Homology-Based Annotation of Large Protein Datasets View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

2016

AUTHORS

Marco Punta , Jaina Mistry

ABSTRACT

Advances in DNA sequencing technologies have led to an increasing amount of protein sequence data being generated. Only a small fraction of this protein sequence data will have experimental annotation associated with them. Here, we describe a protocol for in silico homology-based annotation of large protein datasets that makes extensive use of manually curated collections of protein families. We focus on annotations provided by the Pfam database and suggest ways to identify family outliers and family variations. This protocol may be useful to people who are new to protein data analysis, or who are unfamiliar with the current computational tools that are available. More... »

PAGES

153-76

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/978-1-4939-3572-7_8

DOI

http://dx.doi.org/10.1007/978-1-4939-3572-7_8

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1034239436

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/27115632


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