Y
Yang Yang
Researcher at Shanghai Jiao Tong University
Publications - 105
Citations - 1504
Yang Yang is an academic researcher from Shanghai Jiao Tong University. The author has contributed to research in topics: Medicine & Deep learning. The author has an hindex of 17, co-authored 84 publications receiving 1010 citations. Previous affiliations of Yang Yang include Chinese Ministry of Education & Shanghai Maritime University.
Papers
More filters
Journal ArticleDOI
The lncLocator: a subcellular localization predictor for long non-coding RNAs based on a stacked ensemble classifier.
TL;DR: The current lncLocator can predict five subcellular localizations of lncRNAs, including cytoplasm, nucleus, cytosol, ribosome and exosome, and yield an overall accuracy of 0.59 on the constructed benchmark dataset.
Journal ArticleDOI
Roles of small RNAs in soybean defense against Phytophthora sojae infection
James Wong,Lei Gao,Yang Yang,Jixian Zhai,Siwaret Arikit,Yu Yu,Shuyi Duan,Shuyi Duan,Vicky Chan,Qin Xiong,Qin Xiong,Jun Yan,Shengben Li,Renyi Liu,Yuanchao Wang,Guiliang Tang,Blake C. Meyers,Xuemei Chen,Xuemei Chen,Wenbo Ma +19 more
TL;DR: Data suggest that miR393 promotes soybean defense against P. sojae, and identifies specific miRNAs and phasiRNAs that regulate defense-associated genes in soybean during Phytophthora infection.
Journal ArticleDOI
Hum-mPLoc 3.0: prediction enhancement of human protein subcellular localization through modeling the hidden correlations of gene ontology and functional domain features.
TL;DR: A novel feature representation protocol denoted as HCM (Hidden Correlation Modeling), which will create more compact and discriminative feature vectors by modeling the hidden correlations between annotation terms.
Journal ArticleDOI
Computational prediction of type III secreted proteins from gram-negative bacteria
TL;DR: A machine learning method based on the N-terminal amino acid sequences to predict novel type III effectors in the plant pathogen Pseudomonas syringae and the microsymbiont rhizobia is developed.
Journal ArticleDOI
Recent methodology progress of deep learning for RNA-protein interaction prediction.
TL;DR: An overview of the successful implementation of various deep learning approaches for predicting RNA– protein interactions, mainly focusing on the prediction of RNA–protein interaction pairs and RBP‐binding sites on RNAs is provided.