How to Install and Uninstall libfreecontact-perl Package on Ubuntu 16.04 LTS (Xenial Xerus)

Last updated: May 06,2024

1. Install "libfreecontact-perl" package

This is a short guide on how to install libfreecontact-perl on Ubuntu 16.04 LTS (Xenial Xerus)


    
        
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                sudo apt update
            
                    
    
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                sudo apt install
            
                        
                libfreecontact-perl
            
                    
    
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2. Uninstall "libfreecontact-perl" package

Please follow the steps below to uninstall libfreecontact-perl on Ubuntu 16.04 LTS (Xenial Xerus):


    
        
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                sudo apt remove
            
                        
                libfreecontact-perl
            
                    
    
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                sudo apt autoclean && sudo apt autoremove
            
                    
    
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3. Information about the libfreecontact-perl package on Ubuntu 16.04 LTS (Xenial Xerus)

Package: libfreecontact-perl
Priority: extra
Section: universe/perl
Installed-Size: 134
Maintainer: Ubuntu Developers
Original-Maintainer: Debian Med Packaging Team
Architecture: amd64
Version: 0.08-4build1
Depends: libc6 (>= 2.14), libfreecontact0v5, libgcc1 (>= 1:3.0), perl (>= 5.22.1-1), perlapi-5.22.1
Filename: pool/universe/libf/libfreecontact-perl/libfreecontact-perl_0.08-4build1_amd64.deb
Size: 74328
MD5sum: 7d403f4c4c1b373bc4d21226a2c72460
SHA1: f8c1a11ea67614e65d255bcf610422cace4e3049
SHA256: b49e4d873412eefc7b0f387714ac94541b243b4d917897b00c57b3717d7cd677
Description-en: fast protein contact predictor - binding for Perl
FreeContact is a protein residue contact predictor optimized for speed.
Its input is a multiple sequence alignment. FreeContact can function as an
accelerated drop-in for the published contact predictors
EVfold-mfDCA of DS. Marks (2011) and
PSICOV of D. Jones (2011).
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FreeContact is accelerated by a combination of vector instructions, multiple
threads, and faster implementation of key parts.
Depending on the alignment, 8-fold or higher speedups are possible.
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A sufficiently large alignment is required for meaningful results.
As a minimum, an alignment with an effective (after-weighting) sequence count
bigger than the length of the query sequence should be used. Alignments with
tens of thousands of (effective) sequences are considered good input.
.
jackhmmer(1) from the hmmer package, or hhblits(1) from hhsuite
can be used to generate the alignments, for example.
.
This package contains the Perl binding.
Description-md5: 76746f39e71bf0567588b3a19cf36071
Homepage: http://rostlab.org/
Bugs: https://bugs.launchpad.net/ubuntu/+filebug
Origin: Ubuntu