From gigabyte to kilobyte: a bioinformatics protocol for mining large RNA-Seq transcriptomics data. - Jilong Li; Jie Hou 001; Lin Sun; Jordan Maximillian Wilkins; Yuan Lu; Chad E. Niederhuth; Benjamin Ryan Merideth; Thomas P. Mawhinney; Valeri V. Mossine; Michael Greenlief; John C. Walker; William R. Folk; et al. (BCB, 2015)

Exploring soybean metabolic pathways based on probabilistic graphical model and knowledge-based methods. - Jie Hou 001; Gary Stacey; Jianlin Cheng (EURASIP J. Bioinform. Syst. Biol., 2015)

ConEVA: a toolbox for comprehensive assessment of protein contacts. - Badri Adhikari; Jackson Nowotny; Debswapna Bhattacharya; Jie Hou 001; Jianlin Cheng (BMC Bioinform., 2016)

DeepQA: improving the estimation of single protein model quality with deep belief networks. - Renzhi Cao; Debswapna Bhattacharya; Jie Hou 001; Jianlin Cheng (BMC Bioinform., 2016)

QAcon: single model quality assessment using protein structural and contact information with machine learning techniques. - Renzhi Cao; Badri Adhikari; Debswapna Bhattacharya; Miao Sun; Jie Hou 001; Jianlin Cheng (Bioinform., 2017)

Deep learning methods for protein torsion angle prediction. - Haiou Li; Jie Hou 001; Badri Adhikari; Qiang Lyu; Jianlin Cheng (BMC Bioinform., 2017)

DNCON2: improved protein contact prediction using two-level deep convolutional neural networks. - Badri Adhikari; Jie Hou 001; Jianlin Cheng (Bioinform., 2018)

DeepSF: deep convolutional neural network for mapping protein sequences to folds. - Jie Hou 001; Badri Adhikari; Jianlin Cheng (Bioinform., 2018)

PairedFB: a full hierarchical Bayesian model for paired RNA-seq data with heterogeneous treatment effects. - Yuanyuan Bian; Chong He; Jie Hou 001; Jianlin Cheng; Jing Qiu (Bioinform., 2019)

Deep Ranking in Template-free Protein Structure Prediction. - Xiao Chen; Nasrin Akhter; Zhiye Guo; Tianqi Wu; Jie Hou 001; Amarda Shehu; Jianlin Cheng (BCB, 2020)

Performance Evaluation of Viral Infection Diagnosis using T-Cell Receptor Sequence and Artificial Intelligence. - Tim Kosfeld; Jonathan McMillan; Richard J. DiPaolo; Jie Hou 001; Tae-Hyuk Ahn (BCB, 2020)

Analysis of several key factors influencing deep learning-based inter-residue contact prediction. - Tianqi Wu; Jie Hou 001; Badri Adhikari; Jianlin Cheng (Bioinform., 2020)

Improving deep learning-based protein distance prediction in CASP14. - Zhiye Guo; Tianqi Wu; Jian Liu; Jie Hou 001; Jianlin Cheng (Bioinform., 2021)

DISTEVAL: a web server for evaluating predicted protein distances. - Badri Adhikari; Bikash Shrestha; Matthew Bernardini; Jie Hou 001; Jamie Lea (BMC Bioinform., 2021)

DeepGRN: prediction of transcription factor binding site across cell-types using attention-based deep neural networks. - Chen Chen; Jie Hou 001; Xiaowen Shi; Hua Yang; James A. Birchler; Jianlin Cheng (BMC Bioinform., 2021)

DeepDist: real-value inter-residue distance prediction with deep residual convolutional network. - Tianqi Wu; Zhiye Guo; Jie Hou 001; Jianlin Cheng (BMC Bioinform., 2021)

Correction to: DeepDist: real‑value inter‑residue distance prediction with deep residual convolutional network. - Tianqi Wu; Zhiye Guo; Jie Hou 001; Jianlin Cheng (BMC Bioinform., 2021)

Artificial Intelligence Advances for De Novo Molecular Structure Modeling in Cryo-EM. - Dong Si; Andrew Nakamura; Runbang Tang; Haowen Guan; Jie Hou 001; Ammaar Firozi; Renzhi Cao; Kyle Hippe; Minglei Zhao (CoRR, 2021)

Deep graph learning to estimate protein model quality using structural constraints from multiple sequence alignments. - Mahdi Rahbar; Rahul Kumar Chauhan; Pankil Nimeshbhai Shah; Renzhi Cao; Dong Si; Jie Hou 001 (BCB, 2022)

ZoomQA: residue-level protein model accuracy estimation with machine learning on sequential and 3D structural features. - Kyle Hippe; Cade Lilley; Joshua William Berkenpas; Ciri Chandana Pocha; Kiyomi Kishaba; Hui Ding; Jie Hou 001; Dong Si; Renzhi Cao (Briefings Bioinform., 2022)

22nd International Workshop on Data Mining in Bioinformatics (BIOKDD 2023). - Da Yan 001; Ariful Azad; Jie Hou 001; Jake Y. Chen; Mohammed J. Zaki (KDD, 2023)

Fast and automated protein-DNA/RNA macromolecular complex modeling from cryo-EM maps. - Andrew Nakamura; Hanze Meng; Minglei Zhao; Fengbin Wang; Jie Hou 001; Renzhi Cao; Dong Si (Briefings Bioinform., 2023)

ComplexQA: a deep graph learning approach for protein complex structure assessment. - Lei Zhang; Sheng Wang; Jie Hou 001; Dong Si; Junyong Zhu; Renzhi Cao (Briefings Bioinform., 2023)

Enhancing cryo-EM structure prediction with DeepTracer and AlphaFold2 integration. - Jason Chen; Ayisha Zia; Albert Luo; Hanze Meng; Fengbin Wang; Jie Hou 001; Renzhi Cao; Dong Si (Briefings Bioinform., 2024)

Silver Linings in the Shadows: Harnessing Membership Inference for Machine Unlearning. - Nexhi Sula; Abhinav Kumar; Jie Hou 001; Han Wang 021; Reza Tourani (CoRR, 2024)

Unveiling the Unseen: Exploring Whitebox Membership Inference through the Lens of Explainability. - Chenxi Li; Abhinav Kumar; Zhen Guo; Jie Hou 001; Reza Tourani (CoRR, 2024)

Teaching Coding in the Age of AI: A Hands-on Tutorial on Process Feedback. - Badri Adhikari; Jie Hou 001 (SIGCSE (2), 2025)