"Computational Models & Methods in Systems Biology & Medicine"
Special Issue for IET Systems Biology
Aims and objectives
The current emphasis on 'big data' science marks a new stage in the advance of the biomedical sciences. Further recent improvement in computational capability and the impact of high throughput techniques and genome-wide methods mean that biological and medical fields are now data-rich to a degree that was unrealisable a few decades ago. This enormous amount of data has not only highlighted the complementarity needed between biology and computer science, but has also seen increased interdisciplinary overlap with the mathematical and physical sciences in the formulation of computational models, posing of hypotheses and statistical interpretation of results. The combination of knowledge from diverse sources and experiments means that linking system behaviour to cellular changes has become a viable goal, facilitated by techniques such as network theory, stochastic processes and integrative data analysis. The study of systems of biological components, ranging from molecules to species, their dynamic behaviour and reliance on diverse data, together with their translation to disease progression and treatment options, defines systems biology and medicine.
The aim of this special issue is to provide a forum to discuss recent progress in Systems Biology and Medicine (SBM), based on exploitation of computational methods, increased availability of data and the maturing of biological data science.
Topics will include, but are not limited to:
Submission: Manuscripts should be submitted to:
Note: During the submission process, authors will be prompted to enter the special issue by title, as given above: 'Computational Models & Methods in Systems Biology & Medicine'.
All papers received will be subject to the IET Systems Biology peer-review procedures, and revision will be requested, if needed. Papers will be published online also: (as e-first with a DOI number in advance of print publication).
Intention to Submit:
You are requested to confirm intention to submit by January 5, 2015 to one of the Guest Editors.
Contacts - if you have any queries, please do not hesitate to contact us:
Brief Biographies, (Guest Editors)
Prof. Heather Ruskin (B.Sc., M.Sc., Ph.D. CStat. (FSS), CPhys. FInstP.) is a Professor in Modelling and Computational Science. She has degrees in Physics and Applied Statistics (University of London) and a Ph.D in Statistical and Computational Physics from Trinity College Dublin (TCD) and is a former Head of Department and Dean for Research in the Faculty of Engineering and Computing in Dublin City University, Ireland. She led the Biocomputation research group, (affiliated to the National Institute of Cellular Biotechnology, 1999), Chaired the Modelling and Scientific Computing research group in the School of Computing over an extended period, and steered its incorporation into a university-designated research centre, of which she was founding Director. She has been PI on various national and EC research projects, has mentored some 40 graduate students and has served on Research Committees and Councils at national and international level. A former Chair of the Science Council for the National High End Computing Centre in Ireland and member of the Irish Research Council for Science, Engineering and Technology, she is currently a member of the Royal Irish Academy Interdisciplinary Committee for the Life and Medical Sciences. Prof. Ruskin was Workshop Co-Chair of the recent IEEE Intl. Conference on Bioinformatics & BioMedicine, (IEEE BIBM 2014), Belfast, UK, which has provided one motivation for this Special Issue. Her principal research interests include complexity science, computational models of spatiotemporal processes in physical, biological and related systems, and statistical methods/data analysis applied to natural and medical sciences. (webpage: http://www.computing.dcu.ie/~hruskin/hruskin.html).
Dr. Irina Roznovat is a Postdoctoral Researcher at the European Institute for Systems Biology and Medicine in Lyon, France. She holds a PhD in Computer Science (Computational Biology) from Dublin City University, Ireland and has worked on integrating information on genetic/epigenetic interdependencies, signalling pathways, stem cell dynamics, ageing/gender influences and epigenetic inhibitors, to develop a multi-scale computational model for colon cancer dynamics. Her main research interests are complex systems modelling (epigenetics, cancer, neurodegenerative disorders), machine learning, data analysis and concurrent programming. She was also a co-organizer of the ‘Empowering Systems Medicine through Optimal Computational Modelling’ Workshop, held in conjunction with IEEE BIBM 2014. (webpage: http://www.computing.dcu.ie/~iroznovat/ ).