Ramanujam J - Search Results

1

Augmented drug combination dataset to improve the performance of machine learning models predicting synergistic anticancer effects.

Liu M, Srivastava G, Ramanujam J, Brylinski M. Liu M, et al. Among authors: ramanujam j. Res Sq [Preprint]. 2023 Oct 28:rs.3.rs-3481858. doi: 10.21203/rs.3.rs-3481858/v1. Res Sq. 2023. Update in: Sci Rep. 2024 Jan 18;14(1):1668. doi: 10.1038/s41598-024-51940-9. PMID: 37961281 Free PMC article. Updated. Preprint.

2

GeauxDock: A novel approach for mixed-resolution ligand docking using a descriptor-based force field.

Ding Y, Fang Y, Feinstein WP, Ramanujam J, Koppelman DM, Moreno J, Brylinski M, Jarrell M. Ding Y, et al. Among authors: ramanujam j. J Comput Chem. 2015 Oct 15;36(27):2013-26. doi: 10.1002/jcc.24031. Epub 2015 Aug 6. J Comput Chem. 2015. PMID: 26250822

3

GeauxDock: Accelerating Structure-Based Virtual Screening with Heterogeneous Computing.

Fang Y, Ding Y, Feinstein WP, Koppelman DM, Moreno J, Jarrell M, Ramanujam J, Brylinski M. Fang Y, et al. Among authors: ramanujam j. PLoS One. 2016 Jul 15;11(7):e0158898. doi: 10.1371/journal.pone.0158898. eCollection 2016. PLoS One. 2016. PMID: 27420300 Free PMC article.

4

Assessing the similarity of ligand binding conformations with the Contact Mode Score.

Ding Y, Fang Y, Moreno J, Ramanujam J, Jarrell M, Brylinski M. Ding Y, et al. Among authors: ramanujam j. Comput Biol Chem. 2016 Oct;64:403-413. doi: 10.1016/j.compbiolchem.2016.08.007. Epub 2016 Sep 6. Comput Biol Chem. 2016. PMID: 27620381 Free PMC article.

5

BionoiNet: ligand-binding site classification with off-the-shelf deep neural network.

Shi W, Lemoine JM, Shawky AA, Singha M, Pu L, Yang S, Ramanujam J, Brylinski M. Shi W, et al. Among authors: ramanujam j. Bioinformatics. 2020 May 1;36(10):3077-3083. doi: 10.1093/bioinformatics/btaa094. Bioinformatics. 2020. PMID: 32053156 Free PMC article.

6

Bionoi: A Voronoi Diagram-Based Representation of Ligand-Binding Sites in Proteins for Machine Learning Applications.

Feinstein J, Shi W, Ramanujam J, Brylinski M. Feinstein J, et al. Among authors: ramanujam j. Methods Mol Biol. 2021;2266:299-312. doi: 10.1007/978-1-0716-1209-5_17. Methods Mol Biol. 2021. PMID: 33759134

7

GraphDTI: A robust deep learning predictor of drug-target interactions from multiple heterogeneous data.

Liu G, Singha M, Pu L, Neupane P, Feinstein J, Wu HC, Ramanujam J, Brylinski M. Liu G, et al. Among authors: ramanujam j. J Cheminform. 2021 Aug 11;13(1):58. doi: 10.1186/s13321-021-00540-0. J Cheminform. 2021. PMID: 34380569 Free PMC article.

8

Pocket2Drug: An Encoder-Decoder Deep Neural Network for the Target-Based Drug Design.

Shi W, Singha M, Srivastava G, Pu L, Ramanujam J, Brylinski M. Shi W, et al. Among authors: ramanujam j. Front Pharmacol. 2022 Mar 11;13:837715. doi: 10.3389/fphar.2022.837715. eCollection 2022. Front Pharmacol. 2022. PMID: 35359869 Free PMC article.

9

An integrated network representation of multiple cancer-specific data for graph-based machine learning.

Pu L, Singha M, Wu HC, Busch C, Ramanujam J, Brylinski M. Pu L, et al. Among authors: ramanujam j. NPJ Syst Biol Appl. 2022 Apr 29;8(1):14. doi: 10.1038/s41540-022-00226-9. NPJ Syst Biol Appl. 2022. PMID: 35487924 Free PMC article.

10

CancerOmicsNet: a multi-omics network-based approach to anti-cancer drug profiling.

Pu L, Singha M, Ramanujam J, Brylinski M. Pu L, et al. Among authors: ramanujam j. Oncotarget. 2022 May 19;13:695-706. doi: 10.18632/oncotarget.28234. eCollection 2022. Oncotarget. 2022. PMID: 35601606 Free PMC article.

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