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Gene Prediction: the End of the Beginning Comment Colin Semple
View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by PubMed Central http://genomebiology.com/2000/1/2/reports/4012.1 Meeting report Gene prediction: the end of the beginning comment Colin Semple Address: Department of Medical Sciences, Molecular Medicine Centre, Western General Hospital, Crewe Road, Edinburgh EH4 2XU, UK. E-mail: [email protected] Published: 28 July 2000 reviews Genome Biology 2000, 1(2):reports4012.1–4012.3 The electronic version of this article is the complete one and can be found online at http://genomebiology.com/2000/1/2/reports/4012 © GenomeBiology.com (Print ISSN 1465-6906; Online ISSN 1465-6914) Reducing genomes to genes reports A report from the conference entitled Genome Based Gene All ab initio gene prediction programs have to balance sensi- Structure Determination, Hinxton, UK, 1-2 June, 2000, tivity against accuracy. It is often only possible to detect all organised by the European Bioinformatics Institute (EBI). the real exons present in a sequence at the expense of detect- ing many false ones. Alternatively, one may accept only pre- dictions scoring above a more stringent threshold but lose The draft sequence of the human genome will become avail- those real exons that have lower scores. The trick is to try and able later this year. For some time now it has been accepted increase accuracy without any large loss of sensitivity; this deposited research that this will mark a beginning rather than an end. A vast can be done by comparing the prediction with additional, amount of work will remain to be done, from detailing independent evidence. -
Functional Effects Detailed Research Plan
GeCIP Detailed Research Plan Form Background The Genomics England Clinical Interpretation Partnership (GeCIP) brings together researchers, clinicians and trainees from both academia and the NHS to analyse, refine and make new discoveries from the data from the 100,000 Genomes Project. The aims of the partnerships are: 1. To optimise: • clinical data and sample collection • clinical reporting • data validation and interpretation. 2. To improve understanding of the implications of genomic findings and improve the accuracy and reliability of information fed back to patients. To add to knowledge of the genetic basis of disease. 3. To provide a sustainable thriving training environment. The initial wave of GeCIP domains was announced in June 2015 following a first round of applications in January 2015. On the 18th June 2015 we invited the inaugurated GeCIP domains to develop more detailed research plans working closely with Genomics England. These will be used to ensure that the plans are complimentary and add real value across the GeCIP portfolio and address the aims and objectives of the 100,000 Genomes Project. They will be shared with the MRC, Wellcome Trust, NIHR and Cancer Research UK as existing members of the GeCIP Board to give advance warning and manage funding requests to maximise the funds available to each domain. However, formal applications will then be required to be submitted to individual funders. They will allow Genomics England to plan shared core analyses and the required research and computing infrastructure to support the proposed research. They will also form the basis of assessment by the Project’s Access Review Committee, to permit access to data. -
Algorithms for Computational Biology 8Th International Conference, Alcob 2021 Missoula, MT, USA, June 7–11, 2021 Proceedings
Lecture Notes in Bioinformatics 12715 Subseries of Lecture Notes in Computer Science Series Editors Sorin Istrail Brown University, Providence, RI, USA Pavel Pevzner University of California, San Diego, CA, USA Michael Waterman University of Southern California, Los Angeles, CA, USA Editorial Board Members Søren Brunak Technical University of Denmark, Kongens Lyngby, Denmark Mikhail S. Gelfand IITP, Research and Training Center on Bioinformatics, Moscow, Russia Thomas Lengauer Max Planck Institute for Informatics, Saarbrücken, Germany Satoru Miyano University of Tokyo, Tokyo, Japan Eugene Myers Max Planck Institute of Molecular Cell Biology and Genetics, Dresden, Germany Marie-France Sagot Université Lyon 1, Villeurbanne, France David Sankoff University of Ottawa, Ottawa, Canada Ron Shamir Tel Aviv University, Ramat Aviv, Tel Aviv, Israel Terry Speed Walter and Eliza Hall Institute of Medical Research, Melbourne, VIC, Australia Martin Vingron Max Planck Institute for Molecular Genetics, Berlin, Germany W. Eric Wong University of Texas at Dallas, Richardson, TX, USA More information about this subseries at http://www.springer.com/series/5381 Carlos Martín-Vide • Miguel A. Vega-Rodríguez • Travis Wheeler (Eds.) Algorithms for Computational Biology 8th International Conference, AlCoB 2021 Missoula, MT, USA, June 7–11, 2021 Proceedings 123 Editors Carlos Martín-Vide Miguel A. Vega-Rodríguez Rovira i Virgili University University of Extremadura Tarragona, Spain Cáceres, Spain Travis Wheeler University of Montana Missoula, MT, USA ISSN 0302-9743 ISSN 1611-3349 (electronic) Lecture Notes in Bioinformatics ISBN 978-3-030-74431-1 ISBN 978-3-030-74432-8 (eBook) https://doi.org/10.1007/978-3-030-74432-8 LNCS Sublibrary: SL8 – Bioinformatics © Springer Nature Switzerland AG 2021 This work is subject to copyright. -
Reconstructing Contiguous Regions of an Ancestral Genome
Downloaded from www.genome.org on December 5, 2006 Reconstructing contiguous regions of an ancestral genome Jian Ma, Louxin Zhang, Bernard B. Suh, Brian J. Raney, Richard C. Burhans, W. James Kent, Mathieu Blanchette, David Haussler and Webb Miller Genome Res. 2006 16: 1557-1565; originally published online Sep 18, 2006; Access the most recent version at doi:10.1101/gr.5383506 Supplementary "Supplemental Research Data" data http://www.genome.org/cgi/content/full/gr.5383506/DC1 References This article cites 20 articles, 11 of which can be accessed free at: http://www.genome.org/cgi/content/full/16/12/1557#References Open Access Freely available online through the Genome Research Open Access option. Email alerting Receive free email alerts when new articles cite this article - sign up in the box at the service top right corner of the article or click here Notes To subscribe to Genome Research go to: http://www.genome.org/subscriptions/ © 2006 Cold Spring Harbor Laboratory Press Downloaded from www.genome.org on December 5, 2006 Methods Reconstructing contiguous regions of an ancestral genome Jian Ma,1,5,6 Louxin Zhang,2 Bernard B. Suh,3 Brian J. Raney,3 Richard C. Burhans,1 W. James Kent,3 Mathieu Blanchette,4 David Haussler,3 and Webb Miller1 1Center for Comparative Genomics and Bioinformatics, Penn State University, University Park, Pennsylvania 16802, USA; 2Department of Mathematics, National University of Singapore, Singapore 117543; 3Center for Biomolecular Science and Engineering, University of California Santa Cruz, Santa Cruz, California 95064, USA; 4School of Computer Science, McGill University, Montreal, Quebec H3A 2B4, Canada This article analyzes mammalian genome rearrangements at higher resolution than has been published to date. -
Computational Biology and Bioinformatics
Vol. 30 ISMB 2014, pages i1–i2 BIOINFORMATICS EDITORIAL doi:10.1093/bioinformatics/btu304 Editorial This special issue of Bioinformatics serves as the proceedings of The conference used a two-tier review system, a continuation the 22nd annual meeting of Intelligent Systems for Molecular and refinement of a process begun with ISMB 2013 in an effort Biology (ISMB), which took place in Boston, MA, July 11–15, to better ensure thorough and fair reviewing. Under the revised 2014 (http://www.iscb.org/ismbeccb2014). The official confer- process, each of the 191 submissions was first reviewed by at least ence of the International Society for Computational Biology three expert referees, with a subset receiving between four and (http://www.iscb.org/), ISMB, was accompanied by 12 Special eight reviews, as needed. These formal reviews were frequently Interest Group meetings of one or two days each, two satellite supplemented by online discussion among reviewers and Area meetings, a High School Teachers Workshop and two half-day Chairs to resolve points of dispute and reach a consensus on tutorials. Since its inception, ISMB has grown to be the largest each paper. Among the 191 submissions, 29 were conditionally international conference in computational biology and bioinfor- accepted for publication directly from the first round review Downloaded from matics. It is expected to be the premiere forum in the field for based on an assessment of the reviewers that the paper was presenting new research results, disseminating methods and tech- clearly above par for the conference. A subset of 16 papers niques and facilitating discussions among leading researchers, were viewed as potentially in the top tier but raised significant practitioners and students in the field. -
Duplication, Deletion, and Rearrangement in the Mouse and Human Genomes
Evolution’s cauldron: Duplication, deletion, and rearrangement in the mouse and human genomes W. James Kent*†, Robert Baertsch*, Angie Hinrichs*, Webb Miller‡, and David Haussler§ *Center for Biomolecular Science and Engineering and §Howard Hughes Medical Institute, Department of Computer Science, University of California, Santa Cruz, CA 95064; and ‡Department of Computer Science and Engineering, Pennsylvania State University, University Park, PA 16802 Edited by Michael S. Waterman, University of Southern California, Los Angeles, CA, and approved July 11, 2003 (received for review April 9, 2003) This study examines genomic duplications, deletions, and rear- depending on details of definition and method. The length rangements that have happened at scales ranging from a single distribution of synteny blocks was found to be consistent with the base to complete chromosomes by comparing the mouse and theory of random breakage introduced by Nadeau and Taylor (8, human genomes. From whole-genome sequence alignments, 344 9) before significant gene order data became available. In recent large (>100-kb) blocks of conserved synteny are evident, but these comparisons of the human and mouse genomes, rearrangements are further fragmented by smaller-scale evolutionary events. Ex- of Ն100,000 bases were studied by comparing 558,000 highly cluding transposon insertions, on average in each megabase of conserved short sequence alignments (average length 340 bp) genomic alignment we observe two inversions, 17 duplications within 300-kb windows. An estimated 217 blocks of conserved (five tandem or nearly tandem), seven transpositions, and 200 synteny were found, formed from 342 conserved segments, with deletions of 100 bases or more. This includes 160 inversions and 75 length distribution roughly consistent with the random breakage duplications or transpositions of length >100 kb. -
Open Thesisformatted Final.Pdf
The Pennsylvania State University The Graduate School The Huck Institutes of the Life Sciences COMPUTATIONAL APPROACHES TO PREDICT PHENOTYPE DIFFERENCES IN POPULATIONS FROM HIGH-THROUGHPUT SEQUENCING DATA A Dissertation in Integrative Biosciences in Bioinformatics and Genomics by Oscar Camilo Bedoya Reina 2014 Oscar Camilo Bedoya Reina Submitted in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy May 2014 i The dissertation of Oscar Camilo Bedoya Reina was reviewed and approved* by the following: Webb Miller Professor of Biology and Computer Science and Engineering Dissertation Advisor Chair of Committee Ross Hardison T. Ming Chu Professor of Biochemistry and Molecular Biology George Perry Assistant Professor of Anthropology and Biology Kamesh Madduri Assistant Professor of Computer Science and Engineering Peter Hudson Willaman Professor of Biology Head of the Huck Institutes of the Life Sciences *Signatures are on file in the Graduate School iii ABSTRACT High-throughput sequencing technologies are changing the world. They are revolutionizing the life sciences and will be the foundation of a promising century of innovations. In recent years, the development of new sequencing technologies has dramatically decreased the cost of genome sequencing. Less than twenty years ago, sequencing the human genome cost 3 billion dollars, and took about a decade to complete. Today, high-quality 30X full-genome coverage can be obtained in just one day for US$ 5,000, while sequencing just the ~21,000 human genes to the same depth costs only about US$ 500. The latter is sufficient for detecting most of the rare variants, along with other sources of genetic variability such as indels, copy- number variations, and inversions that are characteristic of complex diseases. -
Applications of Case-Based Reasoning in Molecular Biology
Articles Applications of Case-Based Reasoning in Molecular Biology Igor Jurisica and Janice Glasgow ■ Case-based reasoning (CBR) is a computational problems by recalling old problems and their reasoning paradigm that involves the storage and solutions and adapting these previous experi- retrieval of past experiences to solve novel prob- ences represented as cases. A case generally lems. It is an approach that is particularly relevant comprises an input problem, an output solu- in scientific domains, where there is a wealth of data but often a lack of theories or general princi- tion, and feedback in terms of an evaluation of ples. This article describes several CBR systems that the solution. CBR is founded on the premise have been developed to carry out planning, analy- that similar problems have similar solutions. sis, and prediction in the domain of molecular bi- Thus, one of the primary goals of a CBR system ology. is to find the most similar, or most relevant, cases for new input problems. The effective- ness of CBR depends on the quality and quan- tity of cases in a case base. In some domains, even a small number of cases provide good so- lutions, but in other domains, an increased number of unique cases improves problem- he domain of molecular biology can be solving capabilities of CBR systems because characterized by substantial amounts of there are more experiences to draw on. Howev- Tcomplex data, many unknowns, a lack of er, larger case bases can also decrease the effi- complete theories, and rapid evolution; rea- ciency of a system. The reader can find detailed soning is often based on experience rather descriptions of the CBR process and systems in than general knowledge. -
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. -
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Topics in Signal Processing: applications in genomics and genetics Abdulkadir Elmas Submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in the Graduate School of Arts and Sciences COLUMBIA UNIVERSITY 2016 c 2016 Abdulkadir Elmas All Rights Reserved ABSTRACT Topics in Signal Processing: applications in genomics and genetics Abdulkadir Elmas The information in genomic or genetic data is influenced by various complex processes and appropriate mathematical modeling is required for studying the underlying processes and the data. This dissertation focuses on the formulation of mathematical models for certain problems in genomics and genetics studies and the development of algorithms for proposing efficient solutions. A Bayesian approach for the transcription factor (TF) motif discovery is examined and the extensions are proposed to deal with many interdependent parameters of the TF-DNA binding. The problem is described by statistical terms and a sequential Monte Carlo sampling method is employed for the estimation of unknown param- eters. In particular, a class-based resampling approach is applied for the accurate estimation of a set of intrinsic properties of the DNA binding sites. Through statistical analysis of the gene expressions, a motif-based computational approach is developed for the inference of novel regulatory networks in a given bacterial genome. To deal with high false-discovery rates in the genome-wide TF binding predictions, the discriminative learning approaches are examined in the context of sequence classification, and a novel mathematical model is introduced to the family of kernel-based Support Vector Machines classifiers. Furthermore, the problem of haplotype phasing is examined based on the genetic data obtained from cost-effective genotyping technologies. -
ENCODE Analysis Working Group and Data Analysis Centre Rick Myers
ENCODE Analysis Working Group and Data Analysis Centre Rick Myers Ewan Birney Motivation for mandated DAC y Genesis from the experience of the pilot project y Everyone looking at the ceiling when a key piece of annoying analysis needs to happen y A set of people who are funded to ensure that critical integrative analysis occurs (consistently and timely) y In no way exclusive y Everyone is invited in analysis y DAC should fit around things which are happening at the consortium level y Porous (no distinction expected between DAC members and other consortium members) except… y …the cleaning of the Aegean stables moment (eg, creating repeat libraries, consistently remapping everyone’s chip-seq data) y Interplay with DCC deliberate (trade off where things occur) y When there are too many things on the DAC to-do list - ask AWG to prioritise. AWG Participates in Rick Myers discussion Chair of AWG Birney BickelBickel Project Manager Haussler EBI (Ian Dunham) Bickel Directed Analysis Methods development EBI UCSC Yale BU EBI UCSC Yale BU U. Wash Penn Berkeley U. Wash Penn Berkeley DAC - federated, embedded y Ewan Birney/Paul Flicek/Ian Dunham (EBI)- comparative genomics, short read technology methods y Mark Gerstein (Yale) - chip-seq, link to genes/transcripts, link to modENCODE, P y Zhiping Weng (BU) - chip-chip, chip-seq, motif finding, bayesian analysis y Ross Hardison/Webb Miller (PSU) - comparative genomics, regulatory regions y Jim Kent/David Haussler (UCSC) - comparative genomics, DCC y Peter Bickel (UC Berkeley) - statistician y Bill Nobel (UW) - machine learning - HMMs, change point analysis, wavelets, SVMs New analysis tasks from AWG or community Results Provided Triage and Back to AWG Initial prioritisation Converting Priortisation Active ad hoc of all projects tasks analysis to by AWG handled pipelines by EDAC AWG prioritisation EDAC suggest pipelining tasks Experimental Data exploration, DCC group, in house Normalisation, coordination methods Sanity checking Feedback to AWG and expt. -
Recombinatorics the Algorithmics of Ancestral Recombination Graphs and Explicit Phylogenetic Networks
ReCombinatorics The Algorithmics of Ancestral Recombination Graphs and Explicit Phylogenetic Networks Dan Gusfield ReCombinatorics The Algorithmics of Ancestral Recombination Graphs and Explicit Phylogenetic Networks Dan Gusfield With contributions from Charles H. Langley, Yun S. Song, and Yufeng Wu The MIT Press Cambridge, Massachusetts London, England The metal tree sculpture on the cover was created by Shawnie Briggs of Winters California. Contents Preface xiii 1Introduction 1 1.1 Combinatorial Genomes and the Grand Challenge . 1 1.2 Networks ............................... 2 1.2.1 Recombination and Networks . 4 1.2.2 WhyNetworks?........................ 5 1.2.2.1 Pedigrees . 5 1.2.2.2 Back to Sequences . 6 1.2.2.3 Adding in Mutation and Recombination . 11 1.2.2.4 Transmission Paths Form (Parts of) a Genealog- icalNetwork .................... 12 1.2.2.5 Genealogical Networks Relate Sequences, Not Peo- ple.......................... 13 1.3 The Central Thesis of the Book . 14 1.4 Fundamental Definitions . .................. 14 1.4.1 Mutation, Infinite Sites, Perfect Characters, and Binary Sequences . 16 1.4.1.1 The Infinite-Sites Model . ........ 17 1.4.1.2 SNPs . 18 1.4.1.3 Perfect Characters and Homoplasy . 18 1.4.1.4 Perfection Is an Abstraction . 20 1.4.1.5 And, We Can Often Incorporate Homoplasy . 21 1.5 TheObservedData.......................... 22 1.6 Graph Definitions . 22 1.6.1 Trees and DAGs: The Most Central Graphs in This Book 24 1.6.1.1 Trees and Subtrees . ........ 25 1.6.1.2 Directed Acyclic Graphs (DAGs) . 27 1.6.2 Genealogical Networks and ARGs: First Definitions . 29 1.7 TheBook ..............................