Graph neural networks and their current applications in bioinformatics
XM Zhang, L Liang, L Liu, MJ Tang - Frontiers in genetics, 2021 - frontiersin.org
Graph neural networks (GNNs), as a branch of deep learning in non-Euclidean space,
perform particularly well in various tasks that process graph structure data. With the rapid …
perform particularly well in various tasks that process graph structure data. With the rapid …
Long non-coding RNAs and complex diseases: from experimental results to computational models
LncRNAs have attracted lots of attentions from researchers worldwide in recent decades.
With the rapid advances in both experimental technology and computational prediction …
With the rapid advances in both experimental technology and computational prediction …
LncRNADisease 2.0: an updated database of long non-coding RNA-associated diseases
Mounting evidence suggested that dysfunction of long non-coding RNAs (lncRNAs) is
involved in a wide variety of diseases. A knowledgebase with systematic collection and …
involved in a wide variety of diseases. A knowledgebase with systematic collection and …
RNADisease v4. 0: an updated resource of RNA-associated diseases, providing RNA-disease analysis, enrichment and prediction
J Chen, J Lin, Y Hu, M Ye, L Yao, L Wu… - Nucleic Acids …, 2023 - academic.oup.com
Numerous studies have shown that RNA plays an important role in the occurrence and
development of diseases, and RNA-disease associations are not limited to noncoding RNAs …
development of diseases, and RNA-disease associations are not limited to noncoding RNAs …
Prediction of lncRNA–disease associations based on inductive matrix completion
Motivation Accumulating evidences indicate that long non-coding RNAs (lncRNAs) play
pivotal roles in various biological processes. Mutations and dysregulations of lncRNAs are …
pivotal roles in various biological processes. Mutations and dysregulations of lncRNAs are …
MNDR v3. 0: mammal ncRNA–disease repository with increased coverage and annotation
L Ning, T Cui, B Zheng, N Wang, J Luo… - Nucleic Acids …, 2021 - academic.oup.com
Many studies have indicated that non-coding RNA (ncRNA) dysfunction is closely related to
numerous diseases. Recently, accumulated ncRNA–disease associations have made …
numerous diseases. Recently, accumulated ncRNA–disease associations have made …
DincRNA: a comprehensive web-based bioinformatics toolkit for exploring disease associations and ncRNA function
DincRNA aims to provide a comprehensive web-based bioinformatics toolkit to elucidate the
entangled relationships among diseases and non-coding RNAs (ncRNAs) from the …
entangled relationships among diseases and non-coding RNAs (ncRNAs) from the …
An immune-related six-lncRNA signature to improve prognosis prediction of glioblastoma multiforme
Recent studies have demonstrated the utility and superiority of long non-coding RNAs
(lncRNAs) as novel biomarkers for cancer diagnosis, prognosis, and therapy. In the present …
(lncRNAs) as novel biomarkers for cancer diagnosis, prognosis, and therapy. In the present …
LDAP: a web server for lncRNA-disease association prediction
Motivation Increasing evidences have demonstrated that long noncoding RNAs (lncRNAs)
play important roles in many human diseases. Therefore, predicting novel lncRNA-disease …
play important roles in many human diseases. Therefore, predicting novel lncRNA-disease …
Matrix factorization-based data fusion for the prediction of lncRNA–disease associations
Abstract Motivation Long non-coding RNAs (lncRNAs) play crucial roles in complex disease
diagnosis, prognosis, prevention and treatment, but only a small portion of lncRNA–disease …
diagnosis, prognosis, prevention and treatment, but only a small portion of lncRNA–disease …