Jie Hou

Orcid: 0000-0002-8584-5154

Affiliations:
  • Saint Louis University, Department of Computer Science, MO, USA
  • University of Missouri, Columbia, MO, USA (PhD 2019)


According to our database1, Jie Hou authored at least 25 papers between 2015 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

Online presence:

On csauthors.net:

Bibliography

2024
Unveiling the Unseen: Exploring Whitebox Membership Inference through the Lens of Explainability.
CoRR, 2024

Silver Linings in the Shadows: Harnessing Membership Inference for Machine Unlearning.
CoRR, 2024

2023
ComplexQA: a deep graph learning approach for protein complex structure assessment.
Briefings Bioinform., September, 2023

Fast and automated protein-DNA/RNA macromolecular complex modeling from cryo-EM maps.
Briefings Bioinform., March, 2023

22nd International Workshop on Data Mining in Bioinformatics (BIOKDD 2023).
Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

2022
ZoomQA: residue-level protein model accuracy estimation with machine learning on sequential and 3D structural features.
Briefings Bioinform., 2022

Deep graph learning to estimate protein model quality using structural constraints from multiple sequence alignments.
Proceedings of the BCB '22: 13th ACM International Conference on Bioinformatics, Computational Biology and Health Informatics, Northbrook, Illinois, USA, August 7, 2022

2021
Artificial Intelligence Advances for De Novo Molecular Structure Modeling in Cryo-EM.
CoRR, 2021

Correction to: DeepDist: real‑value inter‑residue distance prediction with deep residual convolutional network.
BMC Bioinform., 2021

DeepDist: real-value inter-residue distance prediction with deep residual convolutional network.
BMC Bioinform., 2021

DeepGRN: prediction of transcription factor binding site across cell-types using attention-based deep neural networks.
BMC Bioinform., 2021

DISTEVAL: a web server for evaluating predicted protein distances.
BMC Bioinform., 2021

Improving deep learning-based protein distance prediction in CASP14.
Bioinform., 2021

2020
Analysis of several key factors influencing deep learning-based inter-residue contact prediction.
Bioinform., 2020

Performance Evaluation of Viral Infection Diagnosis using T-Cell Receptor Sequence and Artificial Intelligence.
Proceedings of the BCB '20: 11th ACM International Conference on Bioinformatics, 2020

Deep Ranking in Template-free Protein Structure Prediction.
Proceedings of the BCB '20: 11th ACM International Conference on Bioinformatics, 2020

2019
PairedFB: a full hierarchical Bayesian model for paired RNA-seq data with heterogeneous treatment effects.
Bioinform., 2019

2018
DeepSF: deep convolutional neural network for mapping protein sequences to folds.
Bioinform., 2018

DNCON2: improved protein contact prediction using two-level deep convolutional neural networks.
Bioinform., 2018

2017
Deep learning methods for protein torsion angle prediction.
BMC Bioinform., 2017

QAcon: single model quality assessment using protein structural and contact information with machine learning techniques.
Bioinform., 2017

2016
DeepQA: improving the estimation of single protein model quality with deep belief networks.
BMC Bioinform., 2016

ConEVA: a toolbox for comprehensive assessment of protein contacts.
BMC Bioinform., 2016

2015
Exploring soybean metabolic pathways based on probabilistic graphical model and knowledge-based methods.
EURASIP J. Bioinform. Syst. Biol., 2015

From gigabyte to kilobyte: a bioinformatics protocol for mining large RNA-Seq transcriptomics data.
Proceedings of the 6th ACM Conference on Bioinformatics, 2015


  Loading...