ProClust: improved clustering of protein sequences with an extended graph-based approach.
about
The Sorcerer II Global Ocean Sampling expedition: expanding the universe of protein familiesClustering protein sequences with a novel metric transformed from sequence similarity scores and sequence alignments with neural networks.Spectral clustering of protein sequences.GenFamClust: an accurate, synteny-aware and reliable homology inference algorithmSEQOPTICS: a protein sequence clustering system.Large scale clustering of protein sequences with FORCE -A layout based heuristic for weighted cluster editingCLUSS: clustering of protein sequences based on a new similarity measure.Probing metagenomics by rapid cluster analysis of very large datasets.Partitioning clustering algorithms for protein sequence data sets.SCPS: a fast implementation of a spectral method for detecting protein families on a genome-wide scale.Genome-wide comparative gene family classificationBrEPS: a flexible and automatic protocol to compute enzyme-specific sequence profiles for functional annotationIntegrating overlapping structures and background information of words significantly improves biological sequence comparison.Ultrafast clustering algorithms for metagenomic sequence analysis.Comprehensive computational analysis of bacterial CRP/FNR superfamily and its target motifs reveals stepwise evolution of transcriptional networks.MotifCluster: an interactive online tool for clustering and visualizing sequences using shared motifs.Genome cluster database. A sequence family analysis platform for Arabidopsis and rice.GFam: a platform for automatic annotation of gene families.Detection of homologous proteins by an intermediate sequence search.MOCASSIN-prot: A Multi-Objective Clustering Approach for Protein Similarity Networks.Markov model plus k-word distributions: a synergy that produces novel statistical measures for sequence comparison.Using Markov model to improve word normalization algorithm for biological sequence comparison.A novel clustering approach and prediction of optimal number of clusters: global optimum search with enhanced positioning
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P2860
ProClust: improved clustering of protein sequences with an extended graph-based approach.
description
2002 nî lūn-bûn
@nan
2002年の論文
@ja
2002年論文
@yue
2002年論文
@zh-hant
2002年論文
@zh-hk
2002年論文
@zh-mo
2002年論文
@zh-tw
2002年论文
@wuu
2002年论文
@zh
2002年论文
@zh-cn
name
ProClust: improved clustering of protein sequences with an extended graph-based approach.
@en
ProClust: improved clustering of protein sequences with an extended graph-based approach.
@nl
type
label
ProClust: improved clustering of protein sequences with an extended graph-based approach.
@en
ProClust: improved clustering of protein sequences with an extended graph-based approach.
@nl
prefLabel
ProClust: improved clustering of protein sequences with an extended graph-based approach.
@en
ProClust: improved clustering of protein sequences with an extended graph-based approach.
@nl
P2093
P356
P1433
P1476
ProClust: improved clustering of protein sequences with an extended graph-based approach
@en
P2093
A Schönhuth
D Schomburg
P Pipenbacher
R Schrader
S Schneckener
P304
P356
10.1093/BIOINFORMATICS/18.SUPPL_2.S182
P407
P478
18 Suppl 2
P577
2002-01-01T00:00:00Z