Collab Network
Our Collab Network members are not only experts within their own domain but educators with the research community. Learn more about the discoveries and findings our collaborators are achieving with IDT.
Member spotlight:
Manja Meggendorfer, PhD
The future of personalized genomics
Manja Meggendorfer is the Head of Molecular Genetics at Munich Leukemia Laboratory (MLL), where she oversees various R&D activities such as the 5,000 genome project, which is aimed at better understanding the genetic factors behind leukemia. She received her Master of Science in Biology from the Ludwig-Maximilians-University in Munich and her PhD. in collaboration with the Helmholtz Center Munich working on gene regulation within the architecture of the cell nucleus. After her post-doctorate, she moved to the field of hematology as a scientist in the department of molecular genetics at MLL. In combination with her MBA in Health Care Management, Manja hopes to improve the diagnostic and prognostic work associated with routine diagnostic approaches for leukemia or lymphoma patients.
Tim A. Steiert
Competence Centre for Genomic Analysis Kiel
CCGA Kiel offers a broad portfolio of sequencing services fitting the needs of academic partners, including different long-read technologies. Long-read sequencing has the potential to overcome challenges in genomic sequencing; long reads covering several heterozygous SNVs can be used to generate haplotype-phased data. Longer stretches containing highly paralogous or repetitive sequences can reliably be aligned to their genomic origin and be resolved.
Despite recent throughput improvements, long-read sequencing for hypothesis-driven studies, including larger cohorts, is still unaffordable for many. CCGA Kiel’s high-throughput and automatization-capable targeted enrichment protocol for long genomic fragments enables large cohort studies for small or comprehensive enrichment panels. CCGA Kiel aims to empower researchers to leverage the potential of long-read sequencing for any project, including the most complex genomic loci.