HIGH DIMENSIONAL DATA ANALYSIS METHODS SOFTWARE

2) Use mouse to drag square areas of cancer and noncancer. Another great convenience is the mutual response between the ion image and the spectrum figure.ДЎ6 IMSmining Work flow: 1) Import the training data and select one algorithm. Users can directly select an area of pixels from the ion image as the training data sets, choose the data sets for testing or classification from folders, and export data sets, mean spectrum, selected m/z list for later usage. The graphical user interface is very friendly and convenient. Statistical algorithm selections include PCA+SVM/LDA, EN/WEN, SPCA+SVM/LDA. 2) Biomarkers selection and classification. It contains the following functions: 1) Data visualization User can view the spectrum of a single pixel, the average spectrum of an area and intensity distribution matrix at a fixed m/z value.

HIGH DIMENSIONAL DATA ANALYSIS METHODS SOFTWARE

MS/IMS Data Processing MS Data Preprocessing with Shuo Chen and Yu Shyr IMS Data Biomarker Discovery and Classification with FQ Zhang and Lu Xiong IMSmining Software Development with JS Liang, FQ Zhang, and JC ZouДЎ5 IMSmining Software Package IMSmining is a newly developed software package by our research group for IMS data processing using statistical methods. Then, fmri data can be measured at voxel by voxel, with a voxel representing a three dimensional cube unit inside the whole brain.ДЎ1 The fmri Data Cube is of HSI Type ДЎ2 Important Characteristics and Challenges in HSI Type Data Processing Data sets are very high dimensional Many challenges in data processing and data analysis: data preprocessing, dimension reduction, spatial information incorporation for feature selection and pattern recognition Requiring interdisciplinary collaboration Advanced mathematical tools and statistical techniques can not only provide significance analysis of experimental data sets but also can help in finding new data features/patterns, guiding biological experiments designs, as well as leading computational tools development.ДЎ3 Important Characteristics and Challenges in HSI Type Medical Data Processing Different from typical image processing emphasis, in HSI type medical data processing, we concentrate on the following 4Cs Content of biology Contrast between groups such as normal data and cancer data Characteristic/feature/biomarker discovery Classification accuracy improvementДЎ4 I. The main principle of fmri is using the difference of blood oxygenation level dependent (BOLD) to observe the local changes of deoxyhemoglobin concentration in the brain vasculature. Reflecting the fundamental importance and applicability of MRI in medicine, Paul Lauterbur of the University of Illinois at Urbana-Champaign and Sir Peter Mansfield of the University of Nottingham were awarded the 2003 Nobel Prize in Medicine for their 'discoveries concerning magnetic resonance imaging'.ДЎ0 fmri Functional magnetic resonance imaging or functional MRI (fmri) is an MRI procedure that measures brain activity by detecting associated changes in blood flow. et al Imaging Mass Spectrometry Based Exploration of Biochemical Tissue Composition using Peak Intensity Weighted PCA.Д§ MALDI-TOF Mass spectra for each x,y coordinate Single m/z value MALDI-TOF MS technique was awarded the 2002 Nobel Prize in ChemistryДЁ IMS Proteomic Cancer Data (mass to-charge) Zhang and Hong, Statistics in Medicine, 30 (2011),Д© Example-2: MRI fmri Magnetic resonance imaging (MRI), different from computed tomography (CT) or X-rays, can visualize internal structures of the body in detail, provide good contrast between the different soft tissues of the body, and thus, become very useful in imaging the brain, muscles, the heart, and cancers. April 16-17, 2015Дў Outline Hyper-spectral imaging type data: IMS and fmri Challenges in HSI type data processing Software package for IMS: IMSmining Markov random fields for IMS and Fusion IMS & Micoscopy GLM, probabilistic group ICA and Multi-task learning for fmri data analysisДЈ HSI Data Hyperspectral images: images produced by imaging spectrometers unlike conventional color cameras that only capture light in just RGB three spectral windows, hyperspectral cameras can capture an entire section of the electromagnetic spectrum at every pixel and collect high resolution spectral detail over a large spatial and broad wavelength region.ДҐ Hyperspectral Imaging (HSI) Type: IMS and fmri Data Cubes Spectral Spatial Medical/biological specificsД¦ Example-1: Imaging Mass Spectrometry (IMS) Data Plas R. 1 High Dimensional Data Analysis with Applications in IMS and fmri Processing Don Hong Department of Mathematical Sciences Center for Computational Sciences Middle Tennessee State University Murfreesboro, Tennessee, USA 1st Annual Workshop on Data Sciences (AWDS 2015), Tennessee State University Nashville, TN.

High dimensional data analysis methods