
معرفی
Goncalo Abecasis is the Felix E. Moore Collegiate Professor of Biostatistics at the University of Michigan School of Public Health, where he leads the Center for Statistical Genetics. He received his DPhil in Human Genetics from the University of Oxford in 2001 and joined the University of Michigan faculty that same year. His research focuses on developing statistical and computational tools for identifying genetic variants associated with human disease and variation.
His research interests include the development of analytical methods for mapping complex traits, utilization of linkage disequilibrium in gene mapping, quantitative trait analysis, and characterization of human genetic variation. He has pioneered computational approaches that enable the analysis of large genomic datasets generated by high-throughput technologies. His work addresses practical challenges in handling real-world genetic data, including genotype error detection and relationship verification.
Abecasis has developed numerous widely-used software tools including Merlin (for pedigree analysis), MACH (for haplotype estimation), LAMP (for association testing), QTDT (for quantitative trait analysis), GOLD (for linkage disequilibrium visualization), and GRR (for relationship error detection). His publications span statistical genetics methodology, software development, and applications to diseases including diabetes, glaucoma, age-related macular degeneration, schizophrenia, and aging-related traits.
His recent work involves large-scale genome-wide association studies with hundreds of thousands of participants, focusing on complex traits related to substance use, cardiovascular health, metabolic disorders, and eye diseases. The computational tools he develops are used in hundreds of gene-mapping projects worldwide.
Abecasis collaborates extensively with researchers studying diabetes (Dr. Michael Boehnke), eye diseases (Drs. Julia Richard and Anand Swaroop), schizophrenia (Dr. Maria Karayiorgou), and aging-related traits (Dr. David Schlessinger).
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