Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Videos

Searching gene and protein sequence databases.

T Barsalou1, D L Brutlag

  • 1IBM Thomas J. Watson Research Center, Yorktown Heights, NY 10598.

M.D. Computing : Computers in Medical Practice
|May 1, 1991
PubMed
Summary
This summary is machine-generated.

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Automated construction of structural motifs for predicting functional sites on protein structures.

Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing·2003
Same author

BioProspector: discovering conserved DNA motifs in upstream regulatory regions of co-expressed genes.

Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing·2001
Same author

Bayesian segmentation of protein secondary structure.

Journal of computational biology : a journal of computational molecular cell biology·2000
Same author

Fast probabilistic analysis of sequence function using scoring matrices.

Bioinformatics (Oxford, England)·2000
Same author

A motion planning approach to flexible ligand binding.

Proceedings. International Conference on Intelligent Systems for Molecular Biology·2000
Same author

The EMOTIF database.

Nucleic acids research·2000
Same journal

A clean slate: initiating a graduate program in health informatics.

M.D. computing : computers in medical practice·2001
Same journal

Drugs, codes, standards, and other incompatible things in the dark.

M.D. computing : computers in medical practice·2001
Same journal

Ambulatory care. Implementing an integrated clinical and practice management system.

M.D. computing : computers in medical practice·2001
Same journal

Currents in medical informatics. The Woods Hole experience.

M.D. computing : computers in medical practice·2001
Same journal

Computer telephony integration. Bringing together a host of new applications for healthcare.

M.D. computing : computers in medical practice·2001
Same journal

eHealthcareWorld 2000. Getting down to business.

M.D. computing : computers in medical practice·2001
See all related articles

This study details computer algorithms essential for analyzing human genome sequencing data. It examines algorithm performance for efficient searching of large molecular sequence databases.

Area of Science:

  • Bioinformatics
  • Computational Biology
  • Genomics

Background:

  • The Human Genome Project requires sophisticated computational tools.
  • Analyzing vast amounts of molecular sequence data is a significant challenge.
  • Efficient algorithms are critical for the success of genomic research.

Purpose of the Study:

  • To describe classic algorithms for similarity searching and sequence alignment.
  • To analyze the performance and running times of these essential bioinformatics algorithms.
  • To discuss recent improvements in algorithm efficiency for large-scale genomic databases.

Main Methods:

  • Description of established algorithms for molecular sequence comparison.
  • Analysis of computational complexity and running times for key algorithms.

Related Experiment Videos

  • Review of recent advancements in algorithm optimization.

    • Main Results:

    • Classic algorithms for similarity searching and sequence alignment are fundamental to genomics.
    • Algorithm performance directly impacts the efficiency of searching large sequence databases.
    • Ongoing improvements are enhancing the speed and scalability of sequence analysis.

    Conclusions:

    • Efficient algorithms are indispensable for the Human Genome Project and related research.
    • Understanding algorithm performance is key to managing and analyzing massive genomic datasets.
    • Continued development in bioinformatics algorithms will accelerate genomic discovery.