October 22, 2020
October 15, 2020
October 1, 2020
November 22, 2020
November 15, 2020
October 31, 2020
November 30, 2020
November 15, 2020
November 30, 2020
November 15, 2020
Massively parallel DNA and RNA sequencing have become widely available, reducing the cost by several orders of magnitude and placing the capacity to generate gigabases to terabases of sequence data into the hands of individual investigators. These next-generation technologies have the potential to dramatically accelerate biological and biomedical research by enabling the comprehensive analysis of genomes and transcriptomes to become inexpensive, routine and widespread. The exploding volume of data has spurred the development of novel algorithmic approaches for primary analyses of sequence data in such areas as error correction, de novo genome assembly, novel transcript discovery, virus quasispecies assembly, etc. This workshop will bring together specialists to discuss the various mathematical and computational challenges presented by next-generation sequencing technologies.
Recent technological advances have enabled high-throughput profiling of genomes, transcriptomes, epigenomes, and proteomes at single cell resolution. These revolutionary single-cell-omics technologies promise to bring unprecedented insights into tissue heterogeneity and unveil subtle regulatory processes that are undetectable by bulk sample analysis. However, fully realizing their potential requires the development of novel computational and statistical analysis methods capable of handling the massive data sizes and significant levels of technical and biological noise. The goal of this workshop is to bring together bioinformaticians, biologists, computer/data scientists, and statisticians to discuss the latest developments in computing infrastructure, mathematical and statistical modeling, algorithms, and visualization methods for single-cell-omics data.
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