Models
Implementation of recently developed dynamic mathematical models of normal and leukemic hematopoiesis to practically impact clinical decision- making.
Fitting available individual patients information, prediction of next-cycle thrombopenia caused by CHOEP treatment based on the individual fits of the preceeding treatment cycles, changing next-cycle relative dosing, posponement of the next cycle, changing follow-up period, visualization of data and simulation
Creator: Markus Scholz
Submitter: René Hänsel
Model type: Not specified
Model format: R package
Environment: Not specified
This is an interactive version of figure 4 of the publication „Integration of Genome-Wide SNP Data and Gene-Expression Profiles Reveals Six Novel Loci and Regulatory Mechanisms for Amino Acids and Acylcarnitines in Whole Blood“.
Creator: Markus Scholz
Submitter: René Hänsel
Model type: Not specified
Model format: R package
Environment: Not specified
A principled approach to parametrize SIR-type epidemiologic models of different complexities by embedding the model structure as a hidden layer into a general Input-Output Non-Linear Dynamical System (IO-NLDS). Non-explicitly modelled impacts on the system are imposed as inputs of the system. Observable data are coupled to hidden states of the model by appropriate data models considering possible biases of the data. We estimate model parameters including their time-dependence by a Bayesian knowledge ...
Creators: Markus Scholz, Holger Kirsten, Yuri Kheifetz
Submitter: Holger Kirsten
Model type: Ordinary differential equations (ODE)
Model format: R package
Environment: Not specified
This shiny app facilitates the download and searching of the summary statistics from "Dissecting the genetics of the human transcriptome identifies novel trait-related trans-eQTLs and corroborates the regulatory relevance of non-protein coding loci" (https://doi.org/10.1093/hmg/ddv194).
Creators: Markus Scholz, Carl Beuchel, Holger Kirsten
Submitter: Carl Beuchel
Model type: Not specified
Model format: R package
Environment: Shiny
This Shiny-App implements the calculation of several CAP (Community-Aquired-Pneumonia) severity scores for one or multiple patients based on user-updated data.
Creators: Markus Scholz, Maciej Rosolowski, Carl Beuchel
Submitter: Carl Beuchel
Model type: Algebraic equations
Model format: R package
Environment: Shiny
Preprocessing Illumina HT12v4 gene expression data including quality filtering, data transformation and normalisation and batch-effect removal as well as visualisation
Creators: Markus Scholz, Holger Kirsten
Submitter: Christoph Beger
Model type: Not specified
Model format: R package
Environment: Not specified
Creators: Markus Scholz, Carl Beuchel, Yuri Kheifetz, Sibylle Schirm
Submitter: Carl Beuchel
Model type: Ordinary differential equations (ODE)
Model format: R package
Environment: Shiny