| scholarly article | Q13442814 |
| P356 | DOI | 10.4155/FMC-2016-0163 |
| P698 | PubMed publication ID | 27627830 |
| P50 | author | Igor V. Tetko | Q30362344 |
| Ola Engkvist | Q43370883 | ||
| Hongming Chen | Q64167890 | ||
| P2860 | cites work | The development of models to predict melting and pyrolysis point data associated with several hundred thousand compounds mined from PATENTS | Q27902250 |
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| Computational Intelligence Modeling of the Macromolecules Release from PLGA Microspheres-Focus on Feature Selection | Q28550344 | ||
| BIGCHEM: Challenges and Opportunities for Big Data Analysis in Chemistry | Q28591396 | ||
| Identification of new potent GPR119 agonists by combining virtual screening and combinatorial chemistry | Q31108267 | ||
| Structure-based design and synthesis of (5-arylamino-2H-pyrazol-3-yl)-biphenyl-2',4'-diols as novel and potent human CHK1 inhibitors | Q33299912 | ||
| Searching Fragment Spaces with feature trees | Q33444088 | ||
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| PGVL Hub: An integrated desktop tool for medicinal chemists to streamline design and synthesis of chemical libraries and singleton compounds | Q33730364 | ||
| Making every SAR point count: the development of Chemistry Connect for the large-scale integration of structure and bioactivity data | Q34056842 | ||
| Automated recycling of chemistry for virtual screening and library design | Q34289511 | ||
| Enumeration of 166 billion organic small molecules in the chemical universe database GDB-17. | Q34307495 | ||
| In silico approaches to prediction of aqueous and DMSO solubility of drug-like compounds: trends, problems and solutions | Q34493552 | ||
| Can we estimate the accuracy of ADME-Tox predictions? | Q34548331 | ||
| Very large virtual compound spaces: construction, storage and utility in drug discovery | Q34992290 | ||
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| Deep Learning in Drug Discovery. | Q38918718 | ||
| How accurately can we predict the melting points of drug-like compounds? | Q39079351 | ||
| Prediction of drug solubility by the general solubility equation (GSE). | Q43558751 | ||
| Inductive transfer of knowledge: application of multi-task learning and feature net approaches to model tissue-air partition coefficients. | Q45964142 | ||
| Introducing conformal prediction in predictive modeling. A transparent and flexible alternative to applicability domain determination | Q51089989 | ||
| The Proximal Lilly Collection: Mapping, Exploring and Exploiting Feasible Chemical Space | Q51709586 | ||
| Calculation of lipophilicity for Pt(II) complexes: experimental comparison of several methods. | Q51892451 | ||
| DeepTox: Toxicity Prediction using Deep Learning | Q55920548 | ||
| Consensus Modeling for HTS Assays Using In silico Descriptors Calculates the Best Balanced Accuracy in Tox21 Challenge | Q57898145 | ||
| Molecular Descriptors Influencing Melting Point and Their Role in Classification of Solid Drugs | Q59188920 | ||
| P921 | main subject | big data | Q858810 |
| P577 | publication date | 2016-09-15 | |
| P1433 | published in | Future Medicinal Chemistry | Q19280078 |
| P1476 | title | Does 'Big Data' exist in medicinal chemistry, and if so, how can it be harnessed? |
| Q47780833 | Automating drug discovery |
| Q104412579 | From Big Data to Artificial Intelligence: chemoinformatics meets new challenges |
| Q114369129 | GenUI: interactive and extensible open source software platform for de novo molecular generation and cheminformatics |
| Q56973767 | Web Resources for Discovery and Development of New Medicines |
| Q47776738 | Welcome to Future Medicinal Chemistry volume 10. |
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