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  An Ontology-based Method for Assessing Batch Effect Adjustment Approaches in Heterogeneous Datasets

Schmidt, F., List, M., Cukuroglu, E., Koehler, S., Goke, J., & Schulz, M. H. (2018). An Ontology-based Method for Assessing Batch Effect Adjustment Approaches in Heterogeneous Datasets. Bioinformatics, 34(17), i908-i916. doi:10.1093/bioinformatics/bty553.

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V C The Author(s) 2018. Published by Oxford University Press. i908 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/ 4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.

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 Creators:
Schmidt, Florian1, Author           
List, Markus1, Author           
Cukuroglu, Engin2, Author
Koehler, Sebastian2, Author
Goke, Jonathan2, Author
Schulz, Marcel H.1, Author           
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1Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society, ou_40046              
2External Organizations, ou_persistent22              

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Language(s): eng - English
 Dates: 20182018
 Publication Status: Issued
 Pages: -
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 Table of Contents: -
 Rev. Type: -
 Identifiers: BibTex Citekey: Schmidt_Bioinformatics2018
DOI: 10.1093/bioinformatics/bty553
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Title: Bioinformatics
Source Genre: Journal
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Publ. Info: Oxford : Oxford University Press
Pages: - Volume / Issue: 34 (17) Sequence Number: - Start / End Page: i908 - i916 Identifier: ISSN: 1367-4803
CoNE: https://pure.mpg.de/cone/journals/resource/954926969991

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Title: The 17th European Conference on Computational Biology
  Abbreviation : ECCB 2018
  Subtitle : Athens, Greece, 8 - 12 September 2018
Source Genre: Proceedings
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Pages: - Volume / Issue: - Sequence Number: - Start / End Page: - Identifier: -