- Location
-
Deutsche Nationalbibliothek Frankfurt am Main
- ISSN
-
1471-2105
- Extent
-
Online-Ressource
- Language
-
Englisch
- Notes
-
online resource.
- Bibliographic citation
-
Improving network inference algorithms using resampling methods ; volume:19 ; number:1 ; day:12 ; month:10 ; year:2018 ; pages:1-9 ; date:12.2018
BMC bioinformatics ; 19, Heft 1 (12.10.2018), 1-9, 12.2018
- Classification
-
Biowissenschaften, Biologie
- Creator
-
Colby, Sean M.
- Contributor
-
McClure, Ryan S.
Overall, Christopher C.
Renslow, Ryan S.
McDermott, Jason E.
SpringerLink (Online service)
- DOI
-
10.1186/s12859-018-2402-0
- URN
-
urn:nbn:de:101:1-2018111716084871218245
- Rights
-
Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Last update
-
14.08.2025, 10:53 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
- Colby, Sean M.
- McClure, Ryan S.
- Overall, Christopher C.
- Renslow, Ryan S.
- McDermott, Jason E.
- SpringerLink (Online service)
Other Objects (12)
Resampling algorithms for high energy physics simulations
Improving network inference by overcoming statistical limitations
Comparison of evolutionary algorithms in gene regulatory network model inference
Resampling imbalanced data for network intrusion detection datasets
Data-geometry and resampling-based inference for selecting predictors for monsoon precipitation
Tensor product algorithms for inference of contact network from epidemiological data
Tuning structure learning algorithms with out-of-sample and resampling strategies
Permutation- and resampling-based inference for semi- and nonparametric effects in dependent data
Compression-decompression of multivariate data via maximum entropy resampling and applications to inference
Permutation- and resampling-based inference for semi- and nonparametric effects in dependent data
Improving weighted least squares inference
Resampling and ensemble techniques for improving ANN-based high-flow forecast accuracy
Resampling algorithms for high energy physics simulations
Improving network inference by overcoming statistical limitations
Comparison of evolutionary algorithms in gene regulatory network model inference
Resampling imbalanced data for network intrusion detection datasets
Data-geometry and resampling-based inference for selecting predictors for monsoon precipitation
Tensor product algorithms for inference of contact network from epidemiological data
Tuning structure learning algorithms with out-of-sample and resampling strategies
Permutation- and resampling-based inference for semi- and nonparametric effects in dependent data
Compression-decompression of multivariate data via maximum entropy resampling and applications to inference
Permutation- and resampling-based inference for semi- and nonparametric effects in dependent data
Improving weighted least squares inference
Resampling and ensemble techniques for improving ANN-based high-flow forecast accuracy
Resampling algorithms for high energy physics simulations
Improving network inference by overcoming statistical limitations
Comparison of evolutionary algorithms in gene regulatory network model inference
Resampling imbalanced data for network intrusion detection datasets
Data-geometry and resampling-based inference for selecting predictors for monsoon precipitation
Tensor product algorithms for inference of contact network from epidemiological data
Tuning structure learning algorithms with out-of-sample and resampling strategies
Permutation- and resampling-based inference for semi- and nonparametric effects in dependent data
Compression-decompression of multivariate data via maximum entropy resampling and applications to inference
Permutation- and resampling-based inference for semi- and nonparametric effects in dependent data
Improving weighted least squares inference