MICFuzzy: A maximal information content based fuzzy approach for reconstructing genetic networks.

ABSTRACT: In systems biology, the accurate reconstruction of Gene Regulatory Networks (GRNs) is crucial since these networks can facilitate the solving of complex biological problems. Amongst the plethora of methods available for GRN reconstruction, information theory and fuzzy concepts-based methods have abiding popularity. However, most of these methods are not only complex, incurring a high computational burden, but they may also produce a high number of false positives, leading to inaccurate inferred networks. In this paper, we propose a novel hybrid fuzzy GRN inference model called MICFuzzy which involves the aggregation of the effects of Maximal Information Coefficient (MIC). This model has an information theory-based pre-processing stage, the output of which is applied as an input to the nove

SUBMITTER: Nakulugamuwa Gamage H 

PROVIDER: S-EPMC10328247 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature