How to Install and Uninstall python3-freecontact Package on Kali Linux

Last updated: May 13,2024

1. Install "python3-freecontact" package

This guide let you learn how to install python3-freecontact on Kali Linux


    
        
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                sudo apt update
            
                    
    
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                sudo apt install
            
                        
                python3-freecontact
            
                    
    
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2. Uninstall "python3-freecontact" package

Please follow the instructions below to uninstall python3-freecontact on Kali Linux:


    
        
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                sudo apt remove
            
                        
                python3-freecontact
            
                    
    
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            $
        

        
            
                sudo apt autoclean && sudo apt autoremove
            
                    
    
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3. Information about the python3-freecontact package on Kali Linux

Package: python3-freecontact
Source: python-freecontact (1.1-6)
Version: 1.1-6+b6
Installed-Size: 372
Maintainer: Debian Med Packaging Team
Architecture: amd64
Depends: python3 (<< 3.13), python3 (>= 3.11~), libboost-python1.83.0 (>= 1.83.0), libboost-python1.83.0-py311, libboost-python1.83.0-py312, libc6 (>= 2.32), libfreecontact0v5 (>= 1.0.21), libgcc-s1 (>= 3.0), libstdc++6 (>= 11)
Size: 92772
SHA256: a3ab14e2ec0d302dbbbd5f4fc99b01e2e35e47b42981e09e2da434496c1ffb1a
SHA1: 61dd0b7d898083f8b0ef2a633b183d4a1bc57e7c
MD5sum: 3f761d8429d56023ae06eded53656ef5
Description: fast protein contact predictor - binding for Python3
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.
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This package contains the Python3 binding.
Description-md5:
Homepage: https://rostlab.org/owiki/index.php/FreeContact
Section: python
Priority: optional
Filename: pool/main/p/python-freecontact/python3-freecontact_1.1-6+b6_amd64.deb