Congratulations, Professor Parker, and colleagues!
Congratulations, Professor Liu!
"Leveraging Generative Artificial Intelligence for the De Novo Design of Biomolecular Probes" was one of the four funded projects lead by Aaron Frank (CCMB Affiliate).
Congratulations, Professor O'Meara!
The Michigan Institute for Data Science (MIDAS) is offering a special round of Propelling Original Data Science (PODS) mini-grants for U-M researchers leveraging data science and artificial intelligence for COVID-19 research.
The first of its kind at U-M, the MIDAS Reproducibility Challenge aims to highlight high-quality, reproducible work at U-M by collecting examples of best practices across diverse fields.
The Mills Lab review modern approaches for investigating structural variations (SV) and proffer that, moving forwards, studies integrating biological information with detection will be necessary to comprehensively understand the impact of SV in the human genome.
Single-cell RNA sequencing (scRNA-seq) offers new opportunities to study gene expression of tens of thousands of single cells simultaneously. We present DeepImpute, a deep neural network-based imputation algorithm that uses dropout layers and loss functions to learn patterns in the data, allowing for accurate imputation.
Congratulations, Mats!
“When you first begin looking at new data like this, it’s like landing on Mars and looking around for the first time, but a Mars with little critters never described before staring back at you,” said Melissa Duhaime, assistant professor of ecology and evolutionary biology & CCMB affiliated faculty member, commenting on the discovery of
