Abstract It is increasingly clear that machine learning algorithms need to be inte-grated in an iterative scientific discovery loop, in which data is queried repeatedly by means of inductive queries and where the computer provides guidance to the experiments that are being performed. In this chapter, we summarise several key challenges in achieving this integration of machine learning and data mining algo-rithms in methods for the discovery of Quantitative Structure Activity Relationships (QSARs). We introduce the concept of a robot scientist, in which all steps of the discovery process are automated; we discuss the representation of molecular data such that knowledge discovery tools can analyse it, and we discuss the adaptation of machine ...
The goal of quantitative structure activity relationship (QSAR) learning is to learn a function that...
Computational methods in medicinal chemistry facilitate drug discovery and design. In particular, ma...
In recent years, the field of quantitative structure–activity/property relationship (QSAR/QSPR) mode...
It is increasingly clear that machine learning algorithms need to be integrated in an iterative scie...
It is increasingly clear that machine learning algorithms need to be integrated in an iterative scie...
Summary: Early quantitative structure-activity relationship (QSAR) technologies have unsatisfactory ...
QSAR (quantitative structure-activity relationship) modeling is one of the well developed areas in d...
During the last decade non-linear machine-learning methods have gained popularity among QSAR modeler...
We explore two avenues where machine learning can help drug discovery: predictive models of in vivo ...
There are several approaches in trying to solve the Quantitative 1Structure-Activity Relationship (Q...
We investigate the learning of quantitative structure activity relationships (QSARs) as a case-study...
We investigate the learning of quantitative structure activity relationships (QSARs) as a case-study...
We investigate the learning of quantitative structure activity relationships (QSARs) as a case-study...
We propose a new boosting method that systematically combines graph mining and mathematical programm...
© The Author(s) 2019. The goal of quantitative structure activity relationship (QSAR) learning is to...
The goal of quantitative structure activity relationship (QSAR) learning is to learn a function that...
Computational methods in medicinal chemistry facilitate drug discovery and design. In particular, ma...
In recent years, the field of quantitative structure–activity/property relationship (QSAR/QSPR) mode...
It is increasingly clear that machine learning algorithms need to be integrated in an iterative scie...
It is increasingly clear that machine learning algorithms need to be integrated in an iterative scie...
Summary: Early quantitative structure-activity relationship (QSAR) technologies have unsatisfactory ...
QSAR (quantitative structure-activity relationship) modeling is one of the well developed areas in d...
During the last decade non-linear machine-learning methods have gained popularity among QSAR modeler...
We explore two avenues where machine learning can help drug discovery: predictive models of in vivo ...
There are several approaches in trying to solve the Quantitative 1Structure-Activity Relationship (Q...
We investigate the learning of quantitative structure activity relationships (QSARs) as a case-study...
We investigate the learning of quantitative structure activity relationships (QSARs) as a case-study...
We investigate the learning of quantitative structure activity relationships (QSARs) as a case-study...
We propose a new boosting method that systematically combines graph mining and mathematical programm...
© The Author(s) 2019. The goal of quantitative structure activity relationship (QSAR) learning is to...
The goal of quantitative structure activity relationship (QSAR) learning is to learn a function that...
Computational methods in medicinal chemistry facilitate drug discovery and design. In particular, ma...
In recent years, the field of quantitative structure–activity/property relationship (QSAR/QSPR) mode...