A review on the computational approaches for gene regulatory network construction
LE Chai, SK Loh, ST Low, MS Mohamad… - Computers in biology …, 2014 - Elsevier
Many biological research areas such as drug design require gene regulatory networks to
provide clear insight and understanding of the cellular process in living cells. This is …
provide clear insight and understanding of the cellular process in living cells. This is …
A survey of gene regulatory networks modelling methods: from differential equations, to Boolean and qualitative bioinspired models
Abstract Gene Regulatory Networks (GRNs) represent the interactions among genes
regulating the activation of specific cell functionalities, such as reception of (chemical) …
regulating the activation of specific cell functionalities, such as reception of (chemical) …
Chapter 5: Network biology approach to complex diseases
DY Cho, YA Kim, TM Przytycka - PLoS computational biology, 2012 - journals.plos.org
Complex diseases are caused by a combination of genetic and environmental factors.
Uncovering the molecular pathways through which genetic factors affect a phenotype is …
Uncovering the molecular pathways through which genetic factors affect a phenotype is …
Autoregressive models for gene regulatory network inference: Sparsity, stability and causality issues
G Michailidis, F d'Alché-Buc - Mathematical biosciences, 2013 - Elsevier
Reconstructing gene regulatory networks from high-throughput measurements represents a
key problem in functional genomics. It also represents a canonical learning problem and …
key problem in functional genomics. It also represents a canonical learning problem and …
WASABI: a dynamic iterative framework for gene regulatory network inference
A Bonnaffoux, U Herbach, A Richard, A Guillemin… - BMC …, 2019 - Springer
Background Inference of gene regulatory networks from gene expression data has been a
long-standing and notoriously difficult task in systems biology. Recently, single-cell …
long-standing and notoriously difficult task in systems biology. Recently, single-cell …
Reconstructing gene regulatory networks from knock-out data using Gaussian Noise Model and Pearson Correlation Coefficient
A gene regulatory network (GRN) is a large and complex network consisting of interacting
elements that, over time, affect each other's state. The dynamics of complex gene regulatory …
elements that, over time, affect each other's state. The dynamics of complex gene regulatory …
Bayesian inference identifies combination therapeutic targets in breast cancer
Objective: Breast cancer is the second leading cause of cancer death among US women;
hence, identifying potential drug targets is an ever increasing need. In this paper, we …
hence, identifying potential drug targets is an ever increasing need. In this paper, we …
Dynamic Bayesian network learning to infer sparse models from time series gene expression data
One of the key challenges in systems biology is to derive gene regulatory networks (GRNs)
from complex high-dimensional sparse data. Bayesian networks (BNs) and dynamic …
from complex high-dimensional sparse data. Bayesian networks (BNs) and dynamic …
Asymptotic stability of Markovian switching genetic regulatory networks with leakage and mode-dependent time delays
K Ratnavelu, M Kalpana… - Journal of the Franklin …, 2016 - Elsevier
The problem of stability analysis of Markovian switching genetic regulatory networks (GRNs)
with leakage and mode-dependent time-varying delays along Brownian motions is reported …
with leakage and mode-dependent time-varying delays along Brownian motions is reported …
Dynamic Bayesian network modeling of the interplay between EGFR and Hedgehog signaling
Aberrant activation of sonic Hegdehog (SHH) signaling has been found to disrupt cellular
differentiation in many human cancers and to increase proliferation. The SHH pathway is …
differentiation in many human cancers and to increase proliferation. The SHH pathway is …