将printprint(ppi.scorePPITreesP(proteinsA, proteinsB))的结果导入到excel表格中
import numpy as np
from matplotlib import pyplot as plt
import PPI as ppi
from sklearn import manifold
# Fanconia Anemia proteins files, D2.fasta, L.fasta,
# shall exist in the sub-folder ./PPIData. These files contain the corresponding protein sequences from Fanconia Anemia
proteinNames = ['FANCE1020_1080', 'FANCD21_60', 'FANCD260_120']
n = len(proteinNames)
n = len(proteinNames)
distM = np.zeros([n, n])
distV = []
for i in range(0, n):
nameA = proteinNames[i]
proteinsA = ppi.getAllSequences(nameA) # The Fanconi Anemia file: one file contain the same protein for different geneomes
print(nameA, len(proteinsA))
for j in range(0, n):
nameB = proteinNames[j]
proteinsB = ppi.getAllSequences(nameB)
print(nameB, len(proteinsB))
dist = 1 - ppi.scorePPITreesP(proteinsA, proteinsB)
distV.append(dist)
distM[i, j] = dist
print(nameA, nameB, dist)
print(ppi.scorePPITreesP(proteinsA, proteinsB))
print(distM)
print()