Joining high-throughput technology with in silico modelling advances genome-wide screening towards targeted discovery
Author(s) -
Thomas Werner
Publication year - 2006
Publication title -
briefings in functional genomics and proteomics
Language(s) - English
Resource type - Journals
eISSN - 1477-4062
pISSN - 1473-9550
DOI - 10.1093/bfgp/ell010
Subject(s) - computational biology , context (archaeology) , in silico , selection (genetic algorithm) , biology , computer science , genome , throughput , process (computing) , high throughput screening , bioinformatics , machine learning , genetics , gene , paleontology , telecommunications , wireless , operating system
Genome research has entered the functional evaluation phase now and high-throughput (HT) methods provide an enormous amount of raw data for that purpose. However, functional verification still requires experimental regimens not suitable for application in a HT style, requiring an efficient discovery and selection process pinpointing biological mechanisms and processes for subsequent targeted verification. Regulatory networks and underlying molecular mechanisms can now be deduced through the interpretation of HT-data in the context of biologic knowledge. Computational models of promoter structures are suitable for genome-wide searches and a number of recent examples demonstrate their usefulness in prediction and selection of functional targets for experimental verification.
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