Melissa Haendel
Affiliations: | Medical Informatics & Clinical Epidemiology | Oregon Health and Science University, Portland, OR |
Area:
informaticsWebsite:
http://www.ohsu.edu/xd/education/library/about/staff-directory/melissa-haendel.cfmGoogle:
"Melissa Haendel"Mean distance: 16.02 | S | N | B | C | P |
Parents
Sign in to add mentor| Gary Lyons | grad student | 1993-1999 | UW Madison |
| Judith Eisen | post-doc | 2000-2002 | University of Oregon |
| George Bailey | post-doc | 2002-2004 | Oregon State |
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Publications
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| Danis D, Bamshad MJ, Bridges Y, et al. (2024) A corpus of GA4GH Phenopackets: case-level phenotyping for genomic diagnostics and discovery. Medrxiv : the Preprint Server For Health Sciences |
| Putman TE, Schaper K, Matentzoglu N, et al. (2023) The Monarch Initiative in 2024: an analytic platform integrating phenotypes, genes and diseases across species. Nucleic Acids Research |
| Gargano MA, Matentzoglu N, Coleman B, et al. (2023) The Human Phenotype Ontology in 2024: phenotypes around the world. Nucleic Acids Research |
| Danis D, Jacobsen JOB, Wagner AH, et al. (2023) Phenopacket-tools: Building and validating GA4GH Phenopackets. Plos One. 18: e0285433 |
| Stefancsik R, Balhoff JP, Balk MA, et al. (2023) The Ontology of Biological Attributes (OBA)-computational traits for the life sciences. Mammalian Genome : Official Journal of the International Mammalian Genome Society |
| Stefancsik R, Balhoff JP, Balk MA, et al. (2023) The Ontology of Biological Attributes (OBA) - Computational Traits for the Life Sciences. Biorxiv : the Preprint Server For Biology |
| Thaxton C, Goldstein J, DiStefano M, et al. (2022) Lumping versus splitting: How to approach defining a disease to enable accurate genomic curation. Cell Genomics. 2 |
| Thessen AE, Grondin CJ, Kulkarni RD, et al. (2020) Community Approaches for Integrating Environmental Exposures into Human Models of Disease. Environmental Health Perspectives. 128: 125002 |
| Thessen AE, Walls RL, Vogt L, et al. (2020) Transforming the study of organisms: Phenomic data models and knowledge bases. Plos Computational Biology. 16: e1008376 |
| Ong E, Wang LL, Schaub J, et al. (2020) Modelling kidney disease using ontology: insights from the Kidney Precision Medicine Project. Nature Reviews. Nephrology |