SIBER: systematic identification of bimodally expressed genes using RNAseq data | Zendy

Pan Tong | Zendy; Yong Chen | Zendy; Xiao Su | Zendy; Kevin R. Coombes | Zendy

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SIBER: systematic identification of bimodally expressed genes using RNAseq data

Author(s) -

Pan Tong,

Yong Chen,

Xiao Su,

Kevin R. Coombes

Publication year - 2013

Publication title -

bioinformatics

Language(s) - English

Resource type - Journals

eISSN - 1367-4811

pISSN - 1367-4803

DOI - 10.1093/bioinformatics/bts713

Subject(s) - identification (biology) , outlier , computational biology , cluster analysis , dna microarray , computer science , data mining , biology , gene , genetics , artificial intelligence , gene expression , botany

Identification of bimodally expressed genes is an important task, as genes with bimodal expression play important roles in cell differentiation, signalling and disease progression. Several useful algorithms have been developed to identify bimodal genes from microarray data. Currently, no method can deal with data from next-generation sequencing, which is emerging as a replacement technology for microarrays.

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