scholarly journals Information Thermodynamics and Reducibility of Large Gene Networks

Entropy ◽  
2021 ◽  
Vol 23 (1) ◽  
pp. 63
Author(s):  
Swarnavo Sarkar ◽  
Joseph B. Hubbard ◽  
Michael Halter ◽  
Anne L. Plant
Keyword(s):  
Free Energy ◽  
Gene Networks ◽  
Regulatory Networks ◽  
Information Loss ◽  
The State ◽  
Small Subset ◽  
Information Theoretic ◽  
Relative Free Energy ◽  
Large Gene ◽  
New Perspective

Gene regulatory networks (GRNs) control biological processes like pluripotency, differentiation, and apoptosis. Omics methods can identify a large number of putative network components (on the order of hundreds or thousands) but it is possible that in many cases a small subset of genes control the state of GRNs. Here, we explore how the topology of the interactions between network components may indicate whether the effective state of a GRN can be represented by a small subset of genes. We use methods from information theory to model the regulatory interactions in GRNs as cascading and superposing information channels. We propose an information loss function that enables identification of the conditions by which a small set of genes can represent the state of all the other genes in the network. This information-theoretic analysis extends to a measure of free energy change due to communication within the network, which provides a new perspective on the reducibility of GRNs. Both the information loss and relative free energy depend on the density of interactions and edge communication error in a network. Therefore, this work indicates that a loss in mutual information between genes in a GRN is directly coupled to a thermodynamic cost, i.e., a reduction of relative free energy, of the system.

STRUCTURAL PRINCIPLES FOR COMPLEX DYNAMICS IN GLASS NETWORKS

2011 ◽  
Vol 21 (01) ◽  
pp. 237-254 ◽  
Author(s):  
LINGHONG LU ◽  
RODERICK EDWARDS
Keyword(s):  
Gene Networks ◽  
Regulatory Networks ◽  
State Transition ◽  
Complex Dynamics ◽  
Piecewise Linear ◽  
Expression Patterns ◽  
The State ◽  
Complex Behavior ◽  
Transition Diagram ◽  
State Transition Diagram

Gene-regulatory networks are potentially capable of more complex behavior than convergence to a stationary state, or even cycling through a simple sequence of expression patterns. The analysis of qualitative dynamics for these networks is facilitated by using piecewise-linear equations and its state transition diagram (an n-dimensional hypercube, in the case of n genes with a single effective threshold for the protein product of each). Our previous work has dealt with cycles of states in the state transition diagram that allow periodic solutions. Here, we study a particular kind of figure-8 pattern in the state transition diagram and determine conditions that allow complex behavior. Previous studies of complex behavior, such as chaos, in such networks have dealt only with specific examples. Our approach allows an appreciation of the design principles that give rise to complex dynamics, which may have application in assessing the dynamical possibilities of gene networks with poorly known parameters, or for synthesis or control of gene networks with complex behavior.

scholarly journals Single cell RNA-seq reveals genes vital to in vitro fertilized embryos and parthenotes in pigs

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Zhi-Qiang Du ◽  
Hao Liang ◽  
Xiao-Man Liu ◽  
Yun-Hua Liu ◽  
Chonglong Wang ◽  
...  
Keyword(s):  
Embryo Development ◽  
Gene Networks ◽  
Regulatory Networks ◽  
Rna Binding ◽  
Expression Patterns ◽  
Early Embryo ◽  
Specific Factor ◽  
Early Embryos ◽  
Genome Activation

AbstractSuccessful early embryo development requires the correct reprogramming and configuration of gene networks by the timely and faithful execution of zygotic genome activation (ZGA). However, the regulatory principle of molecular elements and circuits fundamental to embryo development remains largely obscure. Here, we profiled the transcriptomes of single zygotes and blastomeres, obtained from in vitro fertilized (IVF) or parthenogenetically activated (PA) porcine early embryos (1- to 8-cell), focusing on the gene expression dynamics and regulatory networks associated with maternal-to-zygote transition (MZT) (mainly maternal RNA clearance and ZGA). We found that minor and major ZGAs occur at 1-cell and 4-cell stages for both IVF and PA embryos, respectively. Maternal RNAs gradually decay from 1- to 8-cell embryos. Top abundantly expressed genes (CDV3, PCNA, CDR1, YWHAE, DNMT1, IGF2BP3, ARMC1, BTG4, UHRF2 and gametocyte-specific factor 1-like) in both IVF and PA early embryos identified are of vital roles for embryo development. Differentially expressed genes within IVF groups are different from that within PA groups, indicating bi-parental and maternal-only embryos have specific sets of mRNAs distinctly decayed and activated. Pathways enriched from DEGs showed that RNA associated pathways (RNA binding, processing, transport and degradation) could be important. Moreover, mitochondrial RNAs are found to be actively transcribed, showing dynamic expression patterns, and for DNA/H3K4 methylation and transcription factors as well. Taken together, our findings provide an important resource to investigate further the epigenetic and genome regulation of MZT events in early embryos of pigs.

scholarly journals Relative free energy of binding between antimicrobial peptides and SDS or DPC micelles

2009 ◽  
Vol 35 (10-11) ◽  
pp. 986-997 ◽  
Author(s):  
Abdallah Sayyed-Ahmad ◽  
Himanshu Khandelia ◽  
Yiannis N. Kaznessis
Keyword(s):  
Free Energy ◽  
Antimicrobial Peptides ◽  
Relative Free Energy ◽  
Free Energy Of Binding

A study of structural properties of gene network graphs for mathematical modeling of integrated mosaic gene networks

2017 ◽  
Vol 15 (02) ◽  
pp. 1650045 ◽  
Author(s):  
Olga V. Petrovskaya ◽  
Evgeny D. Petrovskiy ◽  
Inna N. Lavrik ◽  
Vladimir A. Ivanisenko
Keyword(s):  
Mathematical Modeling ◽  
Gene Regulatory Networks ◽  
Gene Networks ◽  
Gene Network ◽  
Regulatory Networks ◽  
Network Modeling ◽  
Computer Experiments ◽  
Linear Control ◽  
Expression Of Genes ◽  
Gene Regulatory

Gene network modeling is one of the widely used approaches in systems biology. It allows for the study of complex genetic systems function, including so-called mosaic gene networks, which consist of functionally interacting subnetworks. We conducted a study of a mosaic gene networks modeling method based on integration of models of gene subnetworks by linear control functionals. An automatic modeling of 10,000 synthetic mosaic gene regulatory networks was carried out using computer experiments on gene knockdowns/knockouts. Structural analysis of graphs of generated mosaic gene regulatory networks has revealed that the most important factor for building accurate integrated mathematical models, among those analyzed in the study, is data on expression of genes corresponding to the vertices with high properties of centrality.

scholarly journals From blastocyst to gastrula: gene regulatory networks of embryonic stem cells and early mouse embryogenesis

2014 ◽  
Vol 369 (1657) ◽  
pp. 20130542 ◽  
Author(s):  
David-Emlyn Parfitt ◽  
Michael M. Shen
Keyword(s):  
Stem Cells ◽  
Gene Networks ◽  
Regulatory Networks ◽  
Embryonic Stem ◽  
Cell Lineage ◽  
Network Models ◽  
Cell Types ◽  
Mammalian Development ◽  
A Genome

To date, many regulatory genes and signalling events coordinating mammalian development from blastocyst to gastrulation stages have been identified by mutational analyses and reverse-genetic approaches, typically on a gene-by-gene basis. More recent studies have applied bioinformatic approaches to generate regulatory network models of gene interactions on a genome-wide scale. Such models have provided insights into the gene networks regulating pluripotency in embryonic and epiblast stem cells, as well as cell-lineage determination in vivo . Here, we review how regulatory networks constructed for different stem cell types relate to corresponding networks in vivo and provide insights into understanding the molecular regulation of the blastocyst–gastrula transition.

scholarly journals Novel cancer subtyping method based on patient-specific gene regulatory network

2021 ◽  
Author(s):  
Mai Adachi Nakazawa ◽  
Yoshinori Tamada ◽  
Yoshihisa Tanaka ◽  
Marie Ikeguchi ◽  
Kako Higashihara ◽  
...  
Keyword(s):  
Gene Networks ◽  
Regulatory Networks ◽  
The Cancer Genome Atlas ◽  
Patient Specific ◽  
Specific Gene ◽  
Omics Data ◽  
Cancer Subtypes ◽  
Molecular Systems ◽  
Molecular Features ◽  
Cancer Genome Atlas

The identification of cancer subtypes is important for the understanding of tumor heterogeneity. In recent years, numerous computational methods have been proposed for this problem based on the multi-omics data of patients. It is widely accepted that different cancer subtypes are induced by different molecular regulatory networks. However, only a few incorporate the differences between their molecular systems into the classification processes. In this study, we present a novel method to classify cancer subtypes based on patient-specific molecular systems. Our method quantifies patient-specific gene networks, which are estimated from their transcriptome data. By clustering their quantified networks, our method allows for cancer subtyping, taking into consideration the differences in the molecular systems of patients. Comprehensive analyses of The Cancer Genome Atlas (TCGA) datasets applied to our method confirmed that they were able to identify more clinically meaningful cancer subtypes than the existing subtypes and found that the identified subtypes comprised different molecular features. Our findings show that the proposed method, based on a simple classification using the patient-specific molecular systems, can identify cancer subtypes even with single omics data, which cannot otherwise be captured by existing methods using multi-omics data.

scholarly journals Independent Sources of Information-Theoretic Descriptors of Electronic States

2020 ◽  
pp. 106-115
Author(s):  
Roman F. Nalewajski
Keyword(s):  
Information Sources ◽  
Electronic States ◽  
The State ◽  
Sources Of Information ◽  
Molecular Electronic ◽  
Information Theoretic ◽  
State Entropy ◽  
Phase Current ◽  
Electronic Wavefunctions ◽  
Information Order

The need for resultant measures of the Information-Theoretic (IT) content of molecular electronic wavefunctions, combining the information contributions due to the probability and phase/current distributions, is reemphasized. Complementary measures of the state entropy (disorder) and information (order) contents are reexamined, the continuities of wavefunction components are summarized, and the probability acceleration concept is used to determine the current and information sources. The experimental elimination of the state uncertainties is discussed and limitations in this information-acquirement process imposed by the Heisenberg indeterminacy principle are commented upon.

scholarly journals Transcription Factors and microRNA Genes Regulatory Network Construction Under Drought Stress in Sesame (Sesamum indicum L.)

2020 ◽  
Author(s):  
Mohammad Amin Baghery ◽  
Seyed Kamal Kazemitabar ◽  
Ali Dehestani ◽  
Pooyan Mehrabanjoubani ◽  
Mohammad Mehdi Naghizadeh ◽  
...  
Keyword(s):  
Transcription Factors ◽  
Drought Stress ◽  
Gene Networks ◽  
Regulatory Networks ◽  
Regulatory Gene ◽  
Sesamum Indicum ◽  
Regulatory Mechanisms ◽  
Oilseed Crop ◽  
Sesame Genotypes ◽  
Almost All

Abstract Background: Drought is one of the most common environmental stresses affecting crops yield and quality. Sesame is an important oilseed crop that most likely faces drought during its growth due to growing in semi-arid and arid areas. Plants responses to drought controlled by regulatory mechanisms. Despite this importance, there is little information about Sesame regulatory mechanisms against drought stress. Results: 458 drought-related genes were identified using comprehensive RNA-seq data analysis of two susceptible and tolerant sesame genotypes under drought stress. These drought-responsive genes were included secondary metabolites biosynthesis-related Like F3H, sucrose biosynthesis-related like SUS2, transporters like SUC2, and protectives like LEA and HSP families. Interactions between identified genes and regulators including TFs and miRNAs were predicted using bioinformatics tools and related regulatory gene networks were constructed. Key regulators and relations of Sesame under drought stress were detected by network analysis. TFs belonged to DREB (DREB2D), MYB (MYB63), ZFP (TFIIIA), bZIP (bZIP16), bHLH (PIF1), WRKY (WRKY30) and NAC (NAC29) families were found among key regulators. mRNAs like miR399, miR169, miR156, miR5685, miR529, miR395, miR396, and miR172 also found as key drought regulators. Furthermore, a total of 117 TFs and 133 miRNAs that might be involved in drought stress were identified with this approach. Conclusions: Most of the identified TFs and almost all of the miRNAs are introduced for the first time as potential regulators of drought response in Sesame. These regulators accompany with identified drought-related genes could be valuable candidates for future studies and breeding programs on Sesame under drought stress. Keywords: Sesamum indicum, Drought stress, Regulatory networks, miRNA, Transcription Factors.

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