TITLE: "Multi-tissue single-cell level understanding of Alzheimer’s disease points to the therapeutic potential of nutritional and metabolic modulation." ABSTRACT: Alzheimer’s disease (AD) is a progressive neurodegenerative disorder characterized by extracellular amyloid […]
TITLE: "Efficient, Multi Sample Inference of Cancer Phylogeny." ABSTRACT: Cancer is characterized by the ongoing accumulation of somatic mutations that may lead to dysregulated cellular proliferation. The selection of advantageous […]
TITLE: "ClusterDE: a post-clustering differentially expressed (DE) gene identification method robust to false-positive inflation caused by double-dipping" ABSTRACT: In typical single-cell RNA-seq data analysis, first, a clustering algorithm is applied […]
TITLE: "Germline structural variants shape prostate cancer clinical and molecular evolution." ABSTRACT: Inherited genetic variation profoundly influences cancer risk and outcome. While the impact of germline single nucleotide polymorphisms has […]
The workshop will cover experimental approaches to protein interaction determination; processing and presentation of interaction data available from online resources, and the role of interaction data in the interpretation of […]
Join us for an illuminating conversation with: Alexander Hoffmann, Director, Institute for Quantitative & Computational Biosciences, Thomas M. Asher Professor of Microbiology, UCLA Microbiology, Immunology & Molecular Genetics Elaine F. Reed, Daljit S. […]
TITLE: "FastGxC: a statistical framework for mapping context-specific regulatory variants using bulk and single-cell RNA-seq data." ABSTRACT: Recent studies suggest that context-specific eQTLs underlie genetic risk factors for complex diseases. However, methods for identifying […]
TITLE: "A lack of distinct cellular identities in scRNA-seq data: revisiting Waddington’s landscape." ABSTRACT: Single-cell RNA sequencing is revolutionizing our understanding of development, differentiation and disease. Analysis of this data is often […]
TITLE: "Single Cell Multiomics Integration to Understand Complex Diseases." ABSTRACT: Recent advances in single cell multiomics technologies such as single cell RNA-seq, single cell ATAC-seq, and spatial transcriptomics have brought […]
