Day 1 :
Imperial College London, UK
Time : 09:30-09:55
Emmanuel Mic. Drakakis received the B.Sc. degree (1st Class Honours) in Physics and the M.Phil. degree (1st Class Honours) in Electronic Physics and Radioelectrology from Aristotle University of Thessaloniki, Macedonia, Greece, and the Ph.D. degree in analogue IC design from the Department of Electrical and Electronic Engineering at Imperial College London, U.K. under the supervision of Dr. Alison Payne. During his PhD he was sponsored by the Micro-Electronics Research Center of LM Ericsson-Stockholm (one of eight in the world at the time). Currently he is Reader in Bio-Circuits and Systems in the Department of Bioengineering at Imperial College London. In the Department of Bioengineering he has founded the Bioinspired VLSI Circuits and Systems Group whose research focuses on “Circuits for and from Biology”. He has authored or co-authored a large number (>120) of peer-reviewed journal and conference papers and several book chapters. Dr. Drakakis has received many prizes for research excellence and is involved in several cross-disciplinary research projects. In the past he has served as Guest Ass.Editor for IET El.Letters and as Subject Editor for the International Journal of Electronics – Taylor & Francis. He has also served as an Associate Editor in IEEE publications, including TCAS1 and TCAS2. He is currently an Associate Editor for IEEE Transactions on Biomedical Circuits and Systems and an Associate Editor for Frontiers in Neuromorphic Engineering.
The physics-dictated sub-threshold operation of MOS transistors can lead to ultra-low-power designs but is also governed by a challenging exponential characteristic. This talk will elucidate how to view such a non-linearity as an asset and how to exploit it by treating it as a powerful computational primitive which can lead to the systematic realisation of non-linear dynamics dictated by biology. We will present a method for the systematic implementation of ultra low power microelectronic circuits aimed at computing nonlinear cellular and molecular dynamics. Several examples of systematic computation of non-linear cellular and molecular dynamics by means of ultra-low-power microelectronic cytomimetic circuits will be elaborated: glycolytic oscillations, nonlinear intracellular calcium oscillations and a gene-protein regulatory system model. Proof-of-concept results from a 1 microwatt cytomimetic prototype chip emulating the complex non-linear mammalian cell cycle dynamics will be reported.
Columbia University, USA
Keynote: Integration of next-generation sequencing data with analytical chemistry, structural biology and cell biology
Time : 09:55-10:20
Peter L. Nagy received his MD degree from the University of Pecs, Hungary in 1989. His interest to pursue a career as a physician scientist led him to Purdue University where he earned his Ph.D. in Biochemistry.He worked under the mentorship of Dr. Howard Zalkin and made important discoveries relating to C1-metabilism in bacteria. Subsequently he completed Anatomic and Molecular Genetic Pathology training and Stanford University as well as postdoctoral training in Michael Cleary’s laboratory. He was the first to purify and functionally characterize the Set1 histone methyltransferase complex from S. cerevisiae in collaboration with Dr. Roger Kornberg. He co-developed the FAIRE method with Jason Lieb allowing physical fractionation of chromatin based on formaldehyde crosslinkability. Currently he leads a research laboratory investigating the role of transcriptional defects in neurodegenerative diseases, such as AOA2 and ALS4, and is director of the clinical next-generation sequencing facility in the Laboratory of Personalized Genomic Medicine at Columbia University Medical Center in the Department of Pathology and Cell Biology.
Next-generation sequencing in the clinical practice allows for a critical review of the literature describing the pathogenicity of specific mutations or the disease relatedness of specific genes and also provides an important discovery tool for new disease genes and disease causing mutations. Because of the large volume and complex nature of the data obtained from large panels and whole exome sequencing testing, the management of the data in a transparent, yet powerful analytical framework is key to a successful clinical operation. Population allele frequency, data from parents and precise, yet concise phenotypic description are the cornerstone for successful clinical evaluation of the pathogenicity of variants identified. The full potential for discovery of new disease associated genes and disease causing mutations can only be realized if there is a tight collaborative effort between the clinicians performing the interpretation and structural biologists and analytical chemists and cell biologists who can help predict and verify the effects of variants identified. My presentation will focus on the need to foster and strengthen this multidirectional information flow. I will review the resources that are already available and propose ways to improve them through integrating new data types or design of more user-friendly interfaces.