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Computationally efficient network inference using information theory: fMIDER

AuthorsVillaverde, A. F. ; Morán, Federico; Banga, Julio R.
Issue Date2014
CitationEuropean Conference of Computational Biology (2014)
AbstractBackground / Purpose: Mutual Information Distance & Entropy Reduction (MIDER) is a recently presented network inference method based on information theory. While it performs well compared to other state of the art methods, it is computationally expensive and requires commercial software (Matlab). Main conclusion: We present fMIDER, a FORTRAN implementation of MIDER that is: more efficient (faster), open source, can be run in parallel environments, and does not require any commercial software.
Description1 póster presentado al European Conference on Computational Biology 2014, 7 - 10 Sep 2014.-- This poster is open access subject to the CC BY-NC Creative Commons 4.0 License
Publisher version (URL)http://f1000.com/posters/browse/summary/1096791
Appears in Collections:(IIM) Comunicaciones congresos
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