Protein Feature Extraction for Machine Learning
Python code to extract features from Protein sequences for Machine Learning/Deep Learning
Protein feature extraction is carried out using Biopython package
**Features inculde:
- AA-count
- aromaticity
- secondary_structure_fraction
- isoelectric_point
- molecular_weight
- instability_index
Packages required (other than built-in) for the execution of code... -Pandas -pickle -Biopython -subprocess
Installation
For windows
pip install discere
For linux
pip3 install discere
Usage
import discere.discere as di
di.extract_feature('./Documents/positive_training.fasta',
'./Documents/negative_training.fasta',
'./Documents')
output
1 maintainer
Release files for discere 0.0.4
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| discere-0.0.4.tar.gz | 5.0 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| discere-0.0.4-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 11.1 kB
Release files / discere-0.0.4.tar.gz
| Download URL | discere-0.0.4.tar.gz |
|---|---|
| Size | 5.0 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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twine/3.0.0 pkginfo/1.5.0.1 requests/2.22.0 setuptools/41.6.0 requests-toolbelt/0.9.1 tqdm/4.38.0 CPython/3.6.8
|
Release files / discere-0.0.4-py3-none-any.whl
| Download URL | discere-0.0.4-py3-none-any.whl |
|---|---|
| Size | 6.1 kB |
| Tags | Python 3 |
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SHA-256 checksum How to use checksums |
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| Uploaded via |
twine/3.0.0 pkginfo/1.5.0.1 requests/2.22.0 setuptools/41.6.0 requests-toolbelt/0.9.1 tqdm/4.38.0 CPython/3.6.8
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