Our new article has been accepted in JCPP Advances: Stroth S, Tauscher J, Wolff N, Küpper C, Poustka L, Roepke S, Roessner V, Heider D, Kamp‐Becker I: Identification of the most indicative and discriminative features from diagnostic instruments for children with autism. JCPP Advances 2021, 1(2): e12023. (Link) Abstract Background Diagnosing autism spectrum disorder (ASD)…
Our new article has been accepted in iScience: Hauschild AC, Eick L, Wienbeck J, Heider D: Fostering reproducibility, reusability, and technology transfer in health informatics. iScience 2021, 24(7): 102803. (Link) Summary Computational methods can transform healthcare. In particular, health informatics with artificial intelligence has shown tremendous potential when applied in various fields of medical research…
The University of Marburg (thru our project MOSLA) is now part of the global DNA Data Storage Alliance! The mission of the DNA Data Storage Alliance is to create and promote an interoperable storage ecosystem based on DNA as a data storage medium. In our project MOSLA, we aim to develop novel, transdisciplinary approaches for…
Our new article has been accepted in Cancers: Park Y, Heider D, Hauschild A.C.: Integrative Analysis of Next-Generation Sequencing for Next-Generation Cancer Research toward Artificial Intelligence. Cancers 2021, 13(13), 3148. (Link) Abstract The rapid improvement of next-generation sequencing (NGS) technologies and their application in large-scale cohorts in cancer research led to common challenges of big…
Our new article has been accepted in NARGAB: Spänig S, Mohsen S, Hattab G, Hauschild AC, Heider D: A large-scale comparative study on peptide encodings for biomedical classification. NAR Genomics and Bioinformatics 2021, 3(2): lqab039. (Link) Abstract Owing to the great variety of distinct peptide encodings, working on a biomedical classification task at hand is…
Our new article has been accepted in Molecular Ecology: Sperlea T, Kreuder N, Beisser D, Hattab G, Boenigk J, Heider D: Quantification of the covariation of lake microbiomes and environmental variables using a machine learning-based framework. Molecular Ecology 2021, 30(9):2131-2144. (Link) Abstract It is known that microorganisms are essential for the functioning of ecosystems, but…
Our new article has been accepted in Scientific Reports: Wagner D, Heider D, Hattab G. Mushroom data creation, curation, and simulation to support classification tasks. Scientific reports. 2021 Apr 14;11(1):1-2. (Link) Abstract Predicting if a set of mushrooms is edible or not corresponds to the task of classifying them into two groups—edible or poisonous—on the…
Dominik gave a talk on „Demystifying Artificial Intelligence“ at the Global Pregnancy CoLab Monthly Webinar 2021 Using Artificial Intelligence (AI) and Innovative Strategies to Study Adverse Pregnancy Outcomes February 25, 2021
Dominik gave a talk at TMF – Technologie- und Methodenplattform für die vernetzte medizinische Forschung: CORDITE – Corona Drug Interactions Database Since the outbreak in 2019, researchers are trying to find effective drugs against the SARS-CoV-2 virus based on de novo drug design and drug repurposing. The former approach is very time consuming and needs…
Our project Deep Insight: Integrating germline and somatic genetic profiles through machine learning to understand esophageal cancer etiology has just been granted by the BMBF (031L0267A). The partner in the project is the University of Cologne. Abstract Esophageal adenocarcinoma (EAC), also known as Barrett’s carcinoma, represents a major socio-medical challenge. It is a highly aggressive…
