Evaluation of BLAST-based edge-weighting metrics used for homology inference with the Markov Clustering algorithm

Background Clustering protein sequences according to inferred homology is a fundamental step in the analysis of many large data sets. Since the publication of the Markov Clustering (MCL) algorithm in 2002, it has been the centerpiece of several popular applications. Each of these approaches generate...

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Veröffentlicht in:	BMC bioinformatics Jg. 16; H. 1; S. 218
Hauptverfasser:	Gibbons, Theodore R., Mount, Stephen M., Cooper, Endymion D., Delwiche, Charles F.
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	London BioMed Central 10.07.2015 BioMed Central Ltd
Schlagworte:	Algorithms Amino Acid Sequence Bioinformatics Biomedical and Life Sciences Cluster Analysis Computational Biology - methods Computational Biology/Bioinformatics Computer Appl. in Life Sciences Databases, Factual Humans Life Sciences Markov Chains Microarrays Molecular Sequence Data Proteins - chemistry Proteins - metabolism Research Article Sequence Alignment - methods Sequence analysis (methods) Sequence Analysis, Protein - methods Sequence Homology, Amino Acid Software Graph High-throughput sequencing Transcriptomics Short-read sequencing Protein clustering Genomics MCL Homology prediction Bioinformatics Sequence clustering
ISSN:	1471-2105, 1471-2105
Online-Zugang:	Volltext
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