Author

Carlos Cuellar

Genentech

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· 2

Signature Assays, Organisms & Methods

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Assay:protein sequence· 2 Research Focus:benchmarking· 1 Approach:deep learning· 1 Approach:machine learning (classical)· 1 Research Focus:protein design· 1 Research Focus:protein structure prediction· 1 Approach:statistical model· 1 Research Focus:variant effect prediction· 1

Frequent Co-Authors

Ambrose J. WilliamsiD· 1 shared Amy WangiD· 1 shared Ananthan NambiariD· 1 shared Andrew J. MaieriD· 1 shared Josephine Neyyan· 1 shared Kelly O’Connor· 1 shared Minjeong Cha· 1 shared Neeraja Sundar Rajan· 1 shared

Activity by Year

2025-2025 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 36 mutual co-author links

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1 shared paperBioinformatics

Ambrose J. WilliamsORCID

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2 papers

Recent·Most cited

Protein Language Models Capture Structural and Functional Epistasis in a Zero-Shot Setting

Ananthan Nambiar, Sayantani B. Littlefield, Carlos Cuellar, Rohit Khorana, Sergei Maslov

This study shows that protein language models capture both structural and functional dependencies from sequence data alone through epistasis analysis.

bioRxiv · Sep 14, 2025 · PreprintBioinformatics

Predicting purification process fit of monoclonal antibodies using machine learning

Andrew J. Maier, Minjeong Cha, Sean Burgess, Amy Wang, Carlos Cuellar, Soo Young Kim, Neeraja Sundar Rajan, Josephine Neyyan, R. SENGUPTA, Kelly O’Connor, Nicole Ott, Ambrose J. Williams

This paper uses machine learning to predict monoclonal antibody purification process fit from amino acid sequences using QSPR models.

mAbs · Jan 9, 2025Peer-reviewedBioinformatics