Cancer gene silencing network analysis using cellular automata

Kalyan Mahata; Anasua Sarkar

doi:10.1109/C3IT.2015.7060127

Cancer gene silencing network analysis using cellular automata

Kalyan Mahata, Anasua Sarkar

Government College of Engineering & Leather Technology, Kolkata

Research output: Chapter in Book/Report/Conference proceeding › Paper in conference proceeding › peer-review

Abstract

Identification of cancer pathways is the central goal in the cancer gene expression data analysis. A cellular automaton is a dynamic system with cells, which are uniform, interconnected and discrete in nature. Cellular automata are well-known methods to predict network traffics in cellular spaces. Therefore, to predict cancer pathways involved, we propose a 2-dimensional cellular automata approach over a chosen cancer gene network. Focusing on the case study, we highlight the potential impact of spatial organization in cellular spaces for the evolution and engineering of gene silencing on cancer gene expression profiles. The gene regulatory network involved in gene silencing breast cancer cell line, analysed with a predefined ranking value, has been simulated using cellular automata to obtain proper insight view of selecting biomarker genes for breast cancer. The predicted biomarker genes have been analysed with other contemporary databases, like KEGG and biologically tested for gene enrichment analysis for their significances. This approach is a novel one in the sense of projecting oncology in cellular spaces over ranking values for predicting significant biomarkers in cancer.

Original language	English
Title of host publication	Proceedings of the 2015 3rd International Conference on Computer, Communication, Control and Information Technology, C3IT 2015
Publisher	IEEE - Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781479944460
DOIs	https://doi.org/10.1109/C3IT.2015.7060127
Publication status	Published - 2015 Jan 1
Externally published	Yes
Event	2015 3rd International Conference on Computer, Communication, Control and Information Technology, C3IT 2015 - Hooghly, India Duration: 2015 Feb 7 → 2015 Feb 8

Conference

Conference	2015 3rd International Conference on Computer, Communication, Control and Information Technology, C3IT 2015
Country/Territory	India
City	Hooghly
Period	2015/02/07 → 2015/02/08

Free keywords

cancer biomarker
cellular automata
Gene correlation network
gene silencing
shared neighbor ranking

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1109/C3IT.2015.7060127

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@inproceedings{837dec7dc12d4e5ca9c5b003b5ddcf37,

title = "Cancer gene silencing network analysis using cellular automata",

abstract = "Identification of cancer pathways is the central goal in the cancer gene expression data analysis. A cellular automaton is a dynamic system with cells, which are uniform, interconnected and discrete in nature. Cellular automata are well-known methods to predict network traffics in cellular spaces. Therefore, to predict cancer pathways involved, we propose a 2-dimensional cellular automata approach over a chosen cancer gene network. Focusing on the case study, we highlight the potential impact of spatial organization in cellular spaces for the evolution and engineering of gene silencing on cancer gene expression profiles. The gene regulatory network involved in gene silencing breast cancer cell line, analysed with a predefined ranking value, has been simulated using cellular automata to obtain proper insight view of selecting biomarker genes for breast cancer. The predicted biomarker genes have been analysed with other contemporary databases, like KEGG and biologically tested for gene enrichment analysis for their significances. This approach is a novel one in the sense of projecting oncology in cellular spaces over ranking values for predicting significant biomarkers in cancer.",

keywords = "cancer biomarker, cellular automata, Gene correlation network, gene silencing, shared neighbor ranking",

author = "Kalyan Mahata and Anasua Sarkar",

year = "2015",

month = jan,

day = "1",

doi = "10.1109/C3IT.2015.7060127",

language = "English",

booktitle = "Proceedings of the 2015 3rd International Conference on Computer, Communication, Control and Information Technology, C3IT 2015",

publisher = "IEEE - Institute of Electrical and Electronics Engineers Inc.",

address = "United States",

note = "2015 3rd International Conference on Computer, Communication, Control and Information Technology, C3IT 2015 ; Conference date: 07-02-2015 Through 08-02-2015",

}

Mahata, K & Sarkar, A 2015, Cancer gene silencing network analysis using cellular automata. in Proceedings of the 2015 3rd International Conference on Computer, Communication, Control and Information Technology, C3IT 2015., 7060127, IEEE - Institute of Electrical and Electronics Engineers Inc., 2015 3rd International Conference on Computer, Communication, Control and Information Technology, C3IT 2015, Hooghly, India, 2015/02/07. https://doi.org/10.1109/C3IT.2015.7060127

Cancer gene silencing network analysis using cellular automata. / Mahata, Kalyan; Sarkar, Anasua.
Proceedings of the 2015 3rd International Conference on Computer, Communication, Control and Information Technology, C3IT 2015. IEEE - Institute of Electrical and Electronics Engineers Inc., 2015. 7060127.

Research output: Chapter in Book/Report/Conference proceeding › Paper in conference proceeding › peer-review

TY - GEN

T1 - Cancer gene silencing network analysis using cellular automata

AU - Mahata, Kalyan

AU - Sarkar, Anasua

PY - 2015/1/1

Y1 - 2015/1/1

N2 - Identification of cancer pathways is the central goal in the cancer gene expression data analysis. A cellular automaton is a dynamic system with cells, which are uniform, interconnected and discrete in nature. Cellular automata are well-known methods to predict network traffics in cellular spaces. Therefore, to predict cancer pathways involved, we propose a 2-dimensional cellular automata approach over a chosen cancer gene network. Focusing on the case study, we highlight the potential impact of spatial organization in cellular spaces for the evolution and engineering of gene silencing on cancer gene expression profiles. The gene regulatory network involved in gene silencing breast cancer cell line, analysed with a predefined ranking value, has been simulated using cellular automata to obtain proper insight view of selecting biomarker genes for breast cancer. The predicted biomarker genes have been analysed with other contemporary databases, like KEGG and biologically tested for gene enrichment analysis for their significances. This approach is a novel one in the sense of projecting oncology in cellular spaces over ranking values for predicting significant biomarkers in cancer.

AB - Identification of cancer pathways is the central goal in the cancer gene expression data analysis. A cellular automaton is a dynamic system with cells, which are uniform, interconnected and discrete in nature. Cellular automata are well-known methods to predict network traffics in cellular spaces. Therefore, to predict cancer pathways involved, we propose a 2-dimensional cellular automata approach over a chosen cancer gene network. Focusing on the case study, we highlight the potential impact of spatial organization in cellular spaces for the evolution and engineering of gene silencing on cancer gene expression profiles. The gene regulatory network involved in gene silencing breast cancer cell line, analysed with a predefined ranking value, has been simulated using cellular automata to obtain proper insight view of selecting biomarker genes for breast cancer. The predicted biomarker genes have been analysed with other contemporary databases, like KEGG and biologically tested for gene enrichment analysis for their significances. This approach is a novel one in the sense of projecting oncology in cellular spaces over ranking values for predicting significant biomarkers in cancer.

KW - cancer biomarker

KW - cellular automata

KW - Gene correlation network

KW - gene silencing

KW - shared neighbor ranking

U2 - 10.1109/C3IT.2015.7060127

DO - 10.1109/C3IT.2015.7060127

M3 - Paper in conference proceeding

AN - SCOPUS:84936103394

BT - Proceedings of the 2015 3rd International Conference on Computer, Communication, Control and Information Technology, C3IT 2015

PB - IEEE - Institute of Electrical and Electronics Engineers Inc.

T2 - 2015 3rd International Conference on Computer, Communication, Control and Information Technology, C3IT 2015

Y2 - 7 February 2015 through 8 February 2015

ER -

Cancer gene silencing network analysis using cellular automata

Abstract

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Free keywords

UN SDGs

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