Author

Ilya Tyagin

University of DelawareORCID 0000-0002-0249-1072Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Research Focus:benchmarking· 3 Approach:statistical model· 2 Research Focus:database / resource· 1 Approach:deep learning· 1 Research Focus:drug response / drug discovery· 1 Approach:graph neural network· 1 Approach:large language model· 1 Research Focus:software / tool· 1

Frequent Co-Authors

Ilya SafroiD· 4 shared Michael S. ShtutmaniD· 3 shared Aliaksandra SikirzhytskayaiD· 2 shared Ankit KulshresthaiD· 1 shared Justin SybrandtiD· 1 shared Krish Matta· 1 shared Michael D. WyattiD· 1 shared S. Scott SuttoniD· 1 shared

Activity by Year

2021-2025 · peak 2/yr

Co-Author Collaboration Network

9 top collaborators · 22 mutual co-author links

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4 shared papersBioinformatics

Ilya SafroORCID

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Author profile →

4 papers

Recent·Most cited

Biomedical Hypothesis Explainability with Graph-Based Context Retrieval

Ilya Tyagin, Saeideh Valipour, Aliaksandra Sikirzhytskaya, Michael S. Shtutman, Ilya Safro

The paper introduces a method to explain biomedical hypotheses using graph-based context retrieval and LLMs, with feedback loops to refine explanations.

bioRxiv · Oct 17, 2025 · PreprintBioinformatics

AI-based mining of biomedical literature: Applications for drug repurposing for the treatment of dementia

Aliaksandra Sikirzhytskaya, Ilya Tyagin, S. Scott Sutton, Michael D. Wyatt, Ilya Safro, Michael S. Shtutman

This paper introduces AGATHA, an AI tool for drug repurposing in dementia by analyzing biomedical literature and identifying gene-disease associations using statistical methods.

Artificial Intelligence in Medicine · Oct 1, 2025Peer-reviewedBioinformatics

Interpretable Visualization of Scientific Hypotheses in Literature-based Discovery

Ilya Tyagin, Ilya Safro

The paper introduces an interpretable visualization approach for scientific hypotheses using semantic concept interconnectivity, network-based methods, and topic modeling, validated with a pipeline evaluated by experts.

bioRxiv · Oct 29, 2021 · PreprintBioinformatics

Accelerating COVID-19 research with graph mining and transformer-based learning

Ilya Tyagin, Ankit Kulshrestha, Justin Sybrandt, Krish Matta, Michael S. Shtutman, Ilya Safro

The paper introduces two hypothesis generation systems for COVID-19 research using graph mining and transformer models, achieving high-quality predictions and discovering new research findings.

bioRxiv · Feb 11, 2021 · PreprintBioinformatics