Comparative Genomics: RECOMB 2005 International Workshop, RCG 2005, Dublin, Ireland, September 18-20, 2005, Proceedings

Author:   Aoife McLysaght ,  Daniel H. Huson
Publisher:   Springer-Verlag Berlin and Heidelberg GmbH & Co. KG
Edition:   2005 ed.
Volume:   3678
ISBN:  

9783540289326


Pages:   168
Publication Date:   06 September 2005
Format:   Paperback
Availability:   In Print   Availability explained
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Comparative Genomics: RECOMB 2005 International Workshop, RCG 2005, Dublin, Ireland, September 18-20, 2005, Proceedings


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Overview

The complexity of genome evolution poses many exciting challenges to devel- ers of mathematical models and algorithms, who have recourse to a spectrum of algorithmic,statisticalandmathematicaltechniques,rangingfromexact,heur- tic, ?xed-parameter and approximation algorithms for problems based on par- mony models to Monte Carlo Markov Chain algorithms for Bayesian analysis of problems based on probabilistic models. The annual RECOMB Satellite Workshop on Comparative Genomics (RECOMB ComparativeGenomics)is aforumonallaspects andcomponents of this ?eld,rangingfromnew quantitativediscoveriesabout genomestructureand process to theorems on the complexity of computational problems inspired by genome comparison. The informal steering committee for this meeting consists of David Sanko?, Jens Lagergren and Aoife McLysaght. Thisvolumecontainsthepaperspresentedatthe3rdRECOMBComparative Genomicsmeeting,whichwasheldinDublin,Ireland,onSeptember18-20,2005. The ?rst two meetings of this series were held in Minneapolis, USA (2003) and Bertinoro, Italy (2004). This year, 21 papers were submitted, of which the Program Committee - lected 14 for presentation at the meeting and inclusion in this proceedings.Each submission was refereed by at least three members of the Program Committee. Aftercompletionofthereferees'reports,anextensiveWeb-baseddiscussiontook placeformakingdecisions.TheRECOMBComparativeGenomics2005Program Committee consisted of the following 27 members: Vineet Bafna, Anne Be- eron, Mathieu Blanchette, Avril Coghlan, Dannie Durand, Nadia El-Mabrouk, Niklas Eriksen, Aaron Halpern, Rose Hoberman, Daniel Huson, Jens Lagergren, Giuseppe Lancia, Emmanuelle Lerat, Aoife McLysaght, Istvan Miklos, Bernard Moret, PavelPevzner, Ben Raphael, Marie-FranceSagot, David Sanko?, Cathal Seoighe, Beth Shapiro, Igor Sharakhov, Mike Steel, Jens Stoye, Glenn Tesler and Louxin Zhan. We would like to thank the ProgramCommittee members for their dedication and hard work.

Full Product Details

Author:   Aoife McLysaght ,  Daniel H. Huson
Publisher:   Springer-Verlag Berlin and Heidelberg GmbH & Co. KG
Imprint:   Springer-Verlag Berlin and Heidelberg GmbH & Co. K
Edition:   2005 ed.
Volume:   3678
Dimensions:   Width: 15.50cm , Height: 0.90cm , Length: 23.50cm
Weight:   0.580kg
ISBN:  

9783540289326


ISBN 10:   3540289321
Pages:   168
Publication Date:   06 September 2005
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Paperback
Publisher's Status:   Active
Availability:   In Print   Availability explained
This item will be ordered in for you from one of our suppliers. Upon receipt, we will promptly dispatch it out to you. For in store availability, please contact us.

Table of Contents

Lower Bounds for Maximum Parsimony with Gene Order Data.- Genes Order and Phylogenetic Reconstruction: Application to ?-Proteobacteria.- Maximizing Synteny Blocks to Identify Ancestral Homologs.- An Expectation-Maximization Algorithm for Analysis of Evolution of Exon-Intron Structure of Eukaryotic Genes.- Likely Scenarios of Intron Evolution.- OMA, A Comprehensive, Automated Project for the Identification of Orthologs from Complete Genome Data: Introduction and First Achievements.- The Incompatible Desiderata of Gene Cluster Properties.- The String Barcoding Problem is NP-Hard.- A Partial Solution to the C-Value Paradox.- Individual Gene Cluster Statistics in Noisy Maps.- Power Boosts for Cluster Tests.- Reversals of Fortune.- Very Low Power to Detect Asymmetric Divergence of Duplicated Genes.- A Framework for Orthology Assignment from Gene Rearrangement Data.

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