Abstract
Analysis of sequence data is inevitable in modern molecular biology, and important information about for example proteins can be inferred efficiently using computational methods. Here, we explain how to use the information in freely available databases together with computational methods for classification and motif detection to assess whether a protein sequence corresponds to a P-type ATPase (and if so, which subtype) or not.
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Acknowledgments
We wish to thank Marco Palos Franco, Bioinformatics Research Centre (BiRC), Aarhus University, for collecting and curating the P-type ATPase dataset.
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Søndergaard, D., Knudsen, M., Pedersen, C.N.S. (2016). Computational Classification of P-Type ATPases. In: Bublitz, M. (eds) P-Type ATPases. Methods in Molecular Biology, vol 1377. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-3179-8_41
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DOI: https://doi.org/10.1007/978-1-4939-3179-8_41
Publisher Name: Humana Press, New York, NY
Print ISBN: 978-1-4939-3178-1
Online ISBN: 978-1-4939-3179-8
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