Author

Oladimeji Macaulay

University of New Mexico

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Bioinformatics· 3 Genomics· 1

Signature Assays, Organisms & Methods

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Research Focus:differential expression· 2 Research Focus:drug response / drug discovery· 2 Research Focus:gene regulatory network inference· 2 Approach:transformer / foundation model· 2 Research Focus:benchmarking· 1 Assay:bulk RNA-seq· 1 Approach:contrastive learning· 1 Approach:deep learning· 1

Frequent Co-Authors

Avinash D SahuiD· 4 shared David ArredondoiD· 4 shared Kushal Virupakshappa· 4 shared Luis E. Tafoya· 4 shared Ala JararwehiD· 2 shared My Nguyen Bach· 2 shared Yanfu ZhangiD· 2 shared Debjani Patangia Hudgens· 1 shared

Activity by Year

2024-2026 · peak 3/yr

Co-Author Collaboration Network

10 top collaborators · 38 mutual co-author links

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4 shared papersBioinformatics

Avinash D SahuORCID

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Author profile →

4 papers

Recent·Most cited

MutQA: A Cross-Validated Q&A Dataset for Genetic Mutations

Robert McCourt, David Arredondo, Oladimeji Macaulay, Shrey Poshiya, Oluoma Edeh, Kushal Virupakshappa, My Nguyen Bach, Enrique Almeida Ruiz, Yue Hu, Luis E. Tafoya, Debjani Patangia Hudgens, Deepali L. Kundnani, Avinash D Sahu

The paper introduces MutQA, a cross-validated Q&A dataset linking genetic mutations to their functional consequences, and demonstrates its utility in improving LLM performance.

bioRxiv · Oct 29, 2026 · PreprintGenomics

DeepVul: A Multi-Task Transformer Model for Joint Prediction of Gene Essentiality and Drug Response

Ala Jararweh, My Nguyen Bach, David Arredondo, Oladimeji Macaulay, Mikaela Dicome, Luis E. Tafoya, Yue Hu, Kushal Virupakshappa, Genevieve Marie Boland, Keith T. Flaherty, Avinash D Sahu

DeepVul predicts gene essentiality and drug response using a multi-task transformer model trained on cancer transcriptome data, improving precision oncology by identifying treatment vulnerabilities.

bioRxiv · Oct 17, 2024 · PreprintBioinformatics

MedGraphNet: Leveraging Multi-Relational Graph Neural Networks and Text Knowledge for Biomedical Predictions

Oladimeji Macaulay, Michael Servilla, David Arredondo, Kushal Virupakshappa, Yue Hu, Luis E. Tafoya, Yanfu Zhang, Avinash D Sahu

MedGraphNet integrates multi-relational biological data with text knowledge to improve biomedical predictions, outperforming single-relation methods and identifying drug side effects without direct training.

bioRxiv · Sep 24, 2024 · PreprintBioinformatics

LitGene: a transformer-based model that uses contrastive learning to integrate textual information into gene representations

Ala Jararweh, Oladimeji Macaulay, David Arredondo, Olufunmilola Oyebamiji, Yue Hu, Luis E. Tafoya, Yanfu Zhang, Kushal Virupakshappa, Avinash D Sahu

LitGene integrates textual information into gene representations using a transformer-based model with contrastive learning, improving disease risk gene prediction and interpretability.

bioRxiv · Aug 7, 2024 · PreprintBioinformatics