Academic Journal
Towards Data Warehousing and Mining of Protein Unfolding Simulation Data.
| Τίτλος: | Towards Data Warehousing and Mining of Protein Unfolding Simulation Data. |
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| Συγγραφείς: | Daniel Berrar, Frederic Stahl, Candida Silva, J. Rodrigues, Rui Brito, Werner Dubitzky |
| Πηγή: | Journal of Clinical Monitoring & Computing; Oct2005, Vol. 19 Issue 4/5, p307-317, 11p |
| Περίληψη: | 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. [ABSTRACT FROM AUTHOR] |
| Copyright of Journal of Clinical Monitoring & Computing is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Βάση Δεδομένων: | Complementary Index |
| FullText | Links: – Type: other Text: Availability: 0 |
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| Header | DbId: edb DbLabel: Complementary Index An: 20169103 RelevancyScore: 832 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 832.355102539063 |
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| Items | – Name: Title Label: Title Group: Ti Data: Towards Data Warehousing and Mining of Protein Unfolding Simulation Data. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Daniel++Berrar%22">Daniel Berrar</searchLink><br /><searchLink fieldCode="AR" term="%22Frederic++Stahl%22">Frederic Stahl</searchLink><br /><searchLink fieldCode="AR" term="%22Candida++Silva%22">Candida Silva</searchLink><br /><searchLink fieldCode="AR" term="%22J%2E++Rodrigues%22">J. Rodrigues</searchLink><br /><searchLink fieldCode="AR" term="%22Rui++Brito%22">Rui Brito</searchLink><br /><searchLink fieldCode="AR" term="%22Werner++Dubitzky%22">Werner Dubitzky</searchLink> – Name: TitleSource Label: Source Group: Src Data: Journal of Clinical Monitoring & Computing; Oct2005, Vol. 19 Issue 4/5, p307-317, 11p – Name: Abstract Label: Abstract Group: Ab Data: 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. [ABSTRACT FROM AUTHOR] – Name: Abstract Label: Group: Ab Data: <i>Copyright of Journal of Clinical Monitoring & Computing is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 11 StartPage: 307 Titles: – TitleFull: Towards Data Warehousing and Mining of Protein Unfolding Simulation Data. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Daniel Berrar – PersonEntity: Name: NameFull: Frederic Stahl – PersonEntity: Name: NameFull: Candida Silva – PersonEntity: Name: NameFull: J. Rodrigues – PersonEntity: Name: NameFull: Rui Brito – PersonEntity: Name: NameFull: Werner Dubitzky IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 10 Text: Oct2005 Type: published Y: 2005 Identifiers: – Type: issn-print Value: 13871307 Numbering: – Type: volume Value: 19 – Type: issue Value: 4/5 Titles: – TitleFull: Journal of Clinical Monitoring & Computing Type: main |
| ResultId | 1 |