Author Archives: WeimerMicroLab

 Dr. Weimer and DJ Darwin Bandoy join The Conversation with their latest article: Where coronavirus variants emerge, surges follow – new research suggests how genomic surveillance can be an early warning system.  How The Conversation is different Every article you read … Continue reading →

Contributed by Cory Schlesener, B.S. Predicting bacterial isolate susceptibility for disease treatment and surveying resistance prevalence broadly is of great interest, especially as antibiotic resistance is increasing globally among clinical isolates. Screening sequence data for genes and alleles that confer antibiotic resistance has increased in availability but … Continue reading →

This past week UC Davis did a press release for the new paper that Dr. Weimer and graduate student DJ Darwin Bandoy have being published in Nature. You can read the article Analysis of SARS-CoV-2 genomic epidemiology reveals disease transmission … Continue reading →

Contributed by Darwin Bandoy, PhD Candidate One year into the pandemic and I already managed to get my first dose of vaccine. The pandemic will end with the achievement of herd immunity and the best path towards herd immunity is … Continue reading →

Contributed by Cory Schlesener, B.S. When conducting biological assays using mammalian cell tissue culture, the cell line used is crucial. It is a given to choose cells derived from the tissue of interest to study. However, as immortalized cell lines … Continue reading →

Click here to watch as Dr. Weimer joins UC Davis live to discuss coronavirus. 

Contributed by Darwin Bandoy, PhD candidate It is the start of another year and we are still in the middle of the winter wave of COVID-19 with a record number of mortalities and new infections. What is different is the … Continue reading →

Contributed by Cory Schlesener, B.S. When analyzing large data files in the realm of gigabytes, system memory and program/function set memory limits becomes an issue. Creating a smaller data set for analysis can bring the working data down to a … Continue reading →

Contributed by Cory Schlesener, B.S. Machine Learning (ML) enables powerful analysis of data to formulate models. These models can be utilized in applications or help dive into the data for insight on relationships between features.  There are many varieties of models … Continue reading →

Contributed by Darwin Bandoy, PhD Candidate We formally started the USDA Food Safety fellowship with a kick-off meeting. Our proposal is to utilize machine learning to parse the basis for virulence and antimicrobial resistance in Salmonella Dublin. This particular strain … Continue reading →