Tools for Virus Sequence and Regulation
Project Area A focuses on the development of bioinformatics tools for nucleic acid sequences. This includes tools for assembly, annotation, genomics, alignments, phylogeny, transcriptomics, and optimizing anti-viral RNA sequences. With the explosion of publicly available virus sequence data, there is a pressing need for specialized tools to analyze these vast datasets accurately. General-purpose sequence analysis tools are often insufficient due to the unique characteristics of viruses. Challenges include accurately representing different virus variants (haplotypes), generating genomic multiple sequence alignments, and annotating virus genomes effectively.
We aim to study the host response to viral infections at the transcriptome level and uncover specific signaling pathways for individual viruses. The COVID-19 pandemic has driven efforts to predict the severity of viral infections using machine learning and sequence data, but these efforts have faced challenges and limitations. We aim to develop computational methods that offer a more nuanced and thorough understanding of viruses, bridging the gap between raw sequence data and diagnosis.
Prof. Dr. Manja Marz
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Prof. Dr. Manja Marz
FSU Jena, Institute for Computer Science
Virus bioinformatics, RNA bioinformatics, HTS data analysis
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Prof. Dr. Manja Marz
Enter Abstract Text Duis autem vel eum iriure dolor in hendrerit in vulputate velit esse molestie consequat, vel illum dolore eu feugiat nulla facilisis at vero eros et accumsan et iusto odio dignissim qui blandit praesent luptatum zzril delenit augue duis dolore te feugait nulla facilisi. Lorem ipsum dolor sit amet, consectetuer adipiscing elit, sed diam nonummy nibh euismod tincidunt ut laoreet dolore magna aliquam erat volutpat. Ut wisi enim ad minim veniam, quis nostrud exerci tation ullamcorper suscipit lobortis nisl ut aliquip ex ea commodo consequat. Duis autem vel eum iriure dolor in hendrerit in vulputate velit esse molestie consequat, vel illum dolore eu feugiat nulla facilisis at vero eros et accumsan et iusto odio dignissim qui blandit praesent luptatum zzril delenit augue duis dolore te feugait nulla facilisi.
Prof. Dr. Manja Marz
Enter Abstract Text Duis autem vel eum iriure dolor in hendrerit in vulputate velit esse molestie consequat, vel illum dolore eu feugiat nulla facilisis at vero eros et accumsan et iusto odio dignissim qui blandit praesent luptatum zzril delenit augue duis dolore te feugait nulla facilisi. Lorem ipsum dolor sit amet, consectetuer adipiscing elit, sed diam nonummy nibh euismod tincidunt ut laoreet dolore magna aliquam erat volutpat. Ut wisi enim ad minim veniam, quis nostrud exerci tation ullamcorper suscipit lobortis nisl ut aliquip ex ea commodo consequat. Duis autem vel eum iriure dolor in hendrerit in vulputate velit esse molestie consequat, vel illum dolore eu feugiat nulla facilisis at vero eros et accumsan et iusto odio dignissim qui blandit praesent luptatum zzril delenit augue duis dolore te feugait nulla facilisi.