🏆 Finalist — NIH Data Sharing Index (“S-Index”) Challenge

Jie Huang

Luoyang Institute of Science and Technology

ORCID: 0000-0002-5832-1769

EngineeringPhysics and AstronomyMaterials Science

Pilot corpus only

This score is computed over theSindex pilot corpus and does not cover the full scientific literature. Scores are relative to papers we have ingested — papers, authors, and institutions outside the pilot are not represented. Methodology.

Top 100%percentile

0Author DataRank

Indexed papers

0in pilot corpus

datarank_citation_only_1hop_v6· scope data_onlyMethodology

Papers

Driven by 3 papers. Top paper: “Co-optimization of therapeutic antibody affinity and specificity using machine learning models that generalize to novel mutational space”.

Co-optimization of therapeutic antibody affinity and specificity using machine learning models that generalize to novel mutational space

Nature Communications(2022)10.1038/s41467-022-31457-3

N/A

4.2DataRank · unranked

160 citations

Patrick C. Kinnunen, Jie Huang, Lina Wu, Matthew D. Smith, Tiexin Wang +8 more

Optimization of therapeutic antibodies for reduced self-association and non-specific binding via interpretable machine learning

Nature Biomedical Engineering(2023)10.1038/s41551-023-01074-6

N/A

0DataRank · unranked

48 citations

Tiexin Wang, Jennifer M. Zupancic, Jie Huang, Lina Wu, John S. Schardt +5 more

Reduction of monoclonal antibody viscosity using interpretable machine learning

mAbs(2024)10.1080/19420862.2024.2303781

N/A

0DataRank · unranked

34 citations

Hsin-Ting Chen, Tiexin Wang, Lina Wu, Jie Huang, Marissa Mock +6 more