ProSAT

PROtein reSidue Annotation Toolkit
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ProSAT Ranking & Summary

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  • Rating:
  • License:
  • Freeware
  • Publisher Name:
  • Huzefa Rangwala
  • Operating Systems:
  • Windows All
  • File Size:
  • 363 KB

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ProSAT Description

The ProSAT toolkit was developed to be a set of programs that allow building SVM based models for annotating amino acid residues in protein sequences using user supplied features (like PSI-BLAST profiles, or PSIPred profiles). In particular, the toolkit builds features using a window around the residue, and is equipped with a specialized kernel function (normalized second order exponential kernel function nsoe ) along with the standard svm kernel function. ProSAT_Learn is the program to learn "n" one-versus-rest classification models, where n are the possible number of annotations. It can also learn a support vector regression model to predict a floating point value. Usage ProSAT_Learn ProSAT_Predict is the program to predict the annotation for each residue from the built models, and output a L x n dimension profile, outputting the score from each of the n one-versus-rest SVM models for each amino acid residue and L is the length of the protein sequence. In case of a regression model, n =1. Usage ProSAT_Predict Input ProSAT_Predict has three required parameters: - test file: The test file provides the list of sequence features for which we need to predict the annotation profiles. It is similar to the input file used in ProSAT_Learn except it does not contain the names of the true annotation files, since we are predicting the same. - model file: The model file is the model file outputted by ProSAT_Learn - prediction file: The prediction file provides the path and the prefix of the output predictions in the form of annotation profiles. Output The output consists of a set of predicted annotations and profiles, which are nothing but the SVM predictions from each of the "num element" SVM models.


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