Literature DB >> 9730921

The LabBase system for data management in large scale biology research laboratories.

N Goodman1, S Rozen, L D Stein, A G Smith.   

Abstract

MOTIVATION: The development of laboratory information management systems (LIMSs) for large scale biology research projects can be a challenging problem. Many such projects generate complex datasets via complex procedures that undergo continuous refinement. A key software challenge is to simplify the database-development task so that databases can be built and modified quickly enough to keep pace with changing project-requirements.
RESULTS: LabBase extends the facilities offered by relational database systems to simplify the task of creating databases for large scale biology research projects. LabBase provides a structural object data model, similar to ACEDB, and adds to this the concepts of Materials, Steps, and States: Materials are objects representing the identifiable things that participate in a laboratory protocol; Steps are objects reporting the results of a laboratory or analytical procedure; and States are objects denoting places in a laboratory protocol. The system provides a data definition language for succinctly defining laboratory databases, and operations for conveniently storing and retrieving data in such databases. The system also provides support for workflow management. LabBase is implemented in Perl5 and provides a natural interface for laboratory application programs written in Perl. AVAILABILITY: The software is freely available. Contact the authors. CONTACT: nat@jax.org

Mesh:

Year:  1998        PMID: 9730921     DOI: 10.1093/bioinformatics/14.7.562

Source DB:  PubMed          Journal:  Bioinformatics        ISSN: 1367-4803            Impact factor:   6.937


  5 in total

1.  Secure web book to store structural genomics research data.

Authors:  Babu A Manjasetty; Klaus Höppner; Uwe Mueller; Udo Heinemann
Journal:  J Struct Funct Genomics       Date:  2003

Review 2.  Bioinformatics and systems biology of the lipidome.

Authors:  Shankar Subramaniam; Eoin Fahy; Shakti Gupta; Manish Sud; Robert W Byrnes; Dawn Cotter; Ashok Reddy Dinasarapu; Mano Ram Maurya
Journal:  Chem Rev       Date:  2011-09-23       Impact factor: 60.622

3.  Mapping by sequencing the Pneumocystis genome using the ordering DNA sequences V3 tool.

Authors:  Zheng Xu; Britton Lance; Claudia Vargas; Budak Arpinar; Suchendra Bhandarkar; Eileen Kraemer; Krys J Kochut; John A Miller; Jeff R Wagner; Michael J Weise; John K Wunderlich; James Stringer; George Smulian; Melanie T Cushion; Jonathan Arnold
Journal:  Genetics       Date:  2003-04       Impact factor: 4.562

4.  'PACLIMS': a component LIM system for high-throughput functional genomic analysis.

Authors:  Nicole Donofrio; Ravi Rajagopalon; Douglas Brown; Stephen Diener; Donald Windham; Shelly Nolin; Anna Floyd; Thomas Mitchell; Natalia Galadima; Sara Tucker; Marc J Orbach; Gayatri Patel; Mark Farman; Vishal Pampanwar; Cari Soderlund; Yong-Hwan Lee; Ralph A Dean
Journal:  BMC Bioinformatics       Date:  2005-04-12       Impact factor: 3.169

5.  Design and implementation of a generalized laboratory data model.

Authors:  Michael C Wendl; Scott Smith; Craig S Pohl; David J Dooling; Asif T Chinwalla; Kevin Crouse; Todd Hepler; Shin Leong; Lynn Carmichael; Mike Nhan; Benjamin J Oberkfell; Elaine R Mardis; LaDeana W Hillier; Richard K Wilson
Journal:  BMC Bioinformatics       Date:  2007-09-26       Impact factor: 3.169

  5 in total

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