MAPPI-DAT: data management and analysis for protein–protein interaction data from the high-throughput MAPPIT cell microarray platform
Author(s) -
Surya Gupta,
Veronic De Puysseleyr,
José Van der Heyden,
Davy Maddelein,
Irma Lemmens,
Sam Lievens,
Sven Degroeve,
Jan Tavernier,
Lennart Martens
Publication year - 2017
Publication title -
bioinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.599
H-Index - 390
eISSN - 1367-4811
pISSN - 1367-4803
DOI - 10.1093/bioinformatics/btx014
Subject(s) - computer science , executable , data management , python (programming language) , metadata , source code , database , profiling (computer programming) , data mining , operating system
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.
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