Author

Roberto Romero

United States Department of Health and Human Services

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Bioinformatics· 1

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Approach:benchmark study· 1 Research Focus:benchmarking· 1 Assay:bulk RNA-seq· 1 Research Focus:cell-cell communication· 1 Research Focus:differential expression· 1 Assay:DNA methylation· 1 Research Focus:gene regulatory network inference· 1 Approach:machine learning (classical)· 1

Frequent Co-Authors

Adi Laurentiu TarcaiD· 1 shared Atul Janardhan ButteiD· 1 shared Claire A. DubiniD· 1 shared Gaurav BhattiiD· 1 shared Gustavo A. StolovitzkyiD· 1 shared Marina SirotaiD· 1 shared Nikolaos KalavrosiD· 1 shared Reuben D. SarwaliD· 1 shared

Activity by Year

2026-2026 · peak 1/yr

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10 top collaborators · 45 mutual co-author links

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1 shared paperBioinformatics

Adi Laurentiu TarcaORCID

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1 paper

Recent·Most cited

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