Literature DB >> 25111257

A behavioral study of healthy and cancer genes by modeling electrical network.

Tanusree Roy1, Soma Barman2.   

Abstract

In recent years, gene network modeling is gaining popularity in genomics to monitor the activity profile of genes. More specifically, the objective of the network modeling concept is to study the genetic behavior associated with disease. Previous researchers have designed network model at nucleotide level which produces more complexity for designing circuits mostly in case of gene expression studies. Whereas the authors have designed the present network model, based on amino acid level which is simpler as well as more appropriate for prediction of the genetic abnormality. In the present concept, SISO continuous and discrete system models of genes are realized using Foster network. The model is designed based on hydropathy index value of amino acids to study the biological system behavior. The time and phase response in continuous (s) domain and pole-zero distribution in discrete (z) domain are used as measurement metric in the present study. The simulated responses of the system show genetic instability for cancer genes which truly reflects the medical reports. The proposed modeling concept can be used, to accurately identify or separate out the diseased genes from healthy genes.
Copyright © 2014 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Cancer; Genetic instability; Genomics; LabVIEW; Network simulation; System model

Mesh:

Substances:

Year:  2014        PMID: 25111257     DOI: 10.1016/j.gene.2014.08.020

Source DB:  PubMed          Journal:  Gene        ISSN: 0378-1119            Impact factor:   3.688


  1 in total

1.  A Markov chain-based feature extraction method for classification and identification of cancerous DNA sequences.

Authors:  Amin Khodaei; Mohammad-Reza Feizi-Derakhshi; Behzad Mozaffari-Tazehkand
Journal:  Bioimpacts       Date:  2020-03-24
  1 in total

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