P
Ping Xuan
Researcher at Heilongjiang University
Publications - 66
Citations - 1701
Ping Xuan is an academic researcher from Heilongjiang University. The author has contributed to research in topics: Computer science & Convolutional neural network. The author has an hindex of 18, co-authored 51 publications receiving 1094 citations. Previous affiliations of Ping Xuan include Harbin Institute of Technology & Northeast Forestry University.
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Journal ArticleDOI
Prediction of microRNAs Associated with Human Diseases Based on Weighted k Most Similar Neighbors
Ping Xuan,Ke Han,Maozu Guo,Yahong Guo,Jinbao Li,Jian Ding,Yong Liu,Qiguo Dai,Jin Li,Zhixia Teng,Yufei Huang +10 more
TL;DR: A new prediction method, HDMP, based on weighted k most similar neighbors is presented for predicting disease miRNAs and it is validated that HDMP achieved significantly higher prediction performance than existing methods.
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Prediction of potential disease-associated microRNAs based on random walk
TL;DR: The functional similarity between a pair of miRNAs is calculated based on their associated diseases to construct a miRNA network and a new prediction method based on random walk on the network is presented, achieving superior performance for 18 human diseases.
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Measuring gene functional similarity based on group-wise comparison of GO terms
TL;DR: A novel method called SORA is proposed to measure gene functional similarity in GO context and evaluated against five state-of-the-art methods in the file on the public platform for collaborative evaluation of GO-based semantic similarity measure.
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Graph Convolutional Network and Convolutional Neural Network Based Method for Predicting lncRNA-Disease Associations
TL;DR: A novel method based on the graph convolutional network and Convolutional neural network, referred to as GCNLDA, to infer disease-related lncRNA candidates and had superior performance against state-of-the-art prediction methods.
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PlantMiRNAPred: efficient classification of real and pseudo plant pre-miRNAs.
TL;DR: The ability of PlantMiRNAPred to discern real and pseudo pre-miRNAs provides a viable method for discovering new non-homologous plant pre- miRNAs.