Clemens Kreutz

PEtab Select provides a standardized format and software for automated model selection in systems biology, supporting diverse modeling frameworks and enabling efficient evaluation of large model spaces.

This study shows NEK7 accelerates NLRP3 inflammasome activation but is not essential, suggesting potential limitations in targeting this interaction for drug development.

The paper introduces mmContext, a framework for multimodal contrastive learning of omics and text data, and demonstrates its utility in RNA-Seq and text integration tasks.

This study shows that combining physical and pharmacological anabolic therapies improves bone strength and mechanoregulation in female mice with osteoporosis.

This study identifies novel functions of Foxi1 in regulating mucociliary progenitor cells and ionocyte specification through transcriptional and epigenetic mechanisms in Xenopus laevis.

The paper introduces 1100 synthetic benchmark problems for dynamic cellular process modeling to improve algorithm evaluation.

This study shows that dermal macrophages can maintain functional diversity without monocyte replenishment, but require monocytes during bacterial infections.

The paper introduces an extended RTF method for modelling dose-dependent kinetics in cellular signalling, demonstrating its effectiveness using inflammasome activation data.

The paper introduces an R package for modelling time course data using the retarded transient function approach, enabling analysis of experimental and ODE model trajectories.

This paper investigates likelihood-ratio test statistics for nonlinear ODE models in finite-sample settings and finds that corrections are needed to avoid anti-conservative results.

The paper investigates how Notch signaling and Hes factors regulate mucociliary cell fate specification in Xenopus tadpole epidermis through competitive de-repression.

The paper presents a method to simulate realistic time-course data for systems biology models, validated on multiple models to assess method performance.

This study evaluates deep generative models for integrating single-cell multi-omics data across varying sample sizes and provides recommendations for experimental design.

DIMA selects an imputation algorithm based on data characteristics, achieving reliable performance across proteomics datasets with missing values.

This study identifies IL1β as an amplifier of IFN-induced antiviral responses through mathematical modeling and experimental validation.

This paper introduces tail-robust quantile normalization to address systematic variance in proteomics data, improving statistical inference by preserving tail features and handling missing values.

The paper presents 20 ODE-based benchmark models for evaluating dynamic modeling methods in systems biology, including parameter estimation and uncertainty analysis.