TL;DR
Translocatome is a comprehensive database of human translocating proteins, combining curated experimental data with machine learning predictions to facilitate research on protein translocation mechanisms and their roles in health and disease.
Contribution
It introduces the first dedicated human translocating protein database integrating experimental data with machine learning predictions for translocation likelihood.
Findings
Provides translocation probability for over 13,000 proteins
Identifies 1,133 high-confidence translocating proteins
Enables systems biology analysis of protein translocation
Abstract
Here we present Translocatome, the first dedicated database of human translocating proteins. The core of the Translocatome database is the manually curated data set of 213 human translocating proteins listing the source of their experimental validation, several details of their translocation mechanism, their local compartmentalized interactome, as well as their involvement in signalling pathways and disease development. In addition, using the well-established and widely used gradient boosting machine learning tool, XGBoost, Translocatome provides translocation probability values for 13,066 human proteins identifying 1133 and 3268 high- and low-confidence translocating proteins, respectively. The database has user-friendly search options with a UniProt autocomplete quick search and advanced search for proteins filtered by their localization, UniProt identifiers, translocation likelihood…
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