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: | Berrar D; School of Biomedical Sciences, University of Ulster, Coleraine, Coleraine, Northern Ireland Cromore Road, BT52 1SA, Coleraine, Northern Ireland. dp.berrar@ulster.ac.uk, Stahl F, Silva C, Rodrigues JR, Brito RM, Dubitzky W |
| Πηγή: | Journal of clinical monitoring and computing [J Clin Monit Comput] 2005 Oct; Vol. 19 (4-5), pp. 307-17. |
| Τύπος έκδοσης: | Journal Article |
| Γλώσσα: | English |
| Στοιχεία περιοδικού: | Publisher: Springer Country of Publication: Netherlands NLM ID: 9806357 Publication Model: Print Cited Medium: Print ISSN: 1387-1307 (Print) Linking ISSN: 13871307 NLM ISO Abbreviation: J Clin Monit Comput Subsets: MEDLINE |
| Imprint Name(s): | Publication: Amsterdam : Springer Original Publication: Dordrecht, The Netherlands ; Boston : Kluwer Academic Publishers, c1998- |
| Ιατρικοί όροι (MeSH): | Computer Simulation* , Information Storage and Retrieval* , Protein Folding*, Computational Biology ; Protein Conformation |
| 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. |
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| Entry Date(s): | Date Created: 20051206 Date Completed: 20060411 Latest Revision: 20220716 |
| Update Code: | 20260130 |
| DOI: | 10.1007/s10877-005-0676-z |
| PMID: | 16328945 |
| Βάση Δεδομένων: | MEDLINE |
| ISSN: | 1387-1307 |
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| DOI: | 10.1007/s10877-005-0676-z |