| scholarly article | Q13442814 |
| P356 | DOI | 10.1042/BST0391365 |
| P8608 | Fatcat ID | release_p5ncpma52bhtjidyxyychce2ri |
| P698 | PubMed publication ID | 21936816 |
| P50 | author | Anna Gaulton | Q28946674 |
| John P. Overington | Q30104439 | ||
| Anne Hersey | Q33035164 | ||
| Benjamin Stauch | Q41666552 | ||
| Mark Davies | Q43370916 | ||
| Louisa Bellis | Q43370917 | ||
| Bissan Al-Lazikani | Q47474762 | ||
| Rita Santos | Q57023868 | ||
| Felix A Kruger | Q57024925 | ||
| Ruth Akhtar | Q57025086 | ||
| Francis Atkinson | Q60651741 | ||
| Patrícia Bento | Q106130863 | ||
| P2093 | author name string | Kazuyoshi Ikeda | |
| Jon Chambers | |||
| Shaun McGlinchey | |||
| Yvonne Light | |||
| P2860 | cites work | Thousands of chemical starting points for antimalarial lead identification | Q24289329 |
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| ZINC--a free database of commercially available compounds for virtual screening | Q27656255 | ||
| Structure of the Human Dopamine D3 Receptor in Complex with a D2/D3 Selective Antagonist | Q27666030 | ||
| Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings | Q27861111 | ||
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| An overview of the PubChem BioAssay resource | Q28749237 | ||
| IUPHAR-DB: new receptors and tools for easy searching and visualization of pharmacological data | Q29043128 | ||
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| The case for open-source software in drug discovery | Q36039834 | ||
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| In silico activity profiling reveals the mechanism of action of antimalarials discovered in a high-throughput screen | Q36736936 | ||
| Probing the links between in vitro potency, ADMET and physicochemical parameters. | Q37848051 | ||
| Role of Open Chemical Data in Aiding Drug Discovery and Design | Q42594717 | ||
| Ligand efficiency indices for an effective mapping of chemico-biological space: the concept of an atlas-like representation. | Q42930682 | ||
| Navigating the kinome | Q43525185 | ||
| The influence of drug-like concepts on decision-making in medicinal chemistry | Q46922861 | ||
| P433 | issue | 5 | |
| P921 | main subject | data mining | Q172491 |
| drug discovery | Q1418791 | ||
| P304 | page(s) | 1365-1370 | |
| P577 | publication date | 2011-10-01 | |
| P1433 | published in | Biochemical Society Transactions | Q864226 |
| P1476 | title | Collation and data-mining of literature bioactivity data for drug discovery | |
| P478 | volume | 39 |
| Q28480436 | A Two-Step Target Binding and Selectivity Support Vector Machines Approach for Virtual Screening of Dopamine Receptor Subtype-Selective Ligands |
| Q35114229 | A chemo-centric view of human health and disease |
| Q30423071 | Compound activity prediction using models of binding pockets or ligand properties in 3D. |
| Q41002933 | Detecting similar binding pockets to enable systems polypharmacology |
| Q47893147 | Evidence-Based Precision Oncology with the Cancer Targetome. |
| Q38424487 | Fast and accurate semantic annotation of bioassays exploiting a hybrid of machine learning and user confirmation |
| Q36320975 | Identification of potential inhibitors based on compound proposal contest: Tyrosine-protein kinase Yes as a target |
| Q39540056 | Large-Scale QSAR in Target Prediction and Phenotypic HTS Assessment |
| Q41831465 | Ligand biological activity predictions using fingerprint-based artificial neural networks (FANN-QSAR). |
| Q42111979 | Molecular Fingerprint-Based Artificial Neural Networks QSAR for Ligand Biological Activity Predictions |
| Q33741666 | The genome and developmental transcriptome of the strongylid nematode Haemonchus contortus |
| Q37986776 | The impact of network biology in pharmacology and toxicology |
| Q28133319 | Towards a Universal SMILES representation - A standard method to generate canonical SMILES based on the InChI |
| Q33827037 | VAV3 mediates resistance to breast cancer endocrine therapy. |
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