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Jie Hou 0001
Person information
- affiliation: Saint Louis University, Department of Computer Science, MO, USA
- affiliation (PhD 2019): University of Missouri, Columbia, MO, USA
Other persons with the same name
- Jie Hou — disambiguation page
- Jie Hou 0002 — Stuttgart University, Germany
- Jie Hou 0003 — Technical University Munich, Germany
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2020 – today
- 2024
- [i5]Nexhi Sula, Abhinav Kumar, Jie Hou, Han Wang, Reza Tourani:
Silver Linings in the Shadows: Harnessing Membership Inference for Machine Unlearning. CoRR abs/2407.00866 (2024) - [i4]Chenxi Li, Abhinav Kumar, Zhen Guo, Jie Hou, Reza Tourani:
Unveiling the Unseen: Exploring Whitebox Membership Inference through the Lens of Explainability. CoRR abs/2407.01306 (2024) - 2023
- [j17]Andrew Nakamura
, Hanze Meng, Minglei Zhao, Fengbin Wang, Jie Hou, Renzhi Cao
Fast and automated protein-DNA/RNA macromolecular complex modeling from cryo-EM maps. Briefings Bioinform. 24(2) (2023) - [j16]Lei Zhang, Sheng Wang, Jie Hou, Dong Si, Junyong Zhu, Renzhi Cao:
ComplexQA: a deep graph learning approach for protein complex structure assessment. Briefings Bioinform. 24(6) (2023) - [c6]Da Yan
22nd International Workshop on Data Mining in Bioinformatics (BIOKDD 2023). KDD 2023: 5897-5898 - 2022
- [j15]Kyle Hippe, Cade Lilley, Joshua William Berkenpas, Ciri Chandana Pocha, Kiyomi Kishaba, Hui Ding, Jie Hou, Dong Si, Renzhi Cao:
ZoomQA: residue-level protein model accuracy estimation with machine learning on sequential and 3D structural features. Briefings Bioinform. 23(1) (2022) - [c5]Mahdi Rahbar
Deep graph learning to estimate protein model quality using structural constraints from multiple sequence alignments. BCB 2022: 21:1-21:10 - 2021
- [j14]Zhiye Guo, Tianqi Wu
Improving deep learning-based protein distance prediction in CASP14. Bioinform. 37(19): 3190-3196 (2021) - [j13]Badri Adhikari
DISTEVAL: a web server for evaluating predicted protein distances. BMC Bioinform. 22(1): 8 (2021) - [j12]Tianqi Wu
DeepDist: real-value inter-residue distance prediction with deep residual convolutional network. BMC Bioinform. 22(1): 30 (2021) - [j11]Chen Chen, Jie Hou, Xiaowen Shi, Hua Yang
DeepGRN: prediction of transcription factor binding site across cell-types using attention-based deep neural networks. BMC Bioinform. 22(1): 38 (2021) - [j10]Tianqi Wu
Correction to: DeepDist: real‑value inter‑residue distance prediction with deep residual convolutional network. BMC Bioinform. 22(1): 354 (2021) - [i3]Dong Si, Andrew Nakamura, Runbang Tang, Haowen Guan, Jie Hou, Ammaar Firozi, Renzhi Cao, Kyle Hippe, Minglei Zhao:
Artificial Intelligence Advances for De Novo Molecular Structure Modeling in Cryo-EM. CoRR abs/2102.06125 (2021) - 2020
- [j9]Tianqi Wu
Analysis of several key factors influencing deep learning-based inter-residue contact prediction. Bioinform. 36(4): 1091-1098 (2020) - [c4]Xiao Chen, Nasrin Akhter, Zhiye Guo, Tianqi Wu
Deep Ranking in Template-free Protein Structure Prediction. BCB 2020: 31:1-31:10 - [c3]Tim Kosfeld
Performance Evaluation of Viral Infection Diagnosis using T-Cell Receptor Sequence and Artificial Intelligence. BCB 2020: 35:1-35:10
2010 – 2019
- 2019
- [j8]Yuanyuan Bian, Chong He, Jie Hou, Jianlin Cheng
PairedFB: a full hierarchical Bayesian model for paired RNA-seq data with heterogeneous treatment effects. Bioinform. 35(5): 787-797 (2019) - 2018
- [j7]Jie Hou, Badri Adhikari, Jianlin Cheng
DeepSF: deep convolutional neural network for mapping protein sequences to folds. Bioinform. 34(8): 1295-1303 (2018) - [j6]Badri Adhikari, Jie Hou, Jianlin Cheng
DNCON2: improved protein contact prediction using two-level deep convolutional neural networks. Bioinform. 34(9): 1466-1472 (2018) - [c2]Jie Hou, Badri Adhikari, Jianlin Cheng:
DeepSF: Deep Convolutional Neural Network for Mapping Protein Sequences to Folds. BCB 2018: 565 - 2017
- [j5]Renzhi Cao, Badri Adhikari, Debswapna Bhattacharya, Miao Sun, Jie Hou, Jianlin Cheng
QAcon: single model quality assessment using protein structural and contact information with machine learning techniques. Bioinform. 33(4): 586-588 (2017) - [j4]Haiou Li, Jie Hou, Badri Adhikari, Qiang Lyu, Jianlin Cheng
Deep learning methods for protein torsion angle prediction. BMC Bioinform. 18(1): 417:1-417:13 (2017) - [i2]Jie Hou, Badri Adhikari, Jianlin Cheng:
DeepSF: deep convolutional neural network for mapping protein sequences to folds. CoRR abs/1706.01010 (2017) - 2016
- [j3]Renzhi Cao, Debswapna Bhattacharya, Jie Hou, Jianlin Cheng
DeepQA: improving the estimation of single protein model quality with deep belief networks. BMC Bioinform. 17: 495:1-495:9 (2016) - [j2]Badri Adhikari, Jackson Nowotny, Debswapna Bhattacharya, Jie Hou, Jianlin Cheng
ConEVA: a toolbox for comprehensive assessment of protein contacts. BMC Bioinform. 17: 517:1-517:12 (2016) - [i1]Renzhi Cao, Debswapna Bhattacharya, Jie Hou, Jianlin Cheng:
DeepQA: Improving the estimation of single protein model quality with deep belief networks. CoRR abs/1607.04379 (2016) - 2015
- [j1]Jie Hou, Gary Stacey, Jianlin Cheng
Exploring soybean metabolic pathways based on probabilistic graphical model and knowledge-based methods. EURASIP J. Bioinform. Syst. Biol. 2015: 5 (2015) - [c1]Jilong Li, Jie Hou, 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, Mark Hannink, Dennis B. Lubahn, James A. Birchler, Jianlin Cheng:
From gigabyte to kilobyte: a bioinformatics protocol for mining large RNA-Seq transcriptomics data. BCB 2015: 535-536
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