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

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STITCH 4 : integration of protein-chemical interactions with user data. / Kuhn, Michael; Szklarczyk, Damian Milosz; Pletscher-Frankild, Sune; Blicher, Thomas H; von Mering, Christian; Jensen, Lars J; Bork, Peer.

In: Nucleic Acids Research, Vol. 42, No. D1, 28.11.2013, p. D401-D407.

Research output: Contribution to journalJournal articleResearchpeer-review

Harvard

Kuhn, M, Szklarczyk, DM, Pletscher-Frankild, S, Blicher, TH, von Mering, C, Jensen, LJ & Bork, P 2013, 'STITCH 4: integration of protein-chemical interactions with user data', Nucleic Acids Research, vol. 42, no. D1, pp. D401-D407. https://doi.org/10.1093/nar/gkt1207

APA

Kuhn, M., Szklarczyk, D. M., Pletscher-Frankild, S., Blicher, T. H., von Mering, C., Jensen, L. J., & Bork, P. (2013). STITCH 4: integration of protein-chemical interactions with user data. Nucleic Acids Research, 42(D1), D401-D407. https://doi.org/10.1093/nar/gkt1207

Vancouver

Kuhn M, Szklarczyk DM, Pletscher-Frankild S, Blicher TH, von Mering C, Jensen LJ et al. STITCH 4: integration of protein-chemical interactions with user data. Nucleic Acids Research. 2013 Nov 28;42(D1):D401-D407. https://doi.org/10.1093/nar/gkt1207

Author

Kuhn, Michael ; Szklarczyk, Damian Milosz ; Pletscher-Frankild, Sune ; Blicher, Thomas H ; von Mering, Christian ; Jensen, Lars J ; Bork, Peer. / STITCH 4 : integration of protein-chemical interactions with user data. In: Nucleic Acids Research. 2013 ; Vol. 42, No. D1. pp. D401-D407.

Bibtex

@article{ea9bc3d4f3de49a0a93324cdb8c5718e,
title = "STITCH 4: integration of protein-chemical interactions with user data",
abstract = "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.",
author = "Michael Kuhn and Szklarczyk, {Damian Milosz} and Sune Pletscher-Frankild and Blicher, {Thomas H} and {von Mering}, Christian and Jensen, {Lars J} and Peer Bork",
year = "2013",
month = "11",
day = "28",
doi = "10.1093/nar/gkt1207",
language = "English",
volume = "42",
pages = "D401--D407",
journal = "Nucleic Acids Research",
issn = "0305-1048",
publisher = "Oxford University Press",
number = "D1",

}

RIS

TY - JOUR

T1 - STITCH 4

T2 - integration of protein-chemical interactions with user data

AU - Kuhn, Michael

AU - Szklarczyk, Damian Milosz

AU - Pletscher-Frankild, Sune

AU - Blicher, Thomas H

AU - von Mering, Christian

AU - Jensen, Lars J

AU - Bork, Peer

PY - 2013/11/28

Y1 - 2013/11/28

N2 - 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.

AB - 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.

U2 - 10.1093/nar/gkt1207

DO - 10.1093/nar/gkt1207

M3 - Journal article

C2 - 24293645

VL - 42

SP - D401-D407

JO - Nucleic Acids Research

JF - Nucleic Acids Research

SN - 0305-1048

IS - D1

ER -

ID: 91134316