Difference between revisions of "Sequence-based predictions HEXA"
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== Prediction of disordered regions == |
== Prediction of disordered regions == |
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| + | * DISOPRED |
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| + | Authors: Ward JJ, Sodhi JS, McGuffin LJ, Buxton BF, Jones DT. |
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| + | Year: 2004 |
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| + | Source: [[http://www.ncbi.nlm.nih.gov/pubmed/15019783 Prediction and functional analysis of native disorder in proteins from the three kingdoms of life.]] |
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| + | Description: |
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| + | This method is based on a neuronal network which was trained on high resolution X-ray structures from PDB. Disordered regions are regions, which appears in the sequence record, but their electrons are missing from electronic density map. This approach can also failed, because missing electrons can also arise because of the cristallization process. |
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| + | The method runs first a PsiBlast search against a filtered sequence database. Next, a profile for each residue is calculated and classified by using the trained neuronal network. |
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| + | Prediction: |
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| + | As a prediction result you get a file with the predicted disordered region, the precision and recall. Furthermore you can a more detailed output. There you see the sequence, and the predictions and also numbers above the sequence (from 0 to 9 which shows you how likly your prediction is) |
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| + | Input: |
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| + | If you run disopred on the console, you have to define the location of your database. The program needs as input your sequence in a file with fasta format. |
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== Prediction of transmembrane alpha-helices and signal peptides == |
== Prediction of transmembrane alpha-helices and signal peptides == |
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Revision as of 16:35, 26 May 2011
Contents
General Information
Secondary Structure prediction
Prediction of disordered regions
- DISOPRED
Authors: Ward JJ, Sodhi JS, McGuffin LJ, Buxton BF, Jones DT. Year: 2004 Source: [Prediction and functional analysis of native disorder in proteins from the three kingdoms of life.]
Description: This method is based on a neuronal network which was trained on high resolution X-ray structures from PDB. Disordered regions are regions, which appears in the sequence record, but their electrons are missing from electronic density map. This approach can also failed, because missing electrons can also arise because of the cristallization process. The method runs first a PsiBlast search against a filtered sequence database. Next, a profile for each residue is calculated and classified by using the trained neuronal network.
Prediction: As a prediction result you get a file with the predicted disordered region, the precision and recall. Furthermore you can a more detailed output. There you see the sequence, and the predictions and also numbers above the sequence (from 0 to 9 which shows you how likly your prediction is)
Input: If you run disopred on the console, you have to define the location of your database. The program needs as input your sequence in a file with fasta format.
