Guidelines for benchmarking of optimization-based approaches for fitting mathematical models
- Standort
-
Deutsche Nationalbibliothek Frankfurt am Main
- ISSN
-
1474-760X
- Umfang
-
Online-Ressource
- Sprache
-
Englisch
- Anmerkungen
-
online resource.
- Erschienen in
-
Guidelines for benchmarking of optimization-based approaches for fitting mathematical models ; volume:20 ; number:1 ; day:16 ; month:12 ; year:2019 ; pages:1-10 ; date:12.2019
Genome biology ; 20, Heft 1 (16.12.2019), 1-10, 12.2019
- Urheber
- Beteiligte Personen und Organisationen
-
SpringerLink (Online service)
- DOI
-
10.1186/s13059-019-1887-9
- URN
-
urn:nbn:de:101:1-2020040703313943186171
- Rechteinformation
-
Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Letzte Aktualisierung
-
14.08.2025, 10:56 MESZ
Datenpartner
Dieses Objekt wird bereitgestellt von:
Deutsche Nationalbibliothek. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Deutsche Nationalbibliothek. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Beteiligte
- Kreutz, Clemens
- SpringerLink (Online service)
Ähnliche Objekte (12)
Guidelines for benchmarking of optimization-based approaches for fitting mathematical models
A new approximation approach for transient differential equation models
Steuerung stochastischer Systeme : : ein Vergleich von Strategien
Rcall: An R interface for MATLAB
Computational study protocol: leveraging synthetic data to validate a benchmark study for differential abundance tests for 16s microbiome sequencing data
RTF: an R package for modelling time course data
Statistical approaches for molecular and systems biology : = Statistische Methoden zur Anwendung in der Molekular- und Systembiologie
Advances in benchmarking methodologies for systems biology
Realistic simulation of time-course measurements in systems biology
Tail‐Robust Quantile Normalization
Likelihood based observability analysis and confidence intervals for predictions of dynamic models
Likelihood based observability analysis and confidence intervals for predictions of dynamic models
Guidelines for benchmarking of optimization-based approaches for fitting mathematical models
A new approximation approach for transient differential equation models
Steuerung stochastischer Systeme : : ein Vergleich von Strategien
Rcall: An R interface for MATLAB
Computational study protocol: leveraging synthetic data to validate a benchmark study for differential abundance tests for 16s microbiome sequencing data
RTF: an R package for modelling time course data
Statistical approaches for molecular and systems biology : = Statistische Methoden zur Anwendung in der Molekular- und Systembiologie
Advances in benchmarking methodologies for systems biology
Realistic simulation of time-course measurements in systems biology
Tail‐Robust Quantile Normalization
Likelihood based observability analysis and confidence intervals for predictions of dynamic models
Likelihood based observability analysis and confidence intervals for predictions of dynamic models
Guidelines for benchmarking of optimization-based approaches for fitting mathematical models
A new approximation approach for transient differential equation models
Steuerung stochastischer Systeme : : ein Vergleich von Strategien
Rcall: An R interface for MATLAB
Computational study protocol: leveraging synthetic data to validate a benchmark study for differential abundance tests for 16s microbiome sequencing data
RTF: an R package for modelling time course data
Statistical approaches for molecular and systems biology : = Statistische Methoden zur Anwendung in der Molekular- und Systembiologie
Advances in benchmarking methodologies for systems biology
Realistic simulation of time-course measurements in systems biology
Tail‐Robust Quantile Normalization
Likelihood based observability analysis and confidence intervals for predictions of dynamic models