Description
- Abstract:
- Despite the fact that the human genome was sequenced ten years ago, there exists no database of cis-regulatory architecture that is validated conclusively by rigorous experimental criteria; this has been a notoriously longstanding unresolved computational biology problem. This proposal describes the construction of the first such database, the cis-Lexicon, containing only causality-inferred DNA sequence structure information on the regulatory regions of transcription factor-encoding genes and other regulatory genes. The data in the Lexicon is purely causality-inferred, meaning that each annotation is backed by experimental techniques which prove causality; there is no information due to noisy experimental methods or computational prediction. This data, previously not available in databases (outside of the original papers) or mixed with lower-quality data, is necessary for understanding the cis-regulatory code, the relationship between sequence structure and regulatory function. Only through completeness of information will correct conclusions be drawn from the Lexicon, and for this purpose we built the cis-Lexicon Ontology Search Engine (CLOSE). CLOSE is an information retrieval system designed to find biology journal articles containing cis-regulatory sequence structure information and evaluate the completeness of the cis-Lexicon. Information must be entered into the Lexicon in a reliable manner to ensure accurate annotations; in addition, the data must be conveniently accessible to be useful for experimental work. For both of these purposes we have built the cis-Browser, a genome browser customized for cis-regulatory analysis.
- Notes:
- Thesis (Ph.D. -- Brown University (2012)
Access Conditions
- Rights
- In Copyright
- Restrictions on Use
- Collection is open for research.
Citation
Tarpine, Ryan C.,
"A database of causality-inferred structure-function information for genomic cis-regulatory architecture"
(2012).
Computer Science Theses and Dissertations.
Brown Digital Repository. Brown University Library.
https://doi.org/10.7301/Z0M32T28
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Computer Science Theses and Dissertations
Theses and Dissertations for the Computer Science department....