Two New Methods for Identifying Essential Proteins Based on the Protein Complexes and Topological Properties

The recognition of essential proteins not only can help to understand the mechanism of cell operation, but also help to study the mechanism of biological evolution. At present, many scholars have been discovering essential proteins according to the topological structure of protein network and comple...
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Autor*in:	Pengli Lu [verfasserIn] Jingjuan Yu [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2020

Schlagwörter:	Protein interaction network essential protein topology protein complex

Übergeordnetes Werk:	In: IEEE Access - IEEE, 2014, 8(2020), Seite 9578-9586
Übergeordnetes Werk:	volume:8 ; year:2020 ; pages:9578-9586

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc

DOI / URN:	10.1109/ACCESS.2019.2963537

Katalog-ID:	DOAJ071755306

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allfields	10.1109/ACCESS.2019.2963537 doi (DE-627)DOAJ071755306 (DE-599)DOAJ745ffb85e32e40cdb50db073977a4178 DE-627 ger DE-627 rakwb eng TK1-9971 Pengli Lu verfasserin aut Two New Methods for Identifying Essential Proteins Based on the Protein Complexes and Topological Properties 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier The recognition of essential proteins not only can help to understand the mechanism of cell operation, but also help to study the mechanism of biological evolution. At present, many scholars have been discovering essential proteins according to the topological structure of protein network and complexes. While some proteins still can not be recognized. In this paper, we proposed two new methods complex degree centrality (CDC) and complex in-degree and betweenness definition (CIBD) which integrate the local character of protein complexes and topological properties to determine the essentiality of proteins. First, we give the definitions of complex average centrality (CAC) and complex hybrid centrality (CHC) which both describe the properties of protein complexes. Then we propose these new methods CDC and CIBD based on CAC and CHC definitions. In order to access these two methods, different Protein-Protein Interaction (PPI) networks of Saccharomyces cerevisiae, DIP, MIPS and YMBD are used as experimental materials. By comparing with the competing methods including DC, BC, LAC, SC, EC, SoECC and the recent method LBCC and UC, our experimental results in networks show that the methods of CDC and CIBD can help to improve the precision of predicting essential proteins. Protein interaction network essential protein topology protein complex Electrical engineering. Electronics. Nuclear engineering Jingjuan Yu verfasserin aut In IEEE Access IEEE, 2014 8(2020), Seite 9578-9586 (DE-627)728440385 (DE-600)2687964-5 21693536 nnns volume:8 year:2020 pages:9578-9586 https://doi.org/10.1109/ACCESS.2019.2963537 kostenfrei https://doaj.org/article/745ffb85e32e40cdb50db073977a4178 kostenfrei https://ieeexplore.ieee.org/document/8947996/ kostenfrei https://doaj.org/toc/2169-3536 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ 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_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 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_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 8 2020 9578-9586
spelling	10.1109/ACCESS.2019.2963537 doi (DE-627)DOAJ071755306 (DE-599)DOAJ745ffb85e32e40cdb50db073977a4178 DE-627 ger DE-627 rakwb eng TK1-9971 Pengli Lu verfasserin aut Two New Methods for Identifying Essential Proteins Based on the Protein Complexes and Topological Properties 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier The recognition of essential proteins not only can help to understand the mechanism of cell operation, but also help to study the mechanism of biological evolution. At present, many scholars have been discovering essential proteins according to the topological structure of protein network and complexes. While some proteins still can not be recognized. In this paper, we proposed two new methods complex degree centrality (CDC) and complex in-degree and betweenness definition (CIBD) which integrate the local character of protein complexes and topological properties to determine the essentiality of proteins. First, we give the definitions of complex average centrality (CAC) and complex hybrid centrality (CHC) which both describe the properties of protein complexes. Then we propose these new methods CDC and CIBD based on CAC and CHC definitions. In order to access these two methods, different Protein-Protein Interaction (PPI) networks of Saccharomyces cerevisiae, DIP, MIPS and YMBD are used as experimental materials. By comparing with the competing methods including DC, BC, LAC, SC, EC, SoECC and the recent method LBCC and UC, our experimental results in networks show that the methods of CDC and CIBD can help to improve the precision of predicting essential proteins. Protein interaction network essential protein topology protein complex Electrical engineering. Electronics. Nuclear engineering Jingjuan Yu verfasserin aut In IEEE Access IEEE, 2014 8(2020), Seite 9578-9586 (DE-627)728440385 (DE-600)2687964-5 21693536 nnns volume:8 year:2020 pages:9578-9586 https://doi.org/10.1109/ACCESS.2019.2963537 kostenfrei https://doaj.org/article/745ffb85e32e40cdb50db073977a4178 kostenfrei https://ieeexplore.ieee.org/document/8947996/ kostenfrei https://doaj.org/toc/2169-3536 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ 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_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 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_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 8 2020 9578-9586
allfields_unstemmed	10.1109/ACCESS.2019.2963537 doi (DE-627)DOAJ071755306 (DE-599)DOAJ745ffb85e32e40cdb50db073977a4178 DE-627 ger DE-627 rakwb eng TK1-9971 Pengli Lu verfasserin aut Two New Methods for Identifying Essential Proteins Based on the Protein Complexes and Topological Properties 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier The recognition of essential proteins not only can help to understand the mechanism of cell operation, but also help to study the mechanism of biological evolution. At present, many scholars have been discovering essential proteins according to the topological structure of protein network and complexes. While some proteins still can not be recognized. In this paper, we proposed two new methods complex degree centrality (CDC) and complex in-degree and betweenness definition (CIBD) which integrate the local character of protein complexes and topological properties to determine the essentiality of proteins. First, we give the definitions of complex average centrality (CAC) and complex hybrid centrality (CHC) which both describe the properties of protein complexes. Then we propose these new methods CDC and CIBD based on CAC and CHC definitions. In order to access these two methods, different Protein-Protein Interaction (PPI) networks of Saccharomyces cerevisiae, DIP, MIPS and YMBD are used as experimental materials. By comparing with the competing methods including DC, BC, LAC, SC, EC, SoECC and the recent method LBCC and UC, our experimental results in networks show that the methods of CDC and CIBD can help to improve the precision of predicting essential proteins. Protein interaction network essential protein topology protein complex Electrical engineering. Electronics. Nuclear engineering Jingjuan Yu verfasserin aut In IEEE Access IEEE, 2014 8(2020), Seite 9578-9586 (DE-627)728440385 (DE-600)2687964-5 21693536 nnns volume:8 year:2020 pages:9578-9586 https://doi.org/10.1109/ACCESS.2019.2963537 kostenfrei https://doaj.org/article/745ffb85e32e40cdb50db073977a4178 kostenfrei https://ieeexplore.ieee.org/document/8947996/ kostenfrei https://doaj.org/toc/2169-3536 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ 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_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 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_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 8 2020 9578-9586
allfieldsGer	10.1109/ACCESS.2019.2963537 doi (DE-627)DOAJ071755306 (DE-599)DOAJ745ffb85e32e40cdb50db073977a4178 DE-627 ger DE-627 rakwb eng TK1-9971 Pengli Lu verfasserin aut Two New Methods for Identifying Essential Proteins Based on the Protein Complexes and Topological Properties 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier The recognition of essential proteins not only can help to understand the mechanism of cell operation, but also help to study the mechanism of biological evolution. At present, many scholars have been discovering essential proteins according to the topological structure of protein network and complexes. While some proteins still can not be recognized. In this paper, we proposed two new methods complex degree centrality (CDC) and complex in-degree and betweenness definition (CIBD) which integrate the local character of protein complexes and topological properties to determine the essentiality of proteins. First, we give the definitions of complex average centrality (CAC) and complex hybrid centrality (CHC) which both describe the properties of protein complexes. Then we propose these new methods CDC and CIBD based on CAC and CHC definitions. In order to access these two methods, different Protein-Protein Interaction (PPI) networks of Saccharomyces cerevisiae, DIP, MIPS and YMBD are used as experimental materials. By comparing with the competing methods including DC, BC, LAC, SC, EC, SoECC and the recent method LBCC and UC, our experimental results in networks show that the methods of CDC and CIBD can help to improve the precision of predicting essential proteins. Protein interaction network essential protein topology protein complex Electrical engineering. Electronics. Nuclear engineering Jingjuan Yu verfasserin aut In IEEE Access IEEE, 2014 8(2020), Seite 9578-9586 (DE-627)728440385 (DE-600)2687964-5 21693536 nnns volume:8 year:2020 pages:9578-9586 https://doi.org/10.1109/ACCESS.2019.2963537 kostenfrei https://doaj.org/article/745ffb85e32e40cdb50db073977a4178 kostenfrei https://ieeexplore.ieee.org/document/8947996/ kostenfrei https://doaj.org/toc/2169-3536 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ 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_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 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_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 8 2020 9578-9586
allfieldsSound	10.1109/ACCESS.2019.2963537 doi (DE-627)DOAJ071755306 (DE-599)DOAJ745ffb85e32e40cdb50db073977a4178 DE-627 ger DE-627 rakwb eng TK1-9971 Pengli Lu verfasserin aut Two New Methods for Identifying Essential Proteins Based on the Protein Complexes and Topological Properties 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier The recognition of essential proteins not only can help to understand the mechanism of cell operation, but also help to study the mechanism of biological evolution. At present, many scholars have been discovering essential proteins according to the topological structure of protein network and complexes. While some proteins still can not be recognized. In this paper, we proposed two new methods complex degree centrality (CDC) and complex in-degree and betweenness definition (CIBD) which integrate the local character of protein complexes and topological properties to determine the essentiality of proteins. First, we give the definitions of complex average centrality (CAC) and complex hybrid centrality (CHC) which both describe the properties of protein complexes. Then we propose these new methods CDC and CIBD based on CAC and CHC definitions. In order to access these two methods, different Protein-Protein Interaction (PPI) networks of Saccharomyces cerevisiae, DIP, MIPS and YMBD are used as experimental materials. By comparing with the competing methods including DC, BC, LAC, SC, EC, SoECC and the recent method LBCC and UC, our experimental results in networks show that the methods of CDC and CIBD can help to improve the precision of predicting essential proteins. Protein interaction network essential protein topology protein complex Electrical engineering. Electronics. Nuclear engineering Jingjuan Yu verfasserin aut In IEEE Access IEEE, 2014 8(2020), Seite 9578-9586 (DE-627)728440385 (DE-600)2687964-5 21693536 nnns volume:8 year:2020 pages:9578-9586 https://doi.org/10.1109/ACCESS.2019.2963537 kostenfrei https://doaj.org/article/745ffb85e32e40cdb50db073977a4178 kostenfrei https://ieeexplore.ieee.org/document/8947996/ kostenfrei https://doaj.org/toc/2169-3536 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ 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_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 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_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 8 2020 9578-9586
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callnumber-first	T - Technology
author	Pengli Lu
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topic_title	TK1-9971 Two New Methods for Identifying Essential Proteins Based on the Protein Complexes and Topological Properties Protein interaction network essential protein topology protein complex
topic	misc TK1-9971 misc Protein interaction network misc essential protein misc topology misc protein complex misc Electrical engineering. Electronics. Nuclear engineering
topic_unstemmed	misc TK1-9971 misc Protein interaction network misc essential protein misc topology misc protein complex misc Electrical engineering. Electronics. Nuclear engineering
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title	Two New Methods for Identifying Essential Proteins Based on the Protein Complexes and Topological Properties
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title_full	Two New Methods for Identifying Essential Proteins Based on the Protein Complexes and Topological Properties
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title_sort	two new methods for identifying essential proteins based on the protein complexes and topological properties
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title_auth	Two New Methods for Identifying Essential Proteins Based on the Protein Complexes and Topological Properties
abstract	The recognition of essential proteins not only can help to understand the mechanism of cell operation, but also help to study the mechanism of biological evolution. At present, many scholars have been discovering essential proteins according to the topological structure of protein network and complexes. While some proteins still can not be recognized. In this paper, we proposed two new methods complex degree centrality (CDC) and complex in-degree and betweenness definition (CIBD) which integrate the local character of protein complexes and topological properties to determine the essentiality of proteins. First, we give the definitions of complex average centrality (CAC) and complex hybrid centrality (CHC) which both describe the properties of protein complexes. Then we propose these new methods CDC and CIBD based on CAC and CHC definitions. In order to access these two methods, different Protein-Protein Interaction (PPI) networks of Saccharomyces cerevisiae, DIP, MIPS and YMBD are used as experimental materials. By comparing with the competing methods including DC, BC, LAC, SC, EC, SoECC and the recent method LBCC and UC, our experimental results in networks show that the methods of CDC and CIBD can help to improve the precision of predicting essential proteins.
abstractGer	The recognition of essential proteins not only can help to understand the mechanism of cell operation, but also help to study the mechanism of biological evolution. At present, many scholars have been discovering essential proteins according to the topological structure of protein network and complexes. While some proteins still can not be recognized. In this paper, we proposed two new methods complex degree centrality (CDC) and complex in-degree and betweenness definition (CIBD) which integrate the local character of protein complexes and topological properties to determine the essentiality of proteins. First, we give the definitions of complex average centrality (CAC) and complex hybrid centrality (CHC) which both describe the properties of protein complexes. Then we propose these new methods CDC and CIBD based on CAC and CHC definitions. In order to access these two methods, different Protein-Protein Interaction (PPI) networks of Saccharomyces cerevisiae, DIP, MIPS and YMBD are used as experimental materials. By comparing with the competing methods including DC, BC, LAC, SC, EC, SoECC and the recent method LBCC and UC, our experimental results in networks show that the methods of CDC and CIBD can help to improve the precision of predicting essential proteins.
abstract_unstemmed	The recognition of essential proteins not only can help to understand the mechanism of cell operation, but also help to study the mechanism of biological evolution. At present, many scholars have been discovering essential proteins according to the topological structure of protein network and complexes. While some proteins still can not be recognized. In this paper, we proposed two new methods complex degree centrality (CDC) and complex in-degree and betweenness definition (CIBD) which integrate the local character of protein complexes and topological properties to determine the essentiality of proteins. First, we give the definitions of complex average centrality (CAC) and complex hybrid centrality (CHC) which both describe the properties of protein complexes. Then we propose these new methods CDC and CIBD based on CAC and CHC definitions. In order to access these two methods, different Protein-Protein Interaction (PPI) networks of Saccharomyces cerevisiae, DIP, MIPS and YMBD are used as experimental materials. By comparing with the competing methods including DC, BC, LAC, SC, EC, SoECC and the recent method LBCC and UC, our experimental results in networks show that the methods of CDC and CIBD can help to improve the precision of predicting essential proteins.
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title_short	Two New Methods for Identifying Essential Proteins Based on the Protein Complexes and Topological Properties
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Two New Methods for Identifying Essential Proteins Based on the Protein Complexes and Topological Properties

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