Comparative Genomics RECOMB 2005 International Workshop, RCG 2005, Dublin, Ireland, September 18-20, 2005, Proceedings /
Comparative Genomics RECOMB 2005 International Workshop, RCG 2005, Dublin, Ireland, September 18-20, 2005, Proceedings / [electronic resource] :
edited by Aoife McLysaght, Daniel H. Huson.
- 1st ed. 2005.
- VIII, 168 p. online resource.
- Lecture Notes in Bioinformatics, 3678 2366-6331 ; .
- Lecture Notes in Bioinformatics, 3678 .
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.
9783540318149
10.1007/11554714 doi
Biochemistry.
Algorithms.
Artificial intelligence--Data processing.
Computer science--Mathematics.
Discrete mathematics.
Database management.
Bioinformatics.
Biochemistry.
Algorithms.
Data Science.
Discrete Mathematics in Computer Science.
Database Management.
Bioinformatics.
QD415-436
572
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.
9783540318149
10.1007/11554714 doi
Biochemistry.
Algorithms.
Artificial intelligence--Data processing.
Computer science--Mathematics.
Discrete mathematics.
Database management.
Bioinformatics.
Biochemistry.
Algorithms.
Data Science.
Discrete Mathematics in Computer Science.
Database Management.
Bioinformatics.
QD415-436
572