Ke Yan

Orcid: 0000-0002-5326-4267

Affiliations:

Beijing Institute of Technology, School of Computer Science and Technology, China
Harbin Institute of Technology, Bio-Computing Research Center, Shenzhen, China

According to our database¹, Ke Yan authored at least 29 papers between 2014 and 2023.

Collaborative distances:

Dijkstra number² of four.
Erdős number³ of four.

Timeline

Legend:

Book

In proceedings

Article

PhD thesis

Dataset

Other

Bibliography

2023

iDRPro-SC: identifying DNA-binding proteins and RNA-binding proteins based on subfunction classifiers.

[BibT_eX]

[DOI]

Briefings Bioinform., July, 2023

DAmiRLocGNet: miRNA subcellular localization prediction by combining miRNA-disease associations and graph convolutional networks.

[BibT_eX]

[DOI]

Tao Bai

Ke Yan

Bin Liu

Briefings Bioinform., July, 2023

PreTP-2L: identification of therapeutic peptides and their types using two-layer ensemble learning framework.

[BibT_eX]

[DOI]

Ke Yan

Yichen Guo

Bin Liu

Bioinform., April, 2023

sAMPpred-GAT: prediction of antimicrobial peptide by graph attention network and predicted peptide structure.

[BibT_eX]

[DOI]

Bioinform., January, 2023

PreTP-Stack: Prediction of Therapeutic Peptides Based on the Stacked Ensemble Learing.

[BibT_eX]

[DOI]

IEEE ACM Trans. Comput. Biol. Bioinform., 2023

2022

AMPpred-EL: An effective antimicrobial peptide prediction model based on ensemble learning.

[BibT_eX]

[DOI]

Comput. Biol. Medicine, 2022

PreRBP-TL: prediction of species-specific RNA-binding proteins based on transfer learning.

[BibT_eX]

[DOI]

Bioinform., 2022

TPpred-ATMV: therapeutic peptide prediction by adaptive multi-view tensor learning model.

[BibT_eX]

[DOI]

Bioinform., 2022

iDRNA-ITF: identifying DNA- and RNA-binding residues in proteins based on induction and transfer framework.

[BibT_eX]

[DOI]

Briefings Bioinform., 2022

2021

Adaptive Graph Completion Based Incomplete Multi-View Clustering.

[BibT_eX]

[DOI]

IEEE Trans. Multim., 2021

Protein Fold Recognition Based on Auto-Weighted Multi-View Graph Embedding Learning Model.

[BibT_eX]

[DOI]

IEEE ACM Trans. Comput. Biol. Bioinform., 2021

Protein Fold Recognition by Combining Support Vector Machines and Pairwise Sequence Similarity Scores.

[BibT_eX]

[DOI]

IEEE ACM Trans. Comput. Biol. Bioinform., 2021

MLDH-Fold: Protein fold recognition based on multi-view low-rank modeling.

[BibT_eX]

[DOI]

Neurocomputing, 2021

FoldRec-C2C: protein fold recognition by combining cluster-to-cluster model and protein similarity network.

[BibT_eX]

[DOI]

Jiangyi Shao

Ke Yan

Bin Liu

Briefings Bioinform., 2021

PreTP-EL: prediction of therapeutic peptides based on ensemble learning.

[BibT_eX]

[DOI]

Briefings Bioinform., 2021

2020

Fold-LTR-TCP: protein fold recognition based on triadic closure principle.

[BibT_eX]

[DOI]

Bin Liu

Yulin Zhu

Ke Yan

Briefings Bioinform., 2020

DeepSVM-fold: protein fold recognition by combining support vector machines and pairwise sequence similarity scores generated by deep learning networks.

[BibT_eX]

[DOI]

Bin Liu

Chen-Chen Li

Ke Yan

Briefings Bioinform., 2020

2019

Low-Rank Preserving Projection Via Graph Regularized Reconstruction.

[BibT_eX]

[DOI]

Jie Wen

Na Han