ProSATPROtein reSidue Annotation Toolkit | |
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ProSAT Ranking & Summary
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- License:
- Freeware
- Publisher Name:
- Huzefa Rangwala
- Operating Systems:
- Windows All
- File Size:
- 363 KB
ProSAT Tags
- annotation Annotation Plug-In Annotation SDK Annotation activex protein video annotation retrieve protein analyze protein compare protein PDF annotation geometric annotation semantic annotation chart annotation protein molecule annotation library annotation processor picture annotation lexical-cohesion annotation semi-automated annotation annotation listener RESTEasy annotation debugging symbol annotation annotation CLI text annotation create annotation protein identification Protein Synthesizer protein crystallization protein translocation protein list protein visualization sequence annotation annotation tool Number Annotation ruby annotation site annotation view annotation protein extraction annotation process Transcript Annotation protein structures refinement protein structure geometric protein features chromosomal annotation gene annotation Image annotation Assay annotation Assign Annotation code annotation audio annotation regulated protein valudation validate regulated protein Protein Viewer quadratic residue quadratic non residue residue Least quadratic non residue discourse annotation annotation mapper annotation analyzer intuitives annotation analyze protein database Protein Evolution Protein Test Drawing annotation protein dichroism protein structures data annotation ontology-based annotation Protein Residue Aminoacid Residue SVM Builder functional annotation cDNA Annotation System evaluate protein complex protein complex prediction view protein complex residue percent amino acid residue Protein Browser prepare structure annotation Brookhaven Protein Data Bank annotation editor view protein view protein file protein analyzer World Wind annotation display annotation make annotation place annotation map annotation annotation control view protein sequences protein sequences viewer nucleotide annotation simulate protein evolution protein evolution simulation align protein Visualize Protein MASCOT Protein Peak Annotation Protein Interaction render protein view protein files manage Protein DataBank protein vizualizer protein 3D structure annotation removal kodak annotation how to play xharbour activex XLS to dtd divx codec linux toshiba video controller karaoke songs for unfreeze 7.00.020.3172 zweckform cd label autocad 2008 down iso r773 pdf
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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