Grouping and identification of sequence tags (GRIST): bioinformatics tools for the NEIBank database

Mol Vis. 2002 Jun 15:8:164-70.


NEIBank is a project to develop and organize genomics and bioinformatics resources for the eye. As part of this effort, tools have been developed for bioinformatics analysis and web based display of data from expressed sequence tag (EST) analyses. EST sequences are identified and formed into groups or clusters representing related transcripts from the same gene. This is carried out by a rules-based procedure called GRIST (GRouping and Identification of Sequence Tags) that uses sequence match parameters derived from BLAST programs. Linked procedures are used to eliminate non-mRNA contaminants. All data are assembled in a relational database and assembled for display as web pages with annotations and links to other informatics resources. Genome projects generate huge amounts of data that need to be classified and organized to become easily accessible to the research community. GRIST provides a useful tool for assembling and displaying the results of EST analyses. The NEIBank web site contains a growing set of pages cataloging the known transcriptional repertoire of eye tissues, derived from new NEIBank cDNA libraries and from eye-related data deposited in the dbEST section of GenBank.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Animals
  • Computational Biology / organization & administration*
  • Databases, Genetic*
  • Expressed Sequence Tags*
  • Eye Proteins / genetics
  • Gene Expression Profiling
  • Human Genome Project
  • Humans
  • National Institutes of Health (U.S.)
  • Oligonucleotide Array Sequence Analysis
  • Ophthalmology / organization & administration*
  • Transcription Factors / genetics
  • United States


  • Eye Proteins
  • Transcription Factors