Publikation:

CIIPro: a new read-across portal to fill data gaps using public large-scale chemical and biological data

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Russo_0-404994.pdf
Russo_0-404994.pdfGröße: 133.62 KBDownloads: 267

Datum

2016

Autor:innen

Russo, Daniel P.
Kim, Marlene T.
Wang, Wenyi
Pinolini, Daniel
Shende, Sunil
Strickland, Judy
Zhu, Hao

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http://nbn-resolving.de/urn:nbn:de:bsz:352-0-404994
DOI (zitierfähiger Link)
https://doi.org/10.1093/bioinformatics/btw640
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Open Access-Veröffentlichung
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Biologie: Publikationen
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Published

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Bioinformatics. 2016, 33(3), pp. 464-466. ISSN 1367-4803. eISSN 1460-2059. Available under: doi: 10.1093/bioinformatics/btw640

Zusammenfassung

We have developed a public Chemical In vitro-In vivo Profiling (CIIPro) portal, which can automatically extract in vitro biological data from public resources (i.e. PubChem) for user-supplied compounds. For compounds with in vivo target activity data (e.g. animal toxicity testing results), the integrated cheminformatics algorithm will optimize the extracted biological data using in vitro-in vivo correlations. The resulting in vitro biological data for target compounds can be used for read-across risk assessment of target compounds. Additionally, the CIIPro portal can identify the most similar compounds based on their optimized bioprofiles. The CIIPro portal provides new powerful assessment capabilities to the scientific community and can be easily integrated with other cheminformatics tools.

Zusammenfassung in einer weiteren Sprache

Fachgebiet (DDC)
570 Biowissenschaften, Biologie

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ISO 690RUSSO, Daniel P., Marlene T. KIM, Wenyi WANG, Daniel PINOLINI, Sunil SHENDE, Judy STRICKLAND, Thomas HARTUNG, Hao ZHU, 2016. CIIPro: a new read-across portal to fill data gaps using public large-scale chemical and biological data. In: Bioinformatics. 2016, 33(3), pp. 464-466. ISSN 1367-4803. eISSN 1460-2059. Available under: doi: 10.1093/bioinformatics/btw640
BibTex
@article{Russo2016CIIPr-39098,
  year={2016},
  doi={10.1093/bioinformatics/btw640},
  title={CIIPro: a new read-across portal to fill data gaps using public large-scale chemical and biological data},
  number={3},
  volume={33},
  issn={1367-4803},
  journal={Bioinformatics},
  pages={464--466},
  author={Russo, Daniel P. and Kim, Marlene T. and Wang, Wenyi and Pinolini, Daniel and Shende, Sunil and Strickland, Judy and Hartung, Thomas and Zhu, Hao}
}
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