Uncovering Biological Network Function via Graphlet Degree Signatures
نویسندگان
چکیده
منابع مشابه
Uncovering Biological Network Function via Graphlet Degree Signatures
MOTIVATION Proteins are essential macromolecules of life and thus understanding their function is of great importance. The number of functionally unclassified proteins is large even for simple and well studied organisms such as baker's yeast. Methods for determining protein function have shifted their focus from targeting specific proteins based solely on sequence homology to analyses of the en...
متن کاملBiological network comparison using graphlet degree distribution
MOTIVATION Analogous to biological sequence comparison, comparing cellular networks is an important problem that could provide insight into biological understanding and therapeutics. For technical reasons, comparing large networks is computationally infeasible, and thus heuristics, such as the degree distribution, clustering coefficient, diameter, and relative graphlet frequency distribution ha...
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Important biological information is encoded in the topology of biological networks. Comparative analyses of biological networks are proving to be valuable, as they can lead to transfer of knowledge between species and give deeper insights into biological function, disease, and evolution. We introduce a new method that uses the Hungarian algorithm to produce optimal global alignment between two ...
متن کاملComparative network analysis via differential graphlet communities
While current protein interaction data provides a rich resource for molecular biology, it mostly lacks condition-specific details. Abundance of mRNA data for most diseases provides potential to model condition-specific transcriptional changes. Transcriptional data enables modeling disease mechanisms, and in turn provide potential treatments. While approaches to compare networks constructed from...
متن کاملGraphlet-based measures are suitable for biological network comparison
MOTIVATION Large amounts of biological network data exist for many species. Analogous to sequence comparison, network comparison aims to provide biological insight. Graphlet-based methods are proving to be useful in this respect. Recently some doubt has arisen concerning the applicability of graphlet-based measures to low edge density networks-in particular that the methods are 'unstable'-and f...
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ژورنال
عنوان ژورنال: Cancer Informatics
سال: 2008
ISSN: 1176-9351,1176-9351
DOI: 10.4137/cin.s680