Exploiting Biological Pathways to Infer Temporal Gene Interaction
Total Page:16
File Type:pdf, Size:1020Kb

Load more
Recommended publications
-
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 -
2015 Wattiezm Memoire
Institutional Repository - Research Portal Dépôt Institutionnel - Portail de la Recherche University of Namurresearchportal.unamur.be THESIS / THÈSE MASTER IN COMPUTER SCIENCE Design of a support system for modelling gene regulatory networks Author(s) - Auteur(s) : Wattiez, Morgan Award date: 2015 Awarding institution: University of Namur Supervisor - Co-Supervisor / Promoteur - Co-Promoteur : Link to publication Publication date - Date de publication : Permanent link - Permalien : Rights / License - Licence de droit d’auteur : General rights Copyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright owners and it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights. • Users may download and print one copy of any publication from the public portal for the purpose of private study or research. • You may not further distribute the material or use it for any profit-making activity or commercial gain • You may freely distribute the URL identifying the publication in the public portal ? Take down policy If you believe that this document breaches copyright please contact us providing details, and we will remove access to the work immediately and investigate your claim. BibliothèqueDownload date: Universitaire 04. oct.. 2021 Moretus Plantin University of Namur Faculty of Computer Science Academic Year 2014{2015 Design of a support system for modelling gene regulatory networks Morgan WATTIEZ Supervisor: (Signed for Release Approval Jean-Marie JACQUET Study Rules art. 40) Thesis submitted in partial fulfillment of the requirements for the degree of Master in Computer Science at the University of Namur Abstract The understanding of gene regulatory networks depends upon the solving of ques- tions related to the interactions in those networks. -
ACCEPTED PAPERS – ABSTRACTS (As of May 5, 2006) Comparative
ACCEPTED PAPERS – ABSTRACTS (as of May 5, 2006) Comparative Genomics Hairpins in a haystack: recognizing microrna precursors in comparative genomics data Author(s): Jana Hertel, Peter F. Stadler Recently, genome wide surveys for non-coding RNAs have provided evidence for tens of thousands of previously undescribed evolutionary conserved RNAs with distinctive secondary structures. The annotation of these putative ncRNAs, however, remains a difficult problem. Here we describe an SVM-based approach that, in conjunction with a non-stringent filter for consensus secondary structures, is capable of efficiently recognizing microRNA precursors in multiple sequence alignments. The software was applied to recent genome-wide RNAz surveys of mammals, urochordates, and nematodes. Keywords: miRNA, support vector machine, non-coding RNA Comparative Genomics Comparative genomics reveals unusually long motifs in mammalian genomes Author(s): Neil Jones, Pavel Pevzner Motivation: The recent discovery of the first small modulatory RNA (smRNA) presents the challenge of finding other molecules of similar length and conservation level. Unlike short interfering RNA (siRNA) and micro-RNA (miRNA), effective computational and experimental screening methods are not currently known for this species of RNA molecule, and the discovery of the one known example was partly fortuitous because it happened to be complementary to a well-studied DNA binding motif (the Neuron Restrictive Silencer Element). Results: The existing comparative genomics approaches (e.g., phylogenetic footprinting) rely on alignments of orthologous regions across multiple genomes. This approach, while extremely valuable, is not suitable for finding motifs with highly diverged ``non-alignable'' flanking regions. Here we show that several unusually long and well conserved motifs can be discovered de novo through a comparative genomics approach that does not require an alignment of orthologous upstream regions. -
Daniel Aalberts Scott Aa
PLOS Computational Biology would like to thank all those who reviewed on behalf of the journal in 2015: Daniel Aalberts Jeff Alstott Benjamin Audit Scott Aaronson Christian Althaus Charles Auffray Henry Abarbanel Benjamin Althouse Jean-Christophe Augustin James Abbas Russ Altman Robert Austin Craig Abbey Eduardo Altmann Bruno Averbeck Hermann Aberle Philipp Altrock Ferhat Ay Robert Abramovitch Vikram Alva Nihat Ay Josep Abril Francisco Alvarez-Leefmans Francisco Azuaje Luigi Acerbi Rommie Amaro Marc Baaden Orlando Acevedo Ettore Ambrosini M. Madan Babu Christoph Adami Bagrat Amirikian Mohan Babu Frederick Adler Uri Amit Marco Bacci Boris Adryan Alexander Anderson Stephen Baccus Tinri Aegerter-Wilmsen Noemi Andor Omar Bagasra Vera Afreixo Isabelle Andre Marc Baguelin Ashutosh Agarwal R. David Andrew Timothy Bailey Ira Agrawal Steven Andrews Wyeth Bair Jacobo Aguirre Ioan Andricioaei Chris Bakal Alaa Ahmed Ioannis Androulakis Joseph Bak-Coleman Hasan Ahmed Iris Antes Adam Baker Natalie Ahn Maciek Antoniewicz Douglas Bakkum Thomas Akam Haroon Anwar Gabor Balazsi Ilya Akberdin Stefano Anzellotti Nilesh Banavali Eyal Akiva Miguel Aon Rahul Banerjee Sahar Akram Lucy Aplin Edward Banigan Tomas Alarcon Kevin Aquino Martin Banks Larissa Albantakis Leonardo Arbiza Mukul Bansal Reka Albert Murat Arcak Shweta Bansal Martí Aldea Gil Ariel Wolfgang Banzhaf Bree Aldridge Nimalan Arinaminpathy Lei Bao Helen Alexander Jeffrey Arle Gyorgy Barabas Alexander Alexeev Alain Arneodo Omri Barak Leonidas Alexopoulos Markus Arnoldini Matteo Barberis Emil Alexov -
Computational Methods for Cis-Regulatory Module Discovery A
Computational Methods for Cis-Regulatory Module Discovery A thesis presented to the faculty of the Russ College of Engineering and Technology of Ohio University In partial fulfillment of the requirements for the degree Master of Science Xiaoyu Liang November 2010 © 2010 Xiaoyu Liang. All Rights Reserved. 2 This thesis titled Computational Methods for Cis-Regulatory Module Discovery by XIAOYU LIANG has been approved for the School of Electrical Engineering and Computer Science and the Russ College of Engineering and Technology by Lonnie R.Welch Professor of Electrical Engineering and Computer Science Dennis Irwin Dean, Russ College of Engineering and Technology 3 ABSTRACT LIANG, XIAOYU, M.S., November 2010, Computer Science Computational Methods for Cis-regulatory Module Discovery Director of Thesis: Lonnie R.Welch In a gene regulation network, the action of a transcription factor binding a short region in non-coding sequence is reported and believed as the key that triggers, or represses genes’ expression. Further analysis revealed that, in higher organisms, multiple transcription factors work together and bind multiple sites that are located nearby in genomic sequences, rather than working alone and binding a single anchor. These multiple binding sites in the non-coding region are called cis -regulatory modules. Identifying these cis - regulatory modules is important for modeling gene regulation network. In this thesis, two methods have been proposed for addressing the problem, and a widely accepted evaluation was applied for assessing the performance. Additionally, two practical case studies were completed and reported as the application of the proposed methods. Approved: _____________________________________________________________ Lonnie R.Welch Professor of Electrical Engineering and Computer Science 4 ACKNOWLEDGEMENTS I would like to express my sincere gratitude to my advisor, Dr. -
Dear Delegates,History of Productive Scientific Discussions of New Challenging Ideas and Participants Contributing from a Wide Range of Interdisciplinary fields
3rd IS CB S t u d ent Co u ncil S ymp os ium Welcome To The 3rd ISCB Student Council Symposium! Welcome to the Student Council Symposium 3 (SCS3) in Vienna. The ISCB Student Council's mis- sion is to develop the next generation of computa- tional biologists. We would like to thank and ac- knowledge our sponsors and the ISCB organisers for their crucial support. The SCS3 provides an ex- citing environment for active scientific discussions and the opportunity to learn vital soft skills for a successful scientific career. In addition, the SCS3 is the biggest international event targeted to students in the field of Computational Biology. We would like to thank our hosts and participants for making this event educative and fun at the same time. Student Council meetings have had a rich Dear Delegates,history of productive scientific discussions of new challenging ideas and participants contributing from a wide range of interdisciplinary fields. Such meet- We are very happy to welcomeings have you proved all touseful the in ISCBproviding Student students Council and postdocs Symposium innovative inputsin Vienna. and an Afterincreased the network suc- cessful symposiums at ECCBof potential 2005 collaborators. in Madrid and at ISMB 2006 in Fortaleza we are determined to con- tinue our efforts to provide an event for students and young researchers in the Computational Biology community. Like in previousWe ar yearse extremely our excitedintention to have is toyou crhereatee and an the opportunity vibrant city of Vforienna students welcomes to you meet to our their SCS3 event. peers from all over the world for exchange of ideas and networking. -
An Expanded Evaluation of Protein Function Prediction Methods Shows an Improvement in Accuracy
The University of Southern Mississippi The Aquila Digital Community Faculty Publications 9-7-2016 An Expanded Evaluation of Protein Function Prediction Methods Shows an Improvement In Accuracy Yuxiang Jiang Indiana University TFollowal Ronnen this and Or onadditional works at: https://aquila.usm.edu/fac_pubs Buck P arInstitutet of the forGenomics Research Commons On Agin Wyatt T. Clark RecommendedYale University Citation AsmaJiang, YR.., OrBankapuron, T. R., Clark, W. T., Bankapur, A. R., D'Andrea, D., Lepore, R., Funk, C. S., Kahanda, I., Verspoor, K. M., Ben-Hur, A., Koo, D. E., Penfold-Brown, D., Shasha, D., Youngs, N., Bonneau, R., Lin, A., Sahraeian, S. Miami University M., Martelli, P. L., Profiti, G., Casadio, R., Cao, R., Zhong, Z., Cheng, J., Altenhoff, A., Skunca, N., Dessimoz, DanielC., Dogan, D'Andr T., Hakala,ea K., Kaewphan, S., Mehryar, F., Salakoski, T., Ginter, F., Fang, H., Smithers, B., Oates, M., UnivGough,ersity J., ofTör Romeönen, P., Koskinen, P., Holm, L., Chen, C., Hsu, W., Bryson, K., Cozzetto, D., Minneci, F., Jones, D. T., Chapan, S., BKC, D., Khan, I. K., Kihara, D., Ofer, D., Rappoport, N., Stern, A., Cibrian-Uhalte, E., Denny, P., Foulger, R. E., Hieta, R., Legge, D., Lovering, R. C., Magrane, M., Melidoni, A. N., Mutowo-Meullenet, P., SeePichler next, K., page Shypitsyna, for additional A., Li, B.,authors Zakeri, P., ElShal, S., Tranchevent, L., Das, S., Dawson, N. L., Lee, D., Lees, J. G., Stilltoe, I., Bhat, P., Nepusz, T., Romero, A. E., Sasidharan, R., Yang, H., Paccanaro, A., Gillis, J., Sedeño- Cortés, A. E., Pavlidis, P., Feng, S., Cejuela, J. -
Gene Regulatory Network Inference Using Machine Learning Techniques
GENE REGULATORY NETWORK INFERENCE USING MACHINE LEARNING TECHNIQUES Stephanie Kamgnia Wonkap A Thesis in the department of Computer Science and Software Engineering Presented in Partial Fulfillment of the Requirements For the Degree of Doctor of Philosophy(Computer Science) Concordia University Montreal,´ Quebec,´ Canada August 26 2020 c Stephanie Kamgnia Wonkap, 2020 Concordia University School of Graduate Studies This is to certify that the thesis prepared By: Miss. Stephanie Kamgnia Wonkap Entitled: Gene Regulatory Network Inference using Machine Learning Techniques and submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy (Computer Science) complies with the regulations of this University and meets the accepted standards with respect to originality and quality. Signed by the final examining committee: Chair Dr. Liangzhu Wang External Examiner Dr. Mathieu Blanchette Examiner Dr. Leila Kosseim Examiner Dr. Malcolm Whiteway Examiner Dr. Volker Haarslev Supervisor Dr. Gregory Butler Approved Dr. Leila Kosseim, Graduate Program Director August 26th, 2020 Dr. Amir Asif, Dean Date of Defence Faculty of Engineering and Computer Science Abstract Gene Regulatory Network Inference using Machine Learning Techniques Stephanie Kamgnia Wonkap, Ph.D. Concordia University, 2020 Systems Biology is a field that models complex biological systems in order to better understand the working of cells and organisms. One of the systems modeled is the gene regulatory network that plays the critical role of controlling an organism's response to changes in its environment. Ideally, we would like a model of the complete gene regulatory network. In recent years, several advances in technology have permitted the collection of an unprecedented amount and variety of data such as genomes, gene expression data, time-series data, and perturbation data. -
Statistic Models in Biological Network Analysis
Statistic Models in Biological Network Analysis WANLU LIU and AUSTIN QUACH, University of California, Los Angeles As the development of high throughput technology, it becomes more and more important for us to look at the behavior of genes, proteins and metabolites at whole genome level. Instead of studying a single gene, by understanding biological process at network level, we can shed light on some new mechanisms in both developmental processes and diseases. Modeling of these networks is an important challenge in the post genomic era. Several statistical models have been applied to analysis the biological networks including logic-based models, continuous models and correlation-based models. In this review, we focus on the di↵erent methods for reconstructing biological networks and analysis of their functionality. Categories and Subject Descriptors: I.5.1 [Networks Analysis]: Models—Biological Networks General Terms: Network Analysis Additional Key Words and Phrases: Biological Network, Statistic Models, Network Construction, Network Analysis 1. INTRODUCTION In the post-genomic era, genome-wide experiments have become commonplace and methods to inter- rogate such datasets are becomingly increasingly important. One approach to analyzing these large datasets is to model the experimental observations using a network approach. In a process known as (re)construction, inference, identification or reverse engineering, model parameters are fit to the data yielding a defined network that can then be analyzed to gain higher level insights into the com- plex molecular biology. Network biology is an expansive field and there are many different methods that are employed. In this survey paper we briefly review the frameworks of several popular mod- eling methods including logical models, boolean networks, Bayesian networks, weighted correlation networks, differential equations, and some basic network analysis concepts. -
PSB 2009 Attendees (As of January 9, 2009) Mario Albrecht Max Planck
PSB 2009 Attendees (as of January 9, 2009) Mario Albrecht Steven Brenner Max Planck Institute for Informatics University of California, Berkeley Hesham Ali Andrzej Brodzik University of Nebraska at Omaha The MITRE Corporation Gil Alterovitz Lukas Burger Harvard/MIT Institute of Bioinformatics, University of Basel Gregory Arnold Amgen Gregory Burrows OHSU Adam Asare UCSF/ITN William Bush Vanderbilt University Pierre Baldi University of California Andrea Califano Columbia University Lars Barquist UC Berkeley J. Gregory Caporaso Univeristy of Colorado Denver James Bassingthwaighte Univeristy of Washington Vincent Carey Harvard Medical School Tanya Berger-Wolf University of Illinois at Chicago Yuhui Cheng University of California, San Diego Ghislain Bidaut INSERM U891 Institut Paoli-Calmette Raymond Cheong Johns Hopkins University Marco Blanchette Stowers Institute for Medical Research Annie Chiang Stanford University Ben Blencowe Gilsoo Cho Anthony Bonner Yonsei University University of Toronto Sung Bum Cho Ingrid Borecki Seoul National University Bioinformatics Washington University Kevin Cohen John Bouck University of Colorado Denver Ceres, Inc. Dilek Colak Philip Bourne King Faisal Specialist Hospital and University of California, San Diego Research Centre PSB 2009 Attendees (as of January 9, 2009) James Costello Laura Elnitski Indiana University NHGRI Anneleen Daemen Drew Endy Dept. Electrical Engineering, KULeuven Stanford University Denise Daley Eric Fahrenthold University of British Columbia Yiping Fan Paul Davis St Jude Children's -
Csb2009 August 10-13, 2009 Stanford, California
CALL FOR PAPERS COMPUTATIONAL SYSTEMS BIOINFORMATICS CSB2009 AUGUST 10-13, 2009 STANFORD, CALIFORNIA You are invited to submit papers to the 2009 Life Sciences Society Computational Systems Bioinformatics Conference (CSB2009). The conference’s goal is to facilitate exchange of ideas and collaborations between computational scientists and biologists by presenting cutting-edge computational and systems 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): • Sequence comparison • Functional Genomics • Promoter Analysis and Discovery • Comparative Genomics • Biological Data Mining and Visualization • Proteomic Data Analysis • Evolution and Phylogenetics • Metagenomics • Protein Structures and Complexes • Drug Discovery • Microarray Data Analysis • Chemical Genetics • Pathways, Networks, Systems Biology • RNAi • SNPs and Haplotyping • Bioenergy • Biological Literature Mining • MicroRNA • Executable Biology • Biomedical Applications • Mathematical and quantitative models of • Translational Research cellular and multicellular systems • Microbial community analysis • High Performance Bio-Computing • Synthetic Biological Systems 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. Papers will have 25 minutes of presentation time. Paper submissions can be made at the site http://csbl.bmb.uga.edu/conference/CSB2009/webconf/ Medline indexes papers appearing in CSB Proceedings. -
Studying the Regulatory Landscape of Flowering Plants
Studying the Regulatory Landscape of Flowering Plants Jan Van de Velde Promoter: Prof. Dr. Klaas Vandepoele Co-Promoter: Prof. Dr. Jan Fostier Ghent University Faculty of Sciences Department of Plant Biotechnology and Bioinformatics VIB Department of Plant Systems Biology Comparative and Integrative Genomics Research funded by a PhD grant of the Institute for the Promotion of Innovation through Science and Technology in Flanders (IWT Vlaanderen). Dissertation submitted in fulfilment of the requirements for the degree of Doctor in Sciences:Bioinformatics. Academic year: 2016-2017 Examination Commitee Prof. Dr. Geert De Jaeger (chair) Faculty of Sciences, Department of Plant Biotechnology and Bioinformatics, Ghent University Prof. Dr. Klaas Vandepoele (promoter) Faculty of Sciences, Department of Plant Biotechnology and Bioinformatics, Ghent University Prof. Dr. Jan Fostier (co-promoter) Faculty of Engineering and Architecture, Department of Information Technology (INTEC), Ghent University - iMinds Prof. Dr. Kerstin Kaufmann Institute for Biochemistry and Biology, Potsdam University Prof. Dr. Pieter de Bleser Inflammation Research Center, Flanders Institute of Biotechnology (VIB) and Department of Biomedical Molecular Biology, Ghent University, Ghent, Belgium Dr. Vanessa Vermeirssen Faculty of Sciences, Department of Plant Biotechnology and Bioinformatics, Ghent University Dr. Stefanie De Bodt Crop Science Division, Bayer CropScience SA-NV, Functional Biology Dr. Inge De Clercq Department of Animal, Plant and Soil Science, ARC Centre of Excellence in Plant Energy Biology, La Trobe University and Faculty of Sciences, Department of Plant Biotechnology and Bioinformatics, Ghent University iii Thank You! Throughout this PhD I have received a lot of support, therefore there are a number of people I would like to thank. First of all, I would like to thank Klaas Vandepoele, for his support and guidance.