Author
University at Buffalo, State University of New YorkORCID 0000-0001-9990-8331Unclaimed ORCID profile · follow to get notified of new preprints
7 papers
Recent·Most cited
Jie Zheng, Yu Lin, Anthony Huffman, Anna Maria Masci, Rebecca Racz, Guanming Wu, Kallan Roan, Edison Ong, Sirarat Sarntivijai, Jie Hu, Eliyas K. Asfaw, Hayleigh Kahn, Xingxian Li, Xumeng Zhang, Joshua Monickaraj, , Yongqun Oliver He
The paper introduces the Vaccine Ontology (VO), a standardized framework for representing vaccines and related data, enhancing data integration and AI research.
Scientific Data · Apr 30, 2026Peer-reviewedBioinformatics
Alexander Bartnik, Lucas M. Serra, Mackenzie Smith, William D. Duncan, Lauren Wishnie, Alan Ruttenberg, Michael G. Dwyer, Alexander D. Diehl
The paper introduces MRIO, an ontology for MRI data acquisition and analysis to standardize and improve reproducibility in neuroimaging research.
Neuroinformatics · May 19, 2024Peer-reviewedBioinformatics
Yongqun Oliver He, Laura M. C. Barisoni, Avi Z. Rosenberg, Peter N. Robinson, Alexander D. Diehl, Yichao Chen, Jimmy Phuong, Jens Hansen, Bruce W. Herr, Katy Börner, Nikki Bonevich, Ghida Arnous, Saketh Boddapati, Jie Zheng, Fadhl Alakwaa, , the Kidney Precision Medicine Project
The paper uses ontologies to integrate clinical, pathological, and molecular kidney data for precision medicine analysis.
bioRxiv · Apr 1, 2024 · PreprintBioinformatics
Theodore Groth, Alexander D. Diehl, Rudiyanto Gunawan, Sriram Neelamegham
GlycoEnzOnto curates 386 human glycoEnzymes across 135 pathways and 134 molecular functions to improve glycosylation pathway analysis.
Bioinformatics · Oct 25, 2022Peer-reviewedBioinformatics
Rebecca Jackson, Nicolas Matentzoglu, James A. Overton, Randi Vita, James P. Balhoff, Pier Luigi Buttigieg, Seth Carbon, Mélanie Courtot, Alexander D. Diehl, Damion Dooley, William D. Duncan, Nomi L. Harris, Melissa Anne Haendel, Suzanna Lewis, Darren A. Natale, , Bjoern Peters
The paper describes how the OBO Foundry formalized its principles into operational rules and implemented automated checks to evaluate ontology compliance, improving interoperability and quality.
Database · Oct 1, 2021Peer-reviewedBioinformatics
Mathys Grapotte, Manu Saraswat, Chloé Bessière, Christophe Menichelli, Jordan A. Ramilowski, Jessica Severin, Yoshihide Hayashizaki, Masayoshi Itoh, Michihira Tagami, Mitsuyoshi Murata, Miki Kojima-Ishiyama, Shohei Noma, Shuhei Noguchi, Takeya Kasukawa, Akira Hasegawa, , Lothar C. Dieterich
The paper identifies widespread transcription initiation at microsatellites across species and develops deep learning models to predict STR-associated transcription and its impact on disease variants.
Nature Communications · Jun 2, 2021Peer-reviewedGenomics
Brian D. Aevermann, Mark A. Novotny, Trygve E. Bakken, Jeremy A. Miller, Alexander D. Diehl, David Osumi-Sutherland, Roger S. Lasken, Ed S. Lein, Richard H. Scheuermann
The paper reviews how single cell RNA sequencing is identifying new human cell types and proposes a machine learning method to improve cell type definitions in the Cell Ontology.
Human Molecular Genetics · Mar 23, 2018Peer-reviewedBioinformatics