FIT: statistical modeling tool for transcriptome dynamics under fluctuating field conditions | Zendy

Koji Iwayama | Zendy; Yuri Aisaka | Zendy; Natsumaro Kutsuna | Zendy; Atsushi J. Nagano | Zendy

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FIT: statistical modeling tool for transcriptome dynamics under fluctuating field conditions

Author(s) -

Koji Iwayama,

Yuri Aisaka,

Natsumaro Kutsuna,

Atsushi J. Nagano

Publication year - 2017

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/btx049

Subject(s) - computer science , transcriptome , field (mathematics) , r package , variation (astronomy) , data mining , biology , mathematics , computational science , biochemistry , gene expression , physics , gene , astrophysics , pure mathematics

Considerable attention has been given to the quantification of environmental effects on organisms. In natural conditions, environmental factors are continuously changing in a complex manner. To reveal the effects of such environmental variations on organisms, transcriptome data in field environments have been collected and analyzed. Nagano et al. proposed a model that describes the relationship between transcriptomic variation and environmental conditions and demonstrated the capability to predict transcriptome variation in rice plants. However, the computational cost of parameter optimization has prevented its wide application.

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