomics: Manolis Kellis (MIT), Ziv Bar-Joseph (CMU). Systems/DREAM: Andrea Califano (Columbia), Gustavo Stolovitzky (IBM). RECOMB Regulatory Genomics 2009 ( Full length manuscript; ► Invited talk; Accepted abstract) Wednesday, Dec. 2, 2009 3pm Conference check-in open, Poster session I set-up 5pm Welcome Remarks 5:15► Mark Biggin: Evidence for Quantitative Transcription Networks ...1 5:45 Sarah E. Calvo: Widespread translational repression...................2 6pm Hilal Kazan: Learning binding preferences....................................3 6:15 Igor Ulitsky: Towards prediction of MicroRNA function..………… 4 Light snacks – 6:30-6:45pm 6:45 Clifford A. Meyer: Inferring key transcriptional regulators .............5 7pm Jason Ernst: Genome-wide discovery of chromatin states……….6 7:15 Mattia Pelizzola: Human DNA methylomes at base resolution .....7 7:30 Leonid Mirny: Different strategies for gene regulation……………8 7:45► Bob Waterston: Deciphering C. Elegans embryonic network.......9 Regulatory Genomics Welcome Reception/Poster Session I 8:15pm-9:45pm Hors d’oeuvres, snacks, refreshments, cash bar Thursday, Dec. 3, 2009 Breakfast – 8am 9am► Rick Young: Programming cell state ...........................................10 9:30 Jesse M. Gray: Widespread RNA polymerase II recruitment......11 9:45 Yue Zhao: Inferring binding energies ..........................................12 10am Guillaume Bourque: Binding site turnover in stem cells ………..13 Coffee / Snacks / Fruit Break – 10:15-10:45am 10:45 Michael Brodsky: Identification and analysis of regulatory regions14 11am Yang Ding: Exact calculation of partition function ………………15 11:15 Sheng Zhong: A analysis of transcription factor interactions….16 11:30 Pouya Kheradpour: Regulatory motifs associated with TF........17 11:45 Quan Zhong: Edgetic perturbation models of human ................18 Lunch Break / Networking Opportunities – 12-1pm 1pm► Naama Barkai: Evolution of nucleosome positioning .................19 1:30 Pieter Meysman: Structural DNA for the prediction of binding....20 1:45 Claes Wadelius: Nucleosomes are positioned in exons..............21 2pm Eugene Bolotin: Identification of human HNF4 target genes….. 22 Coffee / Snacks / Fruit Break – 2:15-2:45pm Poster set-up for Session II 2:45 Damian Wójtowicz: Mapping of non-B DNA structures ...............23 3pm Elizabeth A. Rach: The landscape of transcription initiation .......24 3:15 Julia Lasserre: TSS detection......................................................25 3:30 Ron Shamir : Signaling pathways analysis tool...........................26 Regulatory Genomics Poster Session II – 3:45pm-5:15pm Hors d’oeuvres, snacks, refreshments 5:15► Nikolaus Rajewsky: Post-transcriptional gene regulation............27 5:45 Stein Aerts : Regulatory network for retinal differentiation ..........28 6pm Raja Jothi: A link
Recommended publications
  • Diary James Wickersham Aug 22, 1918 – Jan
    Alaska State Library – Historical Collections Diary of James Wickersham MS 107 BOX 5 DIARY 30 Aug 22, 1918 – Jan. 3, 1919 [cover] Diary James Wickersham Aug 22, 1918 – Jan. 3, 1919 Diary 30, 1918 Aug 23, 1918 August 23 Arrived-in Tanana forenoon and went to Lower House kept by Joe. Aincich. Came up from Ruby on the launch “Sibilla” - N.C. Mail launch. Find much hostility to me here engendered and cultivated by White Pass & the N.C. Co's, and b y Gov. Riggs who is here making Sulzers campaign. There is a Reception to Riggs & wife tonight so I will not speak till tomorrow evening. Am visiting around and renewing my acquaintance with the people. Diary 30, 1918 Aug 24, 1918. August 24 My 61st Birthday Will speak tonight at the Moose Hall - Dinner with Andrew Vachon & wife. Spoke tonight to a good crowd at Moose Hall. Had a very friendly reception and am much encouraged though the Gov. & the White Pass & N.C. officials are moving every element possible against me. Attacked all three of them fairly but strongly in my speech & was earnestly supported by the audience. Noticed Father's Jette & Perron, Capt. Lenoir a many others in the Hall. Am satisfied with my speech Diary 30, 1918 Aug 25th August 25 Attended services at Father Jettes church - He preached a beautiful sermon on the sin of covetousness. The “Alaska” will be here this afternoon & will go up the river to Hot Springs on her. Was requested to make 4 Minute talk at Post tonight at picture show - did it badly! Boarded “Alaska” for the Hot Springs at midnight.
    [Show full text]
  • 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
    [Show full text]
  • 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.
    [Show full text]
  • In Silico Prediction of High-Resolution Hi-C Interaction Matrices
    ARTICLE https://doi.org/10.1038/s41467-019-13423-8 OPEN In silico prediction of high-resolution Hi-C interaction matrices Shilu Zhang1, Deborah Chasman 1, Sara Knaack1 & Sushmita Roy1,2* The three-dimensional (3D) organization of the genome plays an important role in gene regulation bringing distal sequence elements in 3D proximity to genes hundreds of kilobases away. Hi-C is a powerful genome-wide technique to study 3D genome organization. Owing to 1234567890():,; experimental costs, high resolution Hi-C datasets are limited to a few cell lines. Computa- tional prediction of Hi-C counts can offer a scalable and inexpensive approach to examine 3D genome organization across multiple cellular contexts. Here we present HiC-Reg, an approach to predict contact counts from one-dimensional regulatory signals. HiC-Reg pre- dictions identify topologically associating domains and significant interactions that are enri- ched for CCCTC-binding factor (CTCF) bidirectional motifs and interactions identified from complementary sources. CTCF and chromatin marks, especially repressive and elongation marks, are most important for HiC-Reg’s predictive performance. Taken together, HiC-Reg provides a powerful framework to generate high-resolution profiles of contact counts that can be used to study individual locus level interactions and higher-order organizational units of the genome. 1 Wisconsin Institute for Discovery, 330 North Orchard Street, Madison, WI 53715, USA. 2 Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, WI 53715, USA. *email: [email protected] NATURE COMMUNICATIONS | (2019) 10:5449 | https://doi.org/10.1038/s41467-019-13423-8 | www.nature.com/naturecommunications 1 ARTICLE NATURE COMMUNICATIONS | https://doi.org/10.1038/s41467-019-13423-8 he three-dimensional (3D) organization of the genome has Results Temerged as an important component of the gene regulation HiC-Reg for predicting contact count using Random Forests.
    [Show full text]
  • A Computational Approach for Defining a Signature of Β-Cell Golgi Stress in Diabetes Mellitus
    Page 1 of 781 Diabetes A Computational Approach for Defining a Signature of β-Cell Golgi Stress in Diabetes Mellitus Robert N. Bone1,6,7, Olufunmilola Oyebamiji2, Sayali Talware2, Sharmila Selvaraj2, Preethi Krishnan3,6, Farooq Syed1,6,7, Huanmei Wu2, Carmella Evans-Molina 1,3,4,5,6,7,8* Departments of 1Pediatrics, 3Medicine, 4Anatomy, Cell Biology & Physiology, 5Biochemistry & Molecular Biology, the 6Center for Diabetes & Metabolic Diseases, and the 7Herman B. Wells Center for Pediatric Research, Indiana University School of Medicine, Indianapolis, IN 46202; 2Department of BioHealth Informatics, Indiana University-Purdue University Indianapolis, Indianapolis, IN, 46202; 8Roudebush VA Medical Center, Indianapolis, IN 46202. *Corresponding Author(s): Carmella Evans-Molina, MD, PhD ([email protected]) Indiana University School of Medicine, 635 Barnhill Drive, MS 2031A, Indianapolis, IN 46202, Telephone: (317) 274-4145, Fax (317) 274-4107 Running Title: Golgi Stress Response in Diabetes Word Count: 4358 Number of Figures: 6 Keywords: Golgi apparatus stress, Islets, β cell, Type 1 diabetes, Type 2 diabetes 1 Diabetes Publish Ahead of Print, published online August 20, 2020 Diabetes Page 2 of 781 ABSTRACT The Golgi apparatus (GA) is an important site of insulin processing and granule maturation, but whether GA organelle dysfunction and GA stress are present in the diabetic β-cell has not been tested. We utilized an informatics-based approach to develop a transcriptional signature of β-cell GA stress using existing RNA sequencing and microarray datasets generated using human islets from donors with diabetes and islets where type 1(T1D) and type 2 diabetes (T2D) had been modeled ex vivo. To narrow our results to GA-specific genes, we applied a filter set of 1,030 genes accepted as GA associated.
    [Show full text]
  • Preclinical Evaluation of Protein Disulfide Isomerase Inhibitors for the Treatment of Glioblastoma by Andrea Shergalis
    Preclinical Evaluation of Protein Disulfide Isomerase Inhibitors for the Treatment of Glioblastoma By Andrea Shergalis A dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy (Medicinal Chemistry) in the University of Michigan 2020 Doctoral Committee: Professor Nouri Neamati, Chair Professor George A. Garcia Professor Peter J. H. Scott Professor Shaomeng Wang Andrea G. Shergalis [email protected] ORCID 0000-0002-1155-1583 © Andrea Shergalis 2020 All Rights Reserved ACKNOWLEDGEMENTS So many people have been involved in bringing this project to life and making this dissertation possible. First, I want to thank my advisor, Prof. Nouri Neamati, for his guidance, encouragement, and patience. Prof. Neamati instilled an enthusiasm in me for science and drug discovery, while allowing me the space to independently explore complex biochemical problems, and I am grateful for his kind and patient mentorship. I also thank my committee members, Profs. George Garcia, Peter Scott, and Shaomeng Wang, for their patience, guidance, and support throughout my graduate career. I am thankful to them for taking time to meet with me and have thoughtful conversations about medicinal chemistry and science in general. From the Neamati lab, I would like to thank so many. First and foremost, I have to thank Shuzo Tamara for being an incredible, kind, and patient teacher and mentor. Shuzo is one of the hardest workers I know. In addition to a strong work ethic, he taught me pretty much everything I know and laid the foundation for the article published as Chapter 3 of this dissertation. The work published in this dissertation really began with the initial identification of PDI as a target by Shili Xu, and I am grateful for his advice and guidance (from afar!).
    [Show full text]
  • 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.
    [Show full text]
  • PREDICTD: Parallel Epigenomics Data Imputation with Cloud-Based Tensor Decomposition
    bioRxiv preprint doi: https://doi.org/10.1101/123927; this version posted April 4, 2017. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC 4.0 International license. PREDICTD: PaRallel Epigenomics Data Imputation with Cloud-based Tensor Decomposition Timothy J. Durham Maxwell W. Libbrecht Department of Genome Sciences Department of Genome Sciences University of Washington University of Washington J. Jeffry Howbert Jeff Bilmes Department of Genome Sciences Department of Electrical Engineering University of Washington University of Washington William Stafford Noble Department of Genome Sciences Department of Computer Science and Engineering University of Washington April 4, 2017 Abstract The Encyclopedia of DNA Elements (ENCODE) and the Roadmap Epigenomics Project have produced thousands of data sets mapping the epigenome in hundreds of cell types. How- ever, the number of cell types remains too great to comprehensively map given current time and financial constraints. We present a method, PaRallel Epigenomics Data Imputation with Cloud-based Tensor Decomposition (PREDICTD), to address this issue by computationally im- puting missing experiments in collections of epigenomics experiments. PREDICTD leverages an intuitive and natural model called \tensor decomposition" to impute many experiments si- multaneously. Compared with the current state-of-the-art method, ChromImpute, PREDICTD produces lower overall mean squared error, and combining methods yields further improvement. We show that PREDICTD data can be used to investigate enhancer biology at non-coding human accelerated regions. PREDICTD provides reference imputed data sets and open-source software for investigating new cell types, and demonstrates the utility of tensor decomposition and cloud computing, two technologies increasingly applicable in bioinformatics.
    [Show full text]
  • Program Book
    Pacific Symposium on Biocomputing 2016 January 4-8, 2016 Big Island of Hawaii Program Book PACIFIC SYMPOSIUM ON BIOCOMPUTING 2016 Big Island of Hawaii, January 4-8, 2016 Welcome to PSB 2016! We have prepared this program book to give you quick access to information you need for PSB 2016. Enclosed you will find • Logistics information • Menus for PSB hosted meals • Full conference schedule • Call for Session and Workshop Proposals for PSB 2017 • Poster/abstract titles and authors • Participant List Conference materials are also available online at http://psb.stanford.edu/conference-materials/. PSB 2016 gratefully acknowledges the support the Institute for Computational Biology, a collaborative effort of Case Western Reserve University, the Cleveland Clinic Foundation, and University Hospitals; the National Institutes of Health (NIH), the National Science Foundation (NSF); and the International Society for Computational Biology (ISCB). If you or your institution are interested in sponsoring, PSB, please contact Tiffany Murray at [email protected] If you have any questions, the PSB registration staff (Tiffany Murray, Georgia Hansen, Brant Hansen, Kasey Miller, and BJ Morrison-McKay) are happy to help you. Aloha! Russ Altman Keith Dunker Larry Hunter Teri Klein Maryln Ritchie The PSB 2016 Organizers PACIFIC SYMPOSIUM ON BIOCOMPUTING 2016 Big Island of Hawaii, January 4-8, 2016 SPEAKER INFORMATION Oral presentations of accepted proceedings papers will take place in Salon 2 & 3. Speakers are allotted 10 minutes for presentation and 5 minutes for questions for a total of 15 minutes. Instructions for uploading talks were sent to authors with oral presentations. If you need assistance with this, please see Tiffany Murray or another PSB staff member.
    [Show full text]
  • 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.
    [Show full text]
  • 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].
    [Show full text]
  • Manolis Kellis Piotr Indyk
    6.095 / 6.895 Computational Biology: Genomes, Networks, Evolution Manolis Kellis Rapid database search Courtsey of CCRNP, The National Cancer Institute. Piotr Indyk Protein interaction network Courtesy of GTL Center for Molecular and Cellular Systems. Genome duplication Courtesy of Talking Glossary of Genetics. Administrivia • Course information – Lecturers: Manolis Kellis and Piotr Indyk • Grading: Part. Problem sets 50% Final Project 25% Midterm 20% 5% • 5 problem sets: – Each problem set: covers 4 lectures, contains 4 problems. – Algorithmic problems and programming assignments – Graduate version includes 5th problem on current research •Exams – In-class midterm, no final exam • Collaboration policy – Collaboration allowed, but you must: • Work independently on each problem before discussing it • Write solutions on your own • Acknowledge sources and collaborators. No outsourcing. Goals for the term • Introduction to computational biology – Fundamental problems in computational biology – Algorithmic/machine learning techniques for data analysis – Research directions for active participation in the field • Ability to tackle research – Problem set questions: algorithmic rigorous thinking – Programming assignments: hands-on experience w/ real datasets • Final project: – Research initiative to propose an innovative project – Ability to carry out project’s goals, produce deliverables – Write-up goals, approach, and findings in conference format – Present your project to your peers in conference setting Course outline • Organization – Duality:
    [Show full text]