GO2Vec: transforming GO terms and proteins to vector representations via graph embeddings X Zhong, R Kaalia, JC Rajapakse BMC genomics 20, 1-10, 2019 | 29 | 2019 |
Network-based integration of multi-omics data for clinical outcome prediction in neuroblastoma C Wang, W Lue, R Kaalia, P Kumar, JC Rajapakse Scientific Reports 12 (1), 15425, 2022 | 12 | 2022 |
Multiple target-based pharmacophore design from active site structures P Kumar, R Kaalia, A Srinivasan, I Ghosh SAR and QSAR in Environmental Research 29 (1), 1-19, 2018 | 12 | 2018 |
ILP-assisted de novo drug design R Kaalia, A Srinivasan, A Kumar, I Ghosh Machine Learning 103, 309-341, 2016 | 10 | 2016 |
Deep learning and multi-omics approach to predict drug responses in cancer C Wang, X Lye, R Kaalia, P Kumar, JC Rajapakse BMC bioinformatics 22 (Suppl 10), 632, 2021 | 8 | 2021 |
An Ab Initio Method for Designing Multi‐Target Specific Pharmacophores using Complementary Interaction Field of Aspartic Proteases R Kaalia, A Kumar, A Srinivasan, I Ghosh Molecular Informatics 34 (6‐7), 380-393, 2015 | 8 | 2015 |
Semantics based approach for analyzing disease-target associations R Kaalia, I Ghosh Journal of Biomedical Informatics 62, 125-135, 2016 | 7 | 2016 |
Functional homogeneity and specificity of topological modules in human proteome R Kaalia, JC Rajapakse BMC bioinformatics 19, 125-138, 2019 | 4 | 2019 |
Refining modules to determine functionally significant clusters in molecular networks R Kaalia, JC Rajapakse BMC genomics 20, 1-14, 2019 | 3 | 2019 |