To load some SAMPLE DATA click here: More sample training data:
Use this option if you previously trained a NNAlign model (Example) and wish to use it for predictions on evaluation data
Job name
Motif length
Order of the data High values are positive instances Low values are positive instances
Data rescaling Linear rescale Log-transform No rescale
Average target values of identical sequences
Folds for cross-validation No CV 3 4 5 6 7 8 9 10
Perform nested cross-validation
Stop training on best test-set performance
Method to create subsets Random subsets Homology clustering Common-motif clustering User-defined partitions
Threshold for homology clustering
Maximum overlap for common motif
Remove homologous sequences from training set
Alphabet
Number of training cycles
Number of seeds
Number of hidden neurons
Amino acid encoding Sparse Blosum Combined
Maximum length for Deletions
Maximum length for Insertions
Only allow insertions in sequences shorter than the motif length
Burn-in period
Impose amino acid preference at P1 during burn-in
Preferred residues at P1
Length of the PFR for composition encoding
Encode PFR composition as sparse
Encode PFR length
Expected peptide length for encoding
Binned peptide length encoding
Load receptor pseudo-sequences Example
Number of networks (per fold) in the final network ensemble
Sort results by prediction value
Exclude offset correction
Show all logos in the final ensemble
Length of peptides generated from FASTA entries
Sort evaluation results by prediction value
Threshold on evaluation set predictions
Confidentiality: The sequences are kept confidential and will be deleted after processing.
For publication of results, please cite: