Under revision now
Input AA Sequences, each in new line: from Screen: 1000 per line max from DB: Bases Available: SWISS by ID from Heidelberg (SRS5) PIR by ID from Heidelberg (SRS5) SWISS by AC from Heidelberg (SRS5) PIR by AC from Heidelberg (SRS5) from File: File formats here.
Choose method: Weight Matrix Perceptron Linear Fisher Discriminant Neural Networks Error rate (NN) Learning rate (NN) Number of units Property Free energy of transfer to surface Surrounding hydrophobicity in alpha-helix Surrounding hydrophobicity in beta-sheet Surrounding hydrophobicity in beta-turn Accessibility reduction ratio Average number of surrounding residues Volume Local flexibility Flexibility Flexibility for no rigid neighbours Flexibility for one rigid neighbour Average accessibility surface area Flexibility for two rigid neighbours Hydrophobicity (Eisenberg et al.) Accessible surface area in the standard state Average accessible surface area in folded proteins Average surrounding hydrophobicity Hydrophilicity Hydropathy Hydrophilicity from HPLC Hydrophobicity (Jones) Refractivity Percentage of buried residues Normalized frequency of alpha-helix with weights Normalized frequency of beta-sheet with weights Normalized frequency for reverse turn with weights Percentage of exposed residues Hydrophobic index Hydrophobicity in folded form Hydrophobicity in unfolded form Hydrophobicity gain Polarity Average isotopic mass Isoelectric point pK of side chain Energy of transfer from water to ethanol kcal/mol Structural Chemical Functional Charge Hydrophobic
Generate NO sequences:
Number of NO sequences As random with relative frequencies of each aminoacid
A R N D C Q E G H I L K M F P S T V Y W
input from screen: Mixed inside seqs Mixed between seqs in cols Double mixed
Show Sequences in Generated code
See also Code Generation for proteins, Code Generation for nucleotids .
Authors: Vadim Valuev, Misha Ponomarenko, Anatoly Frolov Programming support: Dmitry Grigorovich Leader: Prof. N.A. Kolchanov
