Open Source MATLAB Algorithms

detectMITE - a MATLAB-based tool for detecting miniature inverted repeat transposable elements (MITEs) in genomes. [1] Who are we? Please visit website: http://bioinfolab.miamioh.edu [2] How to cite detectMITE? Ye C, Ji G, Liang C (2016) detectMITE: A novel approach to detect miniature inverted repeat transposable elements in genomes. Sci. Rep. 6, 19688. http://www.nature.com/articles/srep19688 Ye C, Ji G, Li L, Liang C (2014) detectIR: A Novel Program for Detecting Perfect and Imperfect Inverted Repeats Using Complex Numbers and Vector Calculation. PLoS ONE 9(11): e113349. http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0113349 [3] detectMITE user manual Please visit the Wiki page of this website. [4] detectMITE Q&A For Q&A, please visit the Blog page of this website. [5] Update history To see the update history, go to https://sourceforge.net/p/detectmite/wiki/UpdateHistory/

ISAD is a peak detection software that detects individual (pre-)synaptic activity in microscopy images from neuronal cultures transfected with pHluorin. It computes synaptic signals from automatically segmented regions of interest and detects peaks that represent vesicle fusion events, thus, pre-synaptic activity. ISAD is based on MWA, which is a continuous wavelet transform based algorithm that employs multiple wavelets and is published as: Sokoll, S., Tönnies, K., and Heine, M. Detection of Spontaneous Vesicle Release at Individual Synapses Using Multiple Wavelets in a CWT-Based Algorithm. Med Image Comput Comput Assist Interv (MICCAI). 2012;15(Pt 1):165-72 ISAD is written in MATLAB and comes with a graphical user interface.

Online Signature Verification technology requires primarily a digitizing tablet and a special pen connected to the USB port of a computer. An individual can sign on the digitizing tablet using the special pen regardless of his signature size and position. The signature is characterized as pen-strokes consisting x-y coordinates and pressure with the data being stored in a signature database. Dynamic time warping (DTW) and quadratic discriminant analysis (QDA) is used to get results where the system accepts 2% of forged signatures and rejects 5% of true signatures

Wisconsin White Matter Hyperintensity Segmentation [W2MHS] and Quantification Toolbox is an open source MatLab toolbox designed for detecting and quantifying White Matter Hyperintensities (WMH) in Alzheimer’s and aging related neurological disorders. WMHs arise as bright regions on T2- weighted FLAIR images. They reflect comorbid neural injury or cerebral vascular disease burden. Their precise detection is of interest in Alzheimer’s disease (AD) with regard to its prognosis. Our toolbox provides a self-sufficient set of tools for segmenting these WMHs reliably and further quantifying their burden for down-processing studies.

detectIR - a MATLAB-based tool for detecting perfect and imperfect inverted repeats in genomes. [1] Who are we? Please visit website: http://bioinfolab.miamioh.edu [2] How to cite detectIR? Ye C, Ji G, Li L, Liang C (2014) detectIR: A Novel Program for Detecting Perfect and Imperfect Inverted Repeats Using Complex Numbers and Vector Calculation. PLoS ONE 9(11): e113349. http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0113349 [3] detectIR user manual Please visit the Wiki page of this website. [4] detectIR Q&A For Q&A, please visit the Blog page of this website. [5] detectIR bug report You can report a bug as a Ticket request, or start a topic session in the Discussion webpage of this website. [6] Update history To see the update history, go to https://sourceforge.net/p/detectir/wiki/Update%20History/