Welcome to the Home Page of Meta-4mCpred

This is the first meta predictor for 4mC site prediction. In meta-4mCpred, we employed a feature representation learning scheme and generated 56 features based on four different ML (machine learning) algorithms and seven sequence-based feature encodings that cover diverse information, including compositional, physicochemical information, and nucleotide position-specific, etc. Consequently, these features were used as an input to support vector machine to build the meta-prediction models. For a given DNA sequence, Meta-4mCpred predicts its calss and probability values.

Paste or upload Caenorhabditis elegans DNA sequence below

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Sample FASTA sequences

>P1
CGTCATATTAAGCTTACTCTCTTACCAGCTTTTTTTACGAG
>P2
TGAGCTTATGACGGTAGAAGCATACCCCTTTATAAAACTCA
>P3
AAGAGCGCTTCATGTGTCACCATACTTTTGGCGCACCCTGT
>N1
TAGGCTAGATTCAAAAGTGACGTATGGAACTAGTTGATCTT
>N2
TGATAAAGTCCGCTCGATAGCGTTTCGGTTTTTAATCTGTC
>N3
AAGTTATCATGGGGAGGAAACGAAGAATGGAGAGAGGTACG