A.thaliana: 4mCPred_I_A.thaliana , 4mCPred_II_A.thaliana
C.elegans: 4mCPred_I_C.elegans , 4mCPred_II_C.elegans
D.melanogaster: 4mCPred_I_D.melanogaster , 4mCPred_II_D.melanogaster
E.coli: 4mCPred_I_E.coli , 4mCPred_II_E.coli
G.subterraneus: 4mCPred_I_G.subterraneus , 4mCPred_II_G.subterraneus
G.pickeringii: 4mCPred_I_G.pickeringii , 4mCPred_II_G.pickeringii
To maximize the user’s convenience, a step-by-step guide has been provided blow for how to use 4mCPred:
Step 1. Select the corresponding species and model.
Step 2. Paste the query DNA sequences into the input box. The input sequence should be in FASTA format. For the example of DNA sequences in FASTA format, click the FASTA format button top above the input box.
(To recognize the category of cytosine in one input DNA sequence, the window length of 41 was employed to extract sequence fragments centering at this cytosine site as well as containing 20 upstream and 20 downstream flanking nucleotides.)
Step 3. Click on the Submit button to see the predicted result.
(If the prediction result of a cytosine site is positive, its output is ‘4mC’. Otherwise, its output is ‘non-4mC’.)
Step 4. Click on the DataSet button to download the benchmark dataset.
Step 5. Click on the Contact button to contact us.
If you think 4mCPred is useful, please kindly cite the following paper:
4mCPred: Machine Learning Methods for DNA N4-methylcytosine sites Prediction.