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Sahinidis, Nikolaos V. Chang, Youngjung 2015-09-25T20:43:28Z 2015-09-25T20:43:28Z 10000-01-01 2006 2006 Identification of transcription factor binding motif and sites is a crucial effort to elucidate gene regulatory networks and its combinatorial problem is NP -hard. In this thesis, the problem is modeled as an integer linear program with weak assumptions on the binding pattern. A computationally efficient formulation and linearization scheme is developed and the resulting problem is solved to global optimality. The proposed formulation successfully solved the CRP problem to identify its binding motif and sites simultaneously. Made available in DSpace on 2015-09-25T20:43:28Z (GMT). No. of bitstreams: 2 license.txt: 4848 bytes, checksum: 96035ab3f5e1c23cc7138a224ce498bd (MD5) 3250223.pdf: 3515317 bytes, checksum: cc56f4bde50ee929252db40263fe9801 (MD5) Previous issue date: 2006 Embargo set by: Seth Robbins for item 83671 Lift date: Forever Reason: Restricted to the U of I community idenfinitely during batch ingest of legacy ETDs Restricted to the U of I community idenfinitely during batch ingest of legacy ETDs U of I Only 150 p. Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 2006. http://hdl.handle.net/2142/82390 (MiAaPQ)AAI3250223 eng Biology, Bioinformatics Global Optimization in Systems Biology and Bioinformatics text Chemical Engineering Chemical Engineering University of Illinois at Urbana-Champaign Dissertation Ph.D.