about
ChemProt: a disease chemical biology databaseDrug Design for CNS Diseases: Polypharmacological Profiling of Compounds Using Cheminformatic, 3D-QSAR and Virtual Screening MethodologiesStructure and dynamics of molecular networks: a novel paradigm of drug discovery: a comprehensive reviewChem2Bio2RDF: a semantic framework for linking and data mining chemogenomic and systems chemical biology dataIncorporating Commercial and Private Data into an Open Linked Data Platform for Drug DiscoveryCheminformatics analysis of the AR agonist and antagonist datasets in PubChemPubChem as a public resource for drug discoveryDrug repositioning by kernel-based integration of molecular structure, molecular activity, and phenotype dataDrug Repositioning for Cancer Therapy Based on Large-Scale Drug-Induced Transcriptional SignaturesIdentifying plausible adverse drug reactions using knowledge extracted from the literaturePathway analysis for drug repositioning based on public database miningInvestigating the correlations among the chemical structures, bioactivity profiles and molecular targets of small moleculesDrug-induced adverse events prediction with the LINCS L1000 dataFragmentStore--a comprehensive database of fragments linking metabolites, toxic molecules and drugs.Towards building a disease-phenotype knowledge base: extracting disease-manifestation relationship from literature.Predicting drug side-effect profiles: a chemical fragment-based approachExploiting PubChem for Virtual Screening.Unveiling new biological relationships using shared hits of chemical screening assay pairsFrom laptop to benchtop to bedside: structure-based drug design on protein targets.An Ensemble Approach for Drug Side Effect Prediction.Discovering patterns in drug-protein interactions based on their fingerprints.PubChem applications in drug discovery: a bibliometric analysisTarget identification and mechanism of action in chemical biology and drug discovery.Large-scale extraction of accurate drug-disease treatment pairs from biomedical literature for drug repurposingPredicting target-ligand interactions using protein ligand-binding site and ligand substructures.Scalable prediction of compound-protein interactions using minwise hashingInferring protein domains associated with drug side effects based on drug-target interaction networkExploiting drug-disease relationships for computational drug repositioning.Classification of scaffold-hopping approachesGetting the most out of PubChem for virtual screeningMissing Value Estimation for Compound-Target Activity Data.Analysis of molecular networks and targets mining of Chinese herbal medicines on anti-aging.Drug repositioning for personalized medicine.Traditional chinese medicine-based network pharmacology could lead to new multicompound drug discoveryDetermining molecular predictors of adverse drug reactions with causality analysis based on structure learning.The impact of network biology in pharmacology and toxicology.Enzyme informatics.Drug-target interaction prediction via chemogenomic space: learning-based methods.Metabolome-scale de novo pathway reconstruction using regioisomer-sensitive graph alignments.Weak-binding molecules are not drugs?-toward a systematic strategy for finding effective weak-binding drugs.
P2860
Q24608769-02BD1947-0257-4D3B-978D-8A28C00F9D17Q26745421-6DAD673D-152A-46DC-8AD9-FC5ED41F9DE5Q27008867-AD7C7BA7-EF26-4C8B-8EA8-DAC031616BE9Q27136634-227ECF66-E223-43D6-A6F2-B6813BF60098Q27701454-4c0c421a-4995-e29d-6c3b-b07d02e00e87Q27902254-795F9E46-DD75-43F4-ADA3-D3726BD630C7Q28111749-93532818-D1EF-4A0C-B2CF-8AD68192C6BEQ28534990-5A9C5B7F-8395-47DE-8553-D5C15570F73DQ28550603-3EA7D821-CCD7-4B11-94A7-F7A70A5B32F0Q28650098-126C6918-2260-4F4F-BE65-A073FA26F5FBQ28657698-D341CF28-4BDC-4F7D-B4F2-DA2385BCB579Q28748625-11888DAA-7EB1-492C-908B-5783325E1CBBQ31092242-6899F83E-6E06-4DBE-A2C3-149F1E37096FQ33725092-FC585A39-5053-432F-A19B-6028261E5B23Q33796471-F098A289-651E-4E82-ABBB-2DF8B88B399BQ33903536-BAB592BB-614D-4E89-8EC4-2BA722C2290EQ33938092-168AC1A3-C007-4160-9665-4FB6322714E4Q34103220-29B835A0-B577-45DD-A7C5-1512212BBBADQ34153589-A6D024DA-B90B-4BC5-AAF4-122D73C3C049Q34342188-D0F0C0E2-593B-4471-992A-5082CFAA71C2Q34383248-CF4D4CB8-0FC7-43A0-A717-41F677EE6A7BQ34615684-F3B9E6A3-0E39-41CE-BC5D-9BBA31EE2C1EQ34626974-3FD88237-DF55-4B6D-A615-F17DEDD5D5D2Q34761719-7582E155-B3C5-4788-AD08-A310BCB8FCADQ35092840-E69836EF-8D28-4F84-B45B-1AEA0CC3FFCAQ35101862-08AA40E8-F21E-401A-BEF7-316E8D966D37Q35102262-9F381046-8A44-4D2B-947A-8A8080314A37Q35109885-EF23FFDE-263E-42B2-8A34-1013F18050DEQ35893996-976B6DC1-13DA-4B6A-83BB-DBD4117DD961Q36084475-6EFCB705-80D1-4577-8E0B-A19C5C620A2AQ36087357-062AC830-AC7D-4ED6-A1A4-87BD03A35635Q36235005-82C9BD2A-6F50-4EAD-B27A-DB476C83274CQ36245193-6F06DAD8-AF63-4F16-8610-AD42B06949FEQ36522926-73EABB3D-AD4A-4536-8953-05E6972E40ACQ37598956-F1838F23-E270-4F2C-AB72-9E4A27FA66AFQ37986776-68A3C709-D4F7-4E5A-BC7D-23B125662408Q38057006-61814743-E430-481C-87B1-284A0C296F27Q38238930-F5292849-54A5-4AD5-9899-D3D60F912B4DQ38461960-D39E0412-1A08-4962-9C15-FB6170BDE0FBQ38897226-F63CECDB-15E4-43EB-B057-13531B0EC82A
P2860
description
2009 nî lūn-bûn
@nan
2009 թուականի Սեպտեմբերին հրատարակուած գիտական յօդուած
@hyw
2009 թվականի սեպտեմբերին հրատարակված գիտական հոդված
@hy
2009年の論文
@ja
2009年論文
@yue
2009年論文
@zh-hant
2009年論文
@zh-hk
2009年論文
@zh-mo
2009年論文
@zh-tw
2009年论文
@wuu
name
PubChem as a Source of Polypharmacology
@ast
PubChem as a Source of Polypharmacology
@en
PubChem as a Source of Polypharmacology
@nl
type
label
PubChem as a Source of Polypharmacology
@ast
PubChem as a Source of Polypharmacology
@en
PubChem as a Source of Polypharmacology
@nl
prefLabel
PubChem as a Source of Polypharmacology
@ast
PubChem as a Source of Polypharmacology
@en
PubChem as a Source of Polypharmacology
@nl
P3181
P356
P1476
PubChem as a Source of Polypharmacology
@en
P2093
P304
P3181
P356
10.1021/CI9001876
P577
2009-09-28T00:00:00Z