Modeling intercellular communication as a survival strategy of cancer cells: An in-silico approach on a flexible bioinformatics framework


Maura Cárdenas-García, Pedro Pablo González-Pérez, Sara Montagna, Oscar Sánchez Cortés, Elena Hernández Caballero

Bioinformatics and Biology Insights 10, pages 518, March 2016
Libertas Academica

Intercellular communication is very important for cell development and allows a group of cells to survive as a population. Cancer cells have a similar behavior, presenting the same mechanisms characteristic of tissue formation. In this work, we model and simulate the formation of different communication channels that allow an interaction between two cells. This is a first step in order to simulate in the future processes that occur in healthy tissue when normal cells surround a cancer cell, and to interrupt the communication, thus preventing the spread of malignancy into these cells. The purpose is to propose key molecules, which can be targeted to allow us to break the communication between cancer cells and surrounding normal cells. The simulation is carried out using a flexible bioinformatics platform developed by us, which is itself based on the metaphor chemistry based model.

 @article{cardenasBBI2016,
author={Cárdenas-García, Maura and González-Pérez, Pedro Pablo and Montagna, Sara and Sánchez Cortés, Oscar and Hernández Caballero, Elena},
journal={Bioinformatics and Biology Insights},
publisher={Libertas Academica},
title={Modeling Intercellular Communication as a Survival Strategy of Cancer Cells: An In Silico Approach on a Flexible Bioinformatics Framework},
year={2016},
month={03},
volume={10},
url={www.la-press.com/modeling-intercellular-communication-as-a-survival-strategy-of-cancer--article-a5461},
pages={5--18},
doi={10.4137/BBI.S38075},

Tags:

Publication

— authors

Maura Cárdenas-García, Pedro Pablo González-Pérez, Sara Montagna, Oscar Sánchez Cortés, Elena Hernández Caballero

— status

published

— sort

article in journal

Venue

— journal

Bioinformatics and Biology Insights

— volume

10

— pages

518

— publication date

March 2016

URLs

original page  |  original PDF

Identifiers

— DOI

10.4137/BBI.S38075

— PubMed

26997867

— online ISSN

1177-9322

BibTeX

— BibTeX ID
cardenasBBI2016
— BibTeX category
article

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