INCLUSive: INtegrated Clustering, Upstream sequence retrieval and motif Sampling | Zendy

Gert Thijs | Zendy; Yves Moreau | Zendy; Frank De Smet | Zendy; Janick Mathys | Zendy; Magali Lescot | Zendy; Stéphane Rombauts | Zendy; Pierre Rouzé | Zendy; Bart De Moor | Zendy; Kathleen Marchal | Zendy

AI Assistant Blog Pricing

Home ZAIA Blog

Open Access

INCLUSive: INtegrated Clustering, Upstream sequence retrieval and motif Sampling

Author(s) -

Gert Thijs,

Yves Moreau,

Frank De Smet,

Janick Mathys,

Magali Lescot,

Stéphane Rombauts,

Pierre Rouzé,

Bart De Moor,

Kathleen Marchal

Publication year - 2002

Publication title -

bioinformatics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 3.599

H-Index - 390

eISSN - 1367-4811

pISSN - 1367-4803

DOI - 10.1093/bioinformatics/18.2.331

Subject(s) - cluster analysis , sequence motif , motif (music) , computer science , sampling (signal processing) , sequence (biology) , computational biology , artificial intelligence , data mining , biology , genetics , computer vision , physics , acoustics , dna , filter (signal processing)

INCLUSive allows automatic multistep analysis of microarray data (clustering and motif finding). The clustering algorithm (adaptive quality-based clustering) groups together genes with highly similar expression profiles. The upstream sequences of the genes belonging to a cluster are automatically retrieved from GenBank and can be fed directly into Motif Sampler, a Gibbs sampling algorithm that retrieves statistically over-represented motifs in sets of sequences, in this case upstream regions of co-expressed genes.

The content you want is available to Zendy users.

Already have an account? Click here to sign in.

Having issues? You can contact us here

Accelerating Research