TITLE: “Automatic analysis of cryo-electron tomography using computer vision and machine learning.”
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 plaque deposition and intracellular neurofibrillary tangles. The direct cause of abnormal protein accumulation and aggregation is largely unknown, and no treatments exist to effectively delay […]
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 mutations leads to clonal expansions of progressively more aberrant and fit cancer cells. Reconstructing the evolutionary history of a tumor allows us to understand key […]
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 to cluster cells; then, a statistical method is used to identify the differentially expressed (DE) genes between the cell clusters. However, this common procedure uses the same […]
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 been well-studied in several cancer types, the effects of germline structural variants (gSVs) on cancer biology and clinical outcomes is largely unknown. From our cohort […]
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 large scale datasets. Highly encourage: Students should working knowledge of python scripting.
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. and Elaine Sarkaria Endowed Chair in Diagnostic Medicine, Professor, Pathology and Laboratory Medicine, Director, UCLA Immunogenetics Center Aaron Meyer, Assistant Professor, Bioengineering With introductory remarks by Tracy […]
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 them are still nascent, limiting their comprehensive characterization and downstream interpretation of disease-associated variants. In this talk, I will introduce FastGxC, a method to efficiently and powerfully […]
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 challenging, however, and tasks like clustering cells to uncover distinct cellular identities sometimes yields results that fail to align with existing biological knowledge. We analyzed […]
