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iqspr (version 2.3)

Inverse Molecular Design

Description

Autonomous generation of novel organic compounds with target physicochemical properties initially constrained by the user. This package has the ambition to become an unavoidable tool in the innovation of novel materials and/or drugs with specific target properties.

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Version

Install

install.packages('iqspr')

Monthly Downloads

32

Version

2.3

License

MIT + file LICENSE

Last Published

August 1st, 2017

Functions in iqspr (2.3)

QSPRpred-class

QSPRpred class
SmcChem-class

SMILES generator
get_descriptors

get a list of the available descriptors types
get_linearBayes

get the computation of parameters issued from the training of a Bayesian linear regression
ENgram-class

Extended N-gram model for learning SMILES strings
Esmi-class

Extend smi class
use_linearBayes

get the prediction from a Bayesian linear regression
viewstr

view 2D structures from SMILES string vector
get_Model

construct a given regression model thanks to a training set
get_Model_params

get a list of default parameters for a given regression algorithm
get_Models

get a list of the implemented regression algorithms
get_descriptor

get a descriptor (fingerprints and/or CDK physical descriptors) from SMILES strings
dpred

Table of 372 SMILES with predicted internal energy E and HOMO-LUMO gap
engram_5k

n-grams model learned from 5,000 SMILES from PubChem
predinit

Table of predicted internal energy E and HOMO-LUMO gap for the phenol
genENgram

generate SMILES strings from extended N-gram model
gensmis

Table of 372 SMILES with associated QSPRScore
get_targetzone

get a targeted zone
predictions

List of predictions associated to the internal energy E and HOMO-LUMO gap of 500 SMILES
trainedSMI

List of 5,000 SMILES used for training the n-grams model
use_Model

get the prediction from a given model
qspr.data

Table of 16,674 SMILES with associated internal energy E and HOMO-LUMO gap