A comprehensive overview and critical evaluation of gene regulatory network inference technologies
Gene regulatory network (GRN) is the important mechanism of maintaining life process,
controlling biochemical reaction and regulating compound level, which plays an important …
controlling biochemical reaction and regulating compound level, which plays an important …
[HTML][HTML] Review of biological network data and its applications
Studying biological networks, such as protein-protein interactions, is key to understanding
complex biological activities. Various types of large-scale biological datasets have been …
complex biological activities. Various types of large-scale biological datasets have been …
Personalized characterization of diseases using sample-specific networks
A complex disease generally results not from malfunction of individual molecules but from
dysfunction of the relevant system or network, which dynamically changes with time and …
dysfunction of the relevant system or network, which dynamically changes with time and …
dynGENIE3: dynamical GENIE3 for the inference of gene networks from time series expression data
The elucidation of gene regulatory networks is one of the major challenges of systems
biology. Measurements about genes that are exploited by network inference methods are …
biology. Measurements about genes that are exploited by network inference methods are …
STGRNS: an interpretable transformer-based method for inferring gene regulatory networks from single-cell transcriptomic data
J Xu, A Zhang, F Liu, X Zhang - Bioinformatics, 2023 - academic.oup.com
Motivation Single-cell RNA-sequencing (scRNA-seq) technologies provide an opportunity to
infer cell-specific gene regulatory networks (GRNs), which is an important challenge in …
infer cell-specific gene regulatory networks (GRNs), which is an important challenge in …
Inferring gene regulatory networks using the improved Markov blanket discovery algorithm
W Liu, Y Jiang, L Peng, X Sun, W Gan, Q Zhao… - Interdisciplinary …, 2022 - Springer
Inferring gene regulatory networks (GRNs) from microarray data can help us understand the
mechanisms of life and eventually develop effective therapies. Currently, many …
mechanisms of life and eventually develop effective therapies. Currently, many …
Inference of gene regulatory network based on local Bayesian networks
F Liu, SW Zhang, WF Guo, ZG Wei… - PLoS computational …, 2016 - journals.plos.org
The inference of gene regulatory networks (GRNs) from expression data can mine the direct
regulations among genes and gain deep insights into biological processes at a network …
regulations among genes and gain deep insights into biological processes at a network …
Conditional mutual inclusive information enables accurate quantification of associations in gene regulatory networks
Mutual information (MI), a quantity describing the nonlinear dependence between two
random variables, has been widely used to construct gene regulatory networks (GRNs) …
random variables, has been widely used to construct gene regulatory networks (GRNs) …
EMODMI: A multi-objective optimization based method to identify disease modules
After decades of research, it has been widely recognized that complex diseases are caused
by the dysfunction of biological systems induced by disease-associated genes. To …
by the dysfunction of biological systems induced by disease-associated genes. To …
Detecting tissue-specific early warning signals for complex diseases based on dynamical network biomarkers: study of type 2 diabetes by cross-tissue analysis
Identifying early warning signals of critical transitions during disease progression is a key to
achieving early diagnosis of complex diseases. By exploiting rich information of high …
achieving early diagnosis of complex diseases. By exploiting rich information of high …