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Hanne Hendrix

dblp:424/4642 · DBLP profile ↗
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1ranked-venue papers
0as first author
1since 2021 · last 2024
—ORCID · unresolved

Domains — the database's venue-derived domains; a paper can count in several

Applied, interdisciplinary, general and emerging computing · 1 · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Interdisciplinary, comprehensive, and emerging computing
1 paper
Bioinformatics and computational biology · 100%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology › proteomics › post-translational modification
post-translational modification analysis
0.812024
FLAMS: Find Lysine Acylations and other Modification Sites · Bioinform. 2024
Bioinformatics and computational biology
proteomics
0.812024
FLAMS: Find Lysine Acylations and other Modification Sites · Bioinform. 2024
Bioinformatics and computational biology › protein sequence analysis
protein database search
0.212024
FLAMS: Find Lysine Acylations and other Modification Sites · Bioinform. 2024

Methods — techniques the papers use, named apart from their topics

web services · 0.8command-line tool · 0.8
YearPublicationVenuePosition
2024 FLAMS: Find Lysine Acylations and other Modification Sites
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/.
Hannelore Longin, Nand Broeckaert, Maarten Langen, Roshan Hari, Anna Kramarska, Kasper Oikarinen, Hanne Hendrix, Rob Lavigne, Vera van Noort
Bioinform.7