Research in Computational Molecular Biology: 9th Annual International Conference, RECOMB 2005, Cambridge, MA, USA, May 14-18, 2005, Proceedings
Satoru Miyano, Jill Mesirov, Simon Kasif, Sorin Istrail, Pavel Pevzner, Michael Waterman
Springer, Jun 23, 2005 - Computers - 632 pages
This book constitutes the refereed proceedings of the 9th Annual International Conference on Research in Computational Molecular Biology, RECOMB 2005, held in Cambridge, MA, USA in May 2005. The 39 revised full papers presented together with abstracts of keynote talks were carefully reviewed and selected from 217 submissions. As the top conference in computational molecular conference, RECOMB addresses all current issues in algorithmic and theoretical bioinformatics.
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Efficient Algorithms for Detecting Signaling Pathways in Protein
Towards an Integrated ProteinProtein Interaction Network
The Factor Graph Network Model for Biological Systems
37 other sections not shown
algorithm alignment score amino acid analysis approach assignment Bayesian network binding sites Bioinformatics Biol Biology chromosome column complexity components compute conserved contains CoRegs corresponding database dataset define denote distribution domain dynamic programming edge energy estimate example exons Figure function gene trees genome given graph haplotypes inference interaction interval iteration kernel labeled Lemma length lower bound matching matrix maximum method microRNA Molecular molecules motifs mRNA multiple alignment node novo NP-hard nucleotides obtained optical maps optimal overlap p-value pairs pairwise alignments parameters parsimony path peaks peptide phylogenetic network phylogenetic tree phylogeny PPI networks prediction probabilistic probability problem Proc protein proteomes PSSMs random RECOMB reconstruction regions regulation regulatory residue reticulate root sample secondary structure segments sequence side-chain species spectra splits graph stacks subset subtrees tags target Theorem transcription factors translocation tree decomposition variables vector vertex weight