genome-wide modeling of transcription preinitiation complex disassembly mechanisms using chip-chip data全基因组转录始发前复杂的拆卸建模机制使用chip-chip数据.pdfVIP
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genome-wide modeling of transcription preinitiation complex disassembly mechanisms using chip-chip data全基因组转录始发前复杂的拆卸建模机制使用chip-chip数据
Genome-Wide Modeling of Transcription Preinitiation
Complex Disassembly Mechanisms using ChIP-chip Data
Eric Samorodnitsky1,2,3, B. Franklin Pugh1,2,3*
1 Center for Eukaryotic Gene Regulation, The Pennsylvania State University, University Park, Pennsylvania, United States of America, 2 Center for Comparative Genomics
and Bioinformatics, The Pennsylvania State University, University Park, Pennsylvania, United States of America, 3 Department of Biochemistry and Molecular Biology, North
Frear Laboratory, The Pennsylvania State University, University Park, Pennsylvania, United States of America
Abstract
Apparent occupancy levels of proteins bound to DNA in vivo can now be routinely measured on a genomic scale. A
challenge in relating these occupancy levels to assembly mechanisms that are defined with biochemically isolated
components lies in the veracity of assumptions made regarding the in vivo system. Assumptions regarding behavior of
molecules in vivo can neither be proven true nor false, and thus is necessarily subjective. Nevertheless, within those
confines, connecting in vivo protein-DNA interaction observations with defined biochemical mechanisms is an important
step towards fully defining and understanding assembly/disassembly mechanisms in vivo. To this end, we have developed a
computational program PathCom that models in vivo protein-DNA occupancy data as biochemical mechanisms under the
assumption that occupancy levels can be related to binding duration and explicitly defined assembly/disassembly reactions.
We exemplify the process with the assembly of the general transcription factors (TBP, TFIIB, TFIIE, TFIIF, TFIIH, and RNA
polymerase II) at the genes of the budding yeast Saccharomyces. Within the assumption inherent in the system our
modeling suggests
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