Bioinformatics Scientist
Education:
Ph.D., Bioinformatics
Biography
Dr. Bylund’s research centers on the computational design of immunogens using advanced computational and bioinformatics methods. By leveraging tools such as machine learning algorithms, structural modeling, and sequence analysis, Dr. Bylund aims to develop immunogens that can improve the efficacy of vaccines and therapeutic antibodies.
A significant aspect of Dr. Bylund’s work involves the sequence and structural analysis of various viruses, including HIV-1, SARS-CoV-2, Influenza, and Lassa virus, among others. Through analyzing viral sequences and protein structures, Dr. Bylund investigates how viral evolution, genetic diversity, and structural variations influence immune evasion and neutralization sensitivity. This understanding helps identify conserved regions of viral proteins that could serve as stable targets for vaccines or antibodies.
Additionally, Dr. Bylund studies the sequence and structural properties of antibodies, particularly those that exhibit broad neutralizing activity against multiple viral strains. By characterizing these antibodies, including their binding sites, epitope specificities, and structural conformations, the research provides insights into mechanisms of neutralization and informs strategies for antibody-based therapeutics and rational vaccine design.
Overall, Dr. Bylund’s work integrates computational biology, virology, immunology, and structural bioinformatics to address challenges in viral pathogenesis and immune response, ultimately contributing to the design of next-generation vaccines and antibody therapies.