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  • [Name]: DSR
    [Last update]: 2003
    [Usage]: on request
    [Description]: It calculates complexity using reciprocal complexity.
    [Open source?]: no
    [Reference]:

  • [Name]: LPS-annotate
    [Last update]: 2011
    [Usage]: on request
    [Description]: This algorithm defines compositional bias through a thorough search for lowest-probability subsequences (LPSs; Low Probability Sequences) and serves as workbench of tools now available to molecular biologists to generate hypotheses and inferences about the proteins that they are investigating.
    [Open source?]: no
    [Reference]:

  • [Name]: SIMPLE
    [Last update]: 2002
    [Usage]: downloadable web
    [Description]: It facilitates the quantification of the amount of simple sequence in proteins and determines the type of short motifs that show clustering above a certain threshold.
    [Open source?]: yes
    [Reference]:

  • [Name]: SAPS
    [Last update]: 1992
    [Usage]: downloadable / web
    [Description]: It describes several protein sequence statistics for the evaluation of distinctive characteristics of residue content and arrangement in primary structures.
    [Open source?]: yes
    [Reference]:

  • [Name]: SubSeqer
    [Last update]: 2008
    [Usage]: web
    [Description]: A graph-based approach for the detection and identification of repetitive elements in low–complexity sequences.
    [Open source?]: no
    [Reference]:

  • [Name]: XNU
    [Last update]: 1993
    [Usage]: downloadable
    [Description]: It uses the PAM120 scoring matrix for the calculation of complexity.
    [Open source?]: yes
    [Reference]:

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About This Tool

Protein identification based on tandem mass spectrometry has become the mainstream of proteomics, and database search has become one of the most common methods to identify tandem mass spectrometry data. There are already a number of software tools for detecting low-complexity regions in proteins, of which 16 are well-known in this random tool.

The software was developed at different times, and some are free and open-source, while others require an extra fee to upgrade to other advanced features. With the generator, we can see a detailed list of each piece of software, its last iteration date, purpose, brief description, whether it’s open-source or not. The emergence of these softwares, so that the detection of protein in the implementation of low-complexity areas more in place, but also greatly reduce the time cost of biologists and students.

Click the "Display All Items" button and you will get a list of software to detect low complexity regions in proteins.

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