Fangfang Xia

According to our database, Fangfang Xia authored at least 35 papers between 2007 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

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, Vincenzo Lomonaco, Gido M. van de Ven

Neural Networks, 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

Scaling Large Vision-Language Models for Enhanced Multimodal Comprehension in Biomedical Image Analysis.

Robinson Umeike, Neil Getty, Fangfang Xia, Rick Stevens

Proceedings of the 22nd IEEE International Symposium on Biomedical Imaging, 2025

2024

Binding Affinity Prediction: From Conventional to Machine Learning-Based Approaches.

Xuefeng Liu, Songhao Jiang, Xiaotian Duan, Archit Vasan, Chong Liu, Chih-chan Tien, Heng Ma, Thomas S. Brettin, Fangfang Xia, Ian T. Foster, Rick L. Stevens

CoRR, 2024

Contextual Active Model Selection.

Xuefeng Liu, Fangfang Xia, Rick Stevens, Yuxin Chen

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

2023

CholecTriplet2021: A benchmark challenge for surgical action triplet recognition.

Chinedu Innocent Nwoye, Deepak Alapatt, Tong Yu, Armine Vardazaryan, Fangfang Xia, Zixuan Zhao, Tong Xia, Fucang Jia, Yuxuan Yang, Hao Wang, Derong Yu, Guoyan Zheng, Xiaotian Duan, Neil Getty, Ricardo Sanchez-Matilla, Maria Robu, Li Zhang, Huabin Chen, Jiacheng Wang, Liansheng Wang, Bokai Zhang, Beerend G. A. Gerats, Sista Raviteja, Rachana Sathish, Rong Tao, Satoshi Kondo, Winnie Pang, Hongliang Ren, Julian Ronald Abbing, Mohammad Hasan Sarhan, Sebastian Bodenstedt, Nithya Bhasker, Bruno Oliveira, Helena R. Torres, Li Ling, Finn Gaida, Tobias Czempiel, João L. Vilaça, Pedro Morais, Jaime C. Fonseca, Ruby Mae Egging, Inge Nicole Wijma, Chen Qian, Guibin Bian, Zhen Li, Velmurugan Balasubramanian, Debdoot Sheet, Imanol Luengo, Yuanbo Zhu, Shuai Ding, Jakob-Anton Aschenbrenner, Nicolas Elini van der Kar, Mengya Xu, Mobarakol Islam, Lalithkumar Seenivasan, Alexander Jenke, Danail Stoyanov, Didier Mutter, Pietro Mascagni, Barbara Seeliger, Cristians Gonzalez, Nicolas Padoy

Medical Image Anal., May, 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, Donald M. Dempsey, Allan Dickerman, Emily M. Dietrich, Ronald W. Kenyon, Mehmet Kuscuoglu, Elliot J. Lefkowitz, Jian Lu, Dustin Machi, Catherine Macken, Chunhong Mao, Anna Maria Niewiadomska, Marcus Nguyen, Gary J. Olsen, Jamie C. Overbeek, Bruce D. Parrello, Victoria Parrello, Jacob s Porter, Gordon D. Pusch, Maulik Shukla, Indresh Singh, Lucy Stewart, Gene Tan, Chris Thomas, Margo VanOeffelen, Veronika Vonstein, Zachary S. Wallace, Andrew S. Warren, Alice R. Wattam, Fangfang Xia, Hyun Seung Yoo, Yun Zhang, Christian M. Zmasek, Richard H. Scheuermann, Rick L. Stevens

Nucleic Acids Res., January, 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, Rogerio Nespolo, Satoshi Kondo, Satoshi Kasai, Kousuke Hirasawa, Bo Liu, David Austin, Yiheng Wang, Michal Futrega, Jean-Francois Puget, Zhenqiang Li, Yoichi Sato, Ryo Fujii, Ryo Hachiuma, Mana Masuda, Hideo Saito, An Wang, Mengya Xu, Mobarakol Islam, Long Bai, Winnie Pang, Hongliang Ren, Chinedu Innocent Nwoye, Luca Sestini, Nicolas Padoy, Maximilian Nielsen, Samuel Schüttler, Thilo Sentker, Hümeyra Husseini, Ivo M. Baltruschat, Rüdiger Schmitz, René Werner, Aleksandr Matsun, Mugariya Farooq, Numan Saeed, Jose Renato Restom Viera, Mohammad Yaqub, Neil Getty, Fangfang Xia, Zixuan Zhao, Xiaotian Duan, Xing Yao, Ange Lou, Hao Yang, Jintong Han, Jack H. Noble, Jie Ying Wu, Tamer Abdulbaki Alshirbaji, Nour Aldeen Jalal, Herag Arabian, Ning Ding, Knut Moeller, Weiliang Chen, Quan He, Lena Maier-Hein, Danail Stoyanov, Stefanie Speidel, Anthony M. Jarc

CoRR, 2023

Deep Fair Partition for Hyperspectral Image Classification.

Miao Tony He, Fangfang Xia, Rick L. Stevens

Proceedings of the 13th Workshop on Hyperspectral Imaging and Signal Processing: Evolution in Remote Sensing, 2023

2022

Cost-Effective Online Contextual Model Selection.

Xuefeng Liu, Fangfang Xia, Rick L. Stevens, Yuxin Chen

CoRR, 2022

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, Jason Gans, Stewart He, Pinyi Lu, Sergei Maslov, Alexander Partin, Maulik Shukla, Eric A. Stahlberg, Justin M. Wozniak, Hyun Seung Yoo, George F. Zaki, Yitan Zhu, Rick Stevens

Briefings Bioinform., 2022

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, Nicola Scafuri, Sauro Succi, Dieter Kranzlmüller, Gerald Mathias, David Wifling, Yann Donon, Alberto Di Meglio, Sofia Vallecorsa, Heng Ma, Anda Trifan, Arvind Ramanathan, Tom Brettin, Alexander Partin, Fangfang Xia, Xiaotan Duan, Rick Stevens, Peter V. Coveney

CoRR, 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

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

Proceedings of the International Conference for High Performance Computing, 2021

Neko: a Library for Exploring Neuromorphic Learning Rules.

Zixuan Zhao, Nathan Wycoff, Neil Getty, Rick Stevens, Fangfang Xia

Proceedings of the ICONS 2021: International Conference on Neuromorphic Systems 2021, 2021

2020

The PATRIC Bioinformatics Resource Center: expanding data and analysis capabilities.

James J. Davis, 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, Andrew Guard, Ronald W. Kenyon, Dustin Machi, Chunhong Mao, Daniel E. Murphy-Olson, Marcus Nguyen, Eric K. Nordberg, Gary J. Olsen, Robert Olson, Jamie C. Overbeek, Ross A. Overbeek, Bruce D. Parrello, Gordon D. Pusch, Maulik Shukla, Chris Thomas, Margo VanOeffelen, Veronika Vonstein, Andrew S. Warren, Fangfang Xia, Dawen Xie, Hyun Seung Yoo, Rick Stevens

Nucleic Acids Res., 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

Recurrent and Spiking Modeling of Sparse Surgical Kinematics.

Neil Getty, Zixuan Zhou, Stephan Gruessner, Liaohai Chen, 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

Towards On-Chip Bayesian Neuromorphic Learning.

Nathan Wycoff, Prasanna Balaprakash, Fangfang Xia

CoRR, 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

Recurrent and Spiking Modeling of Sparse Surgical Kinematics.

Neil Getty, Zixuan Zhao, Stephan Gruessner, Liaohai Chen, Fangfang Xia

Proceedings of the International Conference on Neuromorphic Systems, 2020

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, Emily M. Dietrich, Terry Disz, Svetlana Gerdes, Ronald W. Kenyon, Dustin Machi, Chunhong Mao, Daniel E. Murphy-Olson, Eric K. Nordberg, Gary J. Olsen, Robert Olson, Ross A. Overbeek, Bruce D. Parrello, Gordon D. Pusch, John Santerre, Maulik Shukla, Rick L. Stevens, Margo VanOeffelen, Veronika Vonstein, Andrew S. Warren, Alice R. Wattam, Fangfang Xia, Hyun Seung Yoo

Briefings Bioinform., 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

Proceedings of the International Conference for High Performance Computing, 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

Proceedings of the 48th International Conference on Parallel Processing, 2019

Neuromorphic Acceleration for Approximate Bayesian Inference on Neural Networks via Permanent Dropout.

Nathan Wycoff, Prasanna Balaprakash, Fangfang Xia

Proceedings of the International Conference on Neuromorphic Systems, 2019

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

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, Matthew Baughman

BMC Bioinform., 2018

2017

Improvements to PATRIC, the all-bacterial Bioinformatics Database and Analysis Resource Center.

Alice R. Wattam, James J. Davis, Rida Assaf, Sébastien Boisvert, Thomas S. Brettin, Christopher Bun, Neal Conrad, Emily M. Dietrich, Terry Disz, Joseph L. Gabbard, Svetlana Gerdes, Christopher S. Henry, Ronald W. Kenyon, Dustin Machi, Chunhong Mao, Eric K. Nordberg, Gary J. Olsen, Daniel E. Murphy-Olson, Robert Olson, Ross A. Overbeek, Bruce D. Parrello, Gordon D. Pusch, Maulik Shukla, Veronika Vonstein, Andrew S. Warren, Fangfang Xia, Hyun Seung Yoo, Rick L. Stevens

Nucleic Acids Res., 2017

2016

Systems-Wide Prediction of Enzyme Promiscuity Reveals a New Underground Alternative Route for Pyridoxal 5'-Phosphate Production in <i>E</i>. <i>coli</i>.

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

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, Terry Disz, Robert A. Edwards, Svetlana Gerdes, Bruce D. Parrello, Maulik Shukla, Veronika Vonstein, Alice R. Wattam, Fangfang Xia, Rick Stevens

Nucleic Acids Res., 2014

Genome-scale bacterial transcriptional regulatory networks: reconstruction and integrated analysis with metabolic models.

José P. Faria, Ross A. Overbeek, Fangfang Xia, Miguel Rocha, Isabel Rocha, Christopher S. Henry

Briefings Bioinform., 2014

2013

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

2009

Inferring a Species Tree from Gene Trees in the Presence of HGT.

Fangfang Xia, Rick Stevens

Proceedings of the International Conference on Bioinformatics & Computational Biology, 2009

2007

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, William Mihalo, Gary J. Olsen, Robert Olson, Andrei Osterman, Daniel Paarmann, Tobias Paczian, Bruce D. Parrello, Gordon D. Pusch, Dmitry A. Rodionov, Xinghua Shi, Olga Vassieva, Veronika Vonstein, Olga Zagnitko, Fangfang Xia, Jenifer Zinner, Ross A. Overbeek, Rick Stevens

Nucleic Acids Res., 2007