Gaoshi Li

Orcid: 0009-0000-9198-6538

According to our database¹, Gaoshi Li authored at least 37 papers between 2016 and 2026.

Collaborative distances:

Dijkstra number² of four.
Erdős number³ of three.

Timeline

Legend:

Book In proceedings Article PhD thesis Dataset Other

Links

On csauthors.net:

Bibliography

2026

A Multi-Attribute Adaptive Fault Diagnosis Framework for Star Networks.

[BibT_eX]

[DOI]

IEEE Trans. Computers, January, 2026

The $g$-Good-Neighbor $r$-Component Diagnosability of Hypercube - Theoretical and Algorithmic Approaches.

[BibT_eX]

[DOI]

IEEE Trans. Reliab., 2026

A Novel Conditional Diagnostic Scheme for Hypercube-Based Multiprocessor Systems.

[BibT_eX]

[DOI]

IEEE Trans. Netw., 2026

An efficient two-stage diagnostic algorithm for assessing system reliability.

[BibT_eX]

[DOI]

Theor. Comput. Sci., 2026

GDCC: scRNA-seq data imputation via Graph-cGAN based dual conditional guidance with constraint training.

[BibT_eX]

[DOI]

Knowl. Based Syst., 2026

CDMI-NTDI: Cancer driver module identification via network topology and deep interaction features.

[BibT_eX]

[DOI]

Neurocomputing, 2026

Learning-based network diagnostics: Handling high fault densities with PMC/MM* model.

[BibT_eX]

[DOI]

Expert Syst. Appl., 2026

2025

A novel ranking scheme for identifying influential nodes in complex networks.

[BibT_eX]

[DOI]

J. Supercomput., December, 2025

An analysis on component reliability of (n, k)-star networks.

[BibT_eX]

[DOI]

J. Supercomput., March, 2025

A novel fault diagnostic algorithm with multiple characteristics for multiprocessor systems.

[BibT_eX]

[DOI]

Theor. Comput. Sci., 2025

The reliability of (n,k)-star network in terms of non-inclusive fault pattern.

[BibT_eX]

[DOI]

Theor. Comput. Sci., 2025

Identifying Cancer Driver Genes Using a Neural Network Framework With Cross-Attention Mechanism.

[BibT_eX]

[DOI]

IEEE Trans. Comput. Biol. Bioinform., 2025

scPEGEnhanced Graph Convolutional Sparse Subspace Clustering Method for scRNA-Seq Data.

[BibT_eX]

[DOI]

IEEE Trans. Comput. Biol. Bioinform., 2025

Using Multi-Feature Weak Consensus Model to Discover Essential Proteins.

[BibT_eX]

[DOI]

IEEE Trans. Comput. Biol. Bioinform., 2025

A Deep Learning Framework for Identifying Cancer Driver Genes Based on Transformer and Graph Convolutional Network.

[BibT_eX]

[DOI]

IEEE Trans. Comput. Biol. Bioinform., 2025

MNMO: discover driver genes from a multi-omics data based-multi-layer network.

[BibT_eX]

[DOI]

Bioinform., 2025

Identification of Potential Cancer Driver Genes Based on Modular Dysregulated Genes.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2025

2024

Identification of cancer driver genes based on hierarchical weak consensus model.

[BibT_eX]

[DOI]

Health Inf. Sci. Syst., December, 2024

AGImpute: imputation of scRNA-seq data based on a hybrid GAN with dropouts identification.

[BibT_eX]

[DOI]

Bioinform., February, 2024

Identification of Cancer Driver Genes based on Dynamic Incentive Model.

[BibT_eX]

[DOI]

IEEE ACM Trans. Comput. Biol. Bioinform., 2024

A model and multi-core parallel co-evolution algorithm for identifying cancer driver pathways.

[BibT_eX]

[DOI]

Eng. Appl. Artif. Intell., 2024

ICDM-GEHC: identifying cancer driver module based on graph embedding and hierarchical clustering.

[BibT_eX]

[DOI]

Complex Intell. Syst., 2024

IntroGRN: Gene Regulatory Network Inference from Single-Cell RNA Data Based on Introspective VAE.

[BibT_eX]

[DOI]

Proceedings of the Bioinformatics Research and Applications - 20th International Symposium, 2024

2023

Essential proteins discovery based on dominance relationship and neighborhood similarity centrality.

[BibT_eX]

[DOI]

Health Inf. Sci. Syst., December, 2023

Identifying driver pathways based on a parameter-free model and a partheno-genetic algorithm.

[BibT_eX]

[DOI]

BMC Bioinform., December, 2023

Mdwgan-gp: data augmentation for gene expression data based on multiple discriminator WGAN-GP.

[BibT_eX]

[DOI]

BMC Bioinform., December, 2023

A model and cooperative co-evolution algorithm for identifying driver pathways based on the integrated data and PPI network.

[BibT_eX]

[DOI]

Expert Syst. Appl., 2023

Essential proteins identification based on weak consensus model and neighborhood aggregation centrality.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2023

2022

Identification of cancer-related module in protein-protein interaction network based on gene prioritization.

[BibT_eX]

[DOI]

Jingli Wu

Qi Zhang

Gaoshi Li

J. Bioinform. Comput. Biol., 2022

Identifying common driver modules by equilibrating coverage and mutual exclusivity across pan-cancer data.

[BibT_eX]

[DOI]

Jingli Wu

Cong Wu

Gaoshi Li

Neurocomputing, 2022

A nonlinear model and an algorithm for identifying cancer driver pathways.

[BibT_eX]

[DOI]

Appl. Soft Comput., 2022

A model and algorithm for identifying driver pathways based on weighted non-binary mutation matrix.

[BibT_eX]

[DOI]

Appl. Intell., 2022

Identifying driver genes in cancer based on Pareto optimality consensus.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2022

2021

IDM-SPS: Identifying driver module with somatic mutation, PPI network and subcellular localization.

[BibT_eX]

[DOI]

Eng. Appl. Artif. Intell., 2021

2020

United Neighborhood Closeness Centrality and Orthology for Predicting Essential Proteins.

[BibT_eX]

[DOI]

IEEE ACM Trans. Comput. Biol. Bioinform., 2020

Two novel models and a parthenogenetic algorithm for detecting common driver pathways from pan-cancer data.

[BibT_eX]

[DOI]

Eng. Appl. Artif. Intell., 2020

2016

Predicting essential proteins based on subcellular localization, orthology and PPI networks.

[BibT_eX]

[DOI]

BMC Bioinform., 2016

Gaoshi Li

Timeline

Legend:

Links

On csauthors.net:

Bibliography

Loading...