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1.  PD5: A General Purpose Library for Primer Design Software 
PLoS ONE  2013;8(11):e80156.
Complex PCR applications for large genome-scale projects require fast, reliable and often highly sophisticated primer design software applications. Presently, such applications use pipelining methods to utilise many third party applications and this involves file parsing, interfacing and data conversion, which is slow and prone to error. A fully integrated suite of software tools for primer design would considerably improve the development time, the processing speed, and the reliability of bespoke primer design software applications.
The PD5 software library is an open-source collection of classes and utilities, providing a complete collection of software building blocks for primer design and analysis. It is written in object-oriented C++ with an emphasis on classes suitable for efficient and rapid development of bespoke primer design programs. The modular design of the software library simplifies the development of specific applications and also integration with existing third party software where necessary. We demonstrate several applications created using this software library that have already proved to be effective, but we view the project as a dynamic environment for building primer design software and it is open for future development by the bioinformatics community. Therefore, the PD5 software library is published under the terms of the GNU General Public License, which guarantee access to source-code and allow redistribution and modification.
The PD5 software library is downloadable from Google Code and the accompanying Wiki includes instructions and examples:
PMCID: PMC3836914  PMID: 24278254
2.  Yeast-based automated high-throughput screens to identify anti-parasitic lead compounds 
Open Biology  2013;3(2):120158.
We have developed a robust, fully automated anti-parasitic drug-screening method that selects compounds specifically targeting parasite enzymes and not their host counterparts, thus allowing the early elimination of compounds with potential side effects. Our yeast system permits multiple parasite targets to be assayed in parallel owing to the strains’ expression of different fluorescent proteins. A strain expressing the human target is included in the multiplexed screen to exclude compounds that do not discriminate between host and parasite enzymes. This form of assay has the advantages of using known targets and not requiring the in vitro culture of parasites. We performed automated screens for inhibitors of parasite dihydrofolate reductases, N-myristoyltransferases and phosphoglycerate kinases, finding specific inhibitors of parasite targets. We found that our ‘hits’ have significant structural similarities to compounds with in vitro anti-parasitic activity, validating our screens and suggesting targets for hits identified in parasite-based assays. Finally, we demonstrate a 60 per cent success rate for our hit compounds in killing or severely inhibiting the growth of Trypanosoma brucei, the causative agent of African sleeping sickness.
PMCID: PMC3603448  PMID: 23446112
drug screening; parasites; yeast; automation; tropical diseases
3.  Towards Robot Scientists for autonomous scientific discovery 
We review the main components of autonomous scientific discovery, and how they lead to the concept of a Robot Scientist. This is a system which uses techniques from artificial intelligence to automate all aspects of the scientific discovery process: it generates hypotheses from a computer model of the domain, designs experiments to test these hypotheses, runs the physical experiments using robotic systems, analyses and interprets the resulting data, and repeats the cycle. We describe our two prototype Robot Scientists: Adam and Eve. Adam has recently proven the potential of such systems by identifying twelve genes responsible for catalysing specific reactions in the metabolic pathways of the yeast Saccharomyces cerevisiae. This work has been formally recorded in great detail using logic. We argue that the reporting of science needs to become fully formalised and that Robot Scientists can help achieve this. This will make scientific information more reproducible and reusable, and promote the integration of computers in scientific reasoning. We believe the greater automation of both the physical and intellectual aspects of scientific investigations to be essential to the future of science. Greater automation improves the accuracy and reliability of experiments, increases the pace of discovery and, in common with conventional laboratory automation, removes tedious and repetitive tasks from the human scientist.
PMCID: PMC2813846  PMID: 20119518
4.  The EXACT description of biomedical protocols 
Bioinformatics  2008;24(13):i295-i303.
Motivation: Many published manuscripts contain experiment protocols which are poorly described or deficient in information. This means that the published results are very hard or impossible to repeat. This problem is being made worse by the increasing complexity of high-throughput/automated methods. There is therefore a growing need to represent experiment protocols in an efficient and unambiguous way.
Results: We have developed the Experiment ACTions (EXACT) ontology as the basis of a method of representing biological laboratory protocols. We provide example protocols that have been formalized using EXACT, and demonstrate the advantages and opportunities created by using this formalization. We argue that the use of EXACT will result in the publication of protocols with increased clarity and usefulness to the scientific community.
Availability: The ontology, examples and code can be downloaded from
Contact: Larisa Soldatova
PMCID: PMC2718634  PMID: 18586727

Results 1-4 (4)