Integration of relational and hierarchical network information for protein function prediction
- Location
-
Deutsche Nationalbibliothek Frankfurt am Main
- ISSN
-
1471-2105
- Extent
-
Online-Ressource
- Language
-
Englisch
- Notes
-
online resource.
- Bibliographic citation
-
Integration of relational and hierarchical network information for protein function prediction ; volume:9 ; number:1 ; day:22 ; month:8 ; year:2008 ; pages:1-15 ; date:12.2008
BMC bioinformatics ; 9, Heft 1 (22.8.2008), 1-15, 12.2008
- Creator
-
Jiang, Xiaoyu
- Contributor
-
Nariai, Naoki
Steffen, Martin
Kasif, Simon
Kolaczyk, Eric D.
SpringerLink (Online service)
- DOI
-
10.1186/1471-2105-9-350
- URN
-
urn:nbn:de:1111-201602172782
- Rights
-
Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Last update
-
15.08.2025, 7:39 AM CEST
Data provider
This object is provided by:
Deutsche Nationalbibliothek. If you have any questions about the object, please contact the data provider.
Deutsche Nationalbibliothek. If you have any questions about the object, please contact the data provider.
Associated
- Jiang, Xiaoyu
- Nariai, Naoki
- Steffen, Martin
- Kasif, Simon
- Kolaczyk, Eric D.
- SpringerLink (Online service)
Other Objects (12)
Using PPI network autocorrelation in hierarchical multi-label classification trees for gene function prediction
Enhancing Relational Database Systems for Managing Hierarchical Data
Hierarchical graph learning with convolutional network for brain disease prediction
NPF:network propagation for protein function prediction
Reduction strategies for hierarchical multi-label classification in protein function prediction
On Supporting Hierarchical Data in Relational Main-Memory Database Systems
Standard relational and network database languages
Hierarchical representation for PPI sites prediction
On multi-relational link prediction with bilinear models
Support vector machine prediction of enzyme function with conjoint triad feature and hierarchical context
Feature extraction with spectral clustering for gene function prediction using hierarchical multi-label classification
Measuring globalization: A hierarchical network approach
Using PPI network autocorrelation in hierarchical multi-label classification trees for gene function prediction
Enhancing Relational Database Systems for Managing Hierarchical Data
Hierarchical graph learning with convolutional network for brain disease prediction
NPF:network propagation for protein function prediction
Reduction strategies for hierarchical multi-label classification in protein function prediction
On Supporting Hierarchical Data in Relational Main-Memory Database Systems
Standard relational and network database languages
Hierarchical representation for PPI sites prediction
On multi-relational link prediction with bilinear models
Support vector machine prediction of enzyme function with conjoint triad feature and hierarchical context
Feature extraction with spectral clustering for gene function prediction using hierarchical multi-label classification
Measuring globalization: A hierarchical network approach
Using PPI network autocorrelation in hierarchical multi-label classification trees for gene function prediction
Enhancing Relational Database Systems for Managing Hierarchical Data
Hierarchical graph learning with convolutional network for brain disease prediction
NPF:network propagation for protein function prediction
Reduction strategies for hierarchical multi-label classification in protein function prediction
On Supporting Hierarchical Data in Relational Main-Memory Database Systems
Standard relational and network database languages
Hierarchical representation for PPI sites prediction
On multi-relational link prediction with bilinear models
Support vector machine prediction of enzyme function with conjoint triad feature and hierarchical context
Feature extraction with spectral clustering for gene function prediction using hierarchical multi-label classification