Deciphering modular and dynamic behaviors of transcriptional networks

Abstract The coordinated and dynamic modulation or interaction of genes or proteins acts as an important mechanism used by a cell in functional regulation. Recent studies have shown that many transcriptional networks exhibit a scale-free topology and hierarchical modular architecture. It has also be...
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Gespeichert in:

Autor*in:	Zhan, Ming [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2007

Schlagwörter:	Systems biology Coexpression Transcriptional module Pathway dynamics Transcriptional intervention ModulePro PathwayPro

Anmerkung:	© Springer Science+Business Media B.V. 2007

Übergeordnetes Werk:	Enthalten in: Genomic medicine - Dordrecht : Springer Netherlands, 2007, 1(2007), 1-2 vom: 11. Mai, Seite 19-28
Übergeordnetes Werk:	volume:1 ; year:2007 ; number:1-2 ; day:11 ; month:05 ; pages:19-28

Links:	Volltext

DOI / URN:	10.1007/s11568-007-9004-7

Katalog-ID:	SPR02078127X

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allfields	10.1007/s11568-007-9004-7 doi (DE-627)SPR02078127X (SPR)s11568-007-9004-7-e DE-627 ger DE-627 rakwb eng Zhan, Ming verfasserin aut Deciphering modular and dynamic behaviors of transcriptional networks 2007 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Springer Science+Business Media B.V. 2007 Abstract The coordinated and dynamic modulation or interaction of genes or proteins acts as an important mechanism used by a cell in functional regulation. Recent studies have shown that many transcriptional networks exhibit a scale-free topology and hierarchical modular architecture. It has also been shown that transcriptional networks or pathways are dynamic and behave only in certain ways and controlled manners in response to disease development, changing cellular conditions, and different environmental factors. Moreover, evolutionarily conserved and divergent transcriptional modules underline fundamental and species-specific molecular mechanisms controlling disease development or cellular phenotypes. Various computational algorithms have been developed to explore transcriptional networks and modules from gene expression data. In silico studies have also been made to mimic the dynamic behavior of regulatory networks, analyzing how disease or cellular phenotypes arise from the connectivity or networks of genes and their products. Here, we review the recent development in computational biology research on deciphering modular and dynamic behaviors of transcriptional networks, highlighting important findings. We also demonstrate how these computational algorithms can be applied in systems biology studies as on disease, stem cells, and drug discovery. Systems biology (dpeaa)DE-He213 Coexpression (dpeaa)DE-He213 Transcriptional module (dpeaa)DE-He213 Pathway dynamics (dpeaa)DE-He213 Transcriptional intervention (dpeaa)DE-He213 ModulePro (dpeaa)DE-He213 PathwayPro (dpeaa)DE-He213 Enthalten in Genomic medicine Dordrecht : Springer Netherlands, 2007 1(2007), 1-2 vom: 11. Mai, Seite 19-28 (DE-627)545783801 (DE-600)2388219-0 1871-7942 nnns volume:1 year:2007 number:1-2 day:11 month:05 pages:19-28 https://dx.doi.org/10.1007/s11568-007-9004-7 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2014 GBV_ILN_2190 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 1 2007 1-2 11 05 19-28
spelling	10.1007/s11568-007-9004-7 doi (DE-627)SPR02078127X (SPR)s11568-007-9004-7-e DE-627 ger DE-627 rakwb eng Zhan, Ming verfasserin aut Deciphering modular and dynamic behaviors of transcriptional networks 2007 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Springer Science+Business Media B.V. 2007 Abstract The coordinated and dynamic modulation or interaction of genes or proteins acts as an important mechanism used by a cell in functional regulation. Recent studies have shown that many transcriptional networks exhibit a scale-free topology and hierarchical modular architecture. It has also been shown that transcriptional networks or pathways are dynamic and behave only in certain ways and controlled manners in response to disease development, changing cellular conditions, and different environmental factors. Moreover, evolutionarily conserved and divergent transcriptional modules underline fundamental and species-specific molecular mechanisms controlling disease development or cellular phenotypes. Various computational algorithms have been developed to explore transcriptional networks and modules from gene expression data. In silico studies have also been made to mimic the dynamic behavior of regulatory networks, analyzing how disease or cellular phenotypes arise from the connectivity or networks of genes and their products. Here, we review the recent development in computational biology research on deciphering modular and dynamic behaviors of transcriptional networks, highlighting important findings. We also demonstrate how these computational algorithms can be applied in systems biology studies as on disease, stem cells, and drug discovery. Systems biology (dpeaa)DE-He213 Coexpression (dpeaa)DE-He213 Transcriptional module (dpeaa)DE-He213 Pathway dynamics (dpeaa)DE-He213 Transcriptional intervention (dpeaa)DE-He213 ModulePro (dpeaa)DE-He213 PathwayPro (dpeaa)DE-He213 Enthalten in Genomic medicine Dordrecht : Springer Netherlands, 2007 1(2007), 1-2 vom: 11. Mai, Seite 19-28 (DE-627)545783801 (DE-600)2388219-0 1871-7942 nnns volume:1 year:2007 number:1-2 day:11 month:05 pages:19-28 https://dx.doi.org/10.1007/s11568-007-9004-7 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2014 GBV_ILN_2190 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 1 2007 1-2 11 05 19-28
allfields_unstemmed	10.1007/s11568-007-9004-7 doi (DE-627)SPR02078127X (SPR)s11568-007-9004-7-e DE-627 ger DE-627 rakwb eng Zhan, Ming verfasserin aut Deciphering modular and dynamic behaviors of transcriptional networks 2007 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Springer Science+Business Media B.V. 2007 Abstract The coordinated and dynamic modulation or interaction of genes or proteins acts as an important mechanism used by a cell in functional regulation. Recent studies have shown that many transcriptional networks exhibit a scale-free topology and hierarchical modular architecture. It has also been shown that transcriptional networks or pathways are dynamic and behave only in certain ways and controlled manners in response to disease development, changing cellular conditions, and different environmental factors. Moreover, evolutionarily conserved and divergent transcriptional modules underline fundamental and species-specific molecular mechanisms controlling disease development or cellular phenotypes. Various computational algorithms have been developed to explore transcriptional networks and modules from gene expression data. In silico studies have also been made to mimic the dynamic behavior of regulatory networks, analyzing how disease or cellular phenotypes arise from the connectivity or networks of genes and their products. Here, we review the recent development in computational biology research on deciphering modular and dynamic behaviors of transcriptional networks, highlighting important findings. We also demonstrate how these computational algorithms can be applied in systems biology studies as on disease, stem cells, and drug discovery. Systems biology (dpeaa)DE-He213 Coexpression (dpeaa)DE-He213 Transcriptional module (dpeaa)DE-He213 Pathway dynamics (dpeaa)DE-He213 Transcriptional intervention (dpeaa)DE-He213 ModulePro (dpeaa)DE-He213 PathwayPro (dpeaa)DE-He213 Enthalten in Genomic medicine Dordrecht : Springer Netherlands, 2007 1(2007), 1-2 vom: 11. Mai, Seite 19-28 (DE-627)545783801 (DE-600)2388219-0 1871-7942 nnns volume:1 year:2007 number:1-2 day:11 month:05 pages:19-28 https://dx.doi.org/10.1007/s11568-007-9004-7 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2014 GBV_ILN_2190 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 1 2007 1-2 11 05 19-28
allfieldsGer	10.1007/s11568-007-9004-7 doi (DE-627)SPR02078127X (SPR)s11568-007-9004-7-e DE-627 ger DE-627 rakwb eng Zhan, Ming verfasserin aut Deciphering modular and dynamic behaviors of transcriptional networks 2007 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Springer Science+Business Media B.V. 2007 Abstract The coordinated and dynamic modulation or interaction of genes or proteins acts as an important mechanism used by a cell in functional regulation. Recent studies have shown that many transcriptional networks exhibit a scale-free topology and hierarchical modular architecture. It has also been shown that transcriptional networks or pathways are dynamic and behave only in certain ways and controlled manners in response to disease development, changing cellular conditions, and different environmental factors. Moreover, evolutionarily conserved and divergent transcriptional modules underline fundamental and species-specific molecular mechanisms controlling disease development or cellular phenotypes. Various computational algorithms have been developed to explore transcriptional networks and modules from gene expression data. In silico studies have also been made to mimic the dynamic behavior of regulatory networks, analyzing how disease or cellular phenotypes arise from the connectivity or networks of genes and their products. Here, we review the recent development in computational biology research on deciphering modular and dynamic behaviors of transcriptional networks, highlighting important findings. We also demonstrate how these computational algorithms can be applied in systems biology studies as on disease, stem cells, and drug discovery. Systems biology (dpeaa)DE-He213 Coexpression (dpeaa)DE-He213 Transcriptional module (dpeaa)DE-He213 Pathway dynamics (dpeaa)DE-He213 Transcriptional intervention (dpeaa)DE-He213 ModulePro (dpeaa)DE-He213 PathwayPro (dpeaa)DE-He213 Enthalten in Genomic medicine Dordrecht : Springer Netherlands, 2007 1(2007), 1-2 vom: 11. Mai, Seite 19-28 (DE-627)545783801 (DE-600)2388219-0 1871-7942 nnns volume:1 year:2007 number:1-2 day:11 month:05 pages:19-28 https://dx.doi.org/10.1007/s11568-007-9004-7 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2014 GBV_ILN_2190 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 1 2007 1-2 11 05 19-28
allfieldsSound	10.1007/s11568-007-9004-7 doi (DE-627)SPR02078127X (SPR)s11568-007-9004-7-e DE-627 ger DE-627 rakwb eng Zhan, Ming verfasserin aut Deciphering modular and dynamic behaviors of transcriptional networks 2007 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Springer Science+Business Media B.V. 2007 Abstract The coordinated and dynamic modulation or interaction of genes or proteins acts as an important mechanism used by a cell in functional regulation. Recent studies have shown that many transcriptional networks exhibit a scale-free topology and hierarchical modular architecture. It has also been shown that transcriptional networks or pathways are dynamic and behave only in certain ways and controlled manners in response to disease development, changing cellular conditions, and different environmental factors. Moreover, evolutionarily conserved and divergent transcriptional modules underline fundamental and species-specific molecular mechanisms controlling disease development or cellular phenotypes. Various computational algorithms have been developed to explore transcriptional networks and modules from gene expression data. In silico studies have also been made to mimic the dynamic behavior of regulatory networks, analyzing how disease or cellular phenotypes arise from the connectivity or networks of genes and their products. Here, we review the recent development in computational biology research on deciphering modular and dynamic behaviors of transcriptional networks, highlighting important findings. We also demonstrate how these computational algorithms can be applied in systems biology studies as on disease, stem cells, and drug discovery. Systems biology (dpeaa)DE-He213 Coexpression (dpeaa)DE-He213 Transcriptional module (dpeaa)DE-He213 Pathway dynamics (dpeaa)DE-He213 Transcriptional intervention (dpeaa)DE-He213 ModulePro (dpeaa)DE-He213 PathwayPro (dpeaa)DE-He213 Enthalten in Genomic medicine Dordrecht : Springer Netherlands, 2007 1(2007), 1-2 vom: 11. Mai, Seite 19-28 (DE-627)545783801 (DE-600)2388219-0 1871-7942 nnns volume:1 year:2007 number:1-2 day:11 month:05 pages:19-28 https://dx.doi.org/10.1007/s11568-007-9004-7 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2014 GBV_ILN_2190 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 1 2007 1-2 11 05 19-28
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author	Zhan, Ming
spellingShingle	Zhan, Ming misc Systems biology misc Coexpression misc Transcriptional module misc Pathway dynamics misc Transcriptional intervention misc ModulePro misc PathwayPro Deciphering modular and dynamic behaviors of transcriptional networks
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topic_title	Deciphering modular and dynamic behaviors of transcriptional networks Systems biology (dpeaa)DE-He213 Coexpression (dpeaa)DE-He213 Transcriptional module (dpeaa)DE-He213 Pathway dynamics (dpeaa)DE-He213 Transcriptional intervention (dpeaa)DE-He213 ModulePro (dpeaa)DE-He213 PathwayPro (dpeaa)DE-He213
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title	Deciphering modular and dynamic behaviors of transcriptional networks
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title_sort	deciphering modular and dynamic behaviors of transcriptional networks
title_auth	Deciphering modular and dynamic behaviors of transcriptional networks
abstract	Abstract The coordinated and dynamic modulation or interaction of genes or proteins acts as an important mechanism used by a cell in functional regulation. Recent studies have shown that many transcriptional networks exhibit a scale-free topology and hierarchical modular architecture. It has also been shown that transcriptional networks or pathways are dynamic and behave only in certain ways and controlled manners in response to disease development, changing cellular conditions, and different environmental factors. Moreover, evolutionarily conserved and divergent transcriptional modules underline fundamental and species-specific molecular mechanisms controlling disease development or cellular phenotypes. Various computational algorithms have been developed to explore transcriptional networks and modules from gene expression data. In silico studies have also been made to mimic the dynamic behavior of regulatory networks, analyzing how disease or cellular phenotypes arise from the connectivity or networks of genes and their products. Here, we review the recent development in computational biology research on deciphering modular and dynamic behaviors of transcriptional networks, highlighting important findings. We also demonstrate how these computational algorithms can be applied in systems biology studies as on disease, stem cells, and drug discovery. © Springer Science+Business Media B.V. 2007
abstractGer	Abstract The coordinated and dynamic modulation or interaction of genes or proteins acts as an important mechanism used by a cell in functional regulation. Recent studies have shown that many transcriptional networks exhibit a scale-free topology and hierarchical modular architecture. It has also been shown that transcriptional networks or pathways are dynamic and behave only in certain ways and controlled manners in response to disease development, changing cellular conditions, and different environmental factors. Moreover, evolutionarily conserved and divergent transcriptional modules underline fundamental and species-specific molecular mechanisms controlling disease development or cellular phenotypes. Various computational algorithms have been developed to explore transcriptional networks and modules from gene expression data. In silico studies have also been made to mimic the dynamic behavior of regulatory networks, analyzing how disease or cellular phenotypes arise from the connectivity or networks of genes and their products. Here, we review the recent development in computational biology research on deciphering modular and dynamic behaviors of transcriptional networks, highlighting important findings. We also demonstrate how these computational algorithms can be applied in systems biology studies as on disease, stem cells, and drug discovery. © Springer Science+Business Media B.V. 2007
abstract_unstemmed	Abstract The coordinated and dynamic modulation or interaction of genes or proteins acts as an important mechanism used by a cell in functional regulation. Recent studies have shown that many transcriptional networks exhibit a scale-free topology and hierarchical modular architecture. It has also been shown that transcriptional networks or pathways are dynamic and behave only in certain ways and controlled manners in response to disease development, changing cellular conditions, and different environmental factors. Moreover, evolutionarily conserved and divergent transcriptional modules underline fundamental and species-specific molecular mechanisms controlling disease development or cellular phenotypes. Various computational algorithms have been developed to explore transcriptional networks and modules from gene expression data. In silico studies have also been made to mimic the dynamic behavior of regulatory networks, analyzing how disease or cellular phenotypes arise from the connectivity or networks of genes and their products. Here, we review the recent development in computational biology research on deciphering modular and dynamic behaviors of transcriptional networks, highlighting important findings. We also demonstrate how these computational algorithms can be applied in systems biology studies as on disease, stem cells, and drug discovery. © Springer Science+Business Media B.V. 2007
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Deciphering modular and dynamic behaviors of transcriptional networks

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