The advent of high-throughput biomolecular technologies has made high-dimensional biological data available for the investigation of many clinical settings. The large numbers of features and low numbers of probes in such data sets poses many challenges for their analysis. Machine learning approaches and statistical methods are essential for the interpretation of the data. For example, clustering methods can detect groups of similar probes. Feature selection techniques are employed to identify features (e.g. marker genes) that are relevant to distinguish certain phenotypes. Classification algorithms can predict the phenotype of a probe according to the measurements.
Our first quantum computing paper "Leveraging quantum computing for dynamic analyses of logical networks in systems biology" has been published in Patterns.
Our paper "Unsupervised domain adaptation for the detection of cardiomegaly in cross-domain chest X-ray images" has been published in Frontiers in Artificial Intelligence.
"Vaccine Side Effects in Health Care Workers after Vaccination against SARS-CoV-2: Data from TüSeRe:exact Study" has been published in Viruses-Basel.
"PREDICT-juvenile-stroke: PRospective evaluation of a prediction score determining individual clinical outcome three months after ischemic stroke in young adults – a study protocol" has been published in BMC Neurology.
Our paper "Federated Electronic Data Capture (fEDC): Architecture and Prototype" has been accepted for publiaction in the Journal of Biomedical Informatics.
Our paper "Efficient cross-valdation traversals in feature subset selection" has been published in Scientific Reports.
Our paper "CANTATA - prediction of missing links in Boolean networks using genetic programming" has been published in Bioinformatics.
Our paper "Interaction Empowerment in Mobile Health: Concepts, Challenges, and Perspectives" has been published in the Journal of Medical Internet Research mhealth and uhealth.
Our paper "Identification of dynamic driver sets controlling phenotypical landscapes" has been published in the Computational and Structural Biotechnology Journal.
Congratulations to Dr. Silke Werle for winning the 1st Prize with her pitch at the 1. Science Day held by ProTrainU.
Our paper "Reconstructing Boolean network ensembles from single-cell data for unraveling dynamics in the aging of human hematopoietic stem cells" has been published in the Computational and Structural Biotechnology Journal.
The position paper "Is there a role for statistics in artificial intelligence" has been published online first in Advances in Data Analysis and Classification.