Progresses and challenges in link prediction
T Zhou - Iscience, 2021 - cell.com
Link prediction is a paradigmatic problem in network science, which aims at estimating the
existence likelihoods of nonobserved links, based on known topology. After a brief …
existence likelihoods of nonobserved links, based on known topology. After a brief …
A comprehensive survey on computational methods of non-coding RNA and disease association prediction
The studies on relationships between non-coding RNAs and diseases are widely carried out
in recent years. A large number of experimental methods and technologies of producing …
in recent years. A large number of experimental methods and technologies of producing …
A weighted bilinear neural collaborative filtering approach for drug repositioning
Drug repositioning is an efficient and promising strategy for traditional drug discovery and
development. Many research efforts are focused on utilizing deep-learning approaches …
development. Many research efforts are focused on utilizing deep-learning approaches …
NCMCMDA: miRNA–disease association prediction through neighborhood constraint matrix completion
Emerging evidence shows that microRNAs (miRNAs) play a critical role in diverse
fundamental and important biological processes associated with human diseases. Inferring …
fundamental and important biological processes associated with human diseases. Inferring …
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 …
GANLDA: graph attention network for lncRNA-disease associations prediction
Increasing studies have indicated that long non-coding RNAs (lncRNAs) play important
roles in many physiological and pathological pathways. Identifying lncRNA-disease …
roles in many physiological and pathological pathways. Identifying lncRNA-disease …
DeepLGP: a novel deep learning method for prioritizing lncRNA target genes
Motivation Although long non-coding RNAs (lncRNAs) have limited capacity for encoding
proteins, they have been verified as biomarkers in the occurrence and development of …
proteins, they have been verified as biomarkers in the occurrence and development of …
CapsNet-LDA: predicting lncRNA-disease associations using attention mechanism and capsule network based on multi-view data
Z Zhang, J Xu, Y Wu, N Liu, Y Wang… - Briefings in …, 2023 - academic.oup.com
Cumulative studies have shown that many long non-coding RNAs (lncRNAs) are crucial in a
number of diseases. Predicting potential lncRNA-disease associations (LDAs) can facilitate …
number of diseases. Predicting potential lncRNA-disease associations (LDAs) can facilitate …
A survey of matrix completion methods for recommendation systems
In recent years, the recommendation systems have become increasingly popular and have
been used in a broad variety of applications. Here, we investigate the matrix completion …
been used in a broad variety of applications. Here, we investigate the matrix completion …
iCircDA-MF: identification of circRNA-disease associations based on matrix factorization
H Wei, B Liu - Briefings in bioinformatics, 2020 - academic.oup.com
Circular RNAs (circRNAs) are a group of novel discovered non-coding RNAs with closed-
loop structure, which play critical roles in various biological processes. Identifying …
loop structure, which play critical roles in various biological processes. Identifying …