Predicts culturing conditions of methanogens using random forests and n-gram analysis. MethanoGram is trained using data from PhyMet2, a database of the methanogenic bacteria.
Usage: upload 16S rRNA nucleotide sequences of unknown methanogens and press the “Submit” button. Sequences may be submitted directly or as .fasta files. Consult the Mean error panel to see results of the jackknife test.
For more information consult the manual.
Restrictions:
Author: Michal Burdukiewicz.
Example 16S rRNA sequences:
>Methanocorpusculum labreanum, 16S ribosomal RNA aaaatagtaattctggttgatcctgccagaggccattgctatcagggtttgactaagccatgcgagtcgagaggtgtaagacctcggcatactgctcagtaacacgtggttaacctgccctaaggtggagaatactcccgggaaactggggctaatgctccatagtggatatgtcctggaatggtatatcctcgaaagatccgtcgccttaggatgggactgcgtccgattaggttgttggcggggtaacggcccaccaagccttttatcggtacgggttgtgggagcaagatcccggagatggattctgagacatgaatccaggccctacggggcgcagcaggcgcgcaaactttacaatgcgagcaatcgtgataaggaaaccctgagtgcctgtcgatgcaggctgttcatatatctaaatcatatgtgaagaaagggcagggcaagaccggtgccagccgccgcggtaataccggctgctcgagtgatggccactattactgggtttaaagcgtccgtagcttgactgttaggtctcttgggaaatcttcgcgctcaacgtgaaggcgtctaagagataccggcagtcttggaactgggagaggtaaaccgtacttcgggggtaggagtgaaatcttgtaatcctcgagggacgacctatggcgaaggcagtttaccagaacagcttcgacagtgagggacgaaagctgggggagcaaacgggattagataccccggtagtcccagccgtaaacaatgtgcgttaggtgtgtcggtaaccacgtgttactgatgcgccgaagagaaatcgtgaaacgcaccacctgggaagtacggtcgcaaggctgaaacttaaaggaattggcgggggagcaccacaacaggtggagcctgcggtttaattggattcaacgccggacatctcaccggataagacagctgaatgattgtcaatctgaaggttttacatgactagctgagaggaggtgcatggccgtcgtcagttcgtactgtgaagcatcctgttaagtcaggcaacgagcgagacccacgccgacaattgccagcagcatctccggatggctggggacattgtcgggaccgcctctgctaaaggggaggaaggaatgggcaacggtaggtcagcatgccccgaattatccgggctacacgcgggctacaatggacgggacaatgggtaacaacaccgaaaggtgcagtcaatctccgaaccccgcccttagttaggattgcgggttgcaactcacccgcatgaatctggaatctgtagtaatcgcgtttcactatagcgcggtgaatacgtccctgctccttgcacacaccgcccgtcaaaccatcctagtggggtttggatgagtccctggtctttgccggggtcgaatctaggttccgtgaggagggttaagtcgtaacaaggtagccgtaggggaatctgcggctggatcacctcctaaa >Methanocaldococcus infernus, 16S ribosomal RNA tttccggttgatcctgccggaggccactgctatcggggtccgattaagccatgcgagtcaaggggctccccttttggggagcaccggcgaacggctcagtaacacgtggctaacctaccctcgggtgggggataacctcgggaaactgaggttaatcccccataggggaggaggtttggaatgatccctccccgaaagcccgtaagggcgcccgaggatggggctgcggcggattaggtagttggtggggtaacggcccaccaagcctacgatccgtacgggccctgagagggggagcccggagatggacactgagacacgggtccaggccctacggggcgcagcaggcgcgaaacctccgcaatgcgcgaaagcgcgacggggggaccccgagtgccctccctttgggagggcttttccggagtgtaaacagctccgggaataagggctgggcaagtccggtgccagcagccgcggtaataccggcggcccaagtggtggccactgttattgggcctaaagcgtccgtagccggcccggtaagtccctgcttaaatcccgcggcttaaccgcggggctggcagggatactgccgggctagggaccgggagaggccgggggtaccccaggggtagcggtgaaatgcgttgatccctgggggaccacctgtggcgaaggcgcccggctggaacgggtccgacggtgagggacgaaggccgggggagcaaaccggattagatacccgggtagtcccggctgtaaactctgcggactaggtgtcgcgtgcccttcgggggcacgcggtgccgaagggaagccgttaagtccgccgcctggggagtacggtcgcaagactgaaacttaaaggaattggcgggggagcactacaacgggtggagcctgcggtttaattggattcaacgccgggaatctcaccaggggcgacggcaggatgaaggccaggttgacgaccttgccagacgcgccgagaggtggtgcatggccgtcgtcagctcgtaccgtgaggcgtcctgttaagtcaggtaacgagcgagacccgtgccccatgttgccatcctcccctccgggggaggggcactcatgggggaccgcctccgctaaggaggaggaaggtgcgggcaacgacaggtccgcatgccccgaatcccctgggctacacgcgggctacaatggccgggacaatgggatgcgaccccgaaagggggagctaatcccctaaacccggtcgtagtccggatcgagggctgtaactcgccctcgtgaagccggaatccgtagtaatcgcgcctcaccatggcgcggtgaatgcgtccctgctccttgcacacaccgcccgtcacgccacccgagtcgagcccangtgaggcccatccgcaagggtggggtcgaacctgggttgcgaaggggg