A Bioinformatic Approach to Inter Functional Interactions within Protein Sequences

Abstract

The primary purpose of the current project was to evaluate the techniques they had developed to infer functional interactions between the sites within a protein and, if appropriate, refine them in the light of the results of evaluation. The initial results revealed significant limitations of their preliminary approaches. As a result of this project, it is now apparent that deep understanding of the significance of co-evolution between sites within a protein family requires sophisticated methods for identifying large groups of co-evolving sites, in some cases more than 100 sites that all co-evolve with one another. They have developed techniques that first identify all pairs of co-evolved sites and then identify all maximal cliques that can be formed from these pairs. In the process they developed a new data mining technique, association networks. In a separate study they have applied their approaches to the problem of whole genome alignment. They have successfully developed an engine that can align whole genomes and are extending it to handle the case of sequence reordering.

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Document Details

Document Type
Technical Report
Publication Date
Feb 23, 2009
Accession Number
ADA494590

Entities

People

  • Geoff Webb
  • James C. Whisstock

Organizations

  • Monash University

Tags

Communities of Interest

  • Biomedical

DTIC Thesaurus Topics

  • Algorithms
  • Amino Acids
  • Artificial Intelligence
  • Computational Science
  • Computer Programming
  • Computer Programs
  • Data Analysis
  • Data Mining
  • Data Science
  • Databases
  • Genetics
  • Information Science
  • Machine Learning
  • Molecular Biology
  • Network Science
  • Proteins
  • Test And Evaluation

Readers

  • Molecular and Cellular Biochemistry
  • Oncology and Biomarker-Based Cancer Detection.
  • Systems Analysis and Design

Technology Areas

  • AI & ML