| Autor: |
Mendik, Peter, Dobronyi, Levente, Hari, Ferenc, Kerepesi, Csaba, Maia-Moco, Leonardo, Buszlai, Donat, Csermely, Peter, Veres, Daniel V. |
| Rok vydání: |
2018 |
| Předmět: |
|
| Zdroj: |
Nucleic Acid Research 2019 47, D495-D505 |
| Druh dokumentu: |
Working Paper |
| DOI: |
10.1093/nar/gky1044 |
| Popis: |
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 or data complexity. Download options of search results, manually curated and predicted translocating protein sets are available on its website. The update of the database is helped by its manual curation framework and connection to the previously published ComPPI compartmentalized protein-protein interaction database. As shown by the application examples of merlin (NF2) and tumor protein 63 (TP63) Translocatome allows a better comprehension of protein translocation as a systems biology phenomenon and can be used as a discovery-tool in the protein translocation field. The database is available here: http://translocatome.linkgroup.hu |
| Databáze: |
arXiv |
| Externí odkaz: |
|
