Circular RNAs and complex diseases: from experimental results to computational models
Circular RNAs (circRNAs) are a class of single-stranded, covalently closed RNA molecules
with a variety of biological functions. Studies have shown that circRNAs are involved in a …
with a variety of biological functions. Studies have shown that circRNAs are involved in a …
A deep learning method for predicting metabolite–disease associations via graph neural network
F Sun, J Sun, Q Zhao - Briefings in bioinformatics, 2022 - academic.oup.com
Metabolism is the process by which an organism continuously replaces old substances with
new substances. It plays an important role in maintaining human life, body growth and …
new substances. It plays an important role in maintaining human life, body growth and …
Predicting metabolite–disease associations based on auto-encoder and non-negative matrix factorization
H Gao, J Sun, Y Wang, Y Lu, L Liu… - Briefings in …, 2023 - academic.oup.com
Metabolism refers to a series of orderly chemical reactions used to maintain life activities in
organisms. In healthy individuals, metabolism remains within a normal range. However …
organisms. In healthy individuals, metabolism remains within a normal range. However …
scAAGA: Single cell data analysis framework using asymmetric autoencoder with gene attention
R Meng, S Yin, J Sun, H Hu, Q Zhao - Computers in biology and medicine, 2023 - Elsevier
In recent years, single-cell RNA sequencing (scRNA-seq) has emerged as a powerful
technique for investigating cellular heterogeneity and structure. However, analyzing scRNA …
technique for investigating cellular heterogeneity and structure. However, analyzing scRNA …
MK-FSVM-SVDD: a multiple kernel-based fuzzy SVM model for predicting DNA-binding proteins via support vector data description
Y Zou, H Wu, X Guo, L Peng, Y Ding… - Current …, 2021 - ingentaconnect.com
Background: Detecting DNA-binding proteins (DBPs) based on biological and chemical
methods is time-consuming and expensive. Objective: In recent years, the rise of …
methods is time-consuming and expensive. Objective: In recent years, the rise of …
Identification of drug–target interactions via dual laplacian regularized least squares with multiple kernel fusion
Abstract Detection of Drug–Target Interactions (DTIs) is the time-consuming and laborious
experiment via biochemical approaches. Machine learning based methods have been …
experiment via biochemical approaches. Machine learning based methods have been …
[HTML][HTML] Identify DNA-binding proteins through the extreme gradient boosting algorithm
Z Zhao, W Yang, Y Zhai, Y Liang, Y Zhao - Frontiers in Genetics, 2022 - frontiersin.org
The exploration of DNA-binding proteins (DBPs) is an important aspect of studying
biological life activities. Research on life activities requires the support of scientific research …
biological life activities. Research on life activities requires the support of scientific research …
DCAMCP: A deep learning model based on capsule network and attention mechanism for molecular carcinogenicity prediction
Z Chen, L Zhang, J Sun, R Meng… - Journal of cellular and …, 2023 - Wiley Online Library
The carcinogenicity of drugs can have a serious impact on human health, so carcinogenicity
testing of new compounds is very necessary before being put on the market. Currently, many …
testing of new compounds is very necessary before being put on the market. Currently, many …
[HTML][HTML] Predicting lncRNA–miRNA interactions based on interactome network and graphlet interaction
In the development and treatment of many human diseases, the regulatory roles between
lncRNAs and miRNAs are important, but much remains unknown about them; moreover …
lncRNAs and miRNAs are important, but much remains unknown about them; moreover …
[HTML][HTML] Hierarchical graph attention network for miRNA-disease association prediction
Many biological studies show that the mutation and abnormal expression of microRNAs
(miRNAs) could cause a variety of diseases. As an important biomarker for disease …
(miRNAs) could cause a variety of diseases. As an important biomarker for disease …