Andrei Kramer
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Explore the profile of Andrei Kramer including associated specialties, affiliations and a list of published articles.
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7
Citations
37
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Recent Articles
1.
Eriksson O, Bhalla U, Blackwell K, Crook S, Keller D, Kramer A, et al.
Elife
. 2022 Jul;
11.
PMID: 35792600
Modeling in neuroscience occurs at the intersection of different points of view and approaches. Typically, hypothesis-driven modeling brings a question into focus so that a model is constructed to investigate...
2.
Santos J, Pajo K, Trpevski D, Stepaniuk A, Eriksson O, Nair A, et al.
Neuroinformatics
. 2021 Oct;
20(1):241-259.
PMID: 34709562
Neuroscience incorporates knowledge from a range of scales, from single molecules to brain wide neural networks. Modeling is a valuable tool in understanding processes at a single scale or the...
3.
Eriksson O, Jauhiainen A, Maad Sasane S, Kramer A, Nair A, Sartorius C, et al.
Bioinformatics
. 2018 Jul;
35(2):284-292.
PMID: 30010712
Motivation: Dynamical models describing intracellular phenomena are increasing in size and complexity as more information is obtained from experiments. These models are often over-parameterized with respect to the quantitative data...
4.
Hamiltonian Monte Carlo methods for efficient parameter estimation in steady state dynamical systems
Kramer A, Calderhead B, Radde N
BMC Bioinformatics
. 2014 Jul;
15:253.
PMID: 25066046
Background: Parameter estimation for differential equation models of intracellular processes is a highly relevant bu challenging task. The available experimental data do not usually contain enough information to identify all...
5.
Kramer A, Stathopoulos V, Girolami M, Radde N
Bioinformatics
. 2014 Jul;
30(20):2991-2.
PMID: 25005749
Summary: We present a new C implementation of an advanced Markov chain Monte Carlo (MCMC) method for the sampling of ordinary differential equation (ode) model parameters. The software mcmc_clib uses...
6.
Vehlow C, Hasenauer J, Kramer A, Raue A, Hug S, Timmer J, et al.
BMC Bioinformatics
. 2014 Feb;
14 Suppl 19:S2.
PMID: 24564335
Background: Mathematical models are nowadays widely used to describe biochemical reaction networks. One of the main reasons for this is that models facilitate the integration of a multitude of different...
7.
Weber P, Kramer A, Dingler C, Radde N
Bioinformatics
. 2012 Sep;
28(18):i535-i541.
PMID: 22962478
Motivation: Experiment design strategies for biomedical models with the purpose of parameter estimation or model discrimination are in the focus of intense research. Experimental limitations such as sparse and noisy...