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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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