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Updated: May 13, 2026

Optimization of Synthetic Proteins: Identification of Interpositional Dependencies Indicating Structurally and/or Functionally Linked Residues
07:08

Optimization of Synthetic Proteins: Identification of Interpositional Dependencies Indicating Structurally and/or Functionally Linked Residues

Published on: July 14, 2015

Increasing sequence search sensitivity with transitive alignments.

Ketil Malde1, Tomasz Furmanek

  • 1Institute of Marine Research, Bergen, Norway. ketil.malde@imr.no

Plos One
|March 5, 2013
PubMed
Summary
This summary is machine-generated.

This study introduces a novel bioinformatics method for sequence alignment. It improves homology detection by using indirect alignments, enhancing sensitivity for finding related sequences in specific databases.

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07:49

Creating and Applying a Reference to Facilitate the Discussion and Classification of Proteins in a Diverse Group

Published on: August 16, 2017

Area of Science:

  • Bioinformatics
  • Computational Biology
  • Genomics

Background:

  • Sequence alignment is crucial for identifying homology but faces challenges with large, poorly annotated sequence databases.
  • Direct alignment against specific subsets of sequences reduces sensitivity and can lead to lower alignment scores.
  • Distinguishing homologous from random hits becomes difficult when using limited target databases.

Purpose of the Study:

  • To develop a method for improving sequence alignment sensitivity against specific target databases.
  • To address the limitations of direct pairwise alignments when searching curated or specialized sequence subsets.
  • To enhance the ability to detect homologous sequences even when using smaller, focused databases.

Main Methods:

  • Proposed a novel indirect (transitive) alignment approach.
  • Involves initial alignment of query sequences against a comprehensive large database.
  • Combines these results with alignments from the large database against the desired target database.

Main Results:

  • The indirect alignment method demonstrated higher sensitivity compared to direct pairwise alignments.
  • Successfully improved the detection of homologous sequences within specific target subsets.
  • Provided a more reliable way to distinguish true homologs from random matches.

Conclusions:

  • The proposed indirect alignment strategy effectively enhances sensitivity in sequence homology searches.
  • This method offers a valuable solution for overcoming the limitations of direct alignments against specialized sequence databases.
  • Facilitates more accurate and sensitive identification of homologous sequences in various bioinformatics applications.