How to Install and Uninstall examl Package on Kali Linux

Last updated: July 07,2024

1. Install "examl" package

Please follow the step by step instructions below to install examl on Kali Linux


    
        
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                sudo apt update
            
                    
    
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                sudo apt install
            
                        
                examl
            
                    
    
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2. Uninstall "examl" package

Learn how to uninstall examl on Kali Linux:


    
        
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                sudo apt remove
            
                        
                examl
            
                    
    
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                sudo apt autoclean && sudo apt autoremove
            
                    
    
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3. Information about the examl package on Kali Linux

Package: examl
Version: 3.0.22-4
Installed-Size: 5969
Maintainer: Debian Med Packaging Team
Architecture: amd64
Depends: libc6 (>= 2.34), libopenmpi3 (>= 4.1.6), openmpi-bin
Size: 953928
SHA256: b131a179f7e0b57c44f615c0d17ffbdbdbbb159ac5b19c66e71b3d4a2dc77b8c
SHA1: 365db40551f3a8850432757c2aa83e0a776a3e3a
MD5sum: 73ef5428ade3cfab41b07b76f286fce5
Description: Exascale Maximum Likelihood (ExaML) code for phylogenetic inference
Exascale Maximum Likelihood (ExaML) is a code for phylogenetic inference
using MPI. This code implements the popular RAxML search algorithm for
maximum likelihood based inference of phylogenetic trees.
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ExaML is a strapped-down light-weight version of RAxML for phylogenetic
inference on huge datasets. It can only execute some very basic
functions and is intended for computer-savvy users that can write little
perl-scripts and have experience using queue submission scripts for
clusters. ExaML only implements the CAT and GAMMA models of rate
heterogeneity for binary, DNA, and protein data.
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ExaML uses a radically new MPI parallelization approach that yields
improved parallel efficiency, in particular on partitioned multi-gene or
whole-genome datasets. It also implements a new load balancing algorithm
that yields better parallel efficiency.
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It is up to 4 times faster than its predecessor RAxML-Light and scales
to a larger number of processors.
Description-md5:
Homepage: https://github.com/stamatak/ExaML
Built-Using: simde (= 0.7.6-1)
Section: science
Priority: optional
Filename: pool/main/e/examl/examl_3.0.22-4_amd64.deb