Time-Based Systems Biology Approaches to Capture and Model Dynamic Gene Regulatory Networks

2021 ◽  
Vol 72 (1) ◽  
Author(s):  
Jose M. Alvarez ◽  
Matthew D. Brooks ◽  
Joseph Swift ◽  
Gloria M. Coruzzi
Keyword(s):  
Systems Biology ◽  
Gene Regulatory Networks ◽  
Regulatory Networks ◽  
Environmental Changes ◽  
Annual Review ◽  
Publication Date ◽  
Learning Approaches ◽  
Dynamic Events ◽  
Genome Wide ◽  
Gene Regulatory

All aspects of transcription and its regulation involve dynamic events. However, capturing these dynamic events in gene regulatory networks (GRNs) offers both a promise and a challenge. The promise is that capturing and modeling the dynamic changes in GRNs will allow us to understand how organisms adapt to a changing environment. The ability to mount a rapid transcriptional response to environmental changes is especially important in nonmotile organisms such as plants. The challenge is to capture these dynamic, genome-wide events and model them in GRNs. In this review, we cover recent progress in capturing dynamic interactions of transcription factors with their targets—at both the local and genome-wide levels—and using them to learn how GRNs operate as a function of time. We also discuss recent advances that employ time-based machine learning approaches to forecast gene expression at future time points, a key goal of systems biology. Expected final online publication date for the Annual Review of Plant Biology, Volume 72 is May 2021. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Beyond Casual Resemblances: Rigorous Frameworks for Comparing Regeneration Across Species

2021 ◽  
Vol 37 (1) ◽  
Author(s):  
Mansi Srivastava
Keyword(s):  
Gene Regulatory Networks ◽  
Regulatory Networks ◽  
Evolutionary History ◽  
Adult Stem Cells ◽  
Annual Review ◽  
Publication Date ◽  
Animal Phyla ◽  
History Of ◽  
Gene Regulatory ◽  
Unifying Principles

The majority of animal phyla have species that can regenerate. Comparing regeneration across animals can reconstruct the molecular and cellular evolutionary history of this process. Recent studies have revealed some similarity in regeneration mechanisms, but rigorous comparative methods are needed to assess whether these resemblances are ancestral pathways (homology) or are the result of convergent evolution (homoplasy). This review aims to provide a framework for comparing regeneration across animals, focusing on gene regulatory networks (GRNs), which are substrates for assessing process homology. The homology of the wound-induced activation of Wnt signaling and of adult stem cells are discussed as examples of ongoing studies of regeneration that enable comparisons in a GRN framework. Expanding the study of regeneration GRNs in currently studied species and broadening taxonomic sampling for these approaches will identify processes that are unifying principles of regeneration biology across animals. These insights are important both for evolutionary studies of regeneration and for human regenerative medicine. Expected final online publication date for the Annual Review of Cell and Developmental Biology, Volume 37 is October 2021. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

scholarly journals Inference of gene regulatory networks from genome-wide knockout fitness data

2012 ◽  
Vol 29 (3) ◽  
pp. 338-346 ◽  
Author(s):  
L. Wang ◽  
X. Wang ◽  
A. P. Arkin ◽  
M. S. Samoilov
Keyword(s):  
Gene Regulatory Networks ◽  
Regulatory Networks ◽  
Genome Wide ◽  
Gene Regulatory

scholarly journals Improving gene regulatory network structure using redundancy reduction in the MRNET algorithm

RSC Advances ◽  
2017 ◽  
Vol 7 (37) ◽  
pp. 23222-23233 ◽  
Author(s):  
Wei Liu ◽  
Wen Zhu ◽  
Bo Liao ◽  
Haowen Chen ◽  
Siqi Ren ◽  
...  
Keyword(s):  
Systems Biology ◽  
Gene Regulatory Network ◽  
Gene Regulatory Networks ◽  
Network Structure ◽  
Regulatory Network ◽  
Regulatory Networks ◽  
Central Problem ◽  
Expression Data ◽  
Redundancy Reduction ◽  
Gene Regulatory

Inferring gene regulatory networks from expression data is a central problem in systems biology.

Dissecting Organismal Morphogenesis by Bridging Genetics and Biophysics

2021 ◽  
Vol 55 (1) ◽  
Author(s):  
Nikhil Mishra ◽  
Carl-Philipp Heisenberg
Keyword(s):  
Cell Fate ◽  
Regulatory Networks ◽  
Annual Review ◽  
Publication Date ◽  
Technological Advances ◽  
Complex Shapes ◽  
Gene Regulatory ◽  
And Mathematics ◽  
Multicellular Organisms ◽  
Shape Changes

Multicellular organisms develop complex shapes from much simpler, single-celled zygotes through a process commonly called morphogenesis. Morphogenesis involves an interplay between several factors, ranging from the gene regulatory networks determining cell fate and differentiation to the mechanical processes underlying cell and tissue shape changes. Thus, the study of morphogenesis has historically been based on multidisciplinary approaches at the interface of biology with physics and mathematics. Recent technological advances have further improved our ability to study morphogenesis by bridging the gap between the genetic and biophysical factors through the development of new tools for visualizing, analyzing, and perturbing these factors and their biochemical intermediaries. Here, we review how a combination of genetic, microscopic, biophysical, and biochemical approaches has aided our attempts to understand morphogenesis and discuss potential approaches that may be beneficial to such an inquiry in the future. Expected final online publication date for the Annual Review of Genetics, Volume 55 is November 2021. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

scholarly journals Chip-seq and gene expression data for the identification of functional sub-pathways: a proof of concept in lung cancer

2020 ◽  
Author(s):  
Xanthoula Atsalaki ◽  
Lefteris Koumakis ◽  
George Potamias ◽  
Manolis Tsiknakis
Keyword(s):  
Gene Expression ◽  
Lung Cancer ◽  
Systems Biology ◽  
Gene Expression Data ◽  
Gene Regulatory Networks ◽  
Regulatory Networks ◽  
Molecular Mechanisms ◽  
Integrative Approach ◽  
Expression Data ◽  
Gene Regulatory

AbstractHigh-throughput technologies, such as chromatin immunoprecipitation (ChIP) with massively parallel sequencing (ChIP-seq) have enabled cost and time efficient generation of immense amount of genome data. The advent of advanced sequencing techniques allowed biologists and bioinformaticians to investigate biological aspects of cell function and understand or reveal unexplored disease etiologies. Systems biology attempts to formulate the molecular mechanisms in mathematical models and one of the most important areas is the gene regulatory networks (GRNs), a collection of DNA segments that somehow interact with each other. GRNs incorporate valuable information about molecular targets that can be corellated to specific phenotype.In our study we highlight the need to develop new explorative tools and approaches for the integration of different types of -omics data such as ChIP-seq and GRNs using pathway analysis methodologies. We present an integrative approach for ChIP-seq and gene expression data on GRNs. Using public microarray expression samples for lung cancer and healthy subjects along with the KEGG human gene regulatory networks, we identified ways to disrupt functional sub-pathways on lung cancer with the aid of CTCF ChIP-seq data, as a proof of concept.We expect that such a systems biology pipeline could assist researchers to identify corellations and causality of transcription factors over functional or disrupted biological sub-pathways.

Sign in / Sign up

Export Citation Format

Share Document