Author

Ashwin Srinivasan

Birla Institute of Technology and Science, Pilani - Goa CampusORCID 0000-0002-4911-0038Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 2 Molecular Biology· 1

Signature Assays, Organisms & Methods

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Research Focus:drug response / drug discovery· 3 Approach:deep learning· 2 Research Focus:benchmarking· 1 Approach:large language model· 1 Approach:machine learning (classical)· 1

Frequent Co-Authors

Tirtharaj DashiD· 3 shared Arijit RoyiD· 2 shared Lovekesh VigiD· 2 shared A. BaskariD· 1 shared Mainak BanerjeeiD· 1 shared Raviprasad AduriiD· 1 shared Sanjay Kumar DeyiD· 1 shared Shreyas Bhat BrahmavariD· 1 shared

Activity by Year

2022-2026 · peak 1/yr

Co-Author Collaboration Network

9 top collaborators · 21 mutual co-author links

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3 shared papersBioinformatics

Tirtharaj DashORCID

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3 papers

Recent·Most cited

BioinformaticsMachine LearningPeer-reviewedSep 1, 2026

Identifying a logical specification and a program for an LLM-based generator of lead molecules

Ashwin Srinivasan, Tirtharaj Dash, A. Baskar…·Mainak Banerjee

The paper develops an LLM-based method for generating feasible lead molecules for DBH inhibitors, achieving comparable affinity to clinical trial drugs.

1 citation

machine learning (classical)drug response / drug discovery

𝕏 PostBluesky

BioinformaticsProceedings of the AAAI Conference on Artificial IntelligencePeer-reviewedMar 24, 2024

Generating Novel Leads for Drug Discovery using LLMs with Logical Feedback

Shreyas Bhat Brahmavar, Ashwin Srinivasan, Tirtharaj Dash…·Raviprasad Aduri

This paper introduces LMLF, a method using logical feedback to guide LLMs in generating drug leads for specific targets, showing improved binding affinities and potential novelty.

17 citationstop 1%

deep learninglarge language model

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Molecular BiologyLecture notes in computer sciencePeer-reviewedJan 1, 2022

Using Domain-Knowledge to Assist Lead Discovery in Early-Stage Drug Design

Tirtharaj Dash, Ashwin Srinivasan, Lovekesh Vig, Arijit Roy

The paper combines deep neural networks and Inductive Logic Programming to generate potential inhibitors for targets with limited data, using domain knowledge to improve molecule generation.

8 citations

deep learningdrug response / drug discovery

𝕏 PostBluesky