Eigenvalue Sensitivity-based Analysis for Evaluation of Biological Network Stability versus disturbances

2021 ◽  
pp. 110941
Author(s):  
Maryam Gholampour ◽  
Ali Khaki Sedigh ◽  
Mohammad Ghassem Mahjani ◽  
Abdorasoul Ghasemi
Keyword(s):  
Biological Network ◽  
Network Stability ◽  
Eigenvalue Sensitivity

scholarly journals Exploring the effect of network topology, mRNA and protein dynamics on gene regulatory network stability

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Yipei Guo ◽  
Ariel Amir
Keyword(s):  
Regulatory Network ◽  
Biological Network ◽  
Structural Features ◽  
Network Stability ◽  
Transcription Network ◽  
Factors Affecting ◽  
E Coli ◽  
Growing Cell ◽  
Gene Regulatory ◽  
Mrna Degradation Rate

AbstractHomeostasis of protein concentrations in cells is crucial for their proper functioning, requiring steady-state concentrations to be stable to fluctuations. Since gene expression is regulated by proteins such as transcription factors (TFs), the full set of proteins within the cell constitutes a large system of interacting components, which can become unstable. We explore factors affecting stability by coupling the dynamics of mRNAs and proteins in a growing cell. We find that mRNA degradation rate does not affect stability, contrary to previous claims. However, global structural features of the network can dramatically enhance stability. Importantly, a network resembling a bipartite graph with a lower fraction of interactions that target TFs has a higher chance of being stable. Scrambling the E. coli transcription network, we find that the biological network is significantly more stable than its randomized counterpart, suggesting that stability constraints may have shaped network structure during the course of evolution.

Differential Drug Target Selection in Blood Coagulation: What can we get from Computational Systems Biology Models?

2020 ◽  
Vol 26 (18) ◽  
pp. 2109-2115 ◽  
Author(s):  
Mikhail A. Panteleev ◽  
Anna A. Andreeva ◽  
Alexey I. Lobanov
Keyword(s):  
Blood Coagulation ◽  
Biological Network ◽  
Target Selection ◽  
Anticoagulation Therapy ◽  
Differential Regulation ◽  
Coagulation Cascade ◽  
Computational Systems Biology ◽  
Analysis Strategies ◽  
Optimal Target ◽  
Computational Systems

Discovery and selection of the potential targets are some of the important issues in pharmacology. Even when all the reactions and the proteins in a biological network are known, how does one choose the optimal target? Here, we review and discuss the application of the computational methods to address this problem using the blood coagulation cascade as an example. The problem of correct antithrombotic targeting is critical for this system because, although several anticoagulants are currently available, all of them are associated with bleeding risks. The advantages and the drawbacks of different sensitivity analysis strategies are considered, focusing on the approaches that emphasize: 1) the functional modularity and the multi-tasking nature of this biological network; and 2) the need to normalize hemostasis during the anticoagulation therapy rather than completely suppress it. To illustrate this effect, we show the possibility of the differential regulation of lag time and endogenous thrombin potential in the thrombin generation. These methods allow to identify the elements in the blood coagulation cascade that may serve as the targets for the differential regulation of this system.

Brief Survey of Biological Network Alignment and a Variant with Incorporation of Functional Annotations

2018 ◽  
Vol 14 (1) ◽  
pp. 4-10
Author(s):  
Fang Jing ◽  
Shao-Wu Zhang ◽  
Shihua Zhang
Keyword(s):  
Gene Ontology ◽  
Topological Structure ◽  
Metabolic Networks ◽  
Biological Network ◽  
Genomic Sequence ◽  
Network Alignment ◽  
Future Directions ◽  
Functional Annotations ◽  
Protein Protein Interaction ◽  
Ppi Networks

Background:Biological network alignment has been widely studied in the context of protein-protein interaction (PPI) networks, metabolic networks and others in bioinformatics. The topological structure of networks and genomic sequence are generally used by existing methods for achieving this task.Objective and Method:Here we briefly survey the methods generally used for this task and introduce a variant with incorporation of functional annotations based on similarity in Gene Ontology (GO). Making full use of GO information is beneficial to provide insights into precise biological network alignment.Results and Conclusion:We analyze the effect of incorporation of GO information to network alignment. Finally, we make a brief summary and discuss future directions about this topic.

A Split Network based Routing Approach in Wireless Sensor Network to Enhance Network Stability

2019 ◽  
Vol 9 (4) ◽  
pp. 480-487 ◽  
Author(s):  
Hardeep S. Saini ◽  
Dinesh Arora
Keyword(s):  
Energy Consumption ◽  
Sensor Network ◽  
Energy Efficient ◽  
Cluster Head ◽  
Base Station ◽  
Operating Efficiency ◽  
Network Stability ◽  
Major Factors ◽  
Ch Selection

Background & Objective: The operating efficiency of a sensor network totally relies upon the energy that is consumed by the nodes to perform various tasks like data transmission etc. Thus, it becomes mandatory to consume the energy in an intelligent way so that the network can run for a long period. This paper proposed an energy efficient Cluster Head (CH) selection mechanism by considering the distance to Base Station (BS), distance to node and energy as major factors. The concept of volunteer node is also introduced with an objective to reduce the energy consumption of the CH to transmit data from source to BS. The role of the volunteer node is to transmit the data successfully from source to destination or BS. Conclusion: The results are observed with respect to the Alive nodes, dead nodes and energy consumption of the network. The outcome of the proposed work proves that it outperforms the traditional mechanisms.

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