Finding motifs using kohonen's neural network (self-organized map)
Karbownik Patrycja https://github.com/PatrycjaKarbownik
Aksamit Sebastian https://github.com/Temebe
Grabowski Kamil https://github.com/Nestus97
Create neural network, which finds motifs from DNA sequences.
python3 sequence_motifs.py <FILE_NAME> <SEQ_SIZE> <MAX_ERROR> <MIN_SEQUENCES> [<OPTIONAL_PARAMETERS>]
| Flags | Parameters | Meaning | Default value |
|---|---|---|---|
| - | <FILE_NAME>, file has to be in "data" folder |
Name of file with sequences. | - |
| - | <SEQ_SIZE>, integer number |
Number of nucleotides in finding motifs | - |
| - | <MAX_ERROR>, integer number |
Maximum number of differences between two sequences that can be considered as the same motif. | - |
| - | <MIN_SEQUENCES>, integer number |
Minimum number of sequences that can be classified as motif | - |
| -h --help |
- | Shows help | - |
| -l --layers_amount |
<integer_number>, minimal value: 2 |
Number of layers of neural network (more of them means faster work and more diverse results). It has to be at least 2 | 4 |
| -t --thresholds |
<numbers_from_0_to_1>, separated by comma. there have to be one less than there is layers, they also should be in ascending order |
Thresholds value for each layer of neural network - determine minimal similarity between sequence and motif | From 0.2 to 0.65, linear growth |
e.g.
python3 sequence_motifs.py "data1.txt" 5 3 5 4 0.2 0.4
python3 sequence_motifs.py "data1.txt" 7 4 3 5 0.4 0.6 0.8
python3 sequence_motifs.py "data3.txt" 13 6 5 5 0.1 0.35 0.5 0.6 0.7
python3 sequence_motifs.py "data3.txt" 15 2 4