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Studies on semantic systems chemical...

Chen, Bin.

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Studies on semantic systems chemical biology.

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Studies on semantic systems chemical biology./
作者:	Chen, Bin.
面頁冊數:	138 p.
附註:	Source: Dissertation Abstracts International, Volume: 74-01(E), Section: A.
Contained By:	Dissertation Abstracts International74-01A(E).
標題:	Information Science. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3527530
ISBN:	9781267619204

Studies on semantic systems chemical biology.
Chen, Bin.

Studies on semantic systems chemical biology. - 138 p.

Source: Dissertation Abstracts International, Volume: 74-01(E), Section: A.

Thesis (Ph.D.)--Indiana University, 2012.

Current "one disease, one target and one drug" drug development paradigm is under question as relatively few drugs have reached the market in the last two decades. Increasingly research focus is being placed on the study of drug action against biological systems as a whole rather than against a single component (called 'Systems Chemical Biology'). This has been made possible by the rapid accumulation of various data in chemistry and biology. Systematic integration of these heterogeneous sets and the provision of algorithms to mine the integrated sets would permit investigation of the complex mechanisms of action of drugs; however, traditional approaches face challenges in the representation and integration of multi-scale data sets and in the discovery of underlying knowledge from the integrated large-scale data sets. The Semantic Web, envisioned to enable machines to understand and respond to complex human requests and to retrieve relevant, yet distributed data, has potential to assist systems chemical biology studies.

ISBN: 9781267619204Subjects--Topical Terms:

1017528
Information Science.

Studies on semantic systems chemical biology.
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500 $a Adviser: David J. Wild.
502 $a Thesis (Ph.D.)--Indiana University, 2012.
520 $a Current "one disease, one target and one drug" drug development paradigm is under question as relatively few drugs have reached the market in the last two decades. Increasingly research focus is being placed on the study of drug action against biological systems as a whole rather than against a single component (called 'Systems Chemical Biology'). This has been made possible by the rapid accumulation of various data in chemistry and biology. Systematic integration of these heterogeneous sets and the provision of algorithms to mine the integrated sets would permit investigation of the complex mechanisms of action of drugs; however, traditional approaches face challenges in the representation and integration of multi-scale data sets and in the discovery of underlying knowledge from the integrated large-scale data sets. The Semantic Web, envisioned to enable machines to understand and respond to complex human requests and to retrieve relevant, yet distributed data, has potential to assist systems chemical biology studies.
520 $a In the dissertation study, I explore cutting edge Semantic Web technologies to represent and integrate data and leverage the network models to mine the integrated data. I first create a single RDF repository called Chem2Bio2RDF by aggregating over 20 data resources, and use it to investigate polypharmacology and identify potential multiple pathway inhibitors. I further develop a generalized OWL ontology called Chem2Bio2OWL that describes the semantics of chemical compounds, drugs, protein targets, pathways, genes, diseases and side-effects, and the relationships between them. I use the ontology to annotate the Chem2Bio2RDF dataset, creating a large heterogeneous network with semantic meanings. I further develop a novel statistical model to assess the entity associations based on the topology and semantics of the network, and apply it to assess drug-target associations that assist the investigation of the mechanisms of action of drugs.
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