Yiheng Zhu

Orcid: 0000-0002-3857-1533

Affiliations:
  • Nanjing Agricultural University, College of Artificial Intelligence, China
  • Nanjing University of Science and Technology, School of Computer Science and Engineering, China (PhD 2023)
  • University of Michigan, Department of Computational Medicine and Bioinformatics, Ann Arbor, MI, USA


According to our database1, Yiheng Zhu authored at least 15 papers between 2019 and 2024.

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

Timeline

2019
2020
2021
2022
2023
2024
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Legend:

Book 
In proceedings 
Article 
PhD thesis 
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Other 

Links

Online presence:

On csauthors.net:

Bibliography

2024
ULDNA: integrating unsupervised multi-source language models with LSTM-attention network for high-accuracy protein-DNA binding site prediction.
Briefings Bioinform., January, 2024

BLAM6A-Merge: Leveraging Attention Mechanisms and Feature Fusion Strategies to Improve the Identification of RNA N6-Methyladenosine Sites.
IEEE ACM Trans. Comput. Biol. Bioinform., 2024

Improving Antifreeze Proteins Prediction With Protein Language Models and Hybrid Feature Extraction Networks.
IEEE ACM Trans. Comput. Biol. Bioinform., 2024

2023
Integrating unsupervised language model with multi-view multiple sequence alignments for high-accuracy inter-chain contact prediction.
Comput. Biol. Medicine, November, 2023

2022
Integrating unsupervised language model with triplet neural networks for protein gene ontology prediction.
PLoS Comput. Biol., December, 2022

TripletGO: Integrating Transcript Expression Profiles with Protein Homology Inferences for Gene Function Prediction.
Genom. Proteom. Bioinform., October, 2022

MAResNet: predicting transcription factor binding sites by combining multi-scale bottom-up and top-down attention and residual network.
Briefings Bioinform., 2022

2021
TargetDBP+: Enhancing the Performance of Identifying DNA-Binding Proteins via Weighted Convolutional Features.
J. Chem. Inf. Model., 2021

Accurate multistage prediction of protein crystallization propensity using deep-cascade forest with sequence-based features.
Briefings Bioinform., 2021

Why can deep convolutional neural networks improve protein fold recognition? A visual explanation by interpretation.
Briefings Bioinform., 2021

Improving protein fold recognition using triplet network and ensemble deep learning.
Briefings Bioinform., 2021

2020
TargetDBP: Accurate DNA-Binding Protein Prediction Via Sequence-Based Multi-View Feature Learning.
IEEE ACM Trans. Comput. Biol. Bioinform., 2020

SSCpred: Single-Sequence-Based Protein Contact Prediction Using Deep Fully Convolutional Network.
J. Chem. Inf. Model., 2020

2019
DNAPred: Accurate Identification of DNA-Binding Sites from Protein Sequence by Ensembled Hyperplane-Distance-Based Support Vector Machines.
J. Chem. Inf. Model., 2019

DeepTF: Accurate Prediction of Transcription Factor Binding Sites by Combining Multi-scale Convolution and Long Short-Term Memory Neural Network.
Proceedings of the Intelligence Science and Big Data Engineering. Big Data and Machine Learning, 2019


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