Recent developments in chemoinformatics education

Chemoinformatics techniques are increasingly being used to analyse the huge volumes of chemical and biological data resulting from combinatorial synthesis and high-throughput screening programmes. Scientists with both the chemical and the computing skills required to carry out such analyses are currently in very short supply, this resulting in the establishment of MSc programmes for the training of chemoinformatics specialists

A method for computing chemical-equilibrium compositions of reacting-gas mixtures by reduction to a single iteration equation

Computing equilibrium chemical composition and thermodynamic properties of reacting gas mixtures by reduction to single iterative equatio

Soft computing for intelligent data analysis

Intelligent data analysis (IDA) is an interdisciplinary study concerned with the effective analysis of data. The paper briefly looks at some of the key issues in intelligent data analysis, discusses the opportunities for soft computing in this context, and presents several IDA case studies in which soft computing has played key roles. These studies are all concerned with complex real-world problem solving, including consistency checking between mass spectral data with proposed chemical structures, screening for glaucoma and other eye diseases, forecasting of visual field deterioration, and diagnosis in an oil refinery involving multivariate time series. Bayesian networks, evolutionary computation, neural networks, and machine learning in general are some of those soft computing techniques effectively used in these studies

Belousov-Zhabotinsky droplet mixing on-chip for chemical computing applications

Without an imposed physical structure, even the most complex chemistries are limited in their ability to process information. For example, the Belousov-Zhabotinsky (BZ) oscillating reaction has been shown to have information procession potential, but only if structure is imposed e.g. using physical barriers or light-sensitive catalysts. Recently, separated BZ droplets in oil have been investigated. Another option for aqueous/oil systems is to add lipid into the oil, which self-assembles into a monolayer at the phase boundary. If the lipid-stabilised droplets are brought into contact, a bilayer is formed, separating the BZ droplets into compartments. This technique is more flexible than other methods of imparting structure, allowing for the creation of droplet arrays inspired by biological neuronal networks

A "fast growth" method of computing free energy differences

Let Delta F be the free energy difference between two equilibrium states of a system. An established method of numerically computing Delta F involves a single, long ``switching simulation'', during which the system is driven reversibly from one state to the other (slow growth, or adiabatic switching). Here we study a method of obtaining the same result from numerous independent, irreversible simulations of much shorter duration (fast growth). We illustrate the fast growth method, computing the excess chemical potential of a Lennard-Jones fluid as a test case, and we examine the performance of fast growth as a practical computational tool.Comment: 17 pages + 4 figures, accepted for publication in J.Chem.Phy

Designing algorithms to aid discovery by chemical robots

Recently, automated robotic systems have become very efficient, thanks to improved coupling between sensor systems and algorithms, of which the latter have been gaining significance thanks to the increase in computing power over the past few decades. However, intelligent automated chemistry platforms for discovery orientated tasks need to be able to cope with the unknown, which is a profoundly hard problem. In this Outlook, we describe how recent advances in the design and application of algorithms, coupled with the increased amount of chemical data available, and automation and control systems may allow more productive chemical research and the development of chemical robots able to target discovery. This is shown through examples of workflow and data processing with automation and control, and through the use of both well-used and cutting-edge algorithms illustrated using recent studies in chemistry. Finally, several algorithms are presented in relation to chemical robots and chemical intelligence for knowledge discovery