Separation of Ion Types in Tandem Mass Spectrometry Data Interpretation - A Graph-Theoretic Approach. - Bo Yan; Chongle Pan; Victor Olman; Robert L. Hettich; Ying Xu 001 (CSB, 2004)

A graph-theoretic approach for the separation of b and y ions in tandem mass spectra. - Bo Yan; Chongle Pan; Victor Olman; Robert L. Hettich; Ying Xu 001 (Bioinform., 2005)

Scientific Data Analysis. - Chandrika Kamath 001; Nikil Wale; George Karypis; Gaurav Pandey 002; Vipin Kumar 001; Krishna Rajan; Nagiza F. Samatova; Paul Breimyer; Guruprasad Kora; Chongle Pan; Srikanth B. Yoginath (Scientific Data Management, 2009)

A high-throughput de novo sequencing approach for shotgun proteomics using high-resolution tandem mass spectrometry. - Chongle Pan; Byung-Hoon Park; William H. McDonald; Patricia A. Carey; Jillian F. Banfield; Nathan Verberkmoes; Robert L. Hettich; Nagiza F. Samatova (BMC Bioinform., 2010)

Exhaustive database searching for amino acid mutations in proteomes. - Doug Hyatt; Chongle Pan (Bioinform., 2012)

Sipros/ProRata: a versatile informatics system for quantitative community proteomics. - Yingfeng Wang; Tae-Hyuk Ahn; Zhou Li; Chongle Pan (Bioinform., 2013)

Omega: an Overlap-graph de novo Assembler for Metagenomics. - Bahlul Haider; Tae-Hyuk Ahn; Brian Bushnell; Juanjuan Chai; Alex Copeland; Chongle Pan (Bioinform., 2014)

Sigma: Strain-level inference of genomes from metagenomic analysis for biosurveillance. - Tae-Hyuk Ahn; Juanjuan Chai; Chongle Pan (Bioinform., 2015)

SORA: Scalable Overlap-graph Reduction Algorithms for Genome Assembly using Apache Spark in the Cloud. - Alexander J. Paul; Dylan Lawrence; Myoungkyu Song; Seung-Hwan Lim; Chongle Pan; Tae-Hyuk Ahn (BIBM, 2018)

Sipros Ensemble improves database searching and filtering for complex metaproteomics. - Xuan Guo; Zhou Li; Qiuming Yao; Ryan S. Mueller; Jimmy K. Eng; David L. Tabb; IV William Judson Hervey; Chongle Pan (Bioinform., 2018)

IDIA: An Integrative Signal Extractor for Data-Independent Acquisition Proteomics. - Jiancheng Li; Chongle Pan; Xuan Guo (BIBM, 2022)

FineFDR: Fine-grained Taxonomy-specific False Discovery Rates Control in Metaproteomics. - Shengze Wang 004; Shichao Feng; Chongle Pan; Xuan Guo (BIBM, 2022)

LINA: A Linearizing Neural Network Architecture for Accurate First-Order and Second-Order Interpretations. - Adrien Badré; Chongle Pan (IEEE Access, 2022)

MetaLP: An integrative linear programming method for protein inference in metaproteomics. - Shichao Feng; Hong-Long Ji; Huan Wang 005; Bailu Zhang; Ryan Sterzenbach; Chongle Pan; Xuan Guo (PLoS Comput. Biol., 2022)

Deep neural network improves the estimation of polygenic risk scores for breast cancer. - Adrien Badré; Li Zhang; Wellington Muchero; Justin C. Reynolds; Chongle Pan (CoRR, 2023)

Explainable multi-task learning improves the parallel estimation of polygenic risk scores for many diseases through shared genetic basis. - Adrien Badré; Chongle Pan (PLoS Comput. Biol., 2023)

Bayesian inference for survival prediction of childhood Leukemia. - Yuning Cui 003; Yifu Li; Chongle Pan; Stephanie R. Brown; Rachel E. Gallant; Rui Zhu (Comput. Biol. Medicine, 2023)

Towards AI-Driven Healthcare: Systematic Optimization, Linguistic Analysis, and Clinicians' Evaluation of Large Language Models for Smoking Cessation Interventions. - Paul Calle; Ruosi Shao; Yunlong Liu; Emily T. Hébert; Darla E. Kendzor; Jordan M. Neil; Michael S. Businelle; Chongle Pan (CHI, 2024)

SEMQuant: Extending Sipros-Ensemble with Match-Between-Runs for Comprehensive Quantitative Metaproteomics. - Bailu Zhang; Shichao Feng; Manushi Parajuli; Yi Xiong; Chongle Pan; Xuan Guo (ISBRA (3), 2024)

Octascope: A Lightweight Pre-Trained Model for Optical Coherence Tomography. - Haoyang Cui; Chen Wang; Paul Calle; Yunlong Liu; Qinghao Zhang; Sinaro Ly; Justin C. Reynolds; Feng Yan; Ke Zhang; Ronghao Liu; Junyuan Liu; Kar-Ming Fung; et al. (IEEE Access, 2025)

Integration of nested cross-validation, automated hyperparameter optimization, high-performance computing to reduce and quantify the variance of test performance estimation of deep learning models. - Paul Calle; Averi Bates; Justin C. Reynolds; Yunlong Liu; Haoyang Cui; Sinaro Ly; Chen Wang; Qinghao Zhang; Alberto J. de Armendi; Shashank S. Shettar; Kar-Ming Fung; Qinggong Tang; et al. (CoRR, 2025)

Unified Modeling Language Code Generation from Diagram Images Using Multimodal Large Language Models. - Averi Bates; Ryan Vavricka; Shane Carleton; Ruosi Shao; Chongle Pan (CoRR, 2025)