The rise of nonnegative matrix factorization: algorithms and applications
YT Guo, QQ Li, CS Liang - Information Systems, 2024 - Elsevier
Although nonnegative matrix factorization (NMF) is widely used, some matrix factorization
methods result in misleading results and waste of computing resources due to lack of timely …
methods result in misleading results and waste of computing resources due to lack of timely …
LMI-DForest: A deep forest model towards the prediction of lncRNA-miRNA interactions
The interactions between miRNAs and long non-coding RNAs (lncRNAs) are subject to
intensive recent studies due to its critical role in gene regulations. Computational prediction …
intensive recent studies due to its critical role in gene regulations. Computational prediction …
[HTML][HTML] A heterogeneous information network learning model with neighborhood-level structural representation for predicting lncRNA-miRNA interactions
Long non-coding RNAs (lncRNAs) and microRNAs (miRNAs) are closely related to the
treatment of human diseases. Traditional biological experiments often require time …
treatment of human diseases. Traditional biological experiments often require time …
MiRNA-Disease association prediction via non-negative matrix factorization based matrix completion
X Zheng, C Zhang, C Wan - Signal Processing, 2022 - Elsevier
A large number of biological studies have shown that microRNAs (miRNAs) are closely
related to the occurrence and development of various human diseases. Nowadays, more …
related to the occurrence and development of various human diseases. Nowadays, more …
A survey of computational methods and databases for lncRNA-miRNA interaction prediction
Long non-coding RNAs (lncRNAs) and microRNAs (miRNAs) are two prevalent non-coding
RNAs in current research. They play critical regulatory roles in the life processes of animals …
RNAs in current research. They play critical regulatory roles in the life processes of animals …
Sparse dual graph-regularized deep nonnegative matrix factorization for image clustering
W Guo - IEEE access, 2021 - ieeexplore.ieee.org
Deep nonnegative matrix factorization (Deep NMF) as an emerging technique for image
clustering has attracted more and more attention. This is because it can effectively reduce …
clustering has attracted more and more attention. This is because it can effectively reduce …
SEBGLMA: Semantic Embedded Bipartite Graph Network for Predicting lncRNA‐miRNA Associations
ZY Zhao, J Lin, Z Wang, JX Guo… - … Journal of Intelligent …, 2023 - Wiley Online Library
Identifying the association between long noncoding RNA (lncRNA) and micro‐RNA (miRNA)
is of great significance for the treatment of diseases by interfering with the combination of …
is of great significance for the treatment of diseases by interfering with the combination of …
ACLNDA: an asymmetric graph contrastive learning framework for predicting noncoding RNA–disease associations in heterogeneous graphs
L Fu, ZY Yao, Y Zhou, Q Peng… - Briefings in …, 2024 - academic.oup.com
Noncoding RNAs (ncRNAs), including long noncoding RNAs (lncRNAs) and microRNAs
(miRNAs), play crucial roles in gene expression regulation and are significant in disease …
(miRNAs), play crucial roles in gene expression regulation and are significant in disease …
Bot-net: a lightweight bag of tricks-based neural network for efficient lncrna–mirna interaction prediction
Background and objective: Interactions of long non-coding ribonucleic acids (lncRNAs) with
micro-ribonucleic acids (miRNAs) play an essential role in gene regulation, cellular …
micro-ribonucleic acids (miRNAs) play an essential role in gene regulation, cellular …
DeepWalk based method to predict lncRNA-miRNA associations via lncRNA-miRNA-disease-protein-drug graph
L Yang, LP Li, HC Yi - BMC bioinformatics, 2022 - Springer
Abstract Background Long non-coding RNAs (lncRNAs) play a crucial role in diverse
biological processes and have been confirmed to be concerned with various diseases …
biological processes and have been confirmed to be concerned with various diseases …