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proDA: Probabilistic Dropout Analysis for Identifying Differentially Abundant Proteins in Label-Free Mass Spectrometry

View ORCID ProfileConstantin Ahlmann-Eltze, View ORCID ProfileSimon Anders
doi: https://doi.org/10.1101/661496
Constantin Ahlmann-Eltze
Center for Molecular Biology (ZMBH), University of Heidelberg, Germany
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Simon Anders
Center for Molecular Biology (ZMBH), University of Heidelberg, Germany
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  • For correspondence: sanders@fs.tum.de
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  • https://github.com/const-ae/proDA

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Posted June 06, 2019.
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proDA: Probabilistic Dropout Analysis for Identifying Differentially Abundant Proteins in Label-Free Mass Spectrometry
Constantin Ahlmann-Eltze, Simon Anders
bioRxiv 661496; doi: https://doi.org/10.1101/661496
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proDA: Probabilistic Dropout Analysis for Identifying Differentially Abundant Proteins in Label-Free Mass Spectrometry
Constantin Ahlmann-Eltze, Simon Anders
bioRxiv 661496; doi: https://doi.org/10.1101/661496

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