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Activity Number: 480 - Novel Statistical Methods for Bioinformatics and Computational Biology
Type: Invited
Date/Time: Wednesday, July 31, 2019 : 10:30 AM to 12:20 PM
Sponsor: Section on Statistics in Genomics and Genetics
Abstract #300084
Title: B-Scaling: A Novel Nonparametric Data Fusion Method
Author(s): Yiwen Liu and Xiaoxiao Sun* and Wenxuan Zhong and Bing Li
Companies: University of Arizona and University of Arizona and University of Georgia and The Pennsylvania State University
Keywords: data fusion; b-spline; epigenetic landscape

With the rapid advancement in science and technology, the proliferation of large-scale data with various types and formats has been growing at an unprecedented rate. Each of these distinct data types provides a different but complementary view of the corresponding scientific problem, which makes systematic integration an essential component in many fields of science. Despite the need for powerful and advanced integrative analysis strategies, it still lacks the coherent statistical framework for data integration. In this talk, I will introduce a novel and unified framework for data integration. In the proposed framework, we observe multiple measurements that measure the same underlying quantity through some linear or nonlinear ways. We seek to find a fused measurement, which is a scalar representation of those observed measurements and highly correlated with the underlying quantity. We also established the asymptotic property of the fused measurement and integrated multiple histone modifications and DNA methylation levels to jointly characterize epigenetic activeness.

Authors who are presenting talks have a * after their name.

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