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Journal of Integrative Bioinformatics

Editor-in-Chief: Schreiber, Falk / Hofestädt, Ralf

Managing Editor: Sommer, Björn

Ed. by Baumbach, Jan / Chen, Ming / Orlov, Yuriy / Allmer, Jens

Editorial Board: Giorgetti, Alejandro / Harrison, Andrew / Kochetov, Aleksey / Krüger, Jens / Ma, Qi / Matsuno, Hiroshi / Mitra, Chanchal K. / Pauling, Josch K. / Rawlings, Chris / Fdez-Riverola, Florentino / Romano, Paolo / Röttger, Richard / Shoshi, Alban / Soares, Siomar de Castro / Taubert, Jan / Tauch, Andreas / Yousef, Malik / Weise, Stephan

4 Issues per year


CiteScore 2017: 0.77

SCImago Journal Rank (SJR) 2017: 0.336

Open Access
Online
ISSN
1613-4516
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Volume 7, Issue 3

Issues

MEMOPS: Data modelling and automatic code generation

Rasmus H. Fogh
  • Department of Biochemistry, University of Cambridge, 80 Tennis Court Road, Cambridge, CB2 1GA, United Kingdom of Great Britain and Northern Ireland
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/ Wayne Boucher
  • Department of Biochemistry, University of Cambridge, 80 Tennis Court Road, Cambridge, CB2 1GA, United Kingdom of Great Britain and Northern Ireland
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/ John M.C. Ionides
  • Department of Biochemistry, University of Cambridge, 80 Tennis Court Road, Cambridge, CB2 1GA, United Kingdom of Great Britain and Northern Ireland
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/ Wim F. Vranken
  • PDBe group, EMBL-EBI, European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1SD, United Kingdom of Great Britain and Northern Ireland
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/ Tim J. Stevens
  • Department of Biochemistry, University of Cambridge, 80 Tennis Court Road, Cambridge, CB2 1GA, United Kingdom of Great Britain and Northern Ireland
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/ Ernest D. Laue
  • Corresponding author
  • Department of Biochemistry, University of Cambridge, 80 Tennis Court Road, Cambridge, CB2 1GA, United Kingdom of Great Britain and Northern Ireland
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Published Online: 2016-10-18 | DOI: https://doi.org/10.1515/jib-2010-123

Summary

In recent years the amount of biological data has exploded to the point where much useful information can only be extracted by complex computational analyses. Such analyses are greatly facilitated by metadata standards, both in terms of the ability to compare data originating from different sources, and in terms of exchanging data in standard forms, e.g. when running processes on a distributed computing infrastructure. However, standards thrive on stability whereas science tends to constantly move, with new methods being developed and old ones modified. Therefore maintaining both metadata standards, and all the code that is required to make them useful, is a non-trivial problem. Memops is a framework that uses an abstract definition of the metadata (described in UML) to generate internal data structures and subroutine libraries for data access (application programming interfaces - APIs - currently in Python, C and Java) and data storage (in XML files or databases). For the individual project these libraries obviate the need for writing code for input parsing, validity checking or output. Memops also ensures that the code is always internally consistent, massively reducing the need for code reorganisation. Across a scientific domain a Memops-supported data model makes it easier to support complex standards that can capture all the data produced in a scientific area, share them among all programs in a complex software pipeline, and carry them forward to deposition in an archive. The principles behind the Memops generation code will be presented, along with example applications in Nuclear Magnetic Resonance (NMR) spectroscopy and structural biology.

About the article

Published Online: 2016-10-18

Published in Print: 2010-12-01


Citation Information: Journal of Integrative Bioinformatics, Volume 7, Issue 3, Pages 112–134, ISSN (Online) 1613-4516, DOI: https://doi.org/10.1515/jib-2010-123.

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© 2010 The Author(s). Published by Journal of Integrative Bioinformatics.. This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License. BY-NC-ND 4.0

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