TITLE: “Inferring positive selection in the human gut microbiome using signatures of genetic linkage.” ABSTRACT: The human gut microbiome is composed of hundreds of simultaneously evolving species that can affect human […]
TITLE: "Quantifying response-specificity to diverse immune threats from single cell transcriptomes" ABSTRACT: Innate immune sentinel cells such as macrophages upregulate over a thousand genes in the minutes to hours following an […]
TITLE: "Efficient variance components analysis across millions of genomes." ABSTRACT: While variance components analysis has emerged as a powerful tool in complex trait genetics, existing methods for fitting variance components do […]
TITLE: "Asymptotic-Numerical Method For Cell Focusing in Microfluidic Channel." ABSTRACT: Inertial microfluidic devices use inertial lift forces to organize the spacing and positions of cells carried by flow. A hybrid […]
TITLE: "A pan-cancer landscape analysis of molecular and functional genomics in tumor proliferation." ABSTRACT: Rapid proliferation is a central hallmark of cancer and is associated with poor prognosis in most […]
Assistant Professor-Biostatistics, Department of Biostatistics and Epidemiology, Rutgers University "Model-based analysis of alternative polyadenylation using 3' end reads" Hosted by Jessica Li
TITLE: "Distal mediator-enriched placental transcriptome-wide association studies reveal genetic mechanisms supporting the Developmental Origins of Health and Disease." ABSTRACT: As the master regulator of the intrauterine environment, the placenta is […]
TITLE: "Clipper: p-value-free FDR control on high-throughput data from two conditions." ABSTRACT: High-throughput biological data analysis commonly involves identifying "interesting" features (e.g., genes, genomic regions, and proteins), whose values differ between two conditions, from numerous features measured simultaneously. The most widely-used criterion to ensure the analysis reliability is the false discovery rate (FDR). Existing bioinformatics […]
Associate Professor, UCLA Institute for Society and Genetics “TBD” Hosted by Paivi Pajukanta
TITLE: "Critical slowing down signals quasi-species extinction in an evolutionary model with environmental heterogeneity." ABSTRACT: Environmental heterogeneity can significantly affect the evolutionary dynamics of a population. A key parameter that determines the influence of heterogeneity is the migration rate--the rate at which organisms explore their heterogeneous environment. We study a model of a population which migrates between […]
