mSplicer Tool to improve the C. elegans genome annotation using machine learning
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predict genome splice splice prediction genome splicer genome annotation

mSplicer Description

Tool to improve the C. elegans genome annotation using machine learning Training the mSplicer tool will involve solving a relatively large linear optimization problem, implemented in MATLAB using the CPLEX optimization package. mSplicer is based on Python scripts that call methods implemented in C++ for predicting splice sites using Support Vector Machines and Dynamic Programming for splice form prediction. These routines are part of the freely available Shogun toolbox for large scale kernel learning. Requirements: · Shogun 0.6.2 or later · Python

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