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Person
Person

Person

Marcus Rosenblatt (1989-)

Physiker

Name

Marcus Rosenblatt

Time

1989- (Date of birth and death)

Place

Karl-Marx-Stadt (Geburtsort)
Deutschland

Profession

Physiker (characteristic profession)

Further information

Dissertation 2021, Albert-Ludwigs-Universität Freiburg im Breisgau, Fakultät für Mathematik und Physik

Record type

Person

GND-Identifier

1126128600

Record ID

1126128600

Involved in

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Design of a Biohybrid Materials Circuit with Binary Decoder Functionality

Design of a Biohybrid Materials Circuit with Binary Decoder Functionality (Adv. Mater. 14/2024)

Design of a Biohybrid Materials Circuit with Binary Decoder Functionality

Activator-blocker model of transcriptional regulation by pioneer-like factors

Activator-blocker model of transcriptional regulation by pioneer-like factors

Design of a biohybrid materials circuit with binary decoder functionality

Non-parametric model-Based estimation of the effective reproduction number for SARS-CoV-2

Uncovering specific mechanisms across cell types in dynamical models

BlotIt - optimal alignment of Western blot and qPCR experiments

Dynamic modeling of Nrf2 pathway activation in liver cells after toxicant exposure

Pluripotency factors determine gene expression repertoire at zygotic genome activation

From steady states to dynamics : : methods for mechanistic modeling of biological systems with applications to interferon apha signaling

On structural and practical identifiability

PEtab - interoperable specification of parameter estimation problems in systems biology

Disentangling molecular mechanisms regulating sensitization of interferon alpha signal transduction

Disentangling molecular mechanisms regulating sensitization of interferon alpha signal transduction

Dynamic modeling, parameter estimation, and uncertainty analysis in R

Expression ratio of the TGF[beta]-inducible gene MYO10 is prognostic for overall survival of squamous cell lung cancer patients and predicts chemotherapy response

Customized steady-state constraints for parameter estimation in non-linear ordinary differential equation models
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