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Jan Tavernier

dblp:199/3434 · DBLP profile ↗
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2ranked-venue papers
0as first author
0since 2021 · last 2017
0000-0002-7609-6462ORCID · corroborated

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

Applied, interdisciplinary, general and emerging computing · 2

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
2 papers
Bioinformatics and computational biology · 75% Computational science and engineering · 25%

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

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology
proteomics
0.622017
sfinx: an R package for the elimination of false positives from affinity purification-mass spectrometry datasets · Bioinform. 2017
MAPPI-DAT: data management and analysis for protein-protein interaction data from the high-throughput MAPPIT cell microarray platform · Bioinform. 2017
Computational science and engineering
false positive filtering
0.312017
sfinx: an R package for the elimination of false positives from affinity purification-mass spectrometry datasets · Bioinform. 2017
Bioinformatics and computational biology › protein analysis › protein-protein interaction
protein-protein interaction analysis
0.312017
MAPPI-DAT: data management and analysis for protein-protein interaction data from the high-throughput MAPPIT cell microarray platform · Bioinform. 2017

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

straightforward filtering index · 0.3meta-analysis · 0.3data management · 0.3
YearPublicationVenuePosition
2017 MAPPI-DAT: data management and analysis for protein-protein interaction data from the high-throughput MAPPIT cell microarray platform
abstract
Summary: Protein-protein interaction (PPI) studies have dramatically expanded our knowledge about cellular behaviour and development in different conditions. A multitude of high-throughput PPI techniques have been developed to achieve proteome-scale coverage for PPI studies, including the microarray based Mammalian Protein-Protein Interaction Trap (MAPPIT) system. Because such high-throughput techniques typically report thousands of interactions, managing and analysing the large amounts of acquired data is a challenge. We have therefore built the MAPPIT cell microArray Protein Protein Interaction-Data management & Analysis Tool (MAPPI-DAT) as an automated data management and analysis tool for MAPPIT cell microarray experiments. MAPPI-DAT stores the experimental data and metadata in a systematic and structured way, automates data analysis and interpretation, and enables the meta-analysis of MAPPIT cell microarray data across all stored experiments. Availability and Implementation: MAPPI-DAT is developed in Python, using R for data analysis and MySQL as data management system. MAPPI-DAT is cross-platform and can be ran on Microsoft Windows, Linux and OS X/macOS. The source code and a Microsoft Windows executable are freely available under the permissive Apache2 open source license at https://github.com/compomics/MAPPI-DAT. Contact: [email protected] or [email protected]. Supplementary information: Supplementary data are available at Bioinformatics online.
Surya Gupta, Veronic De Puysseleyr, José Van der Heyden, Davy Maddelein, Irma Lemmens, Sam Lievens, Sven Degroeve, Jan Tavernier, Lennart Martens
Bioinform.8
2017 sfinx: an R package for the elimination of false positives from affinity purification-mass spectrometry datasets
abstract
SUMMARY: We describe sfinx, an R package providing access to the straightforward filtering index (SFINX) for the separation of true positive from false positive protein interactions in affinity purification - mass spectrometry datasets. This package maintains the reliability and user-friendliness of the SFINX web site interface but is faster, unlimited in input size, and can be run locally within R. AVAILABILITY AND IMPLEMENTATION: The sfinx R package is available for download at the comprehensive R archive network (CRAN) https://cran.r-project.org/web/packages/sfinx/ under the Apache License 2.0. CONTACT: [email protected] or [email protected]. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
Kevin Titeca, Pieter Meysman, Kris Laukens, Lennart Martens, Jan Tavernier, Sven Eyckerman
Bioinform.5