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Evolutionary Relationships through Genome Comparisons02:54

Evolutionary Relationships through Genome Comparisons

Genome comparison is one of the excellent ways to interpret the evolutionary relationships between organisms. The basic principle of genome comparison is that if two species share a common feature, it is likely encoded by the DNA sequence conserved between both species. The advent of genome sequencing technologies in the late 20th century enabled scientists to understand the concept of conservation of domains between species and helped them to deduce evolutionary relationships across diverse...
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Genome Annotation and Assembly

The genome refers to all of the genetic material in an organism. It can range from a few million base pairs in microbial cells to several billion base pairs in many eukaryotic organisms. Genome assembly refers to the process of taking the DNA sequencing data and putting it all back together in a correct order to create a close representation of the original genome. This is followed by the identification of functional elements on the newly assembled genome, a process called genome annotation.

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Constructing and Visualizing Models using Mime-based Machine-learning Framework
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Revealing biological information using data structuring and automated learning.

Irina Mohorianu1, Vincent Moulton

  • 1School of Computing Sciences, University of East Anglia, NR4 7TJ, Norwich, UK. i.mohorianu@uea.ac.uk

Recent Patents on DNA & Gene Sequences
|February 4, 2011
PubMed
Summary
This summary is machine-generated.

This review covers bioinformatics patents for gene studies, highlighting their use in data warehousing, data mining, and network analysis. These patented methods offer broad applications in biological research, including RNA interference studies.

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Area of Science:

  • Bioinformatics
  • Genomics
  • Computational Biology

Background:

  • Bioinformatics tools are crucial for translating biological hypotheses into validated experimental results.
  • The process involves data storage, analysis, and statistical validation, with many steps being patented.

Purpose of the Study:

  • To review bioinformatics patents, primarily for gene study applications.
  • To highlight the universal applicability of these methods in biological research, such as RNA interference.

Main Methods:

  • Overview of key bioinformatics analysis steps: data warehousing, data mining, and network creation.
  • Discussion of patented approaches for each step, focusing on efficiency and insight generation.

Main Results:

  • Patents exist for optimizing database structures in data warehousing for efficient information retrieval.
  • Numerous patents cover data mining techniques, including differential expression, unsupervised, and supervised learning.
  • Patents also describe methods for constructing gene interaction networks to support biological conclusions.

Conclusions:

  • Bioinformatics patents cover essential stages from data management to biological network construction.
  • These patented methods demonstrate wide applicability across various biological study domains.