BioInfoPlus

Requirement

• NumPy
• Pandas
• Matplotlib
• Cython(Optional, for speeding up algorithms)

P.S:
Cython compiler requires a C++ compiler, and if you use Windows 8/8.1/10, please download VC++2017 Build Tools from Visual Studio 2017 Installer.
Next, find out where vcvarsall.bat is in your computer, finally, add its path into system environment PATH.

Get datas from bioinformation databases

use download/dsspGet.py.
see configurations at downloader/dsspPKU.json.

cd downloader && python dsspGet.py dsspPKU.json

Process datas into dataframes

from preprocess.BioParser import bio_parse
dataframe = bio_parse('./dssp/sources/1a00.dssp')
AA = dataframe.AA # amino acid
Structure = dataframe.STRUCTURE # secondary structure

Check the frequency distribution of specific known pattern

from research.n_gram import make_gram
from research.specific_regular import specific_report
cases = np.array([AA, Structure]).T
res =  [each_gram.T.flatten() for each_gram in make_gram(cases, 5)]
frequency = specific_report(res, {1:'A', 2:'A'})
print(frequency.values())

An example about biological sequence detection

• Codes

• 

Explanation:

c1 :
 ('V',  # 1-st amino acid.
  'A',  # 2-nd amino acid.
  'D',  # ...
  'A',  # ...
  'L',  # ...
  'H  X S+  ',  # 1-st secondary structure
  'H  X S+  ',  # ...
  'H  X S+  ',  # ...
  'H  X S+  ',  # ...
  'H  X S+  '   # 5-th secondary structure
  ),
c2 :
    ...

Analysis on big datasets composed by multiple data files

sources = ['./dssp/sources/1a00.dssp', 
           './dssp/sources/1a0a.dssp',
           './dssp/sources/1a0b.dssp',
           './dssp/sources/1a0c.dssp',
           './dssp/sources/1a0d.dssp']

from research.datasets_report import DatasetsReport
from research.plot import plot_frequency
whole = DatasetsReport(*sources).analyze(filtf=lambda probability, std, mean: probability>0.4)
number_of_dist = len(whole)

for test_some_case_dist in list(whole.keys())[:20]:
    plot_frequency(whole[test_some_case_dist])

Some figures have been output, however I have to put quite few ones here: