Graph representation learning in bioinformatics: trends, methods and applications
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 …
objects and relationships. Ubiquitous real-life biomedical problems can be modeled as …
Graph neural network approaches for drug-target interactions
Developing new drugs remains prohibitively expensive, time-consuming, and often involves
safety issues. Accurate prediction of drug-target interactions (DTIs) can guide the drug …
safety issues. Accurate prediction of drug-target interactions (DTIs) can guide the drug …
miRNet 2.0: network-based visual analytics for miRNA functional analysis and systems biology
Abstract miRNet is an easy-to-use, web-based platform designed to help elucidate
microRNA (miRNA) functions by integrating users' data with existing knowledge via network …
microRNA (miRNA) functions by integrating users' data with existing knowledge via network …
A modern approach towards an industry 4.0 model: From driving technologies to management
Every so often, a confluence of novel technologies emerges that radically transforms every
aspect of the industry, the global economy, and finally, the way we live. These sharp leaps of …
aspect of the industry, the global economy, and finally, the way we live. These sharp leaps of …
[HTML][HTML] A guide to conquer the biological network era using graph theory
Networks are one of the most common ways to represent biological systems as complex sets
of binary interactions or relations between different bioentities. In this article, we discuss the …
of binary interactions or relations between different bioentities. In this article, we discuss the …
Circuit and molecular architecture of a ventral hippocampal network
The ventral hippocampus (vHPC) is a critical hub in networks that process emotional
information. While recent studies have indicated that ventral CA1 (vCA1) projection neurons …
information. While recent studies have indicated that ventral CA1 (vCA1) projection neurons …
[HTML][HTML] Microbiome multi-omics network analysis: statistical considerations, limitations, and opportunities
The advent of large-scale microbiome studies affords newfound analytical opportunities to
understand how these communities of microbes operate and relate to their environment …
understand how these communities of microbes operate and relate to their environment …
PaintOmics 4: new tools for the integrative analysis of multi-omics datasets supported by multiple pathway databases
PaintOmics is a web server for the integrative analysis and visualisation of multi-omics
datasets using biological pathway maps. PaintOmics 4 has several notable updates that …
datasets using biological pathway maps. PaintOmics 4 has several notable updates that …
Toward heterogeneous information fusion: bipartite graph convolutional networks for in silico drug repurposing
Motivation Mining drug–disease association and related interactions are essential for
developing in silico drug repurposing (DR) methods and understanding underlying …
developing in silico drug repurposing (DR) methods and understanding underlying …
Methods for depicting overlap in overviews of systematic reviews: an introduction to static tabular and graphical displays
KI Bougioukas, E Vounzoulaki, CD Mantsiou… - Journal of Clinical …, 2021 - Elsevier
Abstract Background and Objective To introduce potential static tabular and graphical
techniques for visually presenting overlap between systematic reviews (SRs) included in …
techniques for visually presenting overlap between systematic reviews (SRs) included in …