Computational Approaches for Analyzing Information Flow in Biological Networks

2012 ◽  
Vol 5 (220) ◽  
pp. re1-re1 ◽  
Author(s):  
B. Kholodenko ◽  
M. B. Yaffe ◽  
W. Kolch
Keyword(s):  
Information Flow ◽  
Biological Networks ◽  
Computational Approaches

Computational Approaches for Reconstruction of Time-Varying Biological Networks from Omics Data

2013 ◽  
pp. 209-239
Author(s):  
Vinay Jethava ◽  
Chiranjib Bhattacharyya ◽  
Devdatt Dubhashi
Keyword(s):  
Biological Networks ◽  
Time Varying ◽  
Omics Data ◽  
Computational Approaches

scholarly journals Beyond the Expanders

2011 ◽  
Vol 2011 ◽  
pp. 1-11 ◽  
Author(s):  
Marianna Bolla
Keyword(s):  
Information Flow ◽  
Biological Networks ◽  
Error Correcting Codes ◽  
Expander Graphs ◽  
Induced Subgraphs ◽  
Regular Behavior ◽  
Communication Problems ◽  
Regularity Properties

Expander graphs are widely used in communication problems and construction of error correcting codes. In such graphs, information gets through very quickly. Typically, it is not true for social or biological networks, though we may find a partition of the vertices such that the induced subgraphs on them and the bipartite subgraphs between any pair of them exhibit regular behavior of information flow within or between the vertex subsets. Implications between spectral and regularity properties are discussed.

Networks and Information Flow

2019 ◽  
pp. 12-20
Author(s):  
David Lazer
Keyword(s):  
Social Media ◽  
Big Data ◽  
World War Ii ◽  
Information Flow ◽  
Golden Age ◽  
World War ◽  
Computational Approaches ◽  
Twentieth Anniversary ◽  
Behavioral Methods ◽  
And Diffusion

This article introduces the first section of The Oxford Handbook of Networked Communication. The volume marks the twentieth anniversary of the second golden age in the study of networks and information flow. The first golden age began shortly after World War II and focused on the canonical bookends of broadcast and social networks as drivers of information flow. The second golden age is marked by a change in the phenomenon under study, with a profusion and confusion of broadcast and network drivers of information flow, in which everyone is a broadcaster, and all broadcasters are also nodes in the network. As a science, the second golden age is marked by a shift from the behavioral methods of the first golden age to computational approaches to big data. The chapters in this section illuminate the emerging scientific opportunities, from our changing understanding of network dynamics and diffusion to computational approaches to studying content and social media.

scholarly journals Network analysis reveals essential proteins that regulate sodium-iodide symporter expression in anaplastic thyroid carcinoma

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Hassan Rakhsh-Khorshid ◽  
Hilda Samimi ◽  
Shukoofeh Torabi ◽  
Sayed Mahmoud Sajjadi-Jazi ◽  
Hamed Samadi ◽  
...  
Keyword(s):  
Thyroid Carcinoma ◽  
Information Flow ◽  
Protein Interaction ◽  
Biological Networks ◽  
Protein Interaction Network ◽  
Sodium Iodide ◽  
Interaction Network ◽  
Anaplastic Thyroid Carcinoma ◽  
Sodium Iodide Symporter ◽  
Essential Proteins

AbstractAnaplastic thyroid carcinoma (ATC) is the most rare and lethal form of thyroid cancer and requires effective treatment. Efforts have been made to restore sodium-iodide symporter (NIS) expression in ATC cells where it has been downregulated, yet without complete success. Systems biology approaches have been used to simplify complex biological networks. Here, we attempt to find more suitable targets in order to restore NIS expression in ATC cells. We have built a simplified protein interaction network including transcription factors and proteins involved in MAPK, TGFβ/SMAD, PI3K/AKT, and TSHR signaling pathways which regulate NIS expression, alongside proteins interacting with them. The network was analyzed, and proteins were ranked based on several centrality indices. Our results suggest that the protein interaction network of NIS expression regulation is modular, and distance-based and information-flow-based centrality indices may be better predictors of important proteins in such networks. We propose that the high-ranked proteins found in our analysis are expected to be more promising targets in attempts to restore NIS expression in ATC cells.

scholarly journals Modeling information flow in biological networks

2011 ◽  
Vol 8 (3) ◽  
pp. 035012 ◽  
Author(s):  
Yoo-Ah Kim ◽  
Jozef H Przytycki ◽  
Stefan Wuchty ◽  
Teresa M Przytycka
Keyword(s):  
Information Flow ◽  
Biological Networks
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