Our Python test suite confinspect allows to assess the effect of demographic confounders such as sex and age on methods for inferring gene regulatory and gene co-expression networks.
In our paper "Inference of differential gene regulatory networks using boosted differential trees", we present BoostDiff, a tree-based method for identifying differences in transcriptional regulation between two conditions.
In our paper "Cracking the black box of deep sequence-based protein-protein interaction prediction", we show that the near-perfect performances reported for deep learning methods for PPI prediction can be entirely attributed to data leakage.
In our paper "Demographic confounders distort inference of gene regulatory and gene co-expression networks in cancer", we show that age and sex are important confounders for GRN and GCN inference.
In our paper "Federated singular value decomposition for high-dimensional data", we present federated privacy-aware SVD algorithms for both horizontal and vertical cross-silo data distribution scenarios.
In our paper "The specific DNA methylation landscape in focal cortical dysplasia ILAE type 3D", we show that histopathological epilepsy subtypes have distinct DNA methylation profiles.
We're happy to announce that Anne has received funding from FAU's Emerging Talents Initiative for her project "CAB: Carbon-aware bioinformatics". She'll develop tools to automatically shift CO2-intensive computations to time slots when green energy is available.