iqspr (version 1.1)

QSPRpred-class: QSPRpredictor class

Description

QSPR model construction using the Bayesian linear regression model.

Fields

ymin

vector representing minimal value in each target property

ymax

vector representing maximum value in each target property

descriptor

function transforming SMILES strings into numeric vector (matrix)

fpnames

name of fingerprint used in a predictor

Methods

initialize(smis = NULL, y = NULL, v_ymin = NULL, v_ymax = NULL, v_descriptor = NULL, v_fpnames = NULL, w0 = NULL, V0_inv = NULL, a0 = NULL, b0 = NULL)

initialize the QSPR predictor

inverse_predx(smis = NULL, temp = 1)

Inverse QSPR prediction of input SMILES strings smis for target property range

qspr_predx(smis = NULL)

QSPR prediction of input SMILES strings smis

set_targety(v_ymin, v_ymax)

set the target propety range

Examples

# NOT RUN {
data(qspr.data)
smis <- paste(qspr.data[,1])
ty <- qspr.data[,c(2,5)]
trainidx <- sample(1:nrow(qspr.data), 5000)
testidx <- (1:nrow(qspr.data))[-trainidx][1:100]

data(qsprpred_EG_5k) 
## same as run => qsprpred_EG_5k <- 

#-----arguments
#smis: SMILES string set (character vector) for training
#y: property sets (matrix) for training  
#v_ymin: minimum value of target properties
#v_ymax: maximum value of target properties
#v_descriptor: function transforming SMILES strings to feature matrix 
#v_fpnames: character vectors indicating finger print used in the descriptor
#w0: matrix representing prior mean of coeffients in linear regression model
#V0_inv: matrix representing the prior variance of coeffients in linear regression model
#a0: numeric value representing the location parameter in gamma prior 
#b0: numeric value representing the shape parameter in gamma prior 
#------

predictions <- qsprpred_EG_5k$qspr_predx(smis[testidx])  
par(mfrow=c(1,2))
plot(predictions[[1]][1,], ty[testidx,1])
plot(predictions[[1]][2,], ty[testidx,2])

#computing the probability which the properties of test structures is in the target range  
# set the minimal values in 2-d target properties
qsprpred_EG_5k$ymin <- c(100, 4)
# set the maximum values in 2-d target properties
qsprpred_EG_5k$ymin <- c(200, 5.5) 
# method inverse_predx returns the probability that input SMILES has property in target range
qsprpred_EG_5k$inverse_predx("c1ccccc1O")
# }