High-dimensional -omics data such as genomic, transcriptomic, and metabolomic data offer great promise in advancing precision medicine. In particular, such data have enabled the investigation of ...

A deep learning framework combines convolutional and bidirectional recurrent networks to improve protein function prediction from genomic ...

The volumes of genetic, biodiversity, and environmental data that can be obtained from individual studies are growing at an impressive rate, as are the public repositories sharing these data. Such ...

An interdisciplinary team of University of Tennessee, Knoxville researchers recently published in Biophysical Journal on their development of a new statistical method that improves analysis in ...

This course is compulsory on the MSc in Data Science, MSc in Health Data Science and MSc in Operations Research & Analytics. This course is available with permission as an outside option to students ...

Members of the university community are invited to participate in a workshop on "Modern Methods for Data Analysis" from Monday, Jan. 11 through Friday, Jan. 15, from 10 a.m. to noon (EST). The ...

This course focuses on experimental design and applied statistical methods for data analysis. Students will learn how to design and interpret experiments considering multiple variables, avoiding ...

The Statistical & Data Sciences (SDS) Program links faculty and students from across the college interested in learning things from data. At Smith, students learn statistics by doing—class time ...

When you use the statistical analysis features in Excel, you are leveraging one of the most powerful tools available for data manipulation and interpretation. Excel is not just a spreadsheet ...