Established in 2003, the UC Davis Genome Center uses state-of-art-technologies to understand how the heritable genetic information of diverse organisms functions in health and disease. The combination of cutting-edge research facilities, diverse service cores, and talented staff make the Genome Center a world class facility for genomics research and training.
Research that makes a difference
A sample of questions being addressed by the UC Davis Genome Center faculty and their collaborators:
- How do variations in the human genome affect the risks of diseases such as cancer, coronary artery disease, and autism?
- Do infection, diet, or stress serve as environmental triggers of Type 1 diabetes?
- What novel, useful organisms will be discovered by sequencing microbes from extreme environments?
- Can characterization of the small molecules in algae lead to new biofuels?
- How can we control diseases of important food crops?
- How can plants be modified to increase their productivity and quality?
- What changes can we make to proteins to enhance their performance?
- Can we model and predict life’s basic processes?
- How can we glean useful information from vast datasets?
Here are just some of the recent highlights involving people and projects at the Genome Center. Please see the news page for a full list of all news items.
Thursday, October 31st
8:00 am- 3:00 pm, GBSF 1005 and LOBBY
8:00-8:45 am Set-up & Registration: Pumpkin Carving, Poster Presenters, and Costume Contestants Morning Coffee Refreshments
8:45 am Opening Remarks and Introduction to the ... Read more...
Recent Publication: Generating the Blood Exposome Database Using a Comprehensive Text Mining and Database Fusion Approach
A recent publication by Dinesh Kumar Barupal and Fiehn in Environmental Health Perspectives used data available on PubMed to generate a comprehensive blood exposome database, which can be found at this link.
Recent Publication: Predicting early risk of chronic kidney disease in cats using routine clinical laboratory tests and machine learning
A recent publication in the Journal of Veterinary Internal Medicine from Bradley et al. presents a model developed to predict the risk of cats developing chronic kidney disease. The study showed that machine learning-based models can support veterinary decision making.
We are happy to announce that the latest long-read sequencing technology is now available at UC Davis. Our new PacBio Sequel IIsequencer is up an running.
> The Sequel II
Recent publication: Temporal changes in postprandial blood transcriptomes reveal subject-specific pattern of expression of innate immunity genes after a high-fat meal
A recent publication from Lemay et al. unexpectedly showed subject-specific differentially expressed genes in response to eating a fatty meal, as shown by a whole blood transcriptome analysis.