OpenFace

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/ MATLAB-basedVector CalculationComplex Numbers

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/ MATLAB-basedVector Calculation

K-Level 2.0 is a Matlab application for performing adjustment of leveling network. The adjustment process is based on the least square method. K-Level can perform unweighted or weighted adjustment. User interface was designed in tabular style. Users can directly input, edit, display the data and results, and summary in all-in-one window. Generate ReportRead data files

Function 1. classifier_knn 2. accuracy_knn 1. Returns the estimated label of one test instance, the k nearest training instances, the k nearest training labels and creates a chart circulating the nearest training instances (chart 2-D of the first two features of each instance). 2. Returns the estimated labels of one or multiple test instances and the accuracy of the estimates.