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dc.contributor.author	BACA LOPEZ, KAROL
dc.contributor.author	HERNANDEZ LEMUS, ENRIQUE
dc.contributor.author	MAYORGA ROJAS, MIGUEL
dc.creator	BACA LOPEZ, KAROL; 290352
dc.creator	HERNANDEZ LEMUS, ENRIQUE; 77407
dc.creator	MAYORGA ROJAS, MIGUEL; 14896
dc.date.accessioned	2016-03-16T17:17:36Z
dc.date.available	2016-03-16T17:17:36Z
dc.date.issued	2009
dc.identifier	http://www.redalyc.org/articulo.oa?id=57013233009
dc.identifier.uri	http://hdl.handle.net/20.500.11799/39369
dc.description	The majority of human diseases are related with the dynamic interaction of many genes and their products as well as environmental constraints. Cancer (and breast cancer in particular) is a paradigmatic example of such complex behavior. Since gene regulation is a non-equilibrium process, the inference and analysis of such phenomena could be done following the tenets of non-equilibrium physics. The traditional programme in statistical mechanics consists in inferring the joint probability distribution for either microscopic states (equilibrium) or mesoscopic-states (non-equilibrium), given a model for the particle interactions (e.g. the potentials). An inverse problem in statistical mechanics, in the other hand, is based on considering a realization of the probability distribution of micro- or meso-states and used it to infer the interaction potentials between particles. This is the approach taken in what follows. We analyzed 261 whole-genome gene expression experiments in breast cancer patients, and by means of an information-theoretical analysis, we deconvolute the associated set of transcriptional interactions, i.e. we discover a set of fundamental biochemical reactions related to this pathology. By doing this, we showed how to apply the tools of non-linear statistical physics to generate hypothesis to be tested on clinical and biochemical settings in relation to cancer phenomenology.
dc.format	application/pdf
dc.language.iso	eng	es
dc.publisher	Sociedad Mexicana de Física A.C.
dc.relation	http://www.redalyc.org/revista.oa?id=570
dc.rights	openAccess	es
dc.rights.uri	http://creativecommons.org/licenses/by-nc-nd/4.0
dc.source	Revista Mexicana de Física (México) Num.6 Vol.55
dc.subject	Física, Astronomía y Matemáticas	es
dc.subject	Cancer genomics	es
dc.subject	information theory	es
dc.subject	molecular networks	es
dc.subject.classification	CIENCIAS FÍSICO MATEMÁTICAS Y CIENCIAS DE LA TIERRA
dc.title	Information-theoretical analysis of gene expression data to infer transcriptional interactions	es
dc.type	Artículo	es
dc.provenance	Científica	es
dc.road	Dorada	es
dc.ambito	Internacional	es
dc.audience	students	es
dc.audience	researchers	es
dc.type.conacyt	article
dc.identificator	1

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