| Chapter title |
Computational Methods for Annotation Transfers from Sequence
|
|---|---|
| Chapter number | 5 |
| Book title |
The Gene Ontology Handbook
|
| Published in |
Methods in molecular biology, January 2017
|
| DOI | 10.1007/978-1-4939-3743-1_5 |
| Pubmed ID | |
| Book ISBNs |
978-1-4939-3741-7, 978-1-4939-3743-1
|
| Authors |
Domenico Cozzetto, David T. Jones, Cozzetto, Domenico, Jones, David T. |
| Editors |
Christophe Dessimoz, Nives Škunca |
| Abstract |
Surveys of public sequence resources show that experimentally supported functional information is still completely missing for a considerable fraction of known proteins and is clearly incomplete for an even larger portion. Bioinformatics methods have long made use of very diverse data sources alone or in combination to predict protein function, with the understanding that different data types help elucidate complementary biological roles. This chapter focuses on methods accepting amino acid sequences as input and producing GO term assignments directly as outputs; the relevant biological and computational concepts are presented along with the advantages and limitations of individual approaches. |
Mendeley readers
Geographical breakdown
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|---|---|---|
| Mexico | 1 | 7% |
| Unknown | 14 | 93% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Bachelor | 3 | 20% |
| Student > Ph. D. Student | 3 | 20% |
| Librarian | 2 | 13% |
| Other | 1 | 7% |
| Student > Master | 1 | 7% |
| Other | 2 | 13% |
| Unknown | 3 | 20% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 5 | 33% |
| Agricultural and Biological Sciences | 3 | 20% |
| Pharmacology, Toxicology and Pharmaceutical Science | 1 | 7% |
| Mathematics | 1 | 7% |
| Computer Science | 1 | 7% |
| Other | 2 | 13% |
| Unknown | 2 | 13% |