期刊
BIOINFORMATICS
卷 34, 期 12, 页码 2136-2138出版社
OXFORD UNIV PRESS
DOI: 10.1093/bioinformatics/bty063
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资金
- Academy of Finland [275151, 292307]
- EU H2020 caLIBRAte project [686239]
- EU H2020 LIFEPATH [633666]
- EU NANOSOLUTIONS project [FP7-309329]
The Summary: Detecting and interpreting responsive modules from gene expression data by using network-based approaches is a common but laborious task. It often requires the application of several computational methods implemented in different software packages, forcing biologists to compile complex analytical pipelines. Here we introduce INfORM (Inference of NetwOrk Response Modules), an R shiny application that enables non-expert users to detect, evaluate and select gene modules with high statistical and biological significance. INfORM is a comprehensive tool for the identification of biologically meaningful response modules from consensus gene networks inferred by using multiple algorithms. It is accessible through an intuitive graphical user interface allowing for a level of abstraction from the computational steps.
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