The exploration of disease-specific gene regulatory networks in esophageal carcinoma and stomach adenocarcinoma

Background Feed-forward loops (FFLs), consisting of miRNAs, transcription factors (TFs) and their common target genes, have been validated to be important for the initialization and development of complex diseases, including cancer. Esophageal Carcinoma (ESCA) and Stomach Adenocarcinoma (STAD) are t...
Ausführliche Beschreibung

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Autor*in:	Qin, Guimin [verfasserIn] Yang, Luqiong Ma, Yuying Liu, Jiayan Huo, Qiuyan

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2019

Schlagwörter:	Esophageal carcinoma Stomach adenocarcinoma Molecular mechanism Feed-forward loop Random walk with restart

Anmerkung:	© The Author(s). 2019

Übergeordnetes Werk:	Enthalten in: BMC bioinformatics - London : BioMed Central, 2000, 20(2019), Suppl 22 vom: 30. Dez.
Übergeordnetes Werk:	volume:20 ; year:2019 ; number:Suppl 22 ; day:30 ; month:12

Links:	Volltext

DOI / URN:	10.1186/s12859-019-3230-6

Katalog-ID:	SPR02692823X

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245	1	4	\|a The exploration of disease-specific gene regulatory networks in esophageal carcinoma and stomach adenocarcinoma
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520			\|a Background Feed-forward loops (FFLs), consisting of miRNAs, transcription factors (TFs) and their common target genes, have been validated to be important for the initialization and development of complex diseases, including cancer. Esophageal Carcinoma (ESCA) and Stomach Adenocarcinoma (STAD) are two types of malignant tumors in the digestive tract. Understanding common and distinct molecular mechanisms of ESCA and STAD is extremely crucial. Results In this paper, we presented a computational framework to explore common and distinct FFLs, and molecular biomarkers for ESCA and STAD. We identified FFLs by combining regulation pairs and RNA-seq data. Then we constructed disease-specific co-expression networks based on the FFLs identified. We also used random walk with restart (RWR) on disease-specific co-expression networks to prioritize candidate molecules. We identified 148 and 242 FFLs for these two types of cancer, respectively. And we found that one TF, E2F3 was related to ESCA, two genes, DTNA and KCNMA1 were related to STAD, while one TF ESR1 and one gene KIT were associated with both of the two types of cancer. Conclusions This proposed computational framework predicted disease-related biomolecules effectively and discovered the correlation between two types of cancers, which helped develop the diagnostic and therapeutic strategies of Esophageal Carcinoma and Stomach Adenocarcinoma.
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allfields	10.1186/s12859-019-3230-6 doi (DE-627)SPR02692823X (SPR)s12859-019-3230-6-e DE-627 ger DE-627 rakwb eng Qin, Guimin verfasserin aut The exploration of disease-specific gene regulatory networks in esophageal carcinoma and stomach adenocarcinoma 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s). 2019 Background Feed-forward loops (FFLs), consisting of miRNAs, transcription factors (TFs) and their common target genes, have been validated to be important for the initialization and development of complex diseases, including cancer. Esophageal Carcinoma (ESCA) and Stomach Adenocarcinoma (STAD) are two types of malignant tumors in the digestive tract. Understanding common and distinct molecular mechanisms of ESCA and STAD is extremely crucial. Results In this paper, we presented a computational framework to explore common and distinct FFLs, and molecular biomarkers for ESCA and STAD. We identified FFLs by combining regulation pairs and RNA-seq data. Then we constructed disease-specific co-expression networks based on the FFLs identified. We also used random walk with restart (RWR) on disease-specific co-expression networks to prioritize candidate molecules. We identified 148 and 242 FFLs for these two types of cancer, respectively. And we found that one TF, E2F3 was related to ESCA, two genes, DTNA and KCNMA1 were related to STAD, while one TF ESR1 and one gene KIT were associated with both of the two types of cancer. Conclusions This proposed computational framework predicted disease-related biomolecules effectively and discovered the correlation between two types of cancers, which helped develop the diagnostic and therapeutic strategies of Esophageal Carcinoma and Stomach Adenocarcinoma. Esophageal carcinoma (dpeaa)DE-He213 Stomach adenocarcinoma (dpeaa)DE-He213 Molecular mechanism (dpeaa)DE-He213 Feed-forward loop (dpeaa)DE-He213 Random walk with restart (dpeaa)DE-He213 Yang, Luqiong aut Ma, Yuying aut Liu, Jiayan aut Huo, Qiuyan aut Enthalten in BMC bioinformatics London : BioMed Central, 2000 20(2019), Suppl 22 vom: 30. Dez. (DE-627)326644814 (DE-600)2041484-5 1471-2105 nnns volume:20 year:2019 number:Suppl 22 day:30 month:12 https://dx.doi.org/10.1186/s12859-019-3230-6 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 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_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_370 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_4326 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 20 2019 Suppl 22 30 12
spelling	10.1186/s12859-019-3230-6 doi (DE-627)SPR02692823X (SPR)s12859-019-3230-6-e DE-627 ger DE-627 rakwb eng Qin, Guimin verfasserin aut The exploration of disease-specific gene regulatory networks in esophageal carcinoma and stomach adenocarcinoma 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s). 2019 Background Feed-forward loops (FFLs), consisting of miRNAs, transcription factors (TFs) and their common target genes, have been validated to be important for the initialization and development of complex diseases, including cancer. Esophageal Carcinoma (ESCA) and Stomach Adenocarcinoma (STAD) are two types of malignant tumors in the digestive tract. Understanding common and distinct molecular mechanisms of ESCA and STAD is extremely crucial. Results In this paper, we presented a computational framework to explore common and distinct FFLs, and molecular biomarkers for ESCA and STAD. We identified FFLs by combining regulation pairs and RNA-seq data. Then we constructed disease-specific co-expression networks based on the FFLs identified. We also used random walk with restart (RWR) on disease-specific co-expression networks to prioritize candidate molecules. We identified 148 and 242 FFLs for these two types of cancer, respectively. And we found that one TF, E2F3 was related to ESCA, two genes, DTNA and KCNMA1 were related to STAD, while one TF ESR1 and one gene KIT were associated with both of the two types of cancer. Conclusions This proposed computational framework predicted disease-related biomolecules effectively and discovered the correlation between two types of cancers, which helped develop the diagnostic and therapeutic strategies of Esophageal Carcinoma and Stomach Adenocarcinoma. Esophageal carcinoma (dpeaa)DE-He213 Stomach adenocarcinoma (dpeaa)DE-He213 Molecular mechanism (dpeaa)DE-He213 Feed-forward loop (dpeaa)DE-He213 Random walk with restart (dpeaa)DE-He213 Yang, Luqiong aut Ma, Yuying aut Liu, Jiayan aut Huo, Qiuyan aut Enthalten in BMC bioinformatics London : BioMed Central, 2000 20(2019), Suppl 22 vom: 30. Dez. (DE-627)326644814 (DE-600)2041484-5 1471-2105 nnns volume:20 year:2019 number:Suppl 22 day:30 month:12 https://dx.doi.org/10.1186/s12859-019-3230-6 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 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_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_370 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_4326 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 20 2019 Suppl 22 30 12
allfields_unstemmed	10.1186/s12859-019-3230-6 doi (DE-627)SPR02692823X (SPR)s12859-019-3230-6-e DE-627 ger DE-627 rakwb eng Qin, Guimin verfasserin aut The exploration of disease-specific gene regulatory networks in esophageal carcinoma and stomach adenocarcinoma 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s). 2019 Background Feed-forward loops (FFLs), consisting of miRNAs, transcription factors (TFs) and their common target genes, have been validated to be important for the initialization and development of complex diseases, including cancer. Esophageal Carcinoma (ESCA) and Stomach Adenocarcinoma (STAD) are two types of malignant tumors in the digestive tract. Understanding common and distinct molecular mechanisms of ESCA and STAD is extremely crucial. Results In this paper, we presented a computational framework to explore common and distinct FFLs, and molecular biomarkers for ESCA and STAD. We identified FFLs by combining regulation pairs and RNA-seq data. Then we constructed disease-specific co-expression networks based on the FFLs identified. We also used random walk with restart (RWR) on disease-specific co-expression networks to prioritize candidate molecules. We identified 148 and 242 FFLs for these two types of cancer, respectively. And we found that one TF, E2F3 was related to ESCA, two genes, DTNA and KCNMA1 were related to STAD, while one TF ESR1 and one gene KIT were associated with both of the two types of cancer. Conclusions This proposed computational framework predicted disease-related biomolecules effectively and discovered the correlation between two types of cancers, which helped develop the diagnostic and therapeutic strategies of Esophageal Carcinoma and Stomach Adenocarcinoma. Esophageal carcinoma (dpeaa)DE-He213 Stomach adenocarcinoma (dpeaa)DE-He213 Molecular mechanism (dpeaa)DE-He213 Feed-forward loop (dpeaa)DE-He213 Random walk with restart (dpeaa)DE-He213 Yang, Luqiong aut Ma, Yuying aut Liu, Jiayan aut Huo, Qiuyan aut Enthalten in BMC bioinformatics London : BioMed Central, 2000 20(2019), Suppl 22 vom: 30. Dez. (DE-627)326644814 (DE-600)2041484-5 1471-2105 nnns volume:20 year:2019 number:Suppl 22 day:30 month:12 https://dx.doi.org/10.1186/s12859-019-3230-6 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 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_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_370 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_4326 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 20 2019 Suppl 22 30 12
allfieldsGer	10.1186/s12859-019-3230-6 doi (DE-627)SPR02692823X (SPR)s12859-019-3230-6-e DE-627 ger DE-627 rakwb eng Qin, Guimin verfasserin aut The exploration of disease-specific gene regulatory networks in esophageal carcinoma and stomach adenocarcinoma 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s). 2019 Background Feed-forward loops (FFLs), consisting of miRNAs, transcription factors (TFs) and their common target genes, have been validated to be important for the initialization and development of complex diseases, including cancer. Esophageal Carcinoma (ESCA) and Stomach Adenocarcinoma (STAD) are two types of malignant tumors in the digestive tract. Understanding common and distinct molecular mechanisms of ESCA and STAD is extremely crucial. Results In this paper, we presented a computational framework to explore common and distinct FFLs, and molecular biomarkers for ESCA and STAD. We identified FFLs by combining regulation pairs and RNA-seq data. Then we constructed disease-specific co-expression networks based on the FFLs identified. We also used random walk with restart (RWR) on disease-specific co-expression networks to prioritize candidate molecules. We identified 148 and 242 FFLs for these two types of cancer, respectively. And we found that one TF, E2F3 was related to ESCA, two genes, DTNA and KCNMA1 were related to STAD, while one TF ESR1 and one gene KIT were associated with both of the two types of cancer. Conclusions This proposed computational framework predicted disease-related biomolecules effectively and discovered the correlation between two types of cancers, which helped develop the diagnostic and therapeutic strategies of Esophageal Carcinoma and Stomach Adenocarcinoma. Esophageal carcinoma (dpeaa)DE-He213 Stomach adenocarcinoma (dpeaa)DE-He213 Molecular mechanism (dpeaa)DE-He213 Feed-forward loop (dpeaa)DE-He213 Random walk with restart (dpeaa)DE-He213 Yang, Luqiong aut Ma, Yuying aut Liu, Jiayan aut Huo, Qiuyan aut Enthalten in BMC bioinformatics London : BioMed Central, 2000 20(2019), Suppl 22 vom: 30. Dez. (DE-627)326644814 (DE-600)2041484-5 1471-2105 nnns volume:20 year:2019 number:Suppl 22 day:30 month:12 https://dx.doi.org/10.1186/s12859-019-3230-6 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 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_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_370 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_4326 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 20 2019 Suppl 22 30 12
allfieldsSound	10.1186/s12859-019-3230-6 doi (DE-627)SPR02692823X (SPR)s12859-019-3230-6-e DE-627 ger DE-627 rakwb eng Qin, Guimin verfasserin aut The exploration of disease-specific gene regulatory networks in esophageal carcinoma and stomach adenocarcinoma 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s). 2019 Background Feed-forward loops (FFLs), consisting of miRNAs, transcription factors (TFs) and their common target genes, have been validated to be important for the initialization and development of complex diseases, including cancer. Esophageal Carcinoma (ESCA) and Stomach Adenocarcinoma (STAD) are two types of malignant tumors in the digestive tract. Understanding common and distinct molecular mechanisms of ESCA and STAD is extremely crucial. Results In this paper, we presented a computational framework to explore common and distinct FFLs, and molecular biomarkers for ESCA and STAD. We identified FFLs by combining regulation pairs and RNA-seq data. Then we constructed disease-specific co-expression networks based on the FFLs identified. We also used random walk with restart (RWR) on disease-specific co-expression networks to prioritize candidate molecules. We identified 148 and 242 FFLs for these two types of cancer, respectively. And we found that one TF, E2F3 was related to ESCA, two genes, DTNA and KCNMA1 were related to STAD, while one TF ESR1 and one gene KIT were associated with both of the two types of cancer. Conclusions This proposed computational framework predicted disease-related biomolecules effectively and discovered the correlation between two types of cancers, which helped develop the diagnostic and therapeutic strategies of Esophageal Carcinoma and Stomach Adenocarcinoma. Esophageal carcinoma (dpeaa)DE-He213 Stomach adenocarcinoma (dpeaa)DE-He213 Molecular mechanism (dpeaa)DE-He213 Feed-forward loop (dpeaa)DE-He213 Random walk with restart (dpeaa)DE-He213 Yang, Luqiong aut Ma, Yuying aut Liu, Jiayan aut Huo, Qiuyan aut Enthalten in BMC bioinformatics London : BioMed Central, 2000 20(2019), Suppl 22 vom: 30. Dez. (DE-627)326644814 (DE-600)2041484-5 1471-2105 nnns volume:20 year:2019 number:Suppl 22 day:30 month:12 https://dx.doi.org/10.1186/s12859-019-3230-6 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 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_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_370 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_4326 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 20 2019 Suppl 22 30 12
language	English
source	Enthalten in BMC bioinformatics 20(2019), Suppl 22 vom: 30. Dez. volume:20 year:2019 number:Suppl 22 day:30 month:12
sourceStr	Enthalten in BMC bioinformatics 20(2019), Suppl 22 vom: 30. Dez. volume:20 year:2019 number:Suppl 22 day:30 month:12
format_phy_str_mv	Article
institution	findex.gbv.de
topic_facet	Esophageal carcinoma Stomach adenocarcinoma Molecular mechanism Feed-forward loop Random walk with restart
isfreeaccess_bool	true
container_title	BMC bioinformatics
authorswithroles_txt_mv	Qin, Guimin @@aut@@ Yang, Luqiong @@aut@@ Ma, Yuying @@aut@@ Liu, Jiayan @@aut@@ Huo, Qiuyan @@aut@@
publishDateDaySort_date	2019-12-30T00:00:00Z
hierarchy_top_id	326644814
id	SPR02692823X
language_de	englisch
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author	Qin, Guimin
spellingShingle	Qin, Guimin misc Esophageal carcinoma misc Stomach adenocarcinoma misc Molecular mechanism misc Feed-forward loop misc Random walk with restart The exploration of disease-specific gene regulatory networks in esophageal carcinoma and stomach adenocarcinoma
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topic_title	The exploration of disease-specific gene regulatory networks in esophageal carcinoma and stomach adenocarcinoma Esophageal carcinoma (dpeaa)DE-He213 Stomach adenocarcinoma (dpeaa)DE-He213 Molecular mechanism (dpeaa)DE-He213 Feed-forward loop (dpeaa)DE-He213 Random walk with restart (dpeaa)DE-He213
topic	misc Esophageal carcinoma misc Stomach adenocarcinoma misc Molecular mechanism misc Feed-forward loop misc Random walk with restart
topic_unstemmed	misc Esophageal carcinoma misc Stomach adenocarcinoma misc Molecular mechanism misc Feed-forward loop misc Random walk with restart
topic_browse	misc Esophageal carcinoma misc Stomach adenocarcinoma misc Molecular mechanism misc Feed-forward loop misc Random walk with restart
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title	The exploration of disease-specific gene regulatory networks in esophageal carcinoma and stomach adenocarcinoma
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title_full	The exploration of disease-specific gene regulatory networks in esophageal carcinoma and stomach adenocarcinoma
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title_sort	exploration of disease-specific gene regulatory networks in esophageal carcinoma and stomach adenocarcinoma
title_auth	The exploration of disease-specific gene regulatory networks in esophageal carcinoma and stomach adenocarcinoma
abstract	Background Feed-forward loops (FFLs), consisting of miRNAs, transcription factors (TFs) and their common target genes, have been validated to be important for the initialization and development of complex diseases, including cancer. Esophageal Carcinoma (ESCA) and Stomach Adenocarcinoma (STAD) are two types of malignant tumors in the digestive tract. Understanding common and distinct molecular mechanisms of ESCA and STAD is extremely crucial. Results In this paper, we presented a computational framework to explore common and distinct FFLs, and molecular biomarkers for ESCA and STAD. We identified FFLs by combining regulation pairs and RNA-seq data. Then we constructed disease-specific co-expression networks based on the FFLs identified. We also used random walk with restart (RWR) on disease-specific co-expression networks to prioritize candidate molecules. We identified 148 and 242 FFLs for these two types of cancer, respectively. And we found that one TF, E2F3 was related to ESCA, two genes, DTNA and KCNMA1 were related to STAD, while one TF ESR1 and one gene KIT were associated with both of the two types of cancer. Conclusions This proposed computational framework predicted disease-related biomolecules effectively and discovered the correlation between two types of cancers, which helped develop the diagnostic and therapeutic strategies of Esophageal Carcinoma and Stomach Adenocarcinoma. © The Author(s). 2019
abstractGer	Background Feed-forward loops (FFLs), consisting of miRNAs, transcription factors (TFs) and their common target genes, have been validated to be important for the initialization and development of complex diseases, including cancer. Esophageal Carcinoma (ESCA) and Stomach Adenocarcinoma (STAD) are two types of malignant tumors in the digestive tract. Understanding common and distinct molecular mechanisms of ESCA and STAD is extremely crucial. Results In this paper, we presented a computational framework to explore common and distinct FFLs, and molecular biomarkers for ESCA and STAD. We identified FFLs by combining regulation pairs and RNA-seq data. Then we constructed disease-specific co-expression networks based on the FFLs identified. We also used random walk with restart (RWR) on disease-specific co-expression networks to prioritize candidate molecules. We identified 148 and 242 FFLs for these two types of cancer, respectively. And we found that one TF, E2F3 was related to ESCA, two genes, DTNA and KCNMA1 were related to STAD, while one TF ESR1 and one gene KIT were associated with both of the two types of cancer. Conclusions This proposed computational framework predicted disease-related biomolecules effectively and discovered the correlation between two types of cancers, which helped develop the diagnostic and therapeutic strategies of Esophageal Carcinoma and Stomach Adenocarcinoma. © The Author(s). 2019
abstract_unstemmed	Background Feed-forward loops (FFLs), consisting of miRNAs, transcription factors (TFs) and their common target genes, have been validated to be important for the initialization and development of complex diseases, including cancer. Esophageal Carcinoma (ESCA) and Stomach Adenocarcinoma (STAD) are two types of malignant tumors in the digestive tract. Understanding common and distinct molecular mechanisms of ESCA and STAD is extremely crucial. Results In this paper, we presented a computational framework to explore common and distinct FFLs, and molecular biomarkers for ESCA and STAD. We identified FFLs by combining regulation pairs and RNA-seq data. Then we constructed disease-specific co-expression networks based on the FFLs identified. We also used random walk with restart (RWR) on disease-specific co-expression networks to prioritize candidate molecules. We identified 148 and 242 FFLs for these two types of cancer, respectively. And we found that one TF, E2F3 was related to ESCA, two genes, DTNA and KCNMA1 were related to STAD, while one TF ESR1 and one gene KIT were associated with both of the two types of cancer. Conclusions This proposed computational framework predicted disease-related biomolecules effectively and discovered the correlation between two types of cancers, which helped develop the diagnostic and therapeutic strategies of Esophageal Carcinoma and Stomach Adenocarcinoma. © The Author(s). 2019
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container_issue	Suppl 22
title_short	The exploration of disease-specific gene regulatory networks in esophageal carcinoma and stomach adenocarcinoma
url	https://dx.doi.org/10.1186/s12859-019-3230-6
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The exploration of disease-specific gene regulatory networks in esophageal carcinoma and stomach adenocarcinoma

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