Author

Kuohao Lee

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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Research Focus:benchmarking· 2 Approach:experimental assay· 1 Approach:machine learning (classical)· 1 Assay:proteomics· 1 Research Focus:software / tool· 1 Approach:statistical model· 1

Frequent Co-Authors

Anton V. SinitskiyiD· 2 shared Alok Dinesh Sharma· 1 shared Amitesh BadkuliD· 1 shared Amos Jaimes· 1 shared Arjun Shrivatsan· 1 shared Arpita Kachhwah· 1 shared Casual Dineshbhai Kalotra· 1 shared Gouri S. A. Thota· 1 shared

Activity by Year

2026-2026 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 37 mutual co-author links

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2 shared papersBioinformatics

Anton V. SinitskiyORCID

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2 papers

Recent·Most cited

BioinformaticsbioRxivPreprintSep 7, 2026

Real Science Is Harder Than Benchmarks: Evaluating Advanced AI Frameworks on Published Studies. II. Antibody Properties, Lipid-RNA Interactions

Priyanka Bhutada, Nitin Goyal, Tatsam K. Lakhankiya…·Anton V. Sinitskiy

This paper evaluates five AI frameworks on predicting antibody properties and modeling lipid-RNA interactions, finding they show strengths but fail to match the scope of original studies.

DOI 10.64898/2026.09.03.749176

proteomicsstatistical model

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BioinformaticsbioRxivPreprintJun 27, 2026

Real Science Is Harder Than Benchmarks: Evaluating Advanced AI Frameworks on Published Studies. I. Uncertainty Quantification, ML on Therapeutic Data Commons, and Agent-Based Modeling

Mohammed O. Ahmed, Sahil Anil Amale, Rhythm Dipak Bhavsar…·Anton V. Sinitskiy

This paper evaluates five AI frameworks on real scientific tasks, finding they excel in hypothesis generation and reporting but struggle with depth and reliability in real-world research.

1 citation

machine learning (classical)experimental assay

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