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Journal of Hazardous Materials|April 9, 2024
Integrating transformer-based machine learning with SERS technology for the analysis of hazardous pesticides in spinachMehdi Hajikhani, Akashata Hegde, John Snyder, et al.
Arxiv|June 9, 2022
Deep Learning Prediction of Severe Health Risks for Pediatric COVID-19 Patients with a Large Feature Set in 2021 BARDA Data ChallengeSajid Mahmud, Elham Soltanikazemi, Frimpong Boadu, et al.
Trends in Plant Science|September 21, 2010
Root hair systems biologyMarc Libault, Laurent Brechenmacher, Jianlin Cheng, et al.
BMC Bioinformatics|May 2, 2012
The MULTICOM toolbox for protein structure predictionJianlin Cheng, Jilong Li, Zheng Wang, et al.
BMC Bioinformatics|September 20, 2017
Deep learning methods for protein torsion angle predictionHaiou Li, Jie Hou, Badri Adhikari, et al.
Nature Machine Intelligence|February 2, 2026
Assessing the potential of deep learning for protein-ligand dockingAlex Morehead, Nabin Giri, Jian Liu, et al.
Bioinformatics (Oxford, England)|February 13, 2019
PairedFB: a full hierarchical Bayesian model for paired RNA-seq data with heterogeneous treatment effectsYuanyuan Bian, Chong He, Jie Hou, et al.
Bioinformatics (Oxford, England)|June 15, 2015
Large-scale model quality assessment for improving protein tertiary structure predictionRenzhi Cao, Debswapna Bhattacharya, Badri Adhikari, et al.
Biorxiv : the Preprint Server for Biology|September 26, 2025
CryoFSL: An Annotation-Efficient, Few-Shot Learning Framework for Robust Protein Particle Picking in Cryo-EM MicrographsBiplab Poudel, Rajan Gyawali, Ashwin Dhakal, et al.
Arxiv|July 17, 2025
Unavailability of experimental 3D structural data on protein folding dynamics and necessity for a new generation of structure prediction methods in this contextAydin Wells, Khalique Newaz, Jennifer Morones, et al.
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