Author

Ilkwon Cho

Carnegie Mellon UniversityORCID 0000-0002-7279-7384Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

Click to filter author papers

Signature Assays, Organisms & Methods

Click to filter · or open tag

Approach:deep learning· 1 Research Focus:drug response / drug discovery· 1 Approach:statistical model· 1

Frequent Co-Authors

Haocheng TangiD· 1 shared Junmei WangiD· 1 shared Kangdelong HuiD· 1 shared Olexandr IsayeviD· 1 shared Runtian GaoiD· 1 shared Shuhao Zhang· 1 shared Taoyu NiuiD· 1 shared Xiang QiuiD· 1 shared

Activity by Year

2026-2026 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 45 mutual co-author links

Click any collaborator node to inspect or filter shared papers

Focal author (center)Selected co-authorORCID co-authorUnlinked name

Curved chords = mutual co-authorship

1 shared paperBiophysics

Haocheng TangORCID

Mutual co-authors in cluster

Author profile →

1 paper

Recent·Most cited

BiophysicsbioRxivPreprintSep 17, 2026

High-throughput physics-based enzyme engineering

Xujian Wang, Xiang Qiu, Yuyang Wu…·Junmei Wang

This paper introduces a physics-based framework for enzyme engineering that combines machine learning and molecular mechanics to predict catalytic rates and selectivity with high accuracy.

DOI 10.64898/2026.09.15.751901

deep learningstatistical model