Bioinformatics Toolbox

Graph Theory, Statistical Learning, and Gene Ontology

Graph Theory and Visualization

Bioinformatics Toolbox enables you to apply basic graph theory to sparse matrices. You can create, view, and manipulate graphs such as interaction maps, hierarchy plots, and pathways. You can determine and view shortest paths in graphs, test for cycles in directed graphs, and find isomorphism between two graphs.

Statistical Learning and Visualization

Bioinformatics Toolbox provides functions that build on the classification and statistical learning algorithms in Statistics Toolbox, including:

  • Support vector machine (SVM) and K-nearest neighbor classifiers
  • Functions for setting up cross-validation experiments and measuring the performance of different classification methods
  • Interactive tools for feature selection, mapping, and displaying hierarchy plots and pathways

Gene Ontology

Bioinformatics Toolbox enables you to access the Gene Ontology database from within MATLAB®, parse gene ontology annotated files, and obtain subsets of the ontology such as ancestors, descendants, or relatives.

Next: Sequence Analysis

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Data Mining in ambiente MATLAB

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