Zekang Bian
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View article: Prediction of microbe-drug associations using a CNN-Bernoulli random forest model
Prediction of microbe-drug associations using a CNN-Bernoulli random forest model Open
Background Antibiotics play a critical role in treating microbial infections. However, their widespread use has contributed to the growing problem of microbial resistance. Addressing this challenge requires the identification of new microb…
View article: A novel adversarial deep TSK fuzzy classifier with its inverse-free fast training
A novel adversarial deep TSK fuzzy classifier with its inverse-free fast training Open
Deep learning is one of the most popular machine learning methods, and has been used in many applications. However, conventional deep learning is a fully deterministic model that has difficulty reducing data uncertainty while shedding no l…
View article: Recognition of MI-EEG signals using extended-LSR-based inductive transfer learning
Recognition of MI-EEG signals using extended-LSR-based inductive transfer learning Open
Introduction Motor imagery electroencephalographic (MI-EEG) signal recognition is used in various brain–computer interface (BCI) systems. In most existing BCI systems, this identification relies on classification algorithms. However, gener…
View article: Three-layer heterogeneous network based on the integration of CircRNA information for MiRNA-disease association prediction
Three-layer heterogeneous network based on the integration of CircRNA information for MiRNA-disease association prediction Open
Increasing research has shown that the abnormal expression of microRNA (miRNA) is associated with many complex diseases. However, biological experiments have many limitations in identifying the potential disease-miRNA associations. Therefo…
View article: Bayes-Decisive Linear KNN with Adaptive Nearest Neighbors
Bayes-Decisive Linear KNN with Adaptive Nearest Neighbors Open
While the classical KNN (k nearest neighbor) shares its avoidance of the consistent distribution assumption between training and testing samples to achieve fast prediction, it still faces two challenges: (a) its generalization ability heav…
View article: An Ensemble Clustering Method Via Learning the Ca Matrix with Fuzzy Neighbors
An Ensemble Clustering Method Via Learning the Ca Matrix with Fuzzy Neighbors Open
View article: Neighborhood-based inference and restricted Boltzmann machine for microbe and drug associations prediction
Neighborhood-based inference and restricted Boltzmann machine for microbe and drug associations prediction Open
Background Efficient identification of microbe-drug associations is critical for drug development and solving problem of antimicrobial resistance. Traditional wet-lab method requires a lot of money and labor in identifying potential microb…
View article: Neighborhood-based Inference and Restricted Boltzmann Machine for microbe and drug associations prediction
Neighborhood-based Inference and Restricted Boltzmann Machine for microbe and drug associations prediction Open
Efficient identification of microbe-drug associations is critical for drug development and solving problem of antimicrobial resistance. Traditional wet-lab method requires a lot of money and labor in identifying potential microbe-drug asso…
View article: Viral Drug prediction with Matrix Decomposition and Two-layer Heterogeneous Graph Inference
Viral Drug prediction with Matrix Decomposition and Two-layer Heterogeneous Graph Inference Open
Recently, the association prediction between viruses and drugs has drawn more and more attention. A growing number of studies have shown that the problem of antiviral drug resistance is increasing and has become a major problem plaguing th…