Tools
Big datasets can be challenging and time-consuming to understand. Our main focus is to provide clear explanations what has been discovered with sharp and often interactive visualizations as part of publications.
Data
Hematology datalake catalogueDashboard of the HUS hematology datalake
Implementing a Functional Precision Medicine Tumor Board for Acute Myeloid LeukemiaClinical, drug sensitivity, RNA sequencing and mutation call data
Computational analysis of RCC tissues and multiomics dataSix texture subtypes and lymphocytes were detected from H&E-stained nephrectomy sections with convolutional neural networks
Immune Cell Contexture in the Leukemia Bone MarrowMultiplex immunohistochemistry stainings on AML, ALL, CML and control human bone marrow samples
Applications
Deep MDS bone marrow tissue analysisUMAP visualization of morphologic features of the bone marrow of patients with diagnosed myelodysplastic syndromes extracted with a convolutional neural network
Computational analysis of RCC tissues and multiomics dataSix texture subtypes and lymphocytes were detected from H&E-stained nephrectomy sections with convolutional neural networks
Code
Deep MDS bone marrow tissue analysisImage and statistical analyses to link images of bone marrow biopsies to understandable information
Bibliometric analysis of geographical and gender representation in high-impact journalsReproduction of plots and statistical analyses of two publications on bibliometric analyses
Computational analysis of RCC tissues and multiomics dataStatistical analyses and visualizations to combine image features with multi-omics data
Computational analysis of RCC tissues and multiomics dataImage analysis to detect texture subtypes and lymphocytes