Integrative network alignment reveals large regions of global network similarity in yeast and human

Motivation: High-throughput methods for detecting molecular interactions have produced large sets of biological network data with much more yet to come. Analogous to sequence alignment, efficient and reliable network alignment methods are expected to improve our understanding of biological systems....

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Veröffentlicht in:	Bioinformatics (Oxford, England) Jg. 27; H. 10; S. 1390 - 1396
Hauptverfasser:	Kuchaiev, Oleksii, Pržulj, Nataša
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Oxford Oxford University Press 15.05.2011
Schlagworte:	Algorithms Artificial Intelligence Biological and medical sciences Computational Biology - methods Fundamental and applied biological sciences. Psychology General aspects Humans Mathematics in biology. Statistical analysis. Models. Metrology. Data processing in biology (general aspects) Molecular Sequence Annotation Proteins - chemistry Proteins - metabolism Saccharomyces cerevisiae - genetics Saccharomyces cerevisiae - metabolism Sequence Alignment Human Yeast Similarity Network
ISSN:	1367-4803, 1367-4811, 1367-4811
Online-Zugang:	Volltext
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