Demonstration venue · read-only. Every page can be browsed; the buttons that would change it are switched off. Create an account to run TaxoReview on your own data. A simulation from public publication records: the people listed were not invited and did not agree to review.
? Tutorial for this page
Demo Data from EDBT 2026 / reviewers in the wild / expert

Anna Fiedler

dblp:184/7110 · DBLP profile ↗
← Back
1ranked-venue papers
0as first author
0since 2021 · last 2018
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Applied, interdisciplinary, general and emerging computing · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Interdisciplinary, comprehensive, and emerging computing
1 paper
Bioinformatics and computational biology · 100%
Theoretical computer science
1 paper
Mathematical optimization · 100%

Topics — the 4 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology › systems biology › parameter estimation
identifiability analysis		 0.312018
PESTO: Parameter EStimation TOolbox · Bioinform. 2018
Bioinformatics and computational biology › systems biology
parameter estimation		 0.312018
PESTO: Parameter EStimation TOolbox · Bioinform. 2018
Bioinformatics and computational biology
systems biology		 0.312018
PESTO: Parameter EStimation TOolbox · Bioinform. 2018
Mathematical optimization
optimization		 0.312018
PESTO: Parameter EStimation TOolbox · Bioinform. 2018

Methods — techniques the papers use, named apart from their topics

uncertainty quantification · 0.7optimization · 0.7
YearPublicationVenuePosition
2018 PESTO: Parameter EStimation TOolbox
abstract
Summary: PESTO is a widely applicable and highly customizable toolbox for parameter estimation in MathWorks MATLAB. It offers scalable algorithms for optimization, uncertainty and identifiability analysis, which work in a very generic manner, treating the objective function as a black box. Hence, PESTO can be used for any parameter estimation problem, for which the user can provide a deterministic objective function in MATLAB. Availability and implementation: PESTO is a MATLAB toolbox, freely available under the BSD license. The source code, along with extensive documentation and example code, can be downloaded from https://github.com/ICB-DCM/PESTO/. Contact: [email protected]. Supplementary information: Supplementary data are available at Bioinformatics online.
Paul Stapor, Daniel Weindl, Benjamin Ballnus, Sabine Hug, Carolin Loos, Anna Fiedler, Sabrina Krause, Sabrina Hross, Fabian Fröhlich, Jan Hasenauer
 Bioinform.6