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Bioinformatics Optimisation Training

Final Activity Report Summary - BIOPTRAIN (Bioinformatics Optimisation Training)

Recent developments in genomic technologies imply that molecular biologists today have access to vast amounts of genetic data, and while this holds enormous potential in terms of guiding clinical decision-making, a number of issues remain to be addressed before the goal of personalised diagnosis and treatment for patients can be achieved. Data has to be turned into useful information if it is to be used in clinical science or to support clinical decision-making. As the technologies for producing bioinformatic data continue to advance, ever-more sophisticated computational algorithms are required to deal effectively with bioinformatic data. The BIOPTRAIN project addressed this need by training a set of young scientists in the range of skills necessary to deal with the specific problems related to the automated analysis of bioinformatic data, as well as by creating new algorithms suitable for the field.

The four-year project provided a total of over 36 person-years of early-stage PhD training for a total of 12 long-term fellows, with posts longer than one year, and eight short-term fellows, with posts less than a year, distributed between four major European universities. The project was led in the United Kingdom by the University of Nottingham by Dr Garibaldi, in the KU Leuven Belgium by Profs. Moreau and De Causmaecker, in the University of Florence in Italy by Prof. Frasconi and, finally, in the Poznan University of Technology in Poland by Prof. Blazewicz.

In line with the original aims and objectives of the project, the training was delivered across a wide range of fundamental techniques for analysing bioinformatics data and optimising the useful information able to be extracted from such data. Areas of training ranged from theoretical research into bioinformatic algorithms through to fundamental advances in the analysis of bioinformatic data, including:
1. computational and statistical analysis techniques to support clinical diagnosis and treatment of diseases. Fellows based at Nottingham, Leuven and Poznan received training in clinical areas such as classifying breast cancer, investigating genetic influences on pre-eclampsia and identifying genetic pathways in complex multi-genetic diseases such as Parkinson.
2. fundamental computational techniques for protein structure prediction and comparison, in which fellows at Florence and Nottingham received training. Long term potential applications included improved understanding of biomedical processes and novel therapeutic drug discovery.
3. methodological development of techniques for gene prioritisation and genetic characterisation, in which fellows at Leuven and Nottingham were trained.
4. theoretical and foundational developments for sequence analysis and other generic bioinformatic optimisation algorithms, in which fellows at Poznan, Florence and Nottingham were trained.

Taken as a whole, the BIOPTRAIN programme resulted in 24 refereed journal publications, approximately another 24 international peer-reviewed conference publications and over 12 other forms of dissemination such as book chapters, web-services and software packages, with at least another 12 publications being either under submission or review by the time of its completion. This constituted an overall average of approximately two journal publications, two international peer-reviewed conference publications and one other miscellaneous dissemination, with another one submission under review, per thirty-six month, i.e. three-year, early-stage researcher. This was an outstanding level of achievement for the programme. In line with its aims, BIOPTRAIN also established successful, lasting collaboration between the four major partners, as evidenced through the establishment of the European computational biology, bioinformatics and medicine (EURO-CBBM) special interest group.