Systems Biology includes the study of interaction networks and, in particular, their dynamic and spatiotemporal aspects. It typically requires the import of concepts from across the disciplines and crosstalk between theory, benchwork, modelling and simulation. The quintessence of Systems Biology is the discovery of the design principles of Life. The logical next step is to apply these principles to synthesize biological systems. This engineering of biology is the ultimate goal of Synthetic Biology: the rational conception and construction of complex systems based on, or inspired by, biology, and endowed with functions that may be absent in Nature.
The Thematic School “advances in Systems and Synthetic Biology - Modelling Complex Biological Systems in the Context of Genomics” aSSB'16 will be held in Evry on March 21-25, 2016 ( http://epigenomique.free.fr/en/index.php ).
We are organising an international workshop for students (PhD and M2) and post-doctoral fellows. This workshop offers the opportunity for students and post-doctoral fellows to get an official recognition through peer-review, to discuss their projects and to get feedback from other participants by sharing their experience in a favorable environment. The M2, PhD or post-doc projects can concern either an introductory presentation, works in progress or some first conclusive results. Topics of interest include any contribution helping to understand or to engineer biological systems by using models coming from biology, physics, chemistry, engineering, computer sciences or mathematics.
Submission procedure: The short paper (between 3 and 8 pages in A4 format) should be written in English, with at least a M2, PhD student or post-doctoral fellow among the authors. It will be reviewed by the scientific committee of the School. Once the paper is accepted, the student must attend the workshop and present their work in English during a 15 minutes-presentation. They are also encouraged to bring a poster. Free registration is proposed to one of the authors (M2, PhD, post-doc) of an accepted paper. The accepted papers will be published in the proceedings book of the School.
It is our pleasure to announce the 2016 Thematic Research School on "advances in Systems & Synthetic Biology: Modelling complex biological systems in the context of genomics". The next session will take place in Evry on March 21-25, 2016.
The program will include conferences (the speakers are listed below), hands-on tutorials, selected talks by students and postdocs, and poster sessions.
Online registration will open on 28 September 2015.
This annual cross-disciplinary Thematic School on Systems and Synthetic Biology started in 2002. Previous session proceedings may be found here.
The aSSB-Evry'16 Scientific Board
aSSB-Evry'16 SESSIONS AND INVITED SPEAKERS:
Metabolism & Signalling
Jonathan Karr - Inst. for Genomics & Multiscale Biology Inst., the Mount Sinai School of Medicine, New York, US
Tamas Korcsmaros – TGAC / Inst. Food Research, Norwich, UK
Modeling gene circuits
Paul François, Dept. of Physics, McGill U., CA
Silvia Santos – MRC clinical sciences centre, Imperial College London, UK
Yannick Rondelez - LIMMS/CNRS-IIS, U. of Tokyo, JP
Friedrich Simmel - Systems Biophysics and Bionanotechnology, Technische Universität München, DE
Computer science – Applications of logical approaches
Liver cancer is one of the most difficult cancers to detect, but synthetic biologist Tal Danino had a left-field thought: What if we could create a probiotic, edible bacteria that was "programmed" to find liver tumors? His insight exploits something we're just beginning to understand about bacteria: their power of quorum sensing, or doing something together once they reach critical mass. Danino, a TED Fellow, explains how quorum sensing works — and how clever bacteria working together could someday change cancer treatment.
A new module on the Étoile Platform, by Jeffrey Johnson
Based on the course presented at the 4th Ph.D. summer School - conference on “Mathematical Modeling of Complex Systems”, Cultural Foundation “Kritiki Estia”, 14 – 25 July, 2014, Athens.
The modern world is complex beyond human understanding and control. The science of complex systems aims to find new ways of thinking about the many interconnected networks of interaction that defy traditional approaches. Thus far, research into networks has largely been restricted to pairwise relationships represented by links between two nodes.
This course marks a major extension of networks to multidimensional hypernetworks for modeling multi-element relationships, such as companies making up the stock market, the neighborhoods forming a city, people making up committees, divisions making up companies, computers making up the internet, men and machines making up armies, or robots working as teams. This course makes an important contribution to the science of complex systems by: (i) extending network theory to include dynamic relationships between many elements; (ii) providing a mathematical theory able to integrate multilevel dynamics in a coherent way; (iii) providing a new methodological approach to analyze complex systems; and (iv) illustrating the theory with practical examples in the design, management and control of complex systems taken from many areas of application.
Do all questions have answers? How much can we know about the world? Is there such a thing as an ultimate truth?
To be human is to want to know, but what we are able to observe is only a tiny portion of what’s “out there.” In The Island of Knowledge, physicist Marcelo Gleiser traces our search for answers to the most fundamental questions of existence. In so doing, he reaches a provocative conclusion: science, the main tool we use to find answers, is fundamentally limited.
These limits to our knowledge arise both from our tools of exploration and from the nature of physical reality: the speed of light, the uncertainty principle, the impossibility of seeing beyond the cosmic horizon, the incompleteness theorem, and our own limitations as an intelligent species. Recognizing limits in this way, Gleiser argues, is not a deterrent to progress or a surrendering to religion. Rather, it frees us to question the meaning and nature of the universe while affirming the central role of life and ourselves in it. Science can and must go on, but recognizing its limits reveals its true mission: to know the universe is to know ourselves.
Telling the dramatic story of our quest for understanding, The Island of Knowledge offers a highly original exploration of the ideas of some of the greatest thinkers in history, from Plato to Einstein, and how they affect us today. An authoritative, broad-ranging intellectual history of our search for knowledge and meaning, The Island of Knowledge is a unique view of what it means to be human in a universe filled with mystery.
Where does this leave MOOCs and the lofty ambition of helping universities use them to educate the world? In the United States, efforts to integrate MOOCs into the existing higher-education credentialing system have been rebuffed. Professors might be amenable to using the courses in place of textbooks, but a recent study suggested that doing that might be more costly than expected. Lately Coursera has focused on making inroads in foreign countries. But how deep can those inroads go?
This course of 25 lectures, filmed at Cornell University in Spring 2014, is intended for newcomers to nonlinear dynamics and chaos. It closely follows Prof. Strogatz's book, "Nonlinear Dynamics and Chaos: With Applications to Physics, Biology, Chemistry, and Engineering." The mathematical treatment is friendly and informal, but still careful. Analytical methods, concrete examples, and geometric intuition are stressed. The theory is developed systematically, starting with first-order differential equations and their bifurcations, followed by phase plane analysis, limit cycles and their bifurcations, and culminating with the Lorenz equations, chaos, iterated maps, period doubling, renormalization, fractals, and strange attractors. A unique feature of the course is its emphasis on applications. These include airplane wing vibrations, biological rhythms, insect outbreaks, chemical oscillators, chaotic waterwheels, and even a technique for using chaos to send secret messages. In each case, the scientific background is explained at an elementary level and closely integrated with the mathematical theory. The theoretical work is enlivened by frequent use of computer graphics, simulations, and videotaped demonstrations of nonlinear phenomena. The essential prerequisite is single-variable calculus, including curve sketching, Taylor series, and separable differential equations. In a few places, multivariable calculus (partial derivatives, Jacobian matrix, divergence theorem) and linear algebra (eigenvalues and eigenvectors) are used. Fourier analysis is not assumed, and is developed where needed. Introductory physics is used throughout. Other scientific prerequisites would depend on the applications considered, but in all cases, a first course should be adequate preparation
Nonlinear Dynamics and Chaos - Steven Strogatz, Cornell University
The topic “GitHub for Science” has been explored quite a few times before and with good reason: it is quite exciting to envision what breakthroughs in scientific collaboration could come from GitHub backed explorations, with substantial capital to invest and a formidable team to execute.
With GitHub’s founder saying that: "In science, I think there’s huge changes that can be made there as well. — Tom Preston-Werner" (...) - by Jure Triglav, 11 January 2014
A BRIEF GUIDE TO THE IDEAS AND ARTEFACTS OF COMPUTATIONAL ARTIFICIAL LIFE Alan Dorin, Animaland, 2014 This guide provides broad coverage of computational Artificial Life, a field encompassing the theories and discoveries underpinning the invention and study of technology-based living systems. It is targetted at students of all ages who are new to Artificial Life or are hoping to gain a broad understanding of its themes. The book focusses specifically on Artificial Life realised in computer software. Topics include: • pre-history of Artificial Life • artificial chemistry • artificial cells • organism development • locomotion • group behaviour • evolution • ecosystem simulation
Biological Bits includes animations and interactive software for experimentation with key processes. Simulations are included to allow exploration of cellular automata, developmental models, group behaviour and ecosystem simulation to aid in illustrating the text. The book can be read cover-to-cover as a general introduction to Artificial Life, or it can serve as a textbook for university or advanced high-school courses.
This lecture treats some enduring misconceptions about modeling. One of these is that the goal is always prediction. The lecture distinguishes between explanation and prediction as modeling goals, and offers sixteen reasons other than prediction to build a model. It also challenges the common assumption that scientific theories arise from and 'summarize' data, when often, theories precede and guide data collection; without theory, in other words, it is not clear what data to collect. Among other things, it also argues that the modeling enterprise enforces habits of mind essential to freedom. It is based on the author's 2008 Bastille Day keynote address to the Second World Congress on Social Simulation, George Mason University, and earlier addresses at the Institute of Medicine, the University of Michigan, and the Santa Fe Institute.
Power grids, road maps, and river streams are examples of infrastructural networks which are highly vulnerable to external perturbations. An abrupt local change of load (voltage, traffic density, or water level) might propagate in a cascading way and affect a significant fraction of the network. Almost discontinuous perturbations can be modeled by shock waves which can eventually interfere constructively and endanger the normal functionality of the infrastructure. We study their dynamics by solving the Burgers equation under random perturbations on several real and artificial directed graphs. Even for graphs with a narrow distribution of node properties (e.g., degree or betweenness), a steady state is reached exhibiting a heterogeneous load distribution, having a difference of one order of magnitude between the highest and average loads. Unexpectedly we find for the European power grid and for finite Watts-Strogatz networks a broad pronounced bimodal distribution for the loads. To identify the most vulnerable nodes, we introduce the concept of node-basin size, a purely topological property which we show to be strongly correlated to the average load of a node.
The Diverse Applications of GenomicsCracking Open NatureFunctional Genome Annotation and In Silico BiologyGenetics, Bioethics, and Equivalency of RiskComplex Genetics: Anticipating a Billion Human Genome SequencesMiniaturized Genomic MonitoringPersonalized Genomics: Towards a Proactive ModelPopulation Genetics: More Traits, More Populations, and More Species
Tyler-Smith C, Yang H, Landweber LF, Dunham I, Knoppers BM, Donnelly P, et al. (2015) Where Next for Genetics and Genomics? PLoS Biol 13(7): e1002216. doi:10.1371/journal.pbio.1002216
Why does modern life revolve around objectives? From how science is funded, to improving how children are educated -- and nearly everything in-between -- our society has become obsessed with a seductive illusion: that greatness results from doggedly measuring improvement in the relentless pursuit of an ambitious goal. In Why Greatness Cannot Be Planned, Stanley and Lehman begin with a surprising scientific discovery in artificial intelligence that leads ultimately to the conclusion that the objective obsession has gone too far. They make the case that great achievement can't be bottled up into mechanical metrics; that innovation is not driven by narrowly focused heroic effort; and that we would be wiser (and the outcomes better) if instead we whole-heartedly embraced serendipitous discovery and playful creativity.
Scientific evidence (from AI) that the moronic protestant pursuit of measures and achievements is actually a barrier to generation of new outcomes (i.e. knowledge) and creativity. Brilliant! (No2 in my summer reading list!)
The Thematic School "Advances in Systems and Synthetic Biology - Modelling Complex Biological Systems in the Context of Genomics" is organising an international workshop for students (PhD ans M2) and post-doctoral fellows. This student workshop offers the opportunity for students and post-doctoral fellows to get an official recognition through peer-review, to discuss their projects and to get feedback from other participants by sharing their experience in a favourable environment.
The M2, PhD or post-doc projects can concern either an introductive presentation, works in progress or some first conclusive results. Topics of interest include any contribution helping to understand or to engineer biological systems by using models coming from physics, chemistry, engineering, computer sciences or mathematics.
Submission procedure: The short paper (between 6 and 14 pages in the book format) should be written in English with at least a M2, PhD student or post-doctoral fellow among the authors. It will be reviewed by the scientific committee of the School. Once the paper is accepted, the student must attend the workshop and present his work in English during a 15 minutes-presentation. Free registration is proposed to one of the authors (M2, PhD, post-doc) of an accepted paper. The short papers will be published in the proceedings book of the School.
Important dates: - Submission deadline of short articles: December 15, 2014 -- EXTENDED 22nd December - Notification of acceptance: January 16, 2015 - Revised version of accepted short articles: January 30, 2015
Authors are invited to submit online their article in the submission webpage, after carefully reading the formats webpage.
What makes the 21st century different from the 20th century? This century is the century of extremes -- political, economic, social, and global black-swan events happening with increasing frequency and severity. Book of Extremes is a tour of the current reality as seen through the lens of complexity theory – the only theory capable of explaining why the Arab Spring happened and why it will happen again; why social networks in the virtual world behave like flashmobs in the physical world; why financial bubbles blow up in our faces and will grow and burst again; why the rich get richer and will continue to get richer regardless of governmental policies; why the future of economic wealth and national power lies in comparative advantage and global trade; why natural disasters will continue to get bigger and happen more frequently; and why the Internet – invented by the US -- is headed for a global monopoly controlled by a non-US corporation. It is also about the extreme innovations and heroic innovators yet to be discovered and recognized over the next 100 years.Complexity theory combines the predictable with the unpredictable. It assumes a nonlinear world of long-tailed distributions instead of the classical linear world of normal distributions. In the complex 21st century, almost nothing is linear or normal. Instead, the world is highly connected, conditional, nonlinear, fractal, and punctuated. Life in the 21st century is a long-tailed random walk – Levy walks -- through extreme events of unprecedented impact. It is an exciting time to be alive.
The field of nonlinear dynamics and chaos has grown very much over the last few decades and is becoming more and more relevant in different disciplines. This book presents a clear and concise introduction to the field of nonlinear dynamics and chaos, suitable for graduate students in mathematics, physics, chemistry, engineering, and in natural sciences in general. It provides a thorough and modern introduction to the concepts of Hamiltonian dynamical systems' theory combining in a comprehensive way classical and quantum mechanical description. It covers a wide range of topics usually not found in similar books. Motivations of the respective subjects and a clear presentation eases the understanding. The book is based on lectures on classical and quantum chaos held by the author at Heidelberg University. It contains exercises and worked examples, which makes it ideal for an introductory course for students as well as for researchers starting to work in the field.
The second round of applications for the Master 2 Systems Biology and Synthetic - MSSB - is open until 9 June 2014 on the site www.mssb.fr.
The M2 is offered by the University of Evry -Val d'Essonne , in partnership with AgroParis Tech, Ecole Centrale Paris , Telecom SudParis and Sup'Biotech , it offers an original scientific training in a privileged environment including the proximity of Genopole ®.
The MSSB is designed for students wishing to acquire a trans-disciplinary high-level training , regardless of their initial course ( Biology, Computer Science , Applied Mathematics, Physics, Chemistry, Engineering Sciences ) . That is why we are asking for the widest possible dissemination to teachers , managers , and especially students from all scientific and engineering disciplines.
As the Thematic School is about to begin on the coming Monday (24th of March). I will be scooping here some pertinent introductory resources on Systems and Synthetic Biology that are available online. Starting with a comprehensive set of directives, ideas and strategies as they have been laid down by NCBI in 2011.
Complex adaptive systems (cas), including ecosystems, governments, biological cells, and markets, are characterized by intricate hierarchical arrangements of boundaries and signals. In ecosystems, for example, niches act as semi-permeable boundaries, and smells and visual patterns serve as signals; governments have departmental hierarchies with memoranda acting as signals; and so it is with other cas. Despite a wealth of data and descriptions concerning different cas, there remain many unanswered questions about "steering" these systems. In Signals and Boundaries, John Holland argues that understanding the origin of the intricate signal/border hierarchies of these systems is the key to answering such questions. He develops an overarching framework for comparing and steering cas through the mechanisms that generate their signal/boundary hierarchies.
Holland lays out a path for developing the framework that emphasizes agents, niches, theory, and mathematical models. He discusses, among other topics, theory construction; signal-processing agents; networks as representations of signal/boundary interaction; adaptation; recombination and reproduction; the use of tagged urn models (adapted from elementary probability theory) to represent boundary hierarchies; finitely generated systems as a way to tie the models examined into a single framework; the framework itself, illustrated by a simple finitely generated version of the development of a multi-celled organism; and Markov processes.
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