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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 -
From DNA Sequence to Chromatin Dynamics: Computational Analysis of Transcriptional Regulation
From DNA Sequence to Chromatin Dynamics: Computational Analysis of Transcriptional Regulation Thesis submitted for the degree of “Doctor of Philosophy” by Tommy Kaplan Submitted to the Senate of the Hebrew University May 2008 This work was carried out under the supervision of Prof. Nir Friedman and Prof. Hanah Margalit Abstract All cells of a living organism share the same DNA. Yet, they differ in structure, activities and interactions. These differences arise through a tight regulatory system which activates different genes and pathways to fit the cell’s specialization, condition, and requirements. Deciphering the regulatory mechanisms underlying a living cell is one of the fundamental challenges in biology. Such knowledge will allow us to better understand how cells work, how they respond to external stimuli, what goes wrong in diseases like cancer (which often involves disruption of gene regulation), and how it can be fought. In my PhD, I focus on regulation of gene expression from three perspectives. First, I present an innovative algorithm for identifying the target genes of novel transcription factors, based on their protein sequence (Chapter 1). Second, I consider how several transcription factors cooperate to process external stimuli and alter the behavior of the cell (Chapter 2). Finally, I study how the genomic position of nucleosomes and their covalent modifications modulate the accessibility of DNA to transcription factors, thus adding a fascinating dimension to transcriptional regulation (Chapters 3 and 4). To understand transcriptional regulation, one should first reconstruct the architecture of the cell’s regulatory map, thus identifying which genes are regulated by which transcription factors (TFs). -
BIOINFORMATICS Doi:10.1093/Bioinformatics/Btq499
Vol. 26 ECCB 2010, pages i409–i411 BIOINFORMATICS doi:10.1093/bioinformatics/btq499 ECCB 2010 Organization CONFERENCE CHAIR B. Comparative Genomics, Phylogeny, and Evolution Yves Moreau, Katholieke Universiteit Leuven, Belgium Martijn Huynen, Radboud University Nijmegen Medical Centre, The Netherlands PROCEEDINGS CHAIR Yves Van de Peer, Ghent University & VIB, Belgium Jaap Heringa, Free University of Amsterdam, The Netherlands C. Protein and Nucleotide Structure LOCAL ORGANIZING COMMITTEE Anna Tramontano, University of Rome ‘La Sapienza’, Italy Jan Gorodkin, University of Copenhagen, Denmark Yves Moreau, Katholieke Universiteit Leuven, Belgium Jaap Heringa, Free University of Amsterdam, The Netherlands D. Annotation and Prediction of Molecular Function Gert Vriend, Radboud University, Nijmegen, The Netherlands Yves Van de Peer, University of Ghent & VIB, Belgium Nir Ben-Tal, Tel-Aviv University, Israel Kathleen Marchal, Katholieke Universiteit Leuven, Belgium Fritz Roth, Harvard Medical School, USA Jacques van Helden, Université Libre de Bruxelles, Belgium Louis Wehenkel, Université de Liège, Belgium E. Gene Regulation and Transcriptomics Antoine van Kampen, University of Amsterdam & Netherlands Jaak Vilo, University of Tartu, Estonia Bioinformatics Center (NBIC) Zohar Yakhini, Agilent Laboratories, Tel-Aviv & the Tech-nion, Peter van der Spek, Erasmus MC, Rotterdam, The Netherlands Haifa, Israel STEERING COMMITTEE F. Text Mining, Ontologies, and Databases Michal Linial (Chair), Hebrew University, Jerusalem, Israel Alfonso Valencia, National -
A Hidden Markov Model Framewrok for Studying Regulation from Chromatin Through RNA
Submitted in part fulfilment of the requirements for the degree of Master of Science in Computer Science and Computational Biology A Hidden Markov Model Framewrok For Studying Regulation From Chromatin Through RNA Eran Rosenthal Supervisor: Dr. Tommy Kaplan October 2017 Hebrew University of Jerusalem Faculty of Science - Computer Science and Engineering Acknowledgments I would like to deeply thank Tommy, for being a great supervisor, giving very useful advices and scientific tutoring. Tommy has great ability to express complex concepts in simple, illustrative stories, and he introduced me to different kinds of experimental data and computational approaches. I would like also to thank for the members of the lab, for the interesting ideas and discussions. I would like to thank for all the people I had worked in collaboration in my master: • Moshe Oren and Gilad Fuchs for the providing me their experimental data of nascent RNA with RNF20 knockdown for studying the role of monoubiquity- lation of H2B. • Michael Berger and Yuval Malka for the exciting project of studying post- transcriptional 3’UTR cleavage of mRNA transcripts, and for Hanah Margalit and Avital Shimony who helped us in the analysis of miRNA regulation in this project. i Abstract Information flows from DNA to RNA, through transcription, followed by trans- lation of the RNA transcript to protein. A viable cell must have proper regulation on genes expression. There are varieties of regulation mechanisms along the way, which include regulation on the DNA and expression level of genes, post-transcriptional regulation, and post-translation regulation. Most of the cells in our body share the same DNA, but they have different func- tions. -
EYAL AKIVA, Phd
Eyal Akiva CV, Nov. 2017 EYAL AKIVA, PhD Department of Bioengineering and Therapeutic Sciences Phone +1-650-504-9008 University of California at San Francisco Email [email protected] 1700 4th street, San Francisco, Web www.babbittlab.ucsf.edu/eakiva CA, USA EDUCATION 2012-2017 Post-doctoral fellowship at UCSF, Dept. Of Bioengineering and Therapeutic Sciences. Host: Prof. Patricia Babbitt. 2010-2012 Post-doctoral fellowship at UCSF, Dept. Of Bioengineering and Therapeutic Sciences. Host: Prof. Tanja Kortemme. 2004-2010 PhD at The Hebrew University of Jerusalem (Israel), bioinformatics. Host: Prof. Hanah Margalit. “Various Aspects of Modularity in Protein-Protein Interaction". 2001-2004 MSc at The Hebrew University of Jerusalem (Israel), bioinformatics and human genetics. Host: Prof. Muli Ben-Sasson. “Exploiting the Exploiters: Identification of Virus-Host Pep- tide Mimicry as a Source for Modules of Functional Significance”. MAGNA CUM LAUDE. 1997-2000 BSc at Bar-Ilan University (Israel), biology (major) and computer science (minor). Final project advisor: Prof. Ramit Mehr “Modeling the Evolution of the Immune System: a Sim- ulation of the Evolution of Genes that Encode the Variable Regions of Immunoglobulins”. MAGNA CUM LAUDE. 1996-1997 First year of "Industrial Engineering and Management" studies, Tel-Aviv University, Israel. OTHER WORK EXPERIENCE 2000-01 ‘Do-coop technologies’: Team leader and chemistry/microbiology researcher; development of biological applications and manufacture of proprietary nanoparticles (Or Yehuda, Israel and Tel-Aviv University (Prof. Eshel Ben-Jacob’s lab at the school of physics)). FUNDING, HONORS AND AWARDS 2017 Grant: Co-PI, “Utilizing metagenomic sequences for enzyme function prediction”, Joint Genome Institute (US Department of Energy) (http://jgi.doe.gov/doe-user-facilities-ficus- join-forces-to-tackle-biology-big-data/). -
The 4Th Bologna Winter School: Hot Topics in Structural Genomics†
Comparative and Functional Genomics Comp Funct Genom 2003; 4: 394–396. Published online in Wiley InterScience (www.interscience.wiley.com). DOI: 10.1002/cfg.314 Conference Report The 4th Bologna Winter School: hot topics in structural genomics† Rita Casadio* Department of Biology/CIRB, University of Bologna, Via Irnerio 42, 40126 Bologna, Italy *Correspondence to: Abstract Rita Casadio, Department of Biology/CIRB, University of The 4th Bologna Winter School on Biotechnologies was held on 9–15 February Bologna, Via Irnerio 42, 40126 2003 at the University of Bologna, Italy, with the specific aim of discussing recent Bologna, Italy. developments in bioinformatics. The school provided an opportunity for students E-mail: [email protected] and scientists to debate current problems in computational biology and possible solutions. The course, co-supported (as last year) by the European Science Foundation program on Functional Genomics, focused mainly on hot topics in structural genomics, including recent CASP and CAPRI results, recent and promising genome- Received: 3 June 2003 wide predictions, protein–protein and protein–DNA interaction predictions and Revised: 5 June 2003 genome functional annotation. The topics were organized into four main sections Accepted: 5 June 2003 (http://www.biocomp.unibo.it). Published in 2003 by John Wiley & Sons, Ltd. Predictive methods in structural Predictive methods in functional genomics genomics • Contemporary challenges in structure prediction • Prediction of protein function (Arthur Lesk, and the CASP5 experiment (John Moult, Uni- University of Cambridge, Cambridge, UK). versity of Maryland, Rockville, MD, USA). • Microarray data analysis and mining (Raf- • Contemporary challenges in structure prediction faele Calogero, University of Torino, Torino, (Anna Tramontano, University ‘La Sapienza’, Italy). -
Speakers Info
CAJAL Online Lecture Series Single Cell Transcriptomics November 2nd-6th, 2020 Keynote speakers Naomi HABIB, PhD | Edmond & Lily Safra Center for Brain Sciences (ELSC), Israel Naomi Habib is an assistant professor at the ELSC Brain Center at the Hebrew University of Jerusalem since July 2018. Habib's research focuses on understanding how complex interactions between diverse cell types in the brain and between the brain and other systems in the body, are mediating neurodegenerative diseases and other aging-related pathologies. Naomi combines in her work computational biology, genomics and genome-engineering, and is a pioneer in single nucleus RNA-sequencing technologies and their applications to study cellular diversity and molecular processes in the brain. Naomi did her postdoctoral at the Broad Institute of MIT/Harvard working with Dr. Feng Zhang and Dr. Aviv Regev, and earned her PhD in computational biology from the Hebrew University of Jerusalem in Israel, working with Prof. Nir Friedman and Prof. Hanah Margalit. Selected publications: - Habib N, McCabe C*, Medina S*, Varshavsky M*, Kitsberg D, Dvir R, Green G, Dionne D, Nguyen L, Marshall J.L, Chen F, Zhang F, Kaplan T, Regev A, Schwartz M. (2019) Unique disease-associated astrocytes in Alzheimer’s disease. Nature Neuroscience. In Press. - Habib N*, Basu A*, Avraham-Davidi I*, Burks T, Choudhury SR, Aguet F, Gelfand E, Ardlie K, Weitz DA, Rozenblatt-Rosen O, Zhang F, and Regev A. (2017). Deciphering cell types in human archived brain tissues by massively-parallel single nucleus RNA-seq. Nature Methods. Oct;14(10):955-958. - Habib N*, Li Y*, Heidenreich M, Sweich L, Avraham-Davidi I, Trombetta J, Hession C, Zhang F, Regev A. -
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. -
Study of Seed-Based Microrna Targeting in Mammals
TECHNISCHE UNIVERSITAT¨ MUNCHEN¨ Lehrstuhl f¨urGenomorientierte Bioinformatik Study of seed-based microRNA targeting in mammals Florian A. B¨uttner Vollst¨andigerAbdruck der von der Fakult¨atWissenschaftszentrum Weihenstephan f¨urErn¨ahrung,Landnutzung und Umwelt der Technischen Universit¨atM¨unchen zur Erlangung des akademischen Grades eines Doktors der Naturwissenschaften genehmigten Dissertation. Vorsitzender: Univ.-Prof. Dr. B. K¨uster Pr¨uferder Dissertation: 1. Univ.-Prof. Dr. H.-W. Mewes 2. Univ.-Prof. Dr. D. Frischmann Die Dissertation wurde am 07.08.2013 bei der Technischen Universit¨atM¨unchen eingereicht und durch die Fakult¨atWissenschaftszentrum Weihenstephan f¨urEr- n¨ahrung,Landnutzung und Umwelt am 22.11.2013 angenommen. To Katrin and Paulo iii Danksagung Zuerst m¨ochte ich mich bei meinem Doktorvater Prof. Dr. Hans-Werner Mewes bedanken, mir diese Doktorarbeit erm¨oglicht zu haben, sowie f¨urdie Betreuung und wohlwollende Unterst¨utzungin den letzten Jahren. F¨urstimulierende und spannende Zusammenarbeit und Diskussionen m¨ochte ich mich vor allem bei Daniel Ellwanger und Florian Giesert, sowie bei Sebastian Toepel, Matthias Arnold, Dominik Lutter und J¨ornLeonhardt bedanken. Weiter geht mein Dank an alle Kollegen vom Institut f¨urBioinformatik und Systembiologie und vom Lehrstuhl f¨urGenomorientierte Bioinformatik in Wei- henstephan f¨urdas freundliche, kollegiale und unterhaltsame Miteinander. Erw¨ahnung finden m¨ussenan dieser Stelle auch meine Freunde und Bekannten außerhalb von IBIS und Universit¨at.Die w¨ochentlichen -
Interact: Interaction Network Inference from Vector
INtERAcT: Interaction Network Inference from Vector Representations of Words Matteo Manica1,2,*, Roland Mathis1,*, Mar´ıaRodr´ıguezMart´ınez1, y ftte,lth,[email protected] 1 IBM Research Z¨urich 2 ETH - Z¨urich * Shared first authorship y Corresponding author Abstract Motivation In recent years, the number of biomedical publications has steadfastly grown, resulting in a rich source of untapped new knowledge. Most biomedical facts are however not readily available, but buried in the form of unstructured text, and hence their exploitation requires the time-consuming manual curation of published articles. Here we present INtERAcT, a novel approach to extract protein-protein interactions from a corpus of biomedical articles related to a broad range of scientific domains in a completely unsupervised way. INtERAcT exploits vector representation of words, computed on a corpus of domain specific knowledge, and implements a new metric that estimates an interaction score between two molecules in the space where the corresponding words are embedded. Results We demonstrate the power of INtERAcT by reconstructing the molecular pathways asso- ciated to 10 different cancer types using a corpus of disease-specific articles for each cancer type. We evaluate INtERAcT using STRING database as a benchmark, and show that our metric outperforms currently adopted approaches for similarity computation at the task of identifying known molecular interactions in all studied cancer types. Furthermore, our approach does not require text annotation, manual curation or the definition of semantic rules based on expert knowledge, and hence it can be easily and efficiently applied to dif- ferent scientific domains. Our findings suggest that INtERAcT may increase our capability to summarize the understanding of a specific disease using the published literature in an automated and completely unsupervised fashion. -
Download Flyer
COLD SPRING HARBOR ASIA ORGANIZERS(Speaker, Affiliation, Country/Region) Steven E. Brenner Frontiers in University of California, Berkeley, USA A Keith Dunker Indiana University School of Medicine, USA Computational Biology Julian Gough MRC Laboratory of Molecular Biology, UK Suzhou, China September 3-7, 2018 Luhua Lai & Bioinformatics Peking University, China Yunlong Liu Abstract deadline: July 13, 2018 Indiana University School of Medicine, USA MAJOR TOPICS Precision medicine, human genome variation, disease & diagnosis Molecular evolution Pathways, networks & developmental biology Molecular structure, with pioneering techniques Molecular machines, their functions & dynamics Intrinsically disordered proteins & their functions RNA function, regulation & splicing 3D genomics & regulatory inferences Single cell analysis KEYNOTE SPEAKERS (Speaker, Affiliation, Country/Region) Nancy Cox, Vanderbilt University, USA Yoshihide Hayashizaki, RIKEN Research Cluster for Innovation, JAPAN INVITED SPEAKERS (Speaker, Affiliation, Country/Region) Russ Altman, Stanford University, USA Manolis Kellis, MIT Computer Science and Broad Institute, USA Lukasz Kurgan, Virginia Commonwealth University, USA Peer Bork, European Molecular Biology Laboratory, GERMANY Luhua Lai, Peking University, CHINA Steven Brenner, University of California, Berkeley, USA Michal Linial, The Hebrew University of Jerusalem, ISRAEL Angela Brooks, University of California, Santa Cruz, USA Yunlong Liu, Indiana University School of Medicine, USA Luonan Chen, Shanghai Institutes for -
Transformer Neural Networks for Protein Prediction Tasks
bioRxiv preprint doi: https://doi.org/10.1101/2020.06.15.153643; this version posted June 16, 2020. 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 4.0 International license. TRANSFORMING THE LANGUAGE OF LIFE:TRANSFORMER NEURAL NETWORKS FOR PROTEIN PREDICTION TASKS Ananthan Nambiar ∗ Maeve Heflin∗ Department of Bioengineering Department of Computer Science Carl R. Woese Inst. for Genomic Biol. Carl R. Woese Inst. for Genomic Biol. University of Illinois at Urbana-Champaign University of Illinois at Urbana-Champaign Urbana, IL 61801 Urbana, IL 61801 [email protected] Simon Liu∗ Sergei Maslov Department of Computer Science Department Bioengineering Carl R. Woese Inst. for Genomic Biol. Department of Physics University of Illinois at Urbana-Champaign Carl R. Woese Inst. for Genomic Biol. Urbana, IL 61801 University of Illinois at Urbana-Champaign Urbana, IL 61801 Mark Hopkinsy Anna Ritzy Department of Computer Science Department of Biology Reed College Reed College Portland, OR 97202 Portland, OR 97202 June 16, 2020 ABSTRACT The scientific community is rapidly generating protein sequence information, but only a fraction of these proteins can be experimentally characterized. While promising deep learning approaches for protein prediction tasks have emerged, they have computational limitations or are designed to solve a specific task. We present a Transformer neural network that pre-trains task-agnostic sequence representations. This model is fine-tuned to solve two different protein prediction tasks: protein family classification and protein interaction prediction.