November 8, 2021
November 1, 2021
November 28, 2021
November 21, 2021
December 6, 2021
December 10, 2021
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.
Molecular epidemiology is an integrative scientific discipline that relates the molecular underpinnings of biological processes and environmental risk factors to the etiology, spread, and prevention of disease in human populations. Over the years, molecular epidemiology has become extensively fused with mathematical and computational science and has benefited immensely from this tight association. This workshop serves as a forum to review and discuss the latest advances in the application of mathematical and computational approaches to molecular epidemiology.
The immune system is one of the most complex biological systems in mammals, comprising dozens of cell types that dynamically modulate their internal molecular states and engage in complex intercellular interactions via hundreds of immune receptors and signaling molecules across multiple anatomic locations. Recent advances in high-throughput profiling technologies are driving a shift towards context driven integrative computational models and algorithms to study immune system responses in both health and disease. The goal of the ASI workshop is to bring together a diverse group of researchers - including bioinformaticians, biotechnologists, clinicians, computer and data scientists, immunologists, and statisticians - to discuss the latest computational advances in systems immunology and foster the development of novel multidisciplinary approaches in this field.
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