Discover regulatory DNA elements using chromatin signatures and artificial neural network | Zendy

Hiram Firpi | Zendy; Duygu Ucar | Zendy; Kai Tan | Zendy

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Discover regulatory DNA elements using chromatin signatures and artificial neural network

Author(s) -

Hiram Firpi,

Duygu Ucar,

Kai Tan

Publication year - 2010

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/btq248

Subject(s) - chromatin , computer science , artificial neural network , encode , transformation (genetics) , source code , chia pet , data mining , feature (linguistics) , computational biology , exploit , artificial intelligence , software , pattern recognition (psychology) , machine learning , dna , biology , chromatin remodeling , genetics , gene , linguistics , philosophy , computer security , operating system , programming language

Recent large-scale chromatin states mapping efforts have revealed characteristic chromatin modification signatures for various types of functional DNA elements. Given the important influence of chromatin states on gene regulation and the rapid accumulation of genome-wide chromatin modification data, there is a pressing need for computational methods to analyze these data in order to identify functional DNA elements. However, existing computational tools do not exploit data transformation and feature extraction as a means to achieve a more accurate prediction.

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