Interactogeneous: disease gene prioritization using heterogeneous networks and full topology scores.
Disease gene prioritization aims to suggest potential implications of genes in disease susceptibility. Often accomplished in a guilt-by-association scheme, promising candidates are sorted according to their relatedness to known disease genes. Network-based methods have been successfully exploiting t...
Main Authors: | Joana P Gonçalves, Alexandre P Francisco, Yves Moreau, Sara C Madeira |
---|---|
Format: | Article |
Language: | English |
Published: |
Public Library of Science (PLoS)
2012-01-01
|
Series: | PLoS ONE |
Online Access: | http://europepmc.org/articles/PMC3501465?pdf=render |
Similar Items
-
Candidate gene prioritization by network analysis of differential expression using machine learning approaches
by: Nitsch Daniela, et al.
Published: (2010-09-01) -
S-score: a scoring system for the identification and prioritization of predicted cancer genes.
by: Jorge E S de Souza, et al.
Published: (2014-01-01) -
Gene prioritization and clustering by multi-view text mining
by: De Moor Bart, et al.
Published: (2010-01-01) -
Arete – candidate gene prioritization using biological network topology with additional evidence types
by: Artem Lysenko, et al.
Published: (2017-07-01) -
Cancer gene prioritization for targeted resequencing using FitSNP scores.
by: Annelies Fieuw, et al.
Published: (2012-01-01)