| Title: |
The Monarch Initiative in 2024: an analytic platform integrating phenotypes, genes and diseases across species |
| Authors: |
Putman, Tim E; Schaper, Kevin; Matentzoglu, Nicolas; Rubinetti, Vincent P; Alquaddoomi, Faisal S; Cox, Corey; Caufield, J Harry; Elsarboukh, Glass; Gehrke, Sarah; Hegde, Harshad; Reese, Justin T; Braun, Ian; Bruskiewich, Richard M; Cappelletti, Luca; Carbon, Seth; Caron, Anita R; Chan, Lauren E; Chute, Christopher G; Cortes, Katherina G; De Souza, Vinícius; Fontana, Tommaso; Harris, Nomi L; Hartley, Emily L; Hurwitz, Eric; Jacobsen, Julius OB; Krishnamurthy, Madan; Laraway, Bryan J; McLaughlin, James A; McMurry, Julie A; Moxon, Sierra AT; Mullen, Kathleen R; O’Neil, Shawn T; Shefchek, Kent A; Stefancsik, Ray; Toro, Sabrina; Vasilevsky, Nicole A; Walls, Ramona L; Whetzel, Patricia L; Osumi-Sutherland, David; Smedley, Damian; Robinson, Peter N; Mungall, Christopher J; Haendel, Melissa A; Munoz-Torres, Monica C |
| Source: |
Nucleic Acids Research, vol 52, iss D1 |
| Publisher Information: |
eScholarship, University of California |
| Publication Year: |
2024 |
| Collection: |
University of California: eScholarship |
| Subject Terms: |
31 Biological Sciences (for-2020); 3105 Genetics (for-2020); Genetics (rcdc); Networking and Information Technology R&D (NITRD) (rcdc); Data Science (rcdc); 1.1 Normal biological development and functioning (hrcs-rac); Generic health relevance (hrcs-hc); 3 Good Health and Well Being (sdg); Humans (mesh); Phenotype (mesh); Internet (mesh); Databases; Factual (mesh); Software (mesh); Genes (mesh); Disease (mesh); 05 Environmental Sciences (for); 06 Biological Sciences (for); 08 Information and Computing Sciences (for); Developmental Biology (science-metrix); 34 Chemical sciences (for-2020); 41 Environmental sciences (for-2020) |
| Subject Geographic: |
d938 - d949 |
| Description: |
Bridging the gap between genetic variations, environmental determinants, and phenotypic outcomes is critical for supporting clinical diagnosis and understanding mechanisms of diseases. It requires integrating open data at a global scale. The Monarch Initiative advances these goals by developing open ontologies, semantic data models, and knowledge graphs for translational research. The Monarch App is an integrated platform combining data about genes, phenotypes, and diseases across species. Monarch's APIs enable access to carefully curated datasets and advanced analysis tools that support the understanding and diagnosis of disease for diverse applications such as variant prioritization, deep phenotyping, and patient profile-matching. We have migrated our system into a scalable, cloud-based infrastructure; simplified Monarch's data ingestion and knowledge graph integration systems; enhanced data mapping and integration standards; and developed a new user interface with novel search and graph navigation features. Furthermore, we advanced Monarch's analytic tools by developing a customized plugin for OpenAI's ChatGPT to increase the reliability of its responses about phenotypic data, allowing us to interrogate the knowledge in the Monarch graph using state-of-the-art Large Language Models. The resources of the Monarch Initiative can be found at monarchinitiative.org and its corresponding code repository at github.com/monarch-initiative/monarch-app. |
| Document Type: |
article in journal/newspaper |
| File Description: |
application/pdf |
| Language: |
unknown |
| Relation: |
qt6pb9p207; https://escholarship.org/uc/item/6pb9p207; https://escholarship.org/content/qt6pb9p207/qt6pb9p207.pdf |
| DOI: |
10.1093/nar/gkad1082 |
| Availability: |
https://escholarship.org/uc/item/6pb9p207; https://escholarship.org/content/qt6pb9p207/qt6pb9p207.pdf; https://doi.org/10.1093/nar/gkad1082 |
| Rights: |
CC-BY |
| Accession Number: |
edsbas.4F1A9A0A |
| Database: |
BASE |