Call for Papers Special Issue on Statistics and AISLADSStatistical Learning and Data Science01Aims and ScopeStatistical ...

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 ...

Our laboratory has developed a range of data analysis workflows that incorporate advanced statistical and computational methods to interpret the complex molecular datasets generated by MS technologies ...

Precision oncology exploits genomic, immunologic, and other biomarkers to drive discovery, drug development, and clinical care for patients with cancer. Precision oncology helps devise individualized ...

A new statistical method provides a more efficient way to uncover biologically meaningful changes in genomic data that span multiple conditions -- such as cell types or tissues. A new statistical ...

Approach developed at the Texas A&M School of Public Health offers promising new knowledge on idiopathic pulmonary fibrosis pathways Texas A&M University A new statistical technique developed by a ...

Various statistical forecasting methods exist designed for use with slow-moving products, new product introductions, stable mature products and products with erratic ...

What physicians should know about FDA's new proposed guidance ...

Finding a convincing explanation of a complex issue is no easy task. The decision about what qualifies as the "best" solution is inevitably subject to biases and approximations. Coupling statistics ...