organisation = "World Federation of Soft Computing (WFSC), European
Neural Network Society (ENNS), North American Fuzzy
Information Processing Society (NAFIPS), European
Society for Fuzzy Logic and Technology (EUSFLAT), and
International Fuzzy Systems Association (IFSA)",
publisher = "Springer",
keywords = "genetic algorithms, genetic programming,
Pharmaceutical applications, Drug design, Particle
swarm optimisation, Support vector machines",
old_abstract = "Pharmaceutical discovery and development is a cascade
of extremely complex and costly research encompassing
many facets from: therapeutic target identification and
bioinformatics study, candidate drug discovery and
optimisation to pre-clinical organism-level evaluations
and beyond to extensive clinical trials assessing
effectiveness and safety of new medicines. Machine
learning, in particular support vector machines SVM,
particle swarm optimisation PSO and genetic programming
GP, is increasingly used.",
abstract = "Machine learning tools, in particular support vector
machines (SVM), Particle Swarm Optimisation (PSO) and
Genetic Programming (GP), are increasingly used in
pharmaceuticals research and development. They are
inherently suitable for use with noisy, high
dimensional (many variables) data, as is commonly used
in cheminformatic (i.e. In silico screening),
bioinformatic (i.e. bio-marker studies, using DNA chip
data) and other types of drug research studies. These
aspects are demonstrated via review of their current
usage and future prospects in context with drug
discovery activities.",
notes = "http://www.cranfield.ac.uk/wsc10/ broken Original
conference title= WSC10: 10th Online World Conference
on Soft Computing in Industrial Applications
http://isxp1010c.sims.cranfield.ac.uk/Presentations/presentation196.pdf
broken slides (1Mbyte)
Revised following conference. Published 2006. See
link.springer.com for published version",