BAGO
Get Started
Backgrounds
With A Jupyter Notebook
With A Windows Software
Encodings
Applications
BAGO Functions
MS data (object)
Read MS data
Generate second gradient
Find top signals
Compute Separation Efficiency
Get BPC
Plot BPC
Spectral similarity
Get unique MS2 spectra
Get unique m/z
Get mobile phase percentage
Output gradient
Gaussian process regression (object)
Gaussian process regression fitting
Generate search space
Compute next gradient
Update model
Acquisition functions
BAGO
Index
Index
B
|
C
|
D
|
E
|
F
|
G
|
O
|
P
|
R
|
S
|
U
B
built-in function
computeNextGradient()
computeSecondGradient()
dotProd()
extractMS1()
extractMS2()
findTopSignals()
fit()
genSearchSpace()
getBPCData()
getMobilePhasePct()
getUniqueMS2()
getUniqueMz()
outputConfig()
plotBPC()
readRawData()
sepEfficiency()
updateModel()
C
computeNextGradient()
built-in function
computeSecondGradient()
built-in function
D
dotProd()
built-in function
E
extractMS1()
built-in function
extractMS2()
built-in function
F
findTopSignals()
built-in function
fit()
built-in function
G
genSearchSpace()
built-in function
getBPCData()
built-in function
getMobilePhasePct()
built-in function
getUniqueMS2()
built-in function
getUniqueMz()
built-in function
O
outputConfig()
built-in function
P
plotBPC()
built-in function
R
readRawData()
built-in function
S
sepEfficiency()
built-in function
U
updateModel()
built-in function