“Analog and Stochastic Computation in Living Cells and Cytomorphic Chips“
by Rahul Sarpeshkar, Thomas E. Kurtz Professor, Dartmouth College, U.S.A.
Chair: Gabriel Rincon-Mora
“Clinical and research challenges in vascular diseases“
by Jean-Claude Tardif, Director, Montreal Heart Institute (MHI) Research Centre, Canada.
Chair: Majid Ahmadi
“Mixed-signal design in the era of Cheap Algorithms; What will an A/D converter look like in the year 2025?“
by Bob Adams, Analog Devices, Inc. Technology Fellow.
Chair: Franco Maloberti
May 23, 2016, 9:15 am – 10:15 am
Salle de bal centre & ouest
Title: Analog and Stochastic Computation in Living Cells and Cytomorphic Chips
Speaker: Rahul Sarpeshkar, Thomas E. Kurtz Professor, Dartmouth College, U.S.A.
— Abstract — Despite more than 15 years of research, synthetic circuits in living cells have been largely limited to a handful of digital logic gates and have not scaled. We show that one important reason for this failure to scale is an overemphasis on digital abstractions rather than on recognizing the true noisy, analog, and probabilistic nature of biological circuits. We show that synthetic and natural DNA, RNA, and protein circuits in cells must use analog, collective analog, probabilistic, and hybrid analog-digital computational approaches to function; otherwise, even relatively simple computations in cells will exceed energy, molecular-count, and cellular-resource budgets.
Analog circuits in electronics and molecular circuits in cell biology are also deeply connected: There are astounding similarities between the equations that describe noisy electronic flow in sub-threshold transistors and the equations that describe noisy molecular flow in chemical reactions, both of which obey the laws of exponential thermodynamics. Based on these similarities, it is possible to take a principled cytomorphic approach to design circuits in living cells. For example, we have engineered logarithmic analog computation in living cells with less than three transcription factors, almost two orders of magnitude more efficient than prior digital approaches to create a ‘bio-molecular slide rule’. In addition, highly computationally intensive noisy DNA-protein and protein-protein networks can be rapidly simulated in mixed-signal supercomputing chips that naturally capture their noisiness, dynamics, and non-modular interactions at lightning-fast speeds. Such an approach may enable large-scale design, analysis, simulation, and measurement of cells to be more precise and robust than it is today. To realize the promise of synthetic biology and systems biology for medicine, biotechnology, agriculture, and energy, we will need to go back to the future of computation and design and implement circuits via a collective analog approach like Nature does.
— Bio — Rahul Sarpeshkar is currently the Thomas E. Kurtz Professor at Dartmouth, and a Professor in the departments of Engineering, Physics, Microbiology&Immunology, and Physiology&Neurobiology. His research creates novel wet DNA-protein circuits in living cells and also advanced dry nano-electronic circuits on silicon chips. His longstanding work on analog and biological computation and his most recent work have helped pioneer the field of analog synthetic biology. His work on a glucose fuel cell for medical implants was featured by Scientific American among 2012’s 10 World Changing Ideas.
He holds over 35 awarded patents and has authored more than 125 publications, including one that was featured on the cover of Nature. His recent book, Ultra Low Power Bioelectronics: Fundamentals, Biomedical Applications, and Bio-inspired Systems revealed the deep connections between analog transistor circuits and biochemical circuits. His group holds several first or best records in analog, bio-inspired, synthetic biology, medical device, ultra low power, and energy harvesting systems. His work has applications in implantable medical devices for the deaf, blind, and paralyzed and in biotechnology and medical applications that benefit from cellular engineering. He has received several awards including the NSF Career Award, the ONR Young Investigator Award, and the Packard Fellows Award. He received Bachelor’s degrees in Electrical Engineering and Physics at MIT and a PhD at CalTech. Before he joined Dartmouth’s faculty, he was a tenured professor at MIT, leading the analog circuits and biological systems group at the Research Lab of Electronics. Before joining MIT, he was a member of the technical staff of Bell Labs’ division of biological computation in their physics department.
May 24, 2016, 9:00 am – 10:00 am
Salle de bal centre & ouest
Title: Clinical and research challenges in vascular diseases
Speaker: Jean-Claude Tardif, Director, Montreal Heart Institute (MHI) Research Centre, Canada.
— Abstract — Cardiovascular diseases remain the first cause of mortality in the world, despite the current standard of care. Atherosclerosis is the disease underlying major manifestations like myocardial infarctions (heart attacks) and ischemic strokes. Because the initial clinical presentation of atherosclerotic disease is often catastrophic, there is a great need for tools to help in the evaluation of the patient’s risk of such events. Although the patient’s profile of risk factors (smoking, diabetes, hypertension and hypercholesterolemia) is helpful in assessing the risk of future cardiovascular events, it only provides moderate ability to identify those who will develop an atherosclerosis-related cardiovascular event and should be treated rapidly and aggressively. Strategies to improve risk stratification are likely to involve increasingly the use of blood biomarkers (e.g. DNA, proteins, metabolites) and imaging (e.g. ultrasonography, magnetic resonance imaging, computed tomography, and nuclear medicine modalities like positron emission tomography). Molecular imaging (e.g. near-infrared spectroscopy and fluorescence) and catheter-based imaging (e.g. intravascular ultrasonography, optical coherence tomography) can also help to address some of the clinical and research challenges in the evaluation of atherosclerosis and to better understand vascular biology and the effects of medical interventions on specific aspects of vascular diseases.
Multiple challenges also exist in relation to the development and optimal use of cardiovascular medications. The predictive value of early, relatively small and short clinical studies for positive outcomes in late-stage trials needs to be improved, potentially through the utilization of some of the tools mentioned above. Improvement of vascular outcomes by medical therapy is likely to require multi-faceted therapies targeting LDL-cholesterol, HDL functionalities, and inflammation. Furthermore, cardiovascular precision medicine will involve the use of genetic markers, other biomarkers and imaging (molecular, cellular and whole-organ), as well as personalized therapies in part based on pharmacogenomics. These strategies raise additional challenges including the bioinformatic processing of large datasets and integration of different types of information (“big data”). Finally, optimization of invasive vascular interventions faces the challenges of the identification of vulnerable plaques and/or hemodynamically significant stenoses warranting a catheter-based treatment.
— Bio — Jean-Claude Tardif is the Director of the Research Centre at the Montreal Heart Institute and Professor of Medicine at the University of Montreal. Dr Tardif graduated from the University of Montreal with his medical degree in 1987 and completed his training in cardiology and research in Montreal and Boston in 1994. Dr Tardif holds the Canada Research Chair (tier 1) in translational and personalized medicine and the University of Montreal endowed research chair in atherosclerosis. He created the Montreal Health Innovations Coordinating Centre (MHICC) and is the Chairman of the steering committees of the CIHR-funded Canadian Atherosclerosis Imaging Network (CAIN) and Medical Imaging Trials NEtwork of Canada (MITNEC).
Dr Tardif has authored and co-authored more than 800 articles and abstracts in peer-reviewed publications including The New England Journal of Medicine, The Journal of the American Medical Association, The Lancet, Circulation, Circulation Cardiovascular Genetics, the Journal of the American College of Cardiology, the European Heart Journal, Nature Genetics, Genes and Development, the British Journal of Pharmacology, and Cardiovascular Research. In addition, he has written more than 30 book chapters (including in Braunwald’s Textbook of Heart Disease) and has edited several books. He has given approximately 400 invited lectures around the world.
His research covers the molecular and genomic aspects of atherosclerosis and related diseases and also involves animal models, mechanistic and observational clinical studies as well as large international randomized clinical trials. Dr Tardif is or has been the international principal investigator or part of the study leadership of several large clinical trials in the field of atherosclerosis and other cardiovascular diseases.
Dr Tardif and his team have created the Beaulieu-Saucier Pharmacogenomics Center at the Montreal Heart Institute and he has created the Center of Excellence in Personalized Medicine (CEPMed), the latter initially funded by the Network of Centers of Excellence (NCE) of Canada and which is also supported by multiple pharmaceutical and biotechnological companies.
Dr Tardif has won multiple awards during his career, including the Research Achievement Award of the Canadian Cardiovascular Society, the Distinguished Lecturer Award of the Canadian Institutes for Health Research, the Genesis Award of Bio-Québec (for his outstanding contributions to life sciences) and the Armand-Frappier Award of the Government of Quebec. He was also named scientific personality of the year by La Presse newspaper. Because of his accomplishments, Dr Tardif was named Fellow of the Canadian Academy of Health Sciences (FCAHS) and was recently inducted in the Order of Canada.
May 25, 2016, 9:00 am – 10:00 am
Salle de bal centre & ouest
— Abstract — The year is 1990, and master analog chip designer Joe Smith is testing his 4th silicon revision of a brand-new A/D converter. Eagerly he fires up his evaluation board and measures the linearity. He mutters an oath as, once again, he is 3dB short of spec. He fires off an email to the process engineer complaining that he needs better on-chip matching. Fast forward to 2025; Joe looks over the shoulder of recent grad Fred who is responsible for an SOC with 1 billion transistors. “Where’s the A/D converter”, he asks. “It’s that little blob in the corner”, Fred replies. “That looks like a RAM to me! Who designed it?” Joe asks. “Oh I just entered the requirements into the compiler, and it popped out the design”, Fred replies. “How does it achieve 16-bit performance on such a lousy process?” Joe asks. “Beats me”, replied Fred, “I have bigger fish to fry”.
At the dawn of the VLSI era, analog IC designers often thought of themselves as artists first and engineers second. They existed in a world apart from the digital designers who worked down the hall, carefully crafting precise circuits that were only married to the digital side near the end of a project schedule. If the resulting design missed its performance target, a fix required multiple, costly iterations. But the advent of modern CMOS process geometries has caused a dramatic shift in the way that the industry approaches the design process. Algorithmic approaches once considered unthinkable are now eminently practical.
Nowhere is this trend more evident than in the design of modern data converters. Noise-shaping converters, which rely on a co-designed system consisting of an analog modulator and a matched digital filter, signaled the beginning of this trend. And more recently, other approaches have been introduced that employ adaptive filters to compensate for analog distortion and quantization noise. In the area of high-speed converters, for example, interleaving is now commonly employed to achieve speeds above 1GSPS, requiring the use of adaptive algorithms to compensate for the inevitable timing errors.
One weakness that still persists today, however, is that minor changes in converter requirements often lead to new, ground-up design efforts. One possible solution: Re-imagine an ADC as an array of neuron-like cells that can be assembled by a compiler tool similar to a RAM generator. No individual cell in such a system is by itself particularly impressive, but the performance of the entire array is greatly increased when the cells communicate with each other. Temporal anti-correlations could be used to achieve noise-shaping over the array, and unique signal requirements could be met by offering a variety of cell libraries, as well as a variable number of cells tiled in an array. There is some evidence to suggest that biological neurons employ a similar mechanism, called “lateral inhibition,” which causes temporal anti-correlation of firing events similar in concept to the principle of noise-shaping. Could the ADC of the future employ such a technique? Might this ADC be produced by a compiler, thus bringing converters solidly into the domain of digital SOC designers?
To tackle this new world, where algorithms are cheap, a designer must be equally comfortable with analog, digital, and algorithmic concepts. This puts a new burden on the institutions which educate engineers, as the industry requires workers who are “wide” and “deep” at the same time.
— Bio — Bob Adams graduated from Tufts University in 1976 and initially worked in the audio industry designing consumer and professional audio products. Early in his career, Bob discovered the principle of log-domain filtering and published the first paper on that topic in 1979.
As the audio industry moved towards widespread adoption of digital storage, Adams began work on the new field of noise-shaped converters, and introduced the world’s first audio A/D converter with more 16-bit resolution in 1985.
In 1989 Adams joined the staff of Analog Devices and continued his work on audio conversion. Over the next 10 years he introduced many fundamental techniques that are now standard, including multi-bit continuous-time converters, mismatch shaping, and noise-shaped segmentation. In 1998 he received the ISSCC “best paper” award for his paper that described many of these concepts, and contributed to several of the first books written on the topic of delta-sigma converters.
In parallel with his work on converters, Adams continued his passion for signal processing, and in 1991 introduced the first integrated asynchronous sample-rate converter for audio, which has now become a ubiquitous requirement for inter-chip audio connectivity. In 2000 Adams introduced a new line of graphically programmed signal-processing IC’s known as “Sigma-DSP”, optimized for streaming audio applications.
Robert Adams is a Fellow of the IEEE, a Fellow and Silver Medal Award recipient of the Audio Engineering Society, and a Fellow of Analog Devices. He received the IEEE Pederson Award in 2015, and holds 34 patents.