STITCH 4: integration of protein–chemical interactions with user data

STITCH is a database of protein–chemical interactions that integrates many sources of experimental and manually curated evidence with text-mining information and interaction predictions. Available at http://stitch.embl.de, the resulting interaction network includes 390 000 chemicals and 3.6 million...

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Main Authors:	Kuhn, Michael, Szklarczyk, Damian, Pletscher-Frankild, Sune, Blicher, Thomas H., von Mering, Christian, Jensen, Lars J., Bork, Peer
Format:	Online
Language:	English
Published:	Oxford University Press 2014
Online Access:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3964996/

id	pubmed-3964996
recordtype	oai_dc
spelling	pubmed-39649962014-03-25 STITCH 4: integration of protein–chemical interactions with user data Kuhn, Michael Szklarczyk, Damian Pletscher-Frankild, Sune Blicher, Thomas H. von Mering, Christian Jensen, Lars J. Bork, Peer II. Protein sequence and structure, motifs and domains STITCH is a database of protein–chemical interactions that integrates many sources of experimental and manually curated evidence with text-mining information and interaction predictions. Available at http://stitch.embl.de, the resulting interaction network includes 390 000 chemicals and 3.6 million proteins from 1133 organisms. Compared with the previous version, the number of high-confidence protein–chemical interactions in human has increased by 45%, to 367 000. In this version, we added features for users to upload their own data to STITCH in the form of internal identifiers, chemical structures or quantitative data. For example, a user can now upload a spreadsheet with screening hits to easily check which interactions are already known. To increase the coverage of STITCH, we expanded the text mining to include full-text articles and added a prediction method based on chemical structures. We further changed our scheme for transferring interactions between species to rely on orthology rather than protein similarity. This improves the performance within protein families, where scores are now transferred only to orthologous proteins, but not to paralogous proteins. STITCH can be accessed with a web-interface, an API and downloadable files. Oxford University Press 2014-01-01 2013-11-28 /pmc/articles/PMC3964996/ /pubmed/24293645 http://dx.doi.org/10.1093/nar/gkt1207 Text en © The Author(s) 2013. Published by Oxford University Press. http://creativecommons.org/licenses/by/3.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by/3.0/), which permits non-commercial reuse, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com
repository_type	Open Access Journal
institution_category	Foreign Institution
institution	US National Center for Biotechnology Information
building	NCBI PubMed
collection	Online Access
language	English
format	Online
author	Kuhn, Michael Szklarczyk, Damian Pletscher-Frankild, Sune Blicher, Thomas H. von Mering, Christian Jensen, Lars J. Bork, Peer
spellingShingle	Kuhn, Michael Szklarczyk, Damian Pletscher-Frankild, Sune Blicher, Thomas H. von Mering, Christian Jensen, Lars J. Bork, Peer STITCH 4: integration of protein–chemical interactions with user data
author_facet	Kuhn, Michael Szklarczyk, Damian Pletscher-Frankild, Sune Blicher, Thomas H. von Mering, Christian Jensen, Lars J. Bork, Peer
author_sort	Kuhn, Michael
title	STITCH 4: integration of protein–chemical interactions with user data
title_short	STITCH 4: integration of protein–chemical interactions with user data
title_full	STITCH 4: integration of protein–chemical interactions with user data
title_fullStr	STITCH 4: integration of protein–chemical interactions with user data
title_full_unstemmed	STITCH 4: integration of protein–chemical interactions with user data
title_sort	stitch 4: integration of protein–chemical interactions with user data
description	STITCH is a database of protein–chemical interactions that integrates many sources of experimental and manually curated evidence with text-mining information and interaction predictions. Available at http://stitch.embl.de, the resulting interaction network includes 390 000 chemicals and 3.6 million proteins from 1133 organisms. Compared with the previous version, the number of high-confidence protein–chemical interactions in human has increased by 45%, to 367 000. In this version, we added features for users to upload their own data to STITCH in the form of internal identifiers, chemical structures or quantitative data. For example, a user can now upload a spreadsheet with screening hits to easily check which interactions are already known. To increase the coverage of STITCH, we expanded the text mining to include full-text articles and added a prediction method based on chemical structures. We further changed our scheme for transferring interactions between species to rely on orthology rather than protein similarity. This improves the performance within protein families, where scores are now transferred only to orthologous proteins, but not to paralogous proteins. STITCH can be accessed with a web-interface, an API and downloadable files.
publisher	Oxford University Press
publishDate	2014
url	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3964996/
_version_	1612071007572459520

STITCH 4: integration of protein–chemical interactions with user data

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