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Related Experiment Videos

Which craft is best in bioinformatics?

T K Attwood1, C J Miller

  • 1School of Biological Sciences, The University of Manchester, UK. attwood@bioinf.man.ac.uk

Computers & Chemistry
|July 19, 2001
PubMed
Summary
This summary is machine-generated.

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Bioinformatics uses computational tools to study genomes, but current limitations in understanding genes, protein folding, and function necessitate a cautious, rigorous, and pragmatic approach to avoid over-enthusiasm.

Area of Science:

  • Genomics and Bioinformatics
  • Computational Biology
  • Molecular Evolution

Background:

  • Global sequencing projects enable large-scale genome analysis.
  • Understanding gene, protein folding, and function is key to 'silicon-based' biology.
  • Current computational models are constrained by incomplete biological understanding.

Purpose of the Study:

  • To highlight the limitations of current computational approaches in bioinformatics.
  • To emphasize the need for a realistic assessment of what computers can achieve in biological research.
  • To advocate for a cautious and rigorous approach in tackling biological complexity.

Main Methods:

  • Comparative genomics analysis.
  • Review of current understanding in gene definition, protein folding, and function.

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  • Lessons learned from artificial intelligence regarding knowledge representation.

    • Main Results:

    • Definitive understanding of gene identity is lacking.
    • Predicting protein structure and diagnosing function from sequence/structure alone is not consistently possible.
    • Capturing and representing complex biological knowledge is challenging and resource-intensive.

    Conclusions:

    • Acknowledge computational limitations to better define capabilities in bioinformatics.
    • Avoid over-enthusiastic claims about bioinformatics program achievements.
    • Embrace caution, rigor, and pragmatism for meaningful progress in computational biology.