FLAMS: Find Lysine Acylations and other Modification Sites

Author:

Longin Hannelore12ORCID,Broeckaert Nand12,Langen Maarten1,Hari Roshan1,Kramarska Anna1,Oikarinen Kasper1,Hendrix Hanne2,Lavigne Rob2ORCID,van Noort Vera13ORCID

Affiliation:

1. KU Leuven, Department of Microbial and Molecular Systems, Computational Systems Biology , Leuven 3001, Belgium

2. KU Leuven, Department of Biosystems, Laboratory of Gene Technology , Leuven 3001, Belgium

3. Leiden University, Institute of Biology Leiden (IBL) , Leiden 2333 BE, The Netherlands

Abstract

Abstract Summary Today, hundreds of post-translational modification (PTM) sites are routinely identified at once, but the comparison of new experimental datasets to already existing ones is hampered by the current inability to search most PTM databases at the protein residue level. We present FLAMS (Find Lysine Acylations and other Modification Sites), a Python3-based command line and web-tool that enables researchers to compare their PTM sites to the contents of the CPLM, the largest dedicated protein lysine modification database, and dbPTM, the most comprehensive general PTM database, at the residue level. FLAMS can be integrated into PTM analysis pipelines, allowing researchers to quickly assess the novelty and conservation of PTM sites across species in newly generated datasets, aiding in the functional assessment of sites and the prioritization of sites for further experimental characterization. Availability and implementation FLAMS is implemented in Python3, and freely available under an MIT license. It can be found as a command line tool at https://github.com/hannelorelongin/FLAMS, pip and conda; and as a web service at https://www.biw.kuleuven.be/m2s/cmpg/research/CSB/tools/flams/.

Funder

KU Leuven project C1 ‘ACES’

Publisher

Oxford University Press (OUP)

Subject

Computational Mathematics,Computational Theory and Mathematics,Computer Science Applications,Molecular Biology,Biochemistry,Statistics and Probability

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