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

Protein family classification using sparse Markov transducers.

E Eskin1, W N Grundy, Y Singer

  • 1Department of Computer Science, Columbia University, USA. eeskin@cs.columbia.edu

Proceedings. International Conference on Intelligent Systems for Molecular Biology
|September 8, 2000
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

Acute Kidney Injury: It's not just the 'big' burns.

Injury·2017
Same author

Increasing the power of meta-analysis of genome-wide association studies to detect heterogeneous effects.

Bioinformatics (Oxford, England)·2017
Same author

Genome-wide association study of NMDA receptor coagonists in human cerebrospinal fluid and plasma.

Molecular psychiatry·2015
Same author

Heritability of periodontal bone loss in mice.

Journal of periodontal research·2015
Same author

Genome-wide association study of monoamine metabolite levels in human cerebrospinal fluid.

Molecular psychiatry·2013
Same author

Genome-wide association study of Tourette's syndrome.

Molecular psychiatry·2012
Same journal

Proceedings of the 8th International Conference on Intelligent Systems for Molecular Biology (ISMB 2000). San Diego, California, USA. August 19-23, 2000.

Proceedings. International Conference on Intelligent Systems for Molecular Biology·2001
Same journal

Analysis of gene expression data with pathway scores.

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

Towards a complete map of the protein space based on a unified sequence and structure analysis of all known proteins.

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

Mining for putative regulatory elements in the yeast genome using gene expression data.

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

A multiple alignment algorithm for metabolic pathway analysis using enzyme hierarchy.

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

Sequence database search using jumping alignments.

Proceedings. International Conference on Intelligent Systems for Molecular Biology·2000
See all related articles

We introduce sparse Markov transducers (SMTs) for protein family classification. This method improves accuracy by using wildcards to model common amino acid substitutions, outperforming previous approaches.

Area of Science:

  • Bioinformatics
  • Computational Biology
  • Machine Learning

Background:

  • Protein families are crucial for understanding biological function.
  • Accurate protein classification is essential for biological research.
  • Existing methods may not fully capture the variability within protein families.

Purpose of the Study:

  • To develop a novel method for protein family classification using sparse Markov transducers (SMTs).
  • To improve classification performance by incorporating wildcard characters into the model.
  • To present efficient data structures for memory optimization in SMT-based classifiers.

Main Methods:

  • Utilizing sparse Markov transducers (SMTs), a generalization of probabilistic suffix trees, for sequence probability estimation.

Related Experiment Videos

  • Incorporating wildcard characters in SMTs to account for amino acid substitutions.
  • Developing two distinct models for building protein family classifiers with SMTs.
  • Implementing efficient data structures to reduce memory footprint.

    • Main Results:

    • SMTs demonstrate improved protein family classification performance compared to existing methods.
    • The inclusion of wildcards significantly enhances the model's ability to handle amino acid substitutions.
    • The developed SMT models achieved competitive results on the Pfam database.

    Conclusions:

    • Sparse Markov transducers offer a powerful and effective approach for protein family classification.
    • The flexibility of SMTs in handling sequence variations makes them well-suited for biological sequence analysis.
    • This work provides an efficient and accurate computational tool for protein family identification.