The National Microbial Pathogen Database Resource (NMPDR): a genomics platform based on subsystem annotation. - Leslie Klis McNeil; Claudia Reich; Ramy K. Aziz; Daniela Bartels; Matthew Cohoon; Terry Disz; Robert A. Edwards; Svetlana Gerdes; Kaitlyn Hwang; Michael Kubal; Gohar Rem Margaryan; Folker Meyer; et al. (Nucleic Acids Res., 2007)

Inferring a Species Tree from Gene Trees in the Presence of HGT. - Fangfang Xia; Rick Stevens (BIOCOMP, 2009)

Human Analysts at Superhuman Scales: What Has Friendly Software To Do? - Élénie Godzaridis; Sébastien Boisvert; Fangfang Xia; Mikhail Kandel; Steve Behling; Bill Long; Carlos P. Sosa; François Laviolette; Jacques Corbeil (Big Data, 2013)

Genome-scale bacterial transcriptional regulatory networks: reconstruction and integrated analysis with metabolic models. - José P. Faria; Ross A. Overbeek; Fangfang Xia; Miguel Rocha 001; Isabel Rocha; Christopher S. Henry (Briefings Bioinform., 2014)

The SEED and the Rapid Annotation of microbial genomes using Subsystems Technology (RAST). - Ross A. Overbeek; Robert Olson; Gordon D. Pusch; Gary J. Olsen; James J. Davis 002; Terry Disz; Robert A. Edwards; Svetlana Gerdes; Bruce D. Parrello; Maulik Shukla; Veronika Vonstein; Alice R. Wattam; et al. (Nucleic Acids Res., 2014)

Systems-Wide Prediction of Enzyme Promiscuity Reveals a New Underground Alternative Route for Pyridoxal 5'-Phosphate Production in E. coli. - Matthew A. Oberhardt; Raphy Zarecki; Leah Reshef; Fangfang Xia; Miquel Duran-Frigola; Rachel Schreiber; Christopher S. Henry; Nir Ben-Tal; Daniel J. Dwyer; Uri Gophna; Eytan Ruppin (PLoS Comput. Biol., 2016)

Improvements to PATRIC, the all-bacterial Bioinformatics Database and Analysis Resource Center. - Alice R. Wattam; James J. Davis 002; Rida Assaf; Sébastien Boisvert; Thomas S. Brettin; Christopher Bun; Neal Conrad; Emily M. Dietrich; Terry Disz; Joseph L. Gabbard; Svetlana Gerdes; Christopher S. Henry; et al. (Nucleic Acids Res., 2017)

CANDLE/Supervisor: a workflow framework for machine learning applied to cancer research. - Justin M. Wozniak; Rajeev Jain; Prasanna Balaprakash; Jonathan Ozik; Nicholson T. Collier; John Bauer; Fangfang Xia; Thomas S. Brettin; Rick Stevens; Jamaludin Mohd-Yusof; Cristina Garcia-Cardona; Brian Van Essen; et al. (BMC Bioinform., 2018)

Predicting tumor cell line response to drug pairs with deep learning. - Fangfang Xia; Maulik Shukla; Thomas S. Brettin; Cristina Garcia-Cardona; Judith D. Cohn; Jonathan E. Allen; Sergei Maslov; Susan L. Holbeck; James H. Doroshow; Yvonne A. Evrard; Eric A. Stahlberg; Rick L. Stevens (BMC Bioinform., 2018)

Neuromorphic Acceleration for Approximate Bayesian Inference on Neural Networks via Permanent Dropout. - Nathan Wycoff; Prasanna Balaprakash; Fangfang Xia (ICONS, 2019)

Performance, Energy, and Scalability Analysis and Improvement of Parallel Cancer Deep Learning CANDLE Benchmarks. - Xingfu Wu; Valerie E. Taylor; Justin M. Wozniak; Rick Stevens; Thomas S. Brettin; Fangfang Xia (ICPP, 2019)

Scalable reinforcement-learning-based neural architecture search for cancer deep learning research. - Prasanna Balaprakash; Romain Egele; Misha Salim; Stefan M. Wild; Venkatram Vishwanath; Fangfang Xia; Tom Brettin; Rick Stevens (SC, 2019)

PATRIC as a unique resource for studying antimicrobial resistance. - Dionysios A. Antonopoulos; Rida Assaf; Ramy Karam Aziz; Thomas S. Brettin; Christopher Bun; Neal Conrad; James J. Davis 002; Emily M. Dietrich; Terry Disz; Svetlana Gerdes; Ronald W. Kenyon; Dustin Machi; et al. (Briefings Bioinform., 2019)

Recurrent and Spiking Modeling of Sparse Surgical Kinematics. - Neil Getty; Zixuan Zhao; Stephan Gruessner; Liaohai Chen; Fangfang Xia (ICONS, 2020)

A Systematic Approach to Featurization for Cancer Drug Sensitivity Predictions with Deep Learning. - Austin Clyde; Tom Brettin; Alexander Partin; Maulik Shaulik; Hyun Seung Yoo; Yvonne A. Evrard; Yitan Zhu; Fangfang Xia; Rick Stevens (CoRR, 2020)

Towards On-Chip Bayesian Neuromorphic Learning. - Nathan Wycoff; Prasanna Balaprakash; Fangfang Xia (CoRR, 2020)

Deep Medical Image Analysis with Representation Learning and Neuromorphic Computing. - Neil Getty; Thomas S. Brettin; Dong Jin; Rick Stevens; Fangfang Xia (CoRR, 2020)

Recurrent and Spiking Modeling of Sparse Surgical Kinematics. - Neil Getty; Zixuan Zhou; Stephan Gruessner; Liaohai Chen; Fangfang Xia (CoRR, 2020)

Ensemble Transfer Learning for the Prediction of Anti-Cancer Drug Response. - Yitan Zhu; Thomas S. Brettin; Yvonne A. Evrard; Alexander Partin; Fangfang Xia; Maulik Shukla; Hyun Seung Yoo; James H. Doroshow; Rick Stevens (CoRR, 2020)

The PATRIC Bioinformatics Resource Center: expanding data and analysis capabilities. - James J. Davis 002; Alice R. Wattam; Ramy K. Aziz; Thomas S. Brettin; Ralph Butler; Rory Butler; Philippe Chlenski; Neal Conrad; Allan Dickerman; Emily M. Dietrich; Joseph L. Gabbard; Svetlana Gerdes; et al. (Nucleic Acids Res., 2020)

Neko: a Library for Exploring Neuromorphic Learning Rules. - Zixuan Zhao; Nathan Wycoff; Neil Getty; Rick Stevens; Fangfang Xia (ICONS, 2021)

AgEBO-tabular: joint neural architecture and hyperparameter search with autotuned data-parallel training for tabular data. - Romain Égelé; Prasanna Balaprakash; Isabelle Guyon; Venkatram Vishwanath; Fangfang Xia; Rick Stevens; Zhengying Liu (SC, 2021)

Learning curves for drug response prediction in cancer cell lines. - Alexander Partin; Thomas S. Brettin; Yvonne A. Evrard; Yitan Zhu; Hyun Seung Yoo; Fangfang Xia; Songhao Jiang; Austin Clyde; Maulik Shukla; Michael Fonstein; James H. Doroshow; Rick L. Stevens (BMC Bioinform., 2021)

Pandemic Drugs at Pandemic Speed: Accelerating COVID-19 Drug Discovery with Hybrid Machine Learning- and Physics-based Simulations on High Performance Computers. - Agastya P. Bhati; Shunzhou Wan; Dario Alfè; Austin R. Clyde; Mathis Bode; Li Tan; Mikhail Titov; André Merzky; Matteo Turilli; Shantenu Jha; Roger R. Highfield; Walter Rocchia; et al. (CoRR, 2021)

A cross-study analysis of drug response prediction in cancer cell lines. - Fangfang Xia; Jonathan E. Allen; Prasanna Balaprakash; Thomas S. Brettin; Cristina Garcia-Cardona; Austin Clyde; Judith D. Cohn; James H. Doroshow; Xiaotian Duan; Veronika Dubinkina; Yvonne A. Evrard; Ya Ju Fan; et al. (Briefings Bioinform., 2022)

Cost-Effective Online Contextual Model Selection. - Xuefeng Liu; Fangfang Xia; Rick L. Stevens; Yuxin Chen 001 (CoRR, 2022)

Deep Fair Partition for Hyperspectral Image Classification. - Miao Tony He; Fangfang Xia; Rick L. Stevens (WHISPERS, 2023)

Surgical tool classification and localization: results and methods from the MICCAI 2022 SurgToolLoc challenge. - Aneeq Zia; Kiran Bhattacharyya; Xi Liu; Max Berniker; Ziheng Wang 003; Rogerio Nespolo; Satoshi Kondo; Satoshi Kasai; Kousuke Hirasawa; Bo Liu; David Austin; Yiheng Wang; et al. (CoRR, 2023)

Introducing the Bacterial and Viral Bioinformatics Resource Center (BV-BRC): a resource combining PATRIC, IRD and ViPR. - Robert D. Olson; Rida Assaf; Thomas S. Brettin; Neal Conrad; Clark Cucinell; James J. Davis 002; Donald M. Dempsey; Allan Dickerman; Emily M. Dietrich; Ronald W. Kenyon; Mehmet Kuscuoglu; Elliot J. Lefkowitz; et al. (Nucleic Acids Res., 2023)

CholecTriplet2021: A benchmark challenge for surgical action triplet recognition. - Chinedu Innocent Nwoye; Deepak Alapatt; Tong Yu 009; Armine Vardazaryan; Fangfang Xia; Zixuan Zhao; Tong Xia; Fucang Jia; Yuxuan Yang; Hao Wang 081; Derong Yu; Guoyan Zheng; et al. (Medical Image Anal., 2023)

Contextual Active Model Selection. - Xuefeng Liu; Fangfang Xia; Rick Stevens; Yuxin Chen 001 (NeurIPS, 2024)

Binding Affinity Prediction: From Conventional to Machine Learning-Based Approaches. - Xuefeng Liu; Songhao Jiang; Xiaotian Duan; Archit Vasan; Chong Liu 007; Chih-chan Tien; Heng Ma; Thomas S. Brettin; Fangfang Xia; Ian T. Foster; Rick L. Stevens (CoRR, 2024)

Scaling Large Vision-Language Models for Enhanced Multimodal Comprehension in Biomedical Image Analysis. - Robinson Umeike; Neil Getty; Fangfang Xia; Rick Stevens (ISBI, 2025)

Data imbalance in drug response prediction: multi-objective optimization approach in deep learning setting. - Oleksandr Narykov; Yitan Zhu; Thomas S. Brettin; Yvonne A. Evrard; Alexander Partin; Fangfang Xia; Maulik Shukla; Priyanka Vasanthakumari; James H. Doroshow; Rick L. Stevens (Briefings Bioinform., 2025)

Continual learning in the presence of repetition. - Hamed Hemati; Lorenzo Pellegrini; Xiaotian Duan; Zixuan Zhao; Fangfang Xia; Marc Masana; Benedikt Tscheschner; Eduardo E. Veas; Yuxiang Zheng; Shiji Zhao; Shao-Yuan Li; Sheng-Jun Huang; et al. (Neural Networks, 2025)