RANKS: a flexible tool for node label ranking and classification in biological networks
Author(s) -
Giorgio Valentini,
Giuliano Armano,
Marco Frasca,
Jianyi Lin,
Marco Mesiti,
Matteo Ré
Publication year - 2016
Publication title -
bioinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.599
H-Index - 390
eISSN - 1367-4811
pISSN - 1367-4803
DOI - 10.1093/bioinformatics/btw235
Subject(s) - computer science , ranking (information retrieval) , r package , node (physics) , multi label classification , embedding , property (philosophy) , machine learning , software , block (permutation group theory) , artificial intelligence , task (project management) , function (biology) , biological network , prioritization , data mining , bioinformatics , programming language , mathematics , philosophy , geometry , management , structural engineering , epistemology , management science , evolutionary biology , engineering , economics , biology
RANKS is a flexible software package that can be easily applied to any bioinformatics task formalizable as ranking of nodes with respect to a property given as a label, such as automated protein function prediction, gene disease prioritization and drug repositioning. To this end RANKS provides an efficient and easy-to-use implementation of kernelized score functions, a semi-supervised algorithmic scheme embedding both local and global learning strategies for the analysis of biomolecular networks. To facilitate comparative assessment, baseline network-based methods, e.g. label propagation and random walk algorithms, have also been implemented.
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