By: Raul Rodriguez Walter Checefsky (Added later)

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Presentation transcript:

By: Raul Rodriguez Walter Checefsky (Added later)

What is Orange? Python based tool for data-mining, developed by the Bioinformatics laboratory of the faculty of Computer and Information Science at the University of Ljubljana in Slovenia.

Why does Bioinformatics need this? Learn about the interaction of different genes Discover different methods of gene expression Learn the structure of proteins Find probable regions of protein encoding

What’s it do? Mainly well known for its Graphical User Interface (GUI) You can script in Python too

Which algorithms can it use? Decision trees (ID3, C4.5, CART) Naïve Bayes Instance Based Learning (kNN, ML-kNN) Function Based Learning (regression analysis(log,lin,lasso,PLS,trees,mean), ANN, SVM(libSVM,liblinear)) Ensemble Learning (bagging, AdaBoost, random forest) Hierarchical clustering (linkage-based) Partition Based Clustering (k-means, partition around medoids, fuzzy-c- means) ANN based clustering(self-organizing) Association Rules(Apriori(sparse, attr.-value)), apriori-SD)

Type of input? Tab delimited file Top row is: Features Type of data Meta information to describe features Data

Example Time!

Why isn’t it perfect? No Spatial Data Analysis No Time Series Analysis No Parallelization Only Naïve Bayes in the Bayes family Less algorithm options than other frameworks Locks you into python