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Predictive Cheminformatics Analysis ...

Capuzzi, Stephen Joseph.

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Predictive Cheminformatics Analysis of Diverse Chemogenomics Data Sources: Applications to Drug Discovery, Assay Interference, and Text Mining.

Record Type:	Electronic resources : Monograph/item
Title/Author:	Predictive Cheminformatics Analysis of Diverse Chemogenomics Data Sources: Applications to Drug Discovery, Assay Interference, and Text Mining./
Author:	Capuzzi, Stephen Joseph.
Published:	Ann Arbor : ProQuest Dissertations & Theses, : 2018,
Description:	138 p.
Notes:	Source: Dissertations Abstracts International, Volume: 79-12, Section: B.
Contained By:	Dissertations Abstracts International79-12B.
Subject:	Pharmaceutical sciences. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10790163
ISBN:	9780438064652

Predictive Cheminformatics Analysis of Diverse Chemogenomics Data Sources: Applications to Drug Discovery, Assay Interference, and Text Mining.
Capuzzi, Stephen Joseph.

Predictive Cheminformatics Analysis of Diverse Chemogenomics Data Sources: Applications to Drug Discovery, Assay Interference, and Text Mining. - Ann Arbor : ProQuest Dissertations & Theses, 2018 - 138 p.

Source: Dissertations Abstracts International, Volume: 79-12, Section: B.

Thesis (Ph.D.)--The University of North Carolina at Chapel Hill, 2018.

This item must not be sold to any third party vendors.

In this dissertation, we describe the cheminformatics analysis of diverse chemogenomics data sources as well as the application of these data to several drug discovery efforts. In Chapter 1, we describe the discovery and characterization of novel Ebola virus inhibitors through QSAR-based virtual screening. In Chapter 2, we report the discovery and analysis of a series of potent and selective doublecortin-like kinase 1 (DCLK1) inhibitors using QSAR modeling, virtual screening, Matched Molecular Pair Analysis (MMPA), and molecular docking. In Chapter 3, we performed a large-scale analysis of publicly available data in PubChem to probe the reliability and applicability of Pan- Assay INterference compoundS (PAINS) alerts, a popular computational drug screening tool. In Chapter 4, we explore the PubMed database as a novel source of biomedical data and describe the development of Chemotext, a publicly available web server capable of text-mining the published literature.

ISBN: 9780438064652Subjects--Topical Terms:

3173021
Pharmaceutical sciences.

Predictive Cheminformatics Analysis of Diverse Chemogenomics Data Sources: Applications to Drug Discovery, Assay Interference, and Text Mining.
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245 1 0 $a Predictive Cheminformatics Analysis of Diverse Chemogenomics Data Sources: Applications to Drug Discovery, Assay Interference, and Text Mining.
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300 $a 138 p.
500 $a Source: Dissertations Abstracts International, Volume: 79-12, Section: B.
500 $a Publisher info.: Dissertation/Thesis.
500 $a Advisor: Tropsha, Alexander.
502 $a Thesis (Ph.D.)--The University of North Carolina at Chapel Hill, 2018.
506 $a This item must not be sold to any third party vendors.
520 $a In this dissertation, we describe the cheminformatics analysis of diverse chemogenomics data sources as well as the application of these data to several drug discovery efforts. In Chapter 1, we describe the discovery and characterization of novel Ebola virus inhibitors through QSAR-based virtual screening. In Chapter 2, we report the discovery and analysis of a series of potent and selective doublecortin-like kinase 1 (DCLK1) inhibitors using QSAR modeling, virtual screening, Matched Molecular Pair Analysis (MMPA), and molecular docking. In Chapter 3, we performed a large-scale analysis of publicly available data in PubChem to probe the reliability and applicability of Pan- Assay INterference compoundS (PAINS) alerts, a popular computational drug screening tool. In Chapter 4, we explore the PubMed database as a novel source of biomedical data and describe the development of Chemotext, a publicly available web server capable of text-mining the published literature.
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