Learning gene regulatory networks from gene expression measurements using non-parametric molecular kinetics

Motivation: Regulation of gene expression is fundamental to the operation of a cell. Revealing the structure and dynamics of a gene regulatory network (GRN) is of great interest and represents a considerably challenging computational problem. The GRN estimation problem is complicated by the fact tha...

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Veröffentlicht in:	Bioinformatics 2009-11, Vol.25 (22), p.2937-2944
Hauptverfasser:	Äijö, Tarmo, Lähdesmäki, Harri
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Bayes Theorem Biological and medical sciences Computational Biology - methods Fundamental and applied biological sciences. Psychology Gene Expression Profiling - methods Gene Expression Regulation Gene Regulatory Networks General aspects Kinetics Mathematics in biology. Statistical analysis. Models. Metrology. Data processing in biology (general aspects)
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