Medina-Franco, 2021
ViewHTML| Publication | Publication Date | Title | 
|---|---|---|
| Medina-Franco | Grand challenges of computer-aided drug design: the road ahead | |
| Bonner et al. | A review of biomedical datasets relating to drug discovery: a knowledge graph perspective | |
| Schaduangrat et al. | Towards reproducible computational drug discovery | |
| Napolitano et al. | gene2drug: a computational tool for pathway-based rational drug repositioning | |
| Capuzzi et al. | Chembench: a publicly accessible, integrated cheminformatics portal | |
| Culhane et al. | MADE4: an R package for multivariate analysis of gene expression data | |
| Shan et al. | Prediction of CYP450 enzyme–substrate selectivity based on the network-based label space division method | |
| Ye et al. | Improving docking-based virtual screening ability by integrating multiple energy auxiliary terms from molecular docking scoring | |
| Attwood et al. | Utopia documents: linking scholarly literature with research data | |
| Jinsong et al. | Molecular fragmentation as a crucial step in the AI-based drug development pathway | |
| Perovic et al. | IDPpi: Protein-protein interaction analyses of human intrinsically disordered proteins | |
| Saifi et al. | Artificial intelligence and cheminformatics tools: a contribution to the drug development and chemical science | |
| Ji et al. | Comprehensive assessment of nine target prediction web services: which should we choose for target fishing? | |
| US20030176978A1 (en) | System and method for simulating cellular biochemical pathways | |
| Tuvi‐Arad et al. | Technology in the service of pedagogy: Teaching with chemistry databases | |
| Senapathi et al. | Biomolecular reaction and interaction dynamics global environment (BRIDGE) | |
| Radusky et al. | pyFoldX: enabling biomolecular analysis and engineering along structural ensembles | |
| Ikeda et al. | DLiP-PPI library: An integrated chemical database of small-to-medium-sized molecules targeting protein–protein interactions | |
| Ferreira et al. | AI-Driven Drug Discovery: A Comprehensive Review | |
| Jamrozik et al. | ADMET-PrInt: evaluation of ADMET properties: prediction and interpretation | |
| Pradhan et al. | The future of ChatGPT in medicinal chemistry: harnessing AI for accelerated drug discovery | |
| Rudrapal | Computational Methods for Rational Drug Design | |
| Saldivar-González et al. | A spanish chemoinformatics GitBook for chemical data retrieval and analysis using Python programming | |
| Azevedo et al. | In silico drug repurposing by combining machine learning classification model and molecular dynamics to identify a potential OGT inhibitor | |
| Tripathi et al. | Computational resources and chemoinformatics for translational health research |