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Information-Theoretic Evaluation for Computational Biomedical Ontologies
The development of effective methods for the prediction of ontological annotations is an important goal in computational biology, yet evaluating their performance is difficult due to problems caused by the structure of biomedical ontologies and incomplete annotations of genes. This work proposes an...
| Clasificación: | Libro Electrónico |
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| Autor principal: | |
| Autor Corporativo: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Cham :
Springer International Publishing : Imprint: Springer,
2014.
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| Edición: | 1st ed. 2014. |
| Colección: | SpringerBriefs in Computer Science,
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| Temas: | |
| Acceso en línea: | Texto Completo |
MARC
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|---|---|---|---|
| 001 | 978-3-319-04138-4 | ||
| 003 | DE-He213 | ||
| 005 | 20220126094416.0 | ||
| 007 | cr nn 008mamaa | ||
| 008 | 140109s2014 sz | s |||| 0|eng d | ||
| 020 | |a 9783319041384 |9 978-3-319-04138-4 | ||
| 024 | 7 | |a 10.1007/978-3-319-04138-4 |2 doi | |
| 050 | 4 | |a QH324.2-324.25 | |
| 072 | 7 | |a PS |2 bicssc | |
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| 082 | 0 | 4 | |a 570.285 |2 23 |
| 082 | 0 | 4 | |a 570.113 |2 23 |
| 100 | 1 | |a Clark, Wyatt Travis. |e author. |4 aut |4 http://id.loc.gov/vocabulary/relators/aut | |
| 245 | 1 | 0 | |a Information-Theoretic Evaluation for Computational Biomedical Ontologies |h [electronic resource] / |c by Wyatt Travis Clark. |
| 250 | |a 1st ed. 2014. | ||
| 264 | 1 | |a Cham : |b Springer International Publishing : |b Imprint: Springer, |c 2014. | |
| 300 | |a VII, 46 p. 12 illus., 6 illus. in color. |b online resource. | ||
| 336 | |a text |b txt |2 rdacontent | ||
| 337 | |a computer |b c |2 rdamedia | ||
| 338 | |a online resource |b cr |2 rdacarrier | ||
| 347 | |a text file |b PDF |2 rda | ||
| 490 | 1 | |a SpringerBriefs in Computer Science, |x 2191-5776 | |
| 505 | 0 | |a Introduction -- Methods -- Experiments and Results -- Discussion. | |
| 520 | |a The development of effective methods for the prediction of ontological annotations is an important goal in computational biology, yet evaluating their performance is difficult due to problems caused by the structure of biomedical ontologies and incomplete annotations of genes. This work proposes an information-theoretic framework to evaluate the performance of computational protein function prediction. A Bayesian network is used, structured according to the underlying ontology, to model the prior probability of a protein's function. The concepts of misinformation and remaining uncertainty are then defined, that can be seen as analogs of precision and recall. Finally, semantic distance is proposed as a single statistic for ranking classification models. The approach is evaluated by analyzing three protein function predictors of gene ontology terms. The work addresses several weaknesses of current metrics, and provides valuable insights into the performance of protein function prediction tools. | ||
| 650 | 0 | |a Bioinformatics. | |
| 650 | 0 | |a Algorithms. | |
| 650 | 0 | |a Medical genetics. | |
| 650 | 0 | |a Pattern recognition systems. | |
| 650 | 0 | |a Medical informatics. | |
| 650 | 1 | 4 | |a Computational and Systems Biology. |
| 650 | 2 | 4 | |a Algorithms. |
| 650 | 2 | 4 | |a Medical Genetics. |
| 650 | 2 | 4 | |a Automated Pattern Recognition. |
| 650 | 2 | 4 | |a Health Informatics. |
| 710 | 2 | |a SpringerLink (Online service) | |
| 773 | 0 | |t Springer Nature eBook | |
| 776 | 0 | 8 | |i Printed edition: |z 9783319041377 |
| 776 | 0 | 8 | |i Printed edition: |z 9783319041391 |
| 830 | 0 | |a SpringerBriefs in Computer Science, |x 2191-5776 | |
| 856 | 4 | 0 | |u https://doi.uam.elogim.com/10.1007/978-3-319-04138-4 |z Texto Completo |
| 912 | |a ZDB-2-SCS | ||
| 912 | |a ZDB-2-SXCS | ||
| 950 | |a Computer Science (SpringerNature-11645) | ||
| 950 | |a Computer Science (R0) (SpringerNature-43710) | ||