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Dr. Heaton is Clinical Assistant Professor of Oral Health Sciences and a licensed clinical psychologist in Washington State. She earned a BA in psychology (1996) from the University of Massachusetts at Amherst, and a Master's of Science (2002) and PhD in Clinical Psychology (2005), both from the University of Kentucky. She completed a pre-doctoral internship in clinical health psychology at the University of Florida before completing a post-doctoral fellowship in the Department of Dental Public Health Sciences at the University of Washington. Her interests include dental fear and anxiety, utilization of oral health services by adults with mental illness, involvement of non-dental health care providers in the provision of oral health care services, and psychometrics of pain and anxiety measures.
Dr. Heaton is currently the Principal Investigator of a K23 Mentored Patient-Oriented Research Career Training grant from the National Institute of Dental and Craniofacial Research (NICDR) entitled, "Addressing Oral Health Disparities in Adults with Mental Health Problems." Combining her training in clinical psychology and dental public health, her current studies include interviewing adults treated for psychiatric disorders about their use of and barriers in accessing oral health resources, and training pharmacists to provide oral health recommendations to individuals in underserved populations.
Clinical researcher at Fred Hutchinson Cancer Research Center in the Vaccine and Infectious Disease and Clinical Research Divisions, and faculty member at the University of Washington. Interested in Infectious Diseases and Infection Prevention, with a focus on epidemiology of major pathogens, antibiotic resistance/usage, development of novel prevention strategies and patient/provider education among immunosuppressed patient populations. Research efforts on emerging pathogens in transplantation, respiratory viruses, fungal infections, and drug resistant bacterial infections. Currently serves as Director of Infection Prevention at the Seattle Cancer Care Alliance.
Martin is a Computational Molecular Biologist by training (B.Sc./M.Sc.hon. at Saarland University, Germany) and received his PhD (Dr. rer. nat.) in Computer Sciences from the University of Leipzig, Germany, in 2011. He has a broad interest in genomics, epigenetics and evolution as well as the development of sequencing protocols, technologies and bioinformatics approaches to advance our capabilities in these fields.
Martin did his Master's thesis on microRNAs and genomic imprinting in the DLK1/GTL2 region in the labs of Jörn Walter and Thomas Lengauer. In 2007, he entered the field of ancient DNA at a time when high-throughput sequencing completely transformed Svante Pääbo's department at the Max Planck Institute for Evolutionary Anthropology. During his PhD, Martin was advised by Janet Kelso and Peter Stadler. He developed a base caller for the Illumina/Solexa systems (IBIS), implemented the analysis pipelines that underlie the Neandertal and Denisova genomes and analysed NGS data for different ancient DNA and comparative gene expression studies.
In the spring of 2012, he moved to the University of Washington (Seattle), when he joined Jay Shendure's lab in the development of methods for the functional scoring of variants (CADD), studying epigenetic signatures and nucleosome patterns in cell-free DNA, and developing methods to functionally assess regulatory variants using massively parallel reporter assays (MPRA). For more than three years, Martin was a member of the analysis group of the University of Washington's Center for Mendelian Genomics and has been actively involved in several studies identifying disease causal variants.
He started a computational research group at the Berlin Institute of Health (BIH) in Germany in March 2017. His research is in the areas of sequence analysis, data mining and functional genomics. One focus area is non-coding sequence variation, specifically analysis of data from Massively Parallel Reporter Assays (MPRA) for promoter and enhancer variants as well computational approaches for identifying functionally relevant genetic changes.