Graph representation learning in bioinformatics: trends, methods and applications

HC Yi, ZH You, DS Huang… - Briefings in …, 2022 - academic.oup.com
Graph is a natural data structure for describing complex systems, which contains a set of
objects and relationships. Ubiquitous real-life biomedical problems can be modeled as …

Machine learning for integrating data in biology and medicine: Principles, practice, and opportunities

M Zitnik, F Nguyen, B Wang, J Leskovec… - Information …, 2019 - Elsevier
New technologies have enabled the investigation of biology and human health at an
unprecedented scale and in multiple dimensions. These dimensions include a myriad of …

Predicting miRNA–disease association based on inductive matrix completion

X Chen, L Wang, J Qu, NN Guan, JQ Li - Bioinformatics, 2018 - academic.oup.com
Motivation It has been shown that microRNAs (miRNAs) play key roles in variety of
biological processes associated with human diseases. In Consideration of the cost and …

Random walks: A review of algorithms and applications

F **a, J Liu, H Nie, Y Fu, L Wan… - IEEE Transactions on …, 2019 - ieeexplore.ieee.org
A random walk is known as a random process which describes a path including a
succession of random steps in the mathematical space. It has increasingly been popular in …

A review on machine learning principles for multi-view biological data integration

Y Li, FX Wu, A Ngom - Briefings in bioinformatics, 2018 - academic.oup.com
Driven by high-throughput sequencing techniques, modern genomic and clinical studies are
in a strong need of integrative machine learning models for better use of vast volumes of …

Updated review of advances in microRNAs and complex diseases: experimental results, databases, webservers and data fusion

L Huang, L Zhang, X Chen - Briefings in bioinformatics, 2022 - academic.oup.com
MicroRNAs (miRNAs) are gene regulators involved in the pathogenesis of complex
diseases such as cancers, and thus serve as potential diagnostic markers and therapeutic …

Application of machine learning in microbiology

K Qu, F Guo, X Liu, Y Lin, Q Zou - Frontiers in microbiology, 2019 - frontiersin.org
Microorganisms are ubiquitous and closely related to people's daily lives. Since they were
first discovered in the 19th century, researchers have shown great interest in …

M6APred-EL: a sequence-based predictor for identifying N6-methyladenosine sites using ensemble learning

L Wei, H Chen, R Su - Molecular Therapy-Nucleic Acids, 2018 - cell.com
N6-methyladenosine (m 6 A) modification is the most abundant RNA methylation
modification and involves various biological processes, such as RNA splicing and …

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 …

Hierarchical graph attention network for miRNA-disease association prediction

Z Li, T Zhong, D Huang, ZH You, R Nie - Molecular Therapy, 2022 - cell.com
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 …