12 Result(s)
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Chapter and Conference Paper
Correction to: Simulating Spiking Neural Networks Based on SW26010pro
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Chapter and Conference Paper
Prediction of Drug-Disease Relationship on Heterogeneous Networks Based on Graph Convolution
Drug-disease association prediction is essential in drug development and repositioning. At present, the proposed drug-disease association prediction models based on graph convolution usually learn the characte...
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Chapter and Conference Paper
Simulating Spiking Neural Networks Based on SW26010pro
The spiking neural network (SNN) simulators play a significant role in modeling neural systems and the study of brain function. Currently, many simulators using CPU or GPU have been developed. However, these s...
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Chapter and Conference Paper
Diabetic Retinopathy Grading Base on Contrastive Learning and Semi-supervised Learning
The diabetic retinopathy (DR) detection based on deep learning is a powerful tool for early screening of DR. Although several automatic DR grading algorithms have been proposed, their performance is still limi...
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Chapter and Conference Paper
An Efficient Greedy Incremental Sequence Clustering Algorithm
Gene sequence clustering is very basic and important in computational biology and bioinformatics for the study of phylogenetic relationships and gene function prediction, etc. With the rapid growth of the amou...
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Chapter and Conference Paper
Predicting Microbe-Disease Association via Tripartite Network and Relation Graph Convolutional Network
Many evidences show that microbes play vital roles in human health and diseases. Thus, predicting microbe-disease associations is helpful for disease prevention. In this study, we propose a predictive model ca...
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Chapter and Conference Paper
Predicting Drug Drug Interactions by Signed Graph Filtering-Based Convolutional Networks
Drug drug interactions (DDIs) are crucial for drug research and pharmacologia. Recently, graph neural networks (GNNs) have handled these interactions successfully and shown great predictive performance, but mo...
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Chapter and Conference Paper
High-Performance Systems for in Silico Microscopy Imaging Studies
High-resolution medical images from advanced instruments provide rich information about morphological and functional characteristics of biological systems. However, most of the information available in biomedi...
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Chapter and Conference Paper
COE: A General Approach for Efficient Genome-Wide Two-Locus Epistasis Test in Disease Association Study
The availability of high density single nucleotide polymorphisms (SNPs) data has made genome-wide association study computationally challenging. Two-locus epistasis (gene-gene interaction) detection has attrac...
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Chapter and Conference Paper
Using Multi-scale Glide Zoom Window Feature Extraction Approach to Predict Protein Homo-oligomer Types
The concept of multi-scale glide zoom window was proposed and a novel approach of multi-scale glide zoom window feature extraction was used for predicting protein homo-oligomers. Based on the concept of multi-...
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Chapter and Conference Paper
Using Decision Templates to Predict Subcellular Localization of Protein
Theoretical and computational methods for the prediction of protein subcellular localization have been proposed and are develo** continuously. Many representations of protein sequence are proposed but a new ...
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Chapter and Conference Paper
Prediction of Protein Subcellular Localizations Using Moment Descriptors and Support Vector Machine
As more and more genomes have been discovered in recent years, it is an urgent need to develop a reliable method to predict protein subcellular localization for further function exploration. However many well-...
