Inferring yeast cell cycle regulators and interactions using transcription factor activities

Background Since transcription factors are often regulated at the post-transcriptional level, their activities, rather than expression levels may provide valuable information for investigating functions and their interactions. The recently developed Network Component Analysis (NCA) and its generalized form (gNCA) provide a robust framework for deducing the transcription factor activities (TFAs) from various types of DNA microarray data and transcription factor-gene connectivity. The goal of this work is to demonstrate the utility of TFAs in inferring transcription factor functions and interactions in Saccharomyces cerevisiae cell cycle regulation. Results Using gNCA, we determined 74 TFAs from both wild type and fkh1 fkh2 deletion mutant microarray data encompassing 1529 ORFs. We hypothesized that transcription factors participating in the cell cycle regulation exhibit cyclic activity profiles. This hypothesis was supported by the TFA profiles of known cell cycle factors and was used as a basis to uncover other potential cell cycle factors. By combining the results from both cluster analysis and periodicity analysis, we recovered nearly 90% of the known cell cycle regulators, and identified 5 putative cell cycle-related transcription factors (Dal81, Hap2, Hir2, Mss11, and Rlm1). In addition, by analyzing expression data from transcription factor knockout strains, we determined 3 verified (Ace2, Ndd1, and Swi5) and 4 putative interaction partners (Cha4, Hap2, Fhl1, and Rts2) of the forkhead transcription factors. Sensitivity of TFAs to connectivity errors was determined to provide confidence level of these predictions. Conclusion By subjecting TFA profiles to analyses based upon physiological signatures we were able to identify cell cycle related transcription factors consistent with current literature, transcription factors with potential cell cycle dependent roles, and interactions between transcription factors. Ausführliche Beschreibung

Gespeichert in:

Autor*in:	Yang, Young-Lyeol [verfasserIn] Suen, Jason Brynildsen, Mark P Galbraith, Simon J Liao, James C

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2005

Schlagwörter:	Transcription Factor Activity Forkhead Transcription Factor Connectivity Information Connectivity Error Putative Cell

Anmerkung:	© Yang et al; licensee BioMed Central Ltd. 2005. This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (

Übergeordnetes Werk:	Enthalten in: BMC genomics - London : BioMed Central, 2000, 6(2005), 1 vom: 10. Juni
Übergeordnetes Werk:	volume:6 ; year:2005 ; number:1 ; day:10 ; month:06

Links:	Volltext

DOI / URN:	10.1186/1471-2164-6-90

Katalog-ID:	SPR027023427

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520			\|a Background Since transcription factors are often regulated at the post-transcriptional level, their activities, rather than expression levels may provide valuable information for investigating functions and their interactions. The recently developed Network Component Analysis (NCA) and its generalized form (gNCA) provide a robust framework for deducing the transcription factor activities (TFAs) from various types of DNA microarray data and transcription factor-gene connectivity. The goal of this work is to demonstrate the utility of TFAs in inferring transcription factor functions and interactions in Saccharomyces cerevisiae cell cycle regulation. Results Using gNCA, we determined 74 TFAs from both wild type and fkh1 fkh2 deletion mutant microarray data encompassing 1529 ORFs. We hypothesized that transcription factors participating in the cell cycle regulation exhibit cyclic activity profiles. This hypothesis was supported by the TFA profiles of known cell cycle factors and was used as a basis to uncover other potential cell cycle factors. By combining the results from both cluster analysis and periodicity analysis, we recovered nearly 90% of the known cell cycle regulators, and identified 5 putative cell cycle-related transcription factors (Dal81, Hap2, Hir2, Mss11, and Rlm1). In addition, by analyzing expression data from transcription factor knockout strains, we determined 3 verified (Ace2, Ndd1, and Swi5) and 4 putative interaction partners (Cha4, Hap2, Fhl1, and Rts2) of the forkhead transcription factors. Sensitivity of TFAs to connectivity errors was determined to provide confidence level of these predictions. Conclusion By subjecting TFA profiles to analyses based upon physiological signatures we were able to identify cell cycle related transcription factors consistent with current literature, transcription factors with potential cell cycle dependent roles, and interactions between transcription factors.
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allfields	10.1186/1471-2164-6-90 doi (DE-627)SPR027023427 (SPR)1471-2164-6-90-e DE-627 ger DE-627 rakwb eng Yang, Young-Lyeol verfasserin aut Inferring yeast cell cycle regulators and interactions using transcription factor activities 2005 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Yang et al; licensee BioMed Central Ltd. 2005. This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( Background Since transcription factors are often regulated at the post-transcriptional level, their activities, rather than expression levels may provide valuable information for investigating functions and their interactions. The recently developed Network Component Analysis (NCA) and its generalized form (gNCA) provide a robust framework for deducing the transcription factor activities (TFAs) from various types of DNA microarray data and transcription factor-gene connectivity. The goal of this work is to demonstrate the utility of TFAs in inferring transcription factor functions and interactions in Saccharomyces cerevisiae cell cycle regulation. Results Using gNCA, we determined 74 TFAs from both wild type and fkh1 fkh2 deletion mutant microarray data encompassing 1529 ORFs. We hypothesized that transcription factors participating in the cell cycle regulation exhibit cyclic activity profiles. This hypothesis was supported by the TFA profiles of known cell cycle factors and was used as a basis to uncover other potential cell cycle factors. By combining the results from both cluster analysis and periodicity analysis, we recovered nearly 90% of the known cell cycle regulators, and identified 5 putative cell cycle-related transcription factors (Dal81, Hap2, Hir2, Mss11, and Rlm1). In addition, by analyzing expression data from transcription factor knockout strains, we determined 3 verified (Ace2, Ndd1, and Swi5) and 4 putative interaction partners (Cha4, Hap2, Fhl1, and Rts2) of the forkhead transcription factors. Sensitivity of TFAs to connectivity errors was determined to provide confidence level of these predictions. Conclusion By subjecting TFA profiles to analyses based upon physiological signatures we were able to identify cell cycle related transcription factors consistent with current literature, transcription factors with potential cell cycle dependent roles, and interactions between transcription factors. Transcription Factor Activity (dpeaa)DE-He213 Forkhead Transcription Factor (dpeaa)DE-He213 Connectivity Information (dpeaa)DE-He213 Connectivity Error (dpeaa)DE-He213 Putative Cell (dpeaa)DE-He213 Suen, Jason aut Brynildsen, Mark P aut Galbraith, Simon J aut Liao, James C aut Enthalten in BMC genomics London : BioMed Central, 2000 6(2005), 1 vom: 10. Juni (DE-627)326644954 (DE-600)2041499-7 1471-2164 nnns volume:6 year:2005 number:1 day:10 month:06 https://dx.doi.org/10.1186/1471-2164-6-90 kostenfrei 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_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 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_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2031 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2061 GBV_ILN_2111 GBV_ILN_2113 GBV_ILN_2190 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 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 6 2005 1 10 06
spelling	10.1186/1471-2164-6-90 doi (DE-627)SPR027023427 (SPR)1471-2164-6-90-e DE-627 ger DE-627 rakwb eng Yang, Young-Lyeol verfasserin aut Inferring yeast cell cycle regulators and interactions using transcription factor activities 2005 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Yang et al; licensee BioMed Central Ltd. 2005. This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( Background Since transcription factors are often regulated at the post-transcriptional level, their activities, rather than expression levels may provide valuable information for investigating functions and their interactions. The recently developed Network Component Analysis (NCA) and its generalized form (gNCA) provide a robust framework for deducing the transcription factor activities (TFAs) from various types of DNA microarray data and transcription factor-gene connectivity. The goal of this work is to demonstrate the utility of TFAs in inferring transcription factor functions and interactions in Saccharomyces cerevisiae cell cycle regulation. Results Using gNCA, we determined 74 TFAs from both wild type and fkh1 fkh2 deletion mutant microarray data encompassing 1529 ORFs. We hypothesized that transcription factors participating in the cell cycle regulation exhibit cyclic activity profiles. This hypothesis was supported by the TFA profiles of known cell cycle factors and was used as a basis to uncover other potential cell cycle factors. By combining the results from both cluster analysis and periodicity analysis, we recovered nearly 90% of the known cell cycle regulators, and identified 5 putative cell cycle-related transcription factors (Dal81, Hap2, Hir2, Mss11, and Rlm1). In addition, by analyzing expression data from transcription factor knockout strains, we determined 3 verified (Ace2, Ndd1, and Swi5) and 4 putative interaction partners (Cha4, Hap2, Fhl1, and Rts2) of the forkhead transcription factors. Sensitivity of TFAs to connectivity errors was determined to provide confidence level of these predictions. Conclusion By subjecting TFA profiles to analyses based upon physiological signatures we were able to identify cell cycle related transcription factors consistent with current literature, transcription factors with potential cell cycle dependent roles, and interactions between transcription factors. Transcription Factor Activity (dpeaa)DE-He213 Forkhead Transcription Factor (dpeaa)DE-He213 Connectivity Information (dpeaa)DE-He213 Connectivity Error (dpeaa)DE-He213 Putative Cell (dpeaa)DE-He213 Suen, Jason aut Brynildsen, Mark P aut Galbraith, Simon J aut Liao, James C aut Enthalten in BMC genomics London : BioMed Central, 2000 6(2005), 1 vom: 10. Juni (DE-627)326644954 (DE-600)2041499-7 1471-2164 nnns volume:6 year:2005 number:1 day:10 month:06 https://dx.doi.org/10.1186/1471-2164-6-90 kostenfrei 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_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 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_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2031 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2061 GBV_ILN_2111 GBV_ILN_2113 GBV_ILN_2190 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 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 6 2005 1 10 06
allfields_unstemmed	10.1186/1471-2164-6-90 doi (DE-627)SPR027023427 (SPR)1471-2164-6-90-e DE-627 ger DE-627 rakwb eng Yang, Young-Lyeol verfasserin aut Inferring yeast cell cycle regulators and interactions using transcription factor activities 2005 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Yang et al; licensee BioMed Central Ltd. 2005. This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( Background Since transcription factors are often regulated at the post-transcriptional level, their activities, rather than expression levels may provide valuable information for investigating functions and their interactions. The recently developed Network Component Analysis (NCA) and its generalized form (gNCA) provide a robust framework for deducing the transcription factor activities (TFAs) from various types of DNA microarray data and transcription factor-gene connectivity. The goal of this work is to demonstrate the utility of TFAs in inferring transcription factor functions and interactions in Saccharomyces cerevisiae cell cycle regulation. Results Using gNCA, we determined 74 TFAs from both wild type and fkh1 fkh2 deletion mutant microarray data encompassing 1529 ORFs. We hypothesized that transcription factors participating in the cell cycle regulation exhibit cyclic activity profiles. This hypothesis was supported by the TFA profiles of known cell cycle factors and was used as a basis to uncover other potential cell cycle factors. By combining the results from both cluster analysis and periodicity analysis, we recovered nearly 90% of the known cell cycle regulators, and identified 5 putative cell cycle-related transcription factors (Dal81, Hap2, Hir2, Mss11, and Rlm1). In addition, by analyzing expression data from transcription factor knockout strains, we determined 3 verified (Ace2, Ndd1, and Swi5) and 4 putative interaction partners (Cha4, Hap2, Fhl1, and Rts2) of the forkhead transcription factors. Sensitivity of TFAs to connectivity errors was determined to provide confidence level of these predictions. Conclusion By subjecting TFA profiles to analyses based upon physiological signatures we were able to identify cell cycle related transcription factors consistent with current literature, transcription factors with potential cell cycle dependent roles, and interactions between transcription factors. Transcription Factor Activity (dpeaa)DE-He213 Forkhead Transcription Factor (dpeaa)DE-He213 Connectivity Information (dpeaa)DE-He213 Connectivity Error (dpeaa)DE-He213 Putative Cell (dpeaa)DE-He213 Suen, Jason aut Brynildsen, Mark P aut Galbraith, Simon J aut Liao, James C aut Enthalten in BMC genomics London : BioMed Central, 2000 6(2005), 1 vom: 10. Juni (DE-627)326644954 (DE-600)2041499-7 1471-2164 nnns volume:6 year:2005 number:1 day:10 month:06 https://dx.doi.org/10.1186/1471-2164-6-90 kostenfrei 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_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 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_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2031 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2061 GBV_ILN_2111 GBV_ILN_2113 GBV_ILN_2190 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 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 6 2005 1 10 06
allfieldsGer	10.1186/1471-2164-6-90 doi (DE-627)SPR027023427 (SPR)1471-2164-6-90-e DE-627 ger DE-627 rakwb eng Yang, Young-Lyeol verfasserin aut Inferring yeast cell cycle regulators and interactions using transcription factor activities 2005 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Yang et al; licensee BioMed Central Ltd. 2005. This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( Background Since transcription factors are often regulated at the post-transcriptional level, their activities, rather than expression levels may provide valuable information for investigating functions and their interactions. The recently developed Network Component Analysis (NCA) and its generalized form (gNCA) provide a robust framework for deducing the transcription factor activities (TFAs) from various types of DNA microarray data and transcription factor-gene connectivity. The goal of this work is to demonstrate the utility of TFAs in inferring transcription factor functions and interactions in Saccharomyces cerevisiae cell cycle regulation. Results Using gNCA, we determined 74 TFAs from both wild type and fkh1 fkh2 deletion mutant microarray data encompassing 1529 ORFs. We hypothesized that transcription factors participating in the cell cycle regulation exhibit cyclic activity profiles. This hypothesis was supported by the TFA profiles of known cell cycle factors and was used as a basis to uncover other potential cell cycle factors. By combining the results from both cluster analysis and periodicity analysis, we recovered nearly 90% of the known cell cycle regulators, and identified 5 putative cell cycle-related transcription factors (Dal81, Hap2, Hir2, Mss11, and Rlm1). In addition, by analyzing expression data from transcription factor knockout strains, we determined 3 verified (Ace2, Ndd1, and Swi5) and 4 putative interaction partners (Cha4, Hap2, Fhl1, and Rts2) of the forkhead transcription factors. Sensitivity of TFAs to connectivity errors was determined to provide confidence level of these predictions. Conclusion By subjecting TFA profiles to analyses based upon physiological signatures we were able to identify cell cycle related transcription factors consistent with current literature, transcription factors with potential cell cycle dependent roles, and interactions between transcription factors. Transcription Factor Activity (dpeaa)DE-He213 Forkhead Transcription Factor (dpeaa)DE-He213 Connectivity Information (dpeaa)DE-He213 Connectivity Error (dpeaa)DE-He213 Putative Cell (dpeaa)DE-He213 Suen, Jason aut Brynildsen, Mark P aut Galbraith, Simon J aut Liao, James C aut Enthalten in BMC genomics London : BioMed Central, 2000 6(2005), 1 vom: 10. Juni (DE-627)326644954 (DE-600)2041499-7 1471-2164 nnns volume:6 year:2005 number:1 day:10 month:06 https://dx.doi.org/10.1186/1471-2164-6-90 kostenfrei 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_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 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_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2031 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2061 GBV_ILN_2111 GBV_ILN_2113 GBV_ILN_2190 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 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 6 2005 1 10 06
allfieldsSound	10.1186/1471-2164-6-90 doi (DE-627)SPR027023427 (SPR)1471-2164-6-90-e DE-627 ger DE-627 rakwb eng Yang, Young-Lyeol verfasserin aut Inferring yeast cell cycle regulators and interactions using transcription factor activities 2005 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Yang et al; licensee BioMed Central Ltd. 2005. This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( Background Since transcription factors are often regulated at the post-transcriptional level, their activities, rather than expression levels may provide valuable information for investigating functions and their interactions. The recently developed Network Component Analysis (NCA) and its generalized form (gNCA) provide a robust framework for deducing the transcription factor activities (TFAs) from various types of DNA microarray data and transcription factor-gene connectivity. The goal of this work is to demonstrate the utility of TFAs in inferring transcription factor functions and interactions in Saccharomyces cerevisiae cell cycle regulation. Results Using gNCA, we determined 74 TFAs from both wild type and fkh1 fkh2 deletion mutant microarray data encompassing 1529 ORFs. We hypothesized that transcription factors participating in the cell cycle regulation exhibit cyclic activity profiles. This hypothesis was supported by the TFA profiles of known cell cycle factors and was used as a basis to uncover other potential cell cycle factors. By combining the results from both cluster analysis and periodicity analysis, we recovered nearly 90% of the known cell cycle regulators, and identified 5 putative cell cycle-related transcription factors (Dal81, Hap2, Hir2, Mss11, and Rlm1). In addition, by analyzing expression data from transcription factor knockout strains, we determined 3 verified (Ace2, Ndd1, and Swi5) and 4 putative interaction partners (Cha4, Hap2, Fhl1, and Rts2) of the forkhead transcription factors. Sensitivity of TFAs to connectivity errors was determined to provide confidence level of these predictions. Conclusion By subjecting TFA profiles to analyses based upon physiological signatures we were able to identify cell cycle related transcription factors consistent with current literature, transcription factors with potential cell cycle dependent roles, and interactions between transcription factors. Transcription Factor Activity (dpeaa)DE-He213 Forkhead Transcription Factor (dpeaa)DE-He213 Connectivity Information (dpeaa)DE-He213 Connectivity Error (dpeaa)DE-He213 Putative Cell (dpeaa)DE-He213 Suen, Jason aut Brynildsen, Mark P aut Galbraith, Simon J aut Liao, James C aut Enthalten in BMC genomics London : BioMed Central, 2000 6(2005), 1 vom: 10. Juni (DE-627)326644954 (DE-600)2041499-7 1471-2164 nnns volume:6 year:2005 number:1 day:10 month:06 https://dx.doi.org/10.1186/1471-2164-6-90 kostenfrei 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_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 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_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2031 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2061 GBV_ILN_2111 GBV_ILN_2113 GBV_ILN_2190 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 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 6 2005 1 10 06
language	English
source	Enthalten in BMC genomics 6(2005), 1 vom: 10. Juni volume:6 year:2005 number:1 day:10 month:06
sourceStr	Enthalten in BMC genomics 6(2005), 1 vom: 10. Juni volume:6 year:2005 number:1 day:10 month:06
format_phy_str_mv	Article
institution	findex.gbv.de
topic_facet	Transcription Factor Activity Forkhead Transcription Factor Connectivity Information Connectivity Error Putative Cell
isfreeaccess_bool	true
container_title	BMC genomics
authorswithroles_txt_mv	Yang, Young-Lyeol @@aut@@ Suen, Jason @@aut@@ Brynildsen, Mark P @@aut@@ Galbraith, Simon J @@aut@@ Liao, James C @@aut@@
publishDateDaySort_date	2005-06-10T00:00:00Z
hierarchy_top_id	326644954
id	SPR027023427
language_de	englisch
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author	Yang, Young-Lyeol
spellingShingle	Yang, Young-Lyeol misc Transcription Factor Activity misc Forkhead Transcription Factor misc Connectivity Information misc Connectivity Error misc Putative Cell Inferring yeast cell cycle regulators and interactions using transcription factor activities
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topic_title	Inferring yeast cell cycle regulators and interactions using transcription factor activities Transcription Factor Activity (dpeaa)DE-He213 Forkhead Transcription Factor (dpeaa)DE-He213 Connectivity Information (dpeaa)DE-He213 Connectivity Error (dpeaa)DE-He213 Putative Cell (dpeaa)DE-He213
topic	misc Transcription Factor Activity misc Forkhead Transcription Factor misc Connectivity Information misc Connectivity Error misc Putative Cell
topic_unstemmed	misc Transcription Factor Activity misc Forkhead Transcription Factor misc Connectivity Information misc Connectivity Error misc Putative Cell
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title	Inferring yeast cell cycle regulators and interactions using transcription factor activities
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title_full	Inferring yeast cell cycle regulators and interactions using transcription factor activities
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author_browse	Yang, Young-Lyeol Suen, Jason Brynildsen, Mark P Galbraith, Simon J Liao, James C
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title_sort	inferring yeast cell cycle regulators and interactions using transcription factor activities
title_auth	Inferring yeast cell cycle regulators and interactions using transcription factor activities
abstract	Background Since transcription factors are often regulated at the post-transcriptional level, their activities, rather than expression levels may provide valuable information for investigating functions and their interactions. The recently developed Network Component Analysis (NCA) and its generalized form (gNCA) provide a robust framework for deducing the transcription factor activities (TFAs) from various types of DNA microarray data and transcription factor-gene connectivity. The goal of this work is to demonstrate the utility of TFAs in inferring transcription factor functions and interactions in Saccharomyces cerevisiae cell cycle regulation. Results Using gNCA, we determined 74 TFAs from both wild type and fkh1 fkh2 deletion mutant microarray data encompassing 1529 ORFs. We hypothesized that transcription factors participating in the cell cycle regulation exhibit cyclic activity profiles. This hypothesis was supported by the TFA profiles of known cell cycle factors and was used as a basis to uncover other potential cell cycle factors. By combining the results from both cluster analysis and periodicity analysis, we recovered nearly 90% of the known cell cycle regulators, and identified 5 putative cell cycle-related transcription factors (Dal81, Hap2, Hir2, Mss11, and Rlm1). In addition, by analyzing expression data from transcription factor knockout strains, we determined 3 verified (Ace2, Ndd1, and Swi5) and 4 putative interaction partners (Cha4, Hap2, Fhl1, and Rts2) of the forkhead transcription factors. Sensitivity of TFAs to connectivity errors was determined to provide confidence level of these predictions. Conclusion By subjecting TFA profiles to analyses based upon physiological signatures we were able to identify cell cycle related transcription factors consistent with current literature, transcription factors with potential cell cycle dependent roles, and interactions between transcription factors. © Yang et al; licensee BioMed Central Ltd. 2005. This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (
abstractGer	Background Since transcription factors are often regulated at the post-transcriptional level, their activities, rather than expression levels may provide valuable information for investigating functions and their interactions. The recently developed Network Component Analysis (NCA) and its generalized form (gNCA) provide a robust framework for deducing the transcription factor activities (TFAs) from various types of DNA microarray data and transcription factor-gene connectivity. The goal of this work is to demonstrate the utility of TFAs in inferring transcription factor functions and interactions in Saccharomyces cerevisiae cell cycle regulation. Results Using gNCA, we determined 74 TFAs from both wild type and fkh1 fkh2 deletion mutant microarray data encompassing 1529 ORFs. We hypothesized that transcription factors participating in the cell cycle regulation exhibit cyclic activity profiles. This hypothesis was supported by the TFA profiles of known cell cycle factors and was used as a basis to uncover other potential cell cycle factors. By combining the results from both cluster analysis and periodicity analysis, we recovered nearly 90% of the known cell cycle regulators, and identified 5 putative cell cycle-related transcription factors (Dal81, Hap2, Hir2, Mss11, and Rlm1). In addition, by analyzing expression data from transcription factor knockout strains, we determined 3 verified (Ace2, Ndd1, and Swi5) and 4 putative interaction partners (Cha4, Hap2, Fhl1, and Rts2) of the forkhead transcription factors. Sensitivity of TFAs to connectivity errors was determined to provide confidence level of these predictions. Conclusion By subjecting TFA profiles to analyses based upon physiological signatures we were able to identify cell cycle related transcription factors consistent with current literature, transcription factors with potential cell cycle dependent roles, and interactions between transcription factors. © Yang et al; licensee BioMed Central Ltd. 2005. This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (
abstract_unstemmed	Background Since transcription factors are often regulated at the post-transcriptional level, their activities, rather than expression levels may provide valuable information for investigating functions and their interactions. The recently developed Network Component Analysis (NCA) and its generalized form (gNCA) provide a robust framework for deducing the transcription factor activities (TFAs) from various types of DNA microarray data and transcription factor-gene connectivity. The goal of this work is to demonstrate the utility of TFAs in inferring transcription factor functions and interactions in Saccharomyces cerevisiae cell cycle regulation. Results Using gNCA, we determined 74 TFAs from both wild type and fkh1 fkh2 deletion mutant microarray data encompassing 1529 ORFs. We hypothesized that transcription factors participating in the cell cycle regulation exhibit cyclic activity profiles. This hypothesis was supported by the TFA profiles of known cell cycle factors and was used as a basis to uncover other potential cell cycle factors. By combining the results from both cluster analysis and periodicity analysis, we recovered nearly 90% of the known cell cycle regulators, and identified 5 putative cell cycle-related transcription factors (Dal81, Hap2, Hir2, Mss11, and Rlm1). In addition, by analyzing expression data from transcription factor knockout strains, we determined 3 verified (Ace2, Ndd1, and Swi5) and 4 putative interaction partners (Cha4, Hap2, Fhl1, and Rts2) of the forkhead transcription factors. Sensitivity of TFAs to connectivity errors was determined to provide confidence level of these predictions. Conclusion By subjecting TFA profiles to analyses based upon physiological signatures we were able to identify cell cycle related transcription factors consistent with current literature, transcription factors with potential cell cycle dependent roles, and interactions between transcription factors. © Yang et al; licensee BioMed Central Ltd. 2005. This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (
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title_short	Inferring yeast cell cycle regulators and interactions using transcription factor activities
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Inferring yeast cell cycle regulators and interactions using transcription factor activities

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