Joachim Ludwig Schultze

ConvexGating automatically learns unbiased, interpretable gating strategies for flow cytometry data, improving consistency and reducing contamination in cell population identification.

The paper develops an in vitro platform to screen immune senomodulators using human-derived immune cells, enabling personalized anti-aging treatments through multi-scale molecular analysis.

This study shows that Satb1 downregulation prevents autoimmunity by maintaining Tfh cell homeostasis and preventing excessive GC formation and auto-antibody secretion.

This study investigates how TREM2 expression levels affect microglial function, metabolism, and response to TREM2 agonists in a mouse model of Alzheimer's disease.

This paper develops a 3D cortical brain tissue model with mature microglia that recapitulates Alzheimer's disease hallmarks and enables study of microglia phenotypes.

This study identifies SATB1 as a regulator that maintains naive CD8+ T cell identity by restricting chromatin remodelling at effector gene loci, preventing premature differentiation during viral infection.

DrugDiff generates novel small molecules with desired properties using a diffusion model guided by predictors.

The paper introduces cyCONDOR, a computational framework for high-dimensional cytometry data analysis, offering scalable and user-friendly tools for preprocessing, clustering, and downstream biological interpretation.

The paper characterizes human CMV-specific CD8+ T cells using a five-layer multi-omics approach and identifies novel T cell receptor sequences for CMV epitopes.

The paper identifies fetal liver macrophage subpopulations and shows their role in regulating granulopoiesis and the HSC niche during embryogenesis.

The paper introduces TimeAx, an algorithm for analyzing disease progression dynamics using time-series data, identifying key molecular transitions and clinical insights in urothelial bladder cancer.

Pytometry provides a Python framework for analyzing flow and mass cytometry data using tools adapted from single-cell genomics analysis, enabling automated preprocessing, cell type annotation, and disease classification.

This paper integrates transcriptome and chromatin state data to develop a scalable pipeline for drug discovery, predicting cancer cell line sensitivity and guiding compound development.

This study shows that Creld2 is essential for maintaining liver metabolism homeostasis by linking the unfolded protein response (UPR) to metabolic regulation, with sex-specific effects in fatty liver disease.

This study identifies two independent mechanisms by which TRIM71 inhibits let-7 miRNA maturation and activity, impacting developmental and oncogenic processes.

The paper generates synthetic embryo-like structures from ESCs through transcription factor-mediated reprogramming, showing implantation and decidual tissue formation.

This study uses single-cell RNA-seq and computational methods to analyze macrophage states in COPD patients, revealing transcriptional changes and metabolic shifts associated with the disease.

This paper demonstrates that memory-driven computing significantly accelerates NGS data processing and reduces energy consumption for RNA-seq tasks.

The paper develops robust and accurate classifiers for AML diagnosis using blood gene expression data and machine learning across 12,029 samples from 105 studies.

FASTGenomics provides a secure, flexible, and user-friendly analytical ecosystem for single-cell transcriptomics data.