Jingyang Gao
Orcid: 0000-0003-1270-6257
According to our database1,
Jingyang Gao
authored at least 29 papers
between 2015 and 2023.
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Bibliography
2023
DeepHipp: accurate segmentation of hippocampus using 3D dense-block based on attention mechanism.
BMC Medical Imaging, December, 2023
Lossless segmentation of cardiac medical images by a resolution consistent network with nondamage data preprocessing.
Multim. Tools Appl., 2023
2022
Proceedings of the Computer Science and Education - 17th International Conference, 2022
GcnSV: A Method Based on Deep Learning of Calling Structural Variations from the Third-Generation Sequencing Data.
Proceedings of the Computer Science and Education - 17th International Conference, 2022
2021
Cnngeno: A high-precision deep learning based strategy for the calling of structural variation genotype.
Comput. Biol. Chem., 2021
BMC Bioinform., 2021
IMDSVs: An integrated method based on machine learning and deep learning of calling structural variations from long-read data.
Proceedings of the 16th International Conference on Computer Science & Education, 2021
2020
Proceedings of the Data Science, 2020
iSchood: a Tool Software for Identifying Suspicious Copied Homework Documents with Definitive Contents.
Proceedings of the 15th International Conference on Computer Science & Education, 2020
A novel synonymous processing method based on amino acid substitution matrics for the classification of G-protein-coupled receptors.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2020
scSNVIndel. accurate and efficient calling of SNVs and indels from single cell sequencing using integrated Bi-LSTM.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2020
2019
DeepSV: accurate calling of genomic deletions from high-throughput sequencing data using deep convolutional neural network.
BMC Bioinform., 2019
Integrated Detection of Copy Number Variation Based on the Assembly of NGS and 3GS Data.
Proceedings of the Bioinformatics and Biomedical Engineering, 2019
Proceedings of the 21st IEEE International Conference on High Performance Computing and Communications; 17th IEEE International Conference on Smart City; 5th IEEE International Conference on Data Science and Systems, 2019
2018
基于深度学习的胃癌病理图像分类方法 (Pathological Image Classification of Gastric Cancer Based on Depth Learning).
计算机科学, 2018
Deletion genotype calling on the basis of sequence visualisation and image classification.
Int. J. Data Min. Bioinform., 2018
Proceedings of the Intelligent Computing Theories and Application, 2018
Proceedings of the 20th IEEE International Conference on High Performance Computing and Communications; 16th IEEE International Conference on Smart City; 4th IEEE International Conference on Data Science and Systems, 2018
Classification of G-protein Coupled Receptors Based on Semi-navïe Bayesian Inference.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2018
cnnCNV: A Sensitive and Efficient Method for Detecting Copy Number Variation based on Convolutional Neural Networks.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2018
2017
基于特征挖掘的基因组缺失变异集成检测方法 (Integrated Feature Mining Based Approach for Calling Genomic Deletions).
计算机科学, 2017
Concod: an effective integration framework of consensus-based calling deletions from next-generation sequencing data.
Int. J. Data Min. Bioinform., 2017
An efficient CNN-based classification on G-protein Coupled Receptors using TF-IDF and N-gram.
Proceedings of the 2017 IEEE Symposium on Computers and Communications, 2017
2016
MrBayes tgMC<sup>3</sup>++: A High Performance and Resource-Efficient GPU-Oriented Phylogenetic Analysis Method.
IEEE ACM Trans. Comput. Biol. Bioinform., 2016
Proceedings of the 2016 IEEE Trustcom/BigDataSE/ISPA, 2016
MrBayes 3.2.6 on Tianhe-1A: A High Performance and Distributed Implementation of Phylogenetic Analysis.
Proceedings of the 22nd IEEE International Conference on Parallel and Distributed Systems, 2016
Concod: Accurate consensus-based approach of calling deletions from high-throughput sequencing data.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2016
A high-precision shallow Convolutional Neural Network based strategy for the detection of Genomic Deletions.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2016
2015
J. Comput. Methods Sci. Eng., 2015