Quantitative prediction of antitarget interaction profiles for chemical compounds. - Wikidata - awgldk - TriplyDB

Quantitative prediction of antitarget interaction profiles for chemical compounds.

Quantitative prediction of antitarget interaction profiles for chemical compounds.

http://www.wikidata.org/entity/Q36501098

about

Design, synthesis and pharmacological evaluation of novel vanadium-containing complexes as antidiabetic agents QSAR modeling of imbalanced high-throughput screening data in PubChem.Predictive in silico off-target profiling in drug discovery.QSAR models of human data can enrich or replace LLNA testing for human skin sensitization.A new approach to radial basis function approximation and its application to QSAR.Chemo- and bioinformatics resources for in silico drug discovery from medicinal plants beyond their traditional use: a critical review.In Silico Identification of Proteins Associated with Drug-induced Liver Injury Based on the Prediction of Drug-target Interactions.Alarms about structural alerts.Drug-likeness of Phytic Acid and Its Analogues.Web Resources for Discovery and Development of New Medicines Virtual Screening for Potential Substances for the Prophylaxis of HIV Infection in Libraries of Commercially Available Organic Compounds Comparison of Quantitative and Qualitative (Q)SAR Models Created for the Prediction of K and IC Values of Antitarget Inhibitors

P2860

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P2860

Quantitative prediction of antitarget interaction profiles for chemical compounds.

http://www.wikidata.org/entity/Q36501098

description

2012 nî lūn-bûn

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2012年の論文

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2012年論文

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2012年論文

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2012年論文

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2012年論文

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2012年論文

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2012年论文

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2012年论文

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2012年论文

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name

Quantitative prediction of antitarget interaction profiles for chemical compounds.

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Quantitative prediction of antitarget interaction profiles for chemical compounds.

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type

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Quantitative prediction of antitarget interaction profiles for chemical compounds.

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Quantitative prediction of antitarget interaction profiles for chemical compounds.

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Quantitative prediction of antitarget interaction profiles for chemical compounds.

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Quantitative prediction of antitarget interaction profiles for chemical compounds.

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Chemical Research in Toxicology

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Quantitative prediction of antitarget interaction profiles for chemical compounds.

@en

P2093

Alexey V Zakharov

http://www.w3.org/2001/XMLSchema#string

P2860

Prediction of potential toxicity and side effect protein targets of a small molecule by a ligand-protein inverse docking approach

How many drug targets are there?

GPCR antitarget modeling: pharmacophore models for biogenic amine binding GPCRs to avoid GPCR-mediated side effects.

Tyrosine kinase inhibitors - small molecular weight compounds inhibiting EGFR.

Cell-mediated side effects of psychopharmacological treatment.

Prediction of biological activity spectra via the Internet.

Prediction of drug-related cardiac adverse effects in humans--A: creation of a database of effects and identification of factors affecting their occurrence.

Genetic predisposition to drug hepatotoxicity: role in hepatitis caused by amineptine, a tricyclic antidepressant.

QNA-based 'Star Track' QSAR approach.

GABA is toxic for mouse striatal neurones through a transporter-mediated process.

P304

2378-2385

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scholarly article

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10.1021/TX300247R

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11

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25

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Vladimir Poroikov

Dmitry Filimonov

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2012-11-02T00:00:00Z

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232318630

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23078046

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3534763

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