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A Visual Guide to Sorting Electrophysiological Recordings Using 'SpikeSorter'
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Sorting permutations by cut-circularize-linearize-and-paste operations.

Keng-Hsuan Huang1, Kun-Tze Chen, Chin Lung Lu

  • 1Institute of Bioinformatics and Systems Biology, National Chiao Tung University, Hsinchu 30010, Taiwan.

BMC Genomics
|February 29, 2012
PubMed
Summary
This summary is machine-generated.

This study introduces a new genome rearrangement operation called cut-circularize-linearize-and-paste (CCLP), which can model various genomic changes. An efficient algorithm sorts gene orders using CCLP operations, aiding in phylogenetic and immune response studies.

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Area of Science:

  • Computational Biology
  • Genomics
  • Evolutionary Biology

Background:

  • Genome rearrangements are crucial for understanding species evolution and are often studied by analyzing gene orders.
  • Various rearrangement operations like reversals and transpositions have been proposed to compare genomic differences.
  • Computational studies typically frame genome rearrangement as sorting permutations.

Purpose of the Study:

  • To investigate a sorting problem using a novel genome rearrangement operation: cut-circularize-linearize-and-paste (CCLP).
  • To develop an efficient algorithm for sorting signed permutations representing chromosomes using CCLP operations.
  • To model known and novel genome rearrangements and their occurrence in biological processes.

Main Methods:

  • The study defines the cut-circularize-linearize-and-paste (CCLP) operation, which involves cutting, circularizing, linearizing, and pasting chromosome segments.
  • A weighted sorting problem is formulated for CCLP operations, considering a weight ratio of 1:2 for reversals to non-reversal CCLP operations.
  • An O(δn) time algorithm is designed using permutation groups in algebra to solve the weighted sorting problem.

Main Results:

  • The CCLP operation can model diverse genome rearrangements, including reversals, transpositions, and block-interchanges, as well as novel ones.
  • A non-reversal CCLP operation is identified and its relevance in higher animal immune responses is noted.
  • An efficient O(δn) algorithm is presented for the weighted sorting problem by CCLP operations.

Conclusions:

  • The developed algorithm is simple and can be implemented using 1-dimensional arrays.
  • The findings are applicable to phylogenetic tree reconstruction.
  • The research has implications for understanding the human immune response to tumors.