scholarly article | Q13442814 |
P8978 | DBLP publication ID | journals/jcamd/Cramer12 |
P356 | DOI | 10.1007/S10822-011-9495-0 |
P2888 | exact match | https://scigraph.springernature.com/pub.10.1007/s10822-011-9495-0 |
P932 | PMC publication ID | 3268966 |
P698 | PubMed publication ID | 22127732 |
P5875 | ResearchGate publication ID | 51840494 |
P2093 | author name string | Richard D Cramer | |
P2860 | cites work | How to improve R&D productivity: the pharmaceutical industry's grand challenge | Q28314992 |
On Outliers and Activity Cliffs - Why QSAR Often Disappoints | Q28649303 | ||
Beware of q2! | Q28842863 | ||
A MATHEMATICAL CONTRIBUTION TO STRUCTURE-ACTIVITY STUDIES. | Q29387463 | ||
Topomer CoMFA: a design methodology for rapid lead optimization | Q31126609 | ||
Toluidinesulfonamide hypoxia-induced factor 1 inhibitors: alleviating drug-drug interactions through use of PubChem data and comparative molecular field analysis guided synthesis. | Q33901205 | ||
Integration of diverse data sources for prediction of adverse drug events | Q34052007 | ||
Pushing the boundaries of 3D-QSAR. | Q36718321 | ||
How not to develop a quantitative structure-activity or structure-property relationship (QSAR/QSPR). | Q37526685 | ||
How to recognize and workaround pitfalls in QSAR studies: a critical review | Q37597312 | ||
Modeling approaches for ligand-based 3D similarity. | Q37855896 | ||
Rethinking 3D-QSAR. | Q42661891 | ||
Capturing structure-activity relationships from chemogenomic spaces | Q43730069 | ||
Virtual screening for R-groups, including predicted pIC50 contributions, within large structural databases, using Topomer CoMFA. | Q45393672 | ||
Quantitative Series Enrichment Analysis (QSEA): a novel procedure for 3D-QSAR analysis. | Q51892184 | ||
Substructural analysis. Novel approach to the problem of drug design | Q52908354 | ||
On model building in structure-activity relationships. A reexamination of adrenergic blocking activity of beta-halo-beta-arylalkylamines. | Q52940373 | ||
The trouble with QSAR (or how I learned to stop worrying and embrace fallacy) | Q80416269 | ||
SAMFA: simplifying molecular description for 3D-QSAR | Q81336641 | ||
3D-QSAR illusions | Q81437679 | ||
Is QSAR relevant to drug discovery? | Q82811393 | ||
Why you should read Dr. Cramer's perspective | Q83380497 | ||
P433 | issue | 1 | |
P304 | page(s) | 35-38 | |
P577 | publication date | 2011-11-30 | |
P1433 | published in | Journal of Computer - Aided Molecular Design | Q15766522 |
P1476 | title | The inevitable QSAR renaissance | |
P478 | volume | 26 |
Q38867278 | A Round Trip from Medicinal Chemistry to Predictive Toxicology |
Q49226937 | A perspective on multi-target drug discovery and design for complex diseases. |
Q38206286 | Advances in quantitative structure-activity relationship models of anti-Alzheimer's agents. |
Q30352841 | Antiprotozoal Nitazoxanide Derivatives: Synthesis, Bioassays and QSAR Study Combined with Docking for Mechanistic Insight. |
Q38615086 | Aromatase inhibitory activity of 1,4-naphthoquinone derivatives and QSAR study. |
Q92899539 | BCL::Mol2D-a robust atom environment descriptor for QSAR modeling and lead optimization |
Q26745421 | Drug Design for CNS Diseases: Polypharmacological Profiling of Compounds Using Cheminformatic, 3D-QSAR and Virtual Screening Methodologies |
Q38465124 | In silico tools used for compound selection during target-based drug discovery and development |
Q51092695 | Insight into the structural requirements of pyrimidine-based phosphodiesterase 10A (PDE10A) inhibitors by multiple validated 3D QSAR approaches. |
Q93047984 | Meta-QSAR: a large-scale application of meta-learning to drug design and discovery |
Q38559373 | Mind the Gap! A Journey towards Computational Toxicology |
Q88878929 | Performance of Machine Learning Algorithms for Qualitative and Quantitative Prediction Drug Blockade of hERG1 channel |
Q93202753 | Prospects of multitarget drug designing strategies by linking molecular docking and molecular dynamics to explore the protein-ligand recognition process |
Q28222668 | QSAR modeling: where have you been? Where are you going to? |
Q38630598 | QSAR studies in the discovery of novel type-II diabetic therapies |
Q47549119 | Quantitative Structure-Activity Relationship Model for HCVNS5B inhibitors based on an Antlion Optimizer-Adaptive Neuro-Fuzzy Inference System |
Q89761451 | Targeting Tumors Using Peptides |
Q36848213 | Three-dimensional QSAR analysis and design of new 1,2,4-oxadiazole antibacterials |
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