dor_id: 41718

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650.#.4.x: Físico Matemáticas y Ciencias de la Tierra

336.#.#.b: info:eu-repo/semantics/article

336.#.#.3: Artículo de Investigación

336.#.#.a: Artículo

351.#.#.6: http://revistas.unam.mx/index.php/rmf

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856.4.0.u: http://revistas.unam.mx/index.php/rmf/article/view/15105/25584

100.1.#.a: Mayorga, M.; Baca-lópez, K.; Hernández-lemus, E.

524.#.#.a: Mayorga, M., et al. (2009). Information-theoretical analysis of gene expression data to infer transcriptional interactions. Revista Mexicana de Física; Vol 55, No 006. Recuperado de https://repositorio.unam.mx/contenidos/41718

245.1.0.a: Information-theoretical analysis of gene expression data to infer transcriptional interactions

502.#.#.c: Universidad Nacional Autónoma de México

561.1.#.a: Facultad de Ciencias, UNAM

264.#.0.c: 2009

264.#.1.c: 2009-01-01

653.#.#.a: Cancer genomics; information theory; molecular networks

506.1.#.a: La titularidad de los derechos patrimoniales de esta obra pertenece a las instituciones editoras. Su uso se rige por una licencia Creative Commons BY-NC-ND 4.0 Internacional, https://creativecommons.org/licenses/by-nc-nd/4.0/legalcode.es, fecha de asignación de la licencia 2009-01-01, para un uso diferente consultar al responsable jurídico del repositorio por medio de rmf@ciencias.unam.mx

884.#.#.k: http://revistas.unam.mx/index.php/rmf/article/view/15105

041.#.7.h: eng

520.3.#.a: The majority of human diseases are related with the dynamic interaction of many genes and their products as well as environmental con- straints. 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. Thetraditional programme in statistical mechanics consists in inferring the joint probability distribution for either microscopic states (equi- librium) or mesoscopic-states (non-equilibrium), given a model for the particle interactions (e.g. the potentials). An inverse problem instatistical 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.

773.1.#.t: Revista Mexicana de Física; Vol 55, No 006 (2009)

773.1.#.o: http://revistas.unam.mx/index.php/rmf

046.#.#.j: 2020-11-25 00:00:00.000000

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handle: 00d6768aee8bd74a

harvesting_date: 2020-09-23 00:00:00.0

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Artículo

Information-theoretical analysis of gene expression data to infer transcriptional interactions

Mayorga, M.; Baca-lópez, K.; Hernández-lemus, E.

Facultad de Ciencias, UNAM, publicado en Revista Mexicana de Física, y cosechado de Revistas UNAM

Licencia de uso

Procedencia del contenido

Entidad o dependencia
Facultad de Ciencias, UNAM
Revista
Repositorio
Contacto
Revistas UNAM. Dirección General de Publicaciones y Fomento Editorial, UNAM en revistas@unam.mx

Cita

Mayorga, M., et al. (2009). Information-theoretical analysis of gene expression data to infer transcriptional interactions. Revista Mexicana de Física; Vol 55, No 006. Recuperado de https://repositorio.unam.mx/contenidos/41718

Descripción del recurso

Autor(es)
Mayorga, M.; Baca-lópez, K.; Hernández-lemus, E.
Tipo
Artículo de Investigación
Área del conocimiento
Físico Matemáticas y Ciencias de la Tierra
Título
Information-theoretical analysis of gene expression data to infer transcriptional interactions
Fecha
2009-01-01
Resumen
The majority of human diseases are related with the dynamic interaction of many genes and their products as well as environmental con- straints. 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. Thetraditional programme in statistical mechanics consists in inferring the joint probability distribution for either microscopic states (equi- librium) or mesoscopic-states (non-equilibrium), given a model for the particle interactions (e.g. the potentials). An inverse problem instatistical 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.
Tema
Cancer genomics; information theory; molecular networks
Idioma
eng
ISSN
2683-2224 (digital); 0035-001X (impresa)

Enlaces