Molecular Genetics Information System (MOLGENIS): alternatives in developing local experimental genomics databases

Bioinformatics. 2004 Sep 1;20(13):2075-83. doi: 10.1093/bioinformatics/bth206. Epub 2004 Apr 1.

Abstract

Motivation: Genomic research laboratories need adequate infrastructure to support management of their data production and research workflow. But what makes infrastructure adequate? A lack of appropriate criteria makes any decision on buying or developing a system difficult. Here, we report on the decision process for the case of a molecular genetics group establishing a microarray laboratory.

Results: Five typical requirements for experimental genomics database systems were identified: (i) evolution ability to keep up with the fast developing genomics field; (ii) a suitable data model to deal with local diversity; (iii) suitable storage of data files in the system; (iv) easy exchange with other software; and (v) low maintenance costs. The computer scientists and the researchers of the local microarray laboratory considered alternative solutions for these five requirements and chose the following options: (i) use of automatic code generation; (ii) a customized data model based on standards; (iii) storage of datasets as black boxes instead of decomposing them in database tables; (iv) loosely linking to other programs for improved flexibility; and (v) a low-maintenance web-based user interface. Our team evaluated existing microarray databases and then decided to build a new system, Molecular Genetics Information System (MOLGENIS), implemented using code generation in a period of three months. This case can provide valuable insights and lessons to both software developers and a user community embarking on large-scale genomic projects.

Availability: http://www.molgenis.nl

Publication types

  • Comparative Study
  • Evaluation Study
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Computational Biology / methods*
  • Database Management Systems
  • Databases, Genetic*
  • Decision Support Techniques*
  • Genomics / methods*
  • Information Storage and Retrieval / methods
  • Molecular Biology / methods*
  • Needs Assessment*
  • Research Design*
  • Technology Assessment, Biomedical
  • User-Computer Interface