Abstract
Through the use of next generation sequencing (NGS) technology, a lot of newly sequenced organisms are now available. Annotating those genes is one of the most challenging tasks in sequence biology. Here, we present an automated workflow to find homologue proteins, annotate sequences according to function and create a three-dimensional model.
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Keywords
- Secondary Structure Prediction
- Query Protein
- Substitution Matrix
- Nucleic Acid Research
- Amino Acid Frequency
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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Blaese, L. (2014). Data Mining for Unidentified Protein Sequences. In: Lamprecht, AL., Margaria, T. (eds) Process Design for Natural Scientists. Communications in Computer and Information Science, vol 500. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-45006-2_6
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DOI: https://doi.org/10.1007/978-3-662-45006-2_6
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