The PCP-ML contains a number of functions that are commonly used when performing ML tasks with proteins.PCP-ML has three principle components: Parsers, Characterizers and Encodes and Writers. The parsers extract commonly used data from the output of programs such as PSIPred and DSSP. Characterizers and Encoders convert this data into forms which are meaningful in ML methods. There are also a number of characterizers provide numerical representations of hydrophobicity, contact potentials, etc. The writers format and output the generated features so as to be compatible with ML programs (e.g., SVMlight).
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BMC Res Notes. 2014 Nov 18;7:810. doi: 10.1186/1756-0500-7-810.
PCP-ML: protein characterization package for machine learning.
Eickholt J1, Wang Z.