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Statistical classification / Bioinformatics / Clinical research / Medicinal chemistry / Support vector machine / G protein-coupled receptor / Protein structure / Drug discovery / Pharmaceutical sciences / Biology / Pharmacology


PROTEIN-CHEMICAL INTERACTION PREDICTION VIA KERNELIZED SPARSE LEARNING SVM YI SHI*1 , XINHUA ZHANG1 , XIAOPING LIAO2 , GUOHUI LIN1 , DALE SCHUURMANS1 1
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Document Date: 2012-09-28 23:25:07

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Edmonton / /

Company

AUC F-Measure Precision / /

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Event

Product Issues / Product Recall / /

Facility

University of Alberta / /

IndustryTerm

throughput technologies / interconnected networks / chemical space / chemical genomics research / software tools / documented protein-chemical interactions / potential energy / drug chemical structure / chemical compounds / chemical / interactome networks / throughput screening technology / protein-chemical interaction database / protein-chemical interactions / /

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Ion Channel / /

OperatingSystem

L3 / /

Organization

Department of Agricultural / Food and Nutritional Science / SS SVM / University of Alberta / Department of Computing Science / SVM SS / /

Person

Ion Channels / Gene Ontology / /

Product

Precision- / 0.1 0.4 0.3 0.2 0.2 0.4 0.6 0.8 1 / curve / previous methods / Tretinoin / Fig / AUPR AUC F-Measure Precision / Metoclopramide / /

ProvinceOrState

Alberta / /

TVStation

N-TV / /

Technology

chemical genomics / drug discovery / high-throughput screening technology / high-throughput technologies / /

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http /

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