Towards Data Warehousing and Mining of Protein Unfolding Simulation Data
Autor(a) principal: | |
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Data de Publicação: | 2005 |
Outros Autores: | , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://hdl.handle.net/10316/7790 https://doi.org/10.1007/s10877-005-0676-z |
Resumo: | Objectives. The prediction of protein structure and the precise understanding of protein folding and unfolding processes remains one of the greatest challenges in structural biology and bioinformatics. Computer simulations based on molecular dynamics (MD) are at the forefront of the effort to gain a deeper understanding of these complex processes. Currently, these MD simulations are usually on the order of tens of nanoseconds, generate a large amount of conformational data and are computationally expensive. More and more groups run such simulations and generate a myriad of data, which raises new challenges in managing and analyzing these data. Because the vast range of proteins researchers want to study and simulate, the computational effort needed to generate data, the large data volumes involved, and the different types of analyses scientists need to perform, it is desirable to provide a public repository allowing researchers to pool and share protein unfolding data.Methods. To adequately organize, manage, and analyze the data generated by unfolding simulation studies, we designed a data warehouse system that is embedded in a grid environment to facilitate the seamless sharing of available computer resources and thus enable many groups to share complex molecular dynamics simulations on a more regular basis.Results.To gain insight into the conformational fluctuations and stability of the monomeric forms of the amyloidogenic protein transthyretin (TTR), molecular dynamics unfolding simulations of the monomer of human TTR have been conducted. Trajectory data and meta-data of the wild-type (WT) protein and the highly amyloidogenic variant L55P-TTR represent the test case for the data warehouse.Conclusions.Web and grid services, especially pre-defined data mining services that can run on or ‘near’ the data repository of the data warehouse, are likely to play a pivotal role in the analysis of molecular dynamics unfolding data. |
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Towards Data Warehousing and Mining of Protein Unfolding Simulation DataObjectives. The prediction of protein structure and the precise understanding of protein folding and unfolding processes remains one of the greatest challenges in structural biology and bioinformatics. Computer simulations based on molecular dynamics (MD) are at the forefront of the effort to gain a deeper understanding of these complex processes. Currently, these MD simulations are usually on the order of tens of nanoseconds, generate a large amount of conformational data and are computationally expensive. More and more groups run such simulations and generate a myriad of data, which raises new challenges in managing and analyzing these data. Because the vast range of proteins researchers want to study and simulate, the computational effort needed to generate data, the large data volumes involved, and the different types of analyses scientists need to perform, it is desirable to provide a public repository allowing researchers to pool and share protein unfolding data.Methods. To adequately organize, manage, and analyze the data generated by unfolding simulation studies, we designed a data warehouse system that is embedded in a grid environment to facilitate the seamless sharing of available computer resources and thus enable many groups to share complex molecular dynamics simulations on a more regular basis.Results.To gain insight into the conformational fluctuations and stability of the monomeric forms of the amyloidogenic protein transthyretin (TTR), molecular dynamics unfolding simulations of the monomer of human TTR have been conducted. Trajectory data and meta-data of the wild-type (WT) protein and the highly amyloidogenic variant L55P-TTR represent the test case for the data warehouse.Conclusions.Web and grid services, especially pre-defined data mining services that can run on or ‘near’ the data repository of the data warehouse, are likely to play a pivotal role in the analysis of molecular dynamics unfolding data.2005info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articlehttp://hdl.handle.net/10316/7790http://hdl.handle.net/10316/7790https://doi.org/10.1007/s10877-005-0676-zengJournal of Clinical Monitoring and Computing. 19:4 (2005) 307-317Berrar, DanielStahl, FredericSilva, CandidaRodrigues, J.Brito, RuiDubitzky, Wernerinfo:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2020-05-25T13:09:10Zoai:estudogeral.uc.pt:10316/7790Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T21:01:27.250777Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse |
dc.title.none.fl_str_mv |
Towards Data Warehousing and Mining of Protein Unfolding Simulation Data |
title |
Towards Data Warehousing and Mining of Protein Unfolding Simulation Data |
spellingShingle |
Towards Data Warehousing and Mining of Protein Unfolding Simulation Data Berrar, Daniel |
title_short |
Towards Data Warehousing and Mining of Protein Unfolding Simulation Data |
title_full |
Towards Data Warehousing and Mining of Protein Unfolding Simulation Data |
title_fullStr |
Towards Data Warehousing and Mining of Protein Unfolding Simulation Data |
title_full_unstemmed |
Towards Data Warehousing and Mining of Protein Unfolding Simulation Data |
title_sort |
Towards Data Warehousing and Mining of Protein Unfolding Simulation Data |
author |
Berrar, Daniel |
author_facet |
Berrar, Daniel Stahl, Frederic Silva, Candida Rodrigues, J. Brito, Rui Dubitzky, Werner |
author_role |
author |
author2 |
Stahl, Frederic Silva, Candida Rodrigues, J. Brito, Rui Dubitzky, Werner |
author2_role |
author author author author author |
dc.contributor.author.fl_str_mv |
Berrar, Daniel Stahl, Frederic Silva, Candida Rodrigues, J. Brito, Rui Dubitzky, Werner |
description |
Objectives. The prediction of protein structure and the precise understanding of protein folding and unfolding processes remains one of the greatest challenges in structural biology and bioinformatics. Computer simulations based on molecular dynamics (MD) are at the forefront of the effort to gain a deeper understanding of these complex processes. Currently, these MD simulations are usually on the order of tens of nanoseconds, generate a large amount of conformational data and are computationally expensive. More and more groups run such simulations and generate a myriad of data, which raises new challenges in managing and analyzing these data. Because the vast range of proteins researchers want to study and simulate, the computational effort needed to generate data, the large data volumes involved, and the different types of analyses scientists need to perform, it is desirable to provide a public repository allowing researchers to pool and share protein unfolding data.Methods. To adequately organize, manage, and analyze the data generated by unfolding simulation studies, we designed a data warehouse system that is embedded in a grid environment to facilitate the seamless sharing of available computer resources and thus enable many groups to share complex molecular dynamics simulations on a more regular basis.Results.To gain insight into the conformational fluctuations and stability of the monomeric forms of the amyloidogenic protein transthyretin (TTR), molecular dynamics unfolding simulations of the monomer of human TTR have been conducted. Trajectory data and meta-data of the wild-type (WT) protein and the highly amyloidogenic variant L55P-TTR represent the test case for the data warehouse.Conclusions.Web and grid services, especially pre-defined data mining services that can run on or ‘near’ the data repository of the data warehouse, are likely to play a pivotal role in the analysis of molecular dynamics unfolding data. |
publishDate |
2005 |
dc.date.none.fl_str_mv |
2005 |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/10316/7790 http://hdl.handle.net/10316/7790 https://doi.org/10.1007/s10877-005-0676-z |
url |
http://hdl.handle.net/10316/7790 https://doi.org/10.1007/s10877-005-0676-z |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
Journal of Clinical Monitoring and Computing. 19:4 (2005) 307-317 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.source.none.fl_str_mv |
reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação instacron:RCAAP |
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Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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RCAAP |
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RCAAP |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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