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Related Experiment Videos

ESTScan: a program for detecting, evaluating, and reconstructing potential coding regions in EST sequences.

C Iseli1, C V Jongeneel, P Bucher

  • 1Swiss Institute of Bioinformatics, Epalinges, Switzerland. Christian.Iseli@isb-sib.ch

Proceedings. International Conference on Intelligent Systems for Molecular Biology
|April 29, 2000
PubMed
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ESTScan, a new tool using hidden Markov models, accurately detects coding regions and corrects frameshift errors in low-quality expressed sequence tag (EST) sequences. This aids gene discovery and quality control in genome sequencing projects.

Area of Science:

  • Bioinformatics
  • Computational Biology
  • Genomics

Background:

  • Large-scale analysis of expressed sequence tag (EST) sequences is crucial for gene discovery.
  • Unannotated and low-quality ESTs present challenges in identifying coding regions and correcting frameshift errors.

Purpose of the Study:

  • To introduce a novel hidden Markov model (HMM) for analyzing error-prone sequences.
  • To develop an efficient program, ESTScan, for coding region detection and frameshift error correction.

Main Methods:

  • Development of a new HMM explicitly designed to handle sequence errors.
  • Implementation of the HMM into a robust software program, ESTScan.
  • Evaluation of ESTScan's performance on low-quality EST sequences.

Related Experiment Videos

Main Results:

  • ESTScan demonstrates high selectivity and sensitivity in detecting and extracting coding regions.
  • The program accurately corrects frameshift errors in EST sequences.
  • ESTScan proves efficient and robust for analyzing large datasets.

Conclusions:

  • ESTScan is a valuable tool for gene discovery in genome sequencing projects.
  • The software facilitates quality control of sequence data.
  • ESTScan aids in the assembly of contigs representing gene coding regions.