In continuum mechanics, the most commonly used measure of stress is the Cauchy stress tensor, often called simply the stress tensor or "true stress". However, several alternative measures of stress can be defined:[1][2][3]
The IMT School for Advanced Studies Lucca organizes an AFNI Bootcamp, as a satellite event of the upcoming Annual Meeting of the Organization for Human Brain Mapping (OHBM Rome 2019). The AFNI Bootcamp will be held in Lucca (Italy) on June 3-7, 2019. This is a course designed to teach
A new method for alignment of LC-MALDI-TOF data | Proteome Science | Full Text
Background In proteomics studies, liquid chromatography coupled to mass spectrometry (LC-MS) has proven to be a powerful technology to investigate differential expression of proteins/peptides that are characterized by their peak intensities, mass-to-charge ratio (m/z), and retention time (RT). The variable complexity of peptide mixtures and occasional drifts lead to substantial variations in m/z and RT dimensions. Thus, label-free differential protein expression studies by LC-MS technology require alignment with respect to both RT and m/z to ensure that same proteins/peptides are compared from multiple runs. Methods In this study, we propose a new strategy to align LC-MALDI-TOF data by combining quality threshold cluster analysis and support vector regression. Our method performs alignment on the basis of measurements in three dimensions (RT, m/z, intensity). Results and conclusions We demonstrate the suitability of our proposed method for alignment of LC-MALDI-TOF data through a previously published spike-in dataset and a new in-house generated spike-in dataset. A comparison of our method with other methods that utilize only RT and m/z dimensions reveals that the use of intensity measurements enhances alignment performance.
A Limited Memory Algorithm for Bound Constrained Optimization | SIAM Journal on Scientific Computing | Vol. 16, No. 5 | Society for Industrial and Applied Mathematics
A data driven approach to diagnosing and treating disease | Proceedings of the 20th ACM SIGKDD international conference on Knowledge discovery and data mining