Egyszerű nézet

dc.contributor.author Mendik Péter
dc.contributor.author Dobronyi Levente
dc.contributor.author Hári Ferenc
dc.contributor.author Kerepesi Csaba
dc.contributor.author Maia-Moço Leonardo
dc.contributor.author Buszlai Donát
dc.contributor.author Csermely Péter
dc.contributor.author Veres Dániel V
dc.date.accessioned 2022-04-14T08:49:23Z
dc.date.available 2022-04-14T08:49:23Z
dc.date.issued 2019
dc.identifier
dc.identifier.citation journalVolume=47;journalIssueNumber=D1;journalTitle=NUCLEIC ACIDS RESEARCH ;pagerange=D495-D505;journalAbbreviatedTitle=NUCLEIC ACIDS RES;
dc.identifier.uri http://repo.lib.semmelweis.hu//handle/123456789/6670
dc.identifier.uri doi:10.1093/nar/gky1044
dc.description.abstract Here we present Translocatome, the first dedicated database of human translocating proteins (URL: http://translocatome.linkgroup.hu). 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 (http://comppi.linkgroup.hu). 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.
dc.relation.ispartof urn:issn:0305-1048
dc.title Translocatome: a novel resource for the analysis of protein translocation between cellular organelles
dc.type Journal Article
dc.date.updated 2019-01-21T08:31:38Z
dc.language.rfc3066 en
dc.rights.holder NULL
dc.identifier.mtmt 30628111
dc.identifier.pubmed 30380112
dc.contributor.institution Protein Information Technology Bioinformatikai Csoport
dc.contributor.institution Informatikai Kutatólaboratórium
dc.contributor.institution PhD Informatika Doktori Iskola
dc.contributor.institution Doktori Iskola
dc.contributor.institution Orvosi Vegytani, Molekuláris Biológiai és Patobiokémiai Intézet


Kapcsolódó fájlok:

A fájl jelenleg csak egyetemi IP címről érhető el.

Megtekintés/Megnyitás

Ez a rekord az alábbi gyűjteményekben szerepel:

Egyszerű nézet