Author

Gaurav Bhatti

National Institutes of HealthORCID 0000-0002-8557-3347Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 2 Cancer Biology· 1 Systems Biology· 1

Signature Assays, Organisms & Methods

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Assay:bulk RNA-seq· 3 Research Focus:benchmarking· 2 Research Focus:differential expression· 2 Organism:human· 2 Approach:statistical model· 2 Approach:benchmark study· 1 Research Focus:cancer & tumor microenvironment· 1 Research Focus:cell-cell communication· 1

Frequent Co-Authors

Adi Laurentiu TarcaiD· 4 shared Gustavo A. StolovitzkyiD· 3 shared Marina SirotaiD· 2 shared Roberto J. RomeroiD· 2 shared Thomas Von YuiD· 2 shared Andrew M. FribleyiD· 1 shared Attila GáboriD· 1 shared Atul Janardhan ButteiD· 1 shared

Activity by Year

2020-2026 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 29 mutual co-author links

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4 shared papersBioinformatics

Adi Laurentiu TarcaORCID

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Author profile →

4 papers

Recent·Most cited

MNRR1 is required for Triple Negative Breast Cancer growth and metastasis and can be targeted by repurposed drugs.

Mrunal Sathe, Paige M. Minchella, Caleb Vegh, Mithra Modikuppam Dharmalingam, Vignesh Pasupathi, Yue Xi, Sagarika Rai, Mrunmayee Patil, Habiba Elshenawy, Sydney Rudolph, Gaurav Bhatti, Adi Laurentiu Tarca, Neeraja Purandare, Andrew M. Fribley, Lawrence I. Grossman, Siddhesh Aras

This study identifies MNRR1 as a critical driver of TNBC growth and metastasis, showing it can be targeted by existing drugs.

bioRxiv · Feb 3, 2026 · PreprintCancer Biology

Benchmarking Large Language Models for Predictive Modeling in Biomedical Research With a Focus on Reproductive Health

Reuben D. Sarwal, Victor Tarca, Claire A. Dubin, Nikolaos Kalavros, Gaurav Bhatti, Sanchita Bhattacharya, Atul Janardhan Butte, Roberto Romero, Gustavo A. Stolovitzky, Tomiko Oskotsky, Adi Laurentiu Tarca, Marina Sirota

This study evaluates large language models' ability to generate predictive modeling code for reproductive health using standardized datasets, finding R code generation more successful than Python and some models matching top DREAM challenge teams.

Cell Reports Medicine · Feb 1, 2026Peer-reviewedBioinformatics

Crowdsourcing assessment of maternal blood multi-omics for predicting gestational age and preterm birth

Adi Laurentiu Tarca, Bálint Pataki, Roberto J. Romero, Marina Sirota, Yuanfang Guan, Rintu Kutum, Nardhy Gomez‐Lopez, Bogdan Done, Gaurav Bhatti, Thomas Von Yu, Gaia Andreoletti, Tinnakorn Chaiworapongsa, Sonia S. Hassan, Chaur‐Dong Hsu, Nima Aghaeepour, , James C. Costello

The paper develops predictive models for preterm birth using maternal blood multi-omics data, finding transcriptomic and proteomic markers can predict gestational age and spontaneous preterm birth with high accuracy.

Cell Reports Medicine · Jun 1, 2021Peer-reviewedBioinformatics

Predicting cellular position in the Drosophila embryo from Single-Cell Transcriptomics data

Jovan Tanevski, Thin Nguyen, Buu Minh Thanh Truong, Nikos Karaiskos, Mehmet Eren Ahsen, Xinyu Zhang, Chang Shu, Ke Xu, Xiaoyu Liang, Ying Hu, Vu Pham, Xiaomei Li, Thuc Duy Le, Adi Laurentiu Tarca, Gaurav Bhatti, , Pablo Meyer

The paper predicts cellular positions in the Drosophila embryo using scRNA-seq data by benchmarking methods against spatially annotated genes.

Life Science Alliance · Sep 24, 2020Peer-reviewedSystems Biology