Browsing Fakultät für Biologie und Psychologie (inkl. GAUSS) by Referee "Söding, Johannes Dr."
Now showing items 1-6 of 6
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Computational Analysis of Prognostic Factors, Immune Microenvironment, and T-Cell Receptor Repertoires in Lymphoma
(2024-11-22)The immune system plays an important role in the development and progression of cancer. While solid cancers like carcinomas primarily affect specific organs and tissues, hematologic malignancies are not always so localized, ... -
Understanding the role of the transcription factor MGA in primordial germ cell differentiation
(2023-06-20)One of the most crucial cell lineage decisions in mammalian embryos is the differentiation of a few pluripotent epiblast cells into primordial germ cells (PGCs). PGCs are unique for their ability to mature into either sperm ... -
Alignment-free Phylogenetic Placement and its Applications
(2023-03-03)The study of the evolutionary interrelations of living organisms has been at the heart of biological sciences all along. A revolution in sequencing techniques in the past decades has caused a massive increase in molecular ... -
Computational methods for de novo assembly and sequencing error correction of short reads in the era of (viral) metagenomics
(2022-12-15)Viruses can affect all types of living cells, including bacteria, archaea and eukaryotes. Especially in the form of bacteriophages - bacteria infecting viruses - they have a huge impact on their host communities, driving ... -
Investigation on the molecular factors driving the formation of distinct tau 'strains'
(2022-11-28)Pathological aggregation of the microtubule-binding protein tau into amyloid fibrils is a hallmark of different neurodegenerative diseases collectively termed tauopathies. To date, tau amyloid structures associated with ... -
Explaining decisions of graph convolutional neural networks for analyses of molecular subnetworks in cancer
(2022-05-03)Contemporary deep learning approaches exhibit state-of-the-art performance in various areas. In healthcare, the application of deep learning remains limited since deep learning methods are often considered as non-interpretable ...