Publications by Eduardo D. Sontag in year 2010
Articles in journal or book chapters
  1. R. Albert, B. Dasgupta, and E.D. Sontag. Inference of signal transduction networks from double causal evidence. In David Fenyö, editor, Computational Biology, Methods in Molecular Biology vol. 673, pages 239-251. Springer, 2010. [PDF] Keyword(s): systems biology, biochemical networks, algorithms, signal transduction networks, graph algorithms.
    We present a novel computational method, and related software, to synthesize signal transduction networks from single and double causal evidence.

  2. B. Dasgupta, P. Vera-Licona, and E.D. Sontag. Reverse engineering of molecular networks from a common combinatorial approach. In M. Elloumi and A.Y. Zomaya, editors, Algorithms in computational molecular biology: Techniques, Approaches and Applications, pages 941-954. Wiley, Hoboken, 2010. [PDF] Keyword(s): reverse engineering, systems biology.

  3. E.D. Sontag. Contractive systems with inputs. In Jan Willems, Shinji Hara, Yoshito Ohta, and Hisaya Fujioka, editors, Perspectives in Mathematical System Theory, Control, and Signal Processing, pages 217-228. Springer-verlag, 2010. [PDF] Keyword(s): contractions, contractive systems, consensus, synchronization.
    Contraction theory provides an elegant way of analyzing the behaviors of systems subject to external inputs. Under sometimes easy to check hypotheses, systems can be shown to have the incremental stability property that all trajectories converge to a unique solution. This property is especially interesting when forcing functions are periodic (globally attracting limit cycles result), as well as in the context of establishing synchronization results. The present paper provides a self-contained introduction to some basic results, with a focus on contractions with respect to non-Euclidean metrics.

  4. D. Angeli, P. de Leenheer, and E.D. Sontag. Graph-theoretic characterizations of monotonicity of chemical networks in reaction coordinates. J. Mathematical Biology, 61:581-616, 2010. [PDF] Keyword(s): MAPK cascades, biochemical networks, fluxes, monotone systems, reaction cordinates, Petri nets, persistence, futile cycles.
    This paper derives new results for certain classes of chemical reaction networks, linking structural to dynamical properties. In particular, it investigates their monotonicity and convergence without making assumptions on the form of the kinetics (e.g., mass-action) of the dynamical equations involved, and relying only on stoichiometric constraints. The key idea is to find an alternative representation under which the resulting system is monotone. As a simple example, the paper shows that a phosphorylation/dephosphorylation process, which is involved in many signaling cascades, has a global stability property.

  5. G. Russo, M. di Bernardo, and E.D. Sontag. Global entrainment of transcriptional systems to periodic inputs. PLoS Computational Biology, 6:e1000739, 2010. [PDF] Keyword(s): contractive systems, contractions, systems biology, biochemical networks, gene and protein networks.
    This paper addresses the problem of giving conditions for transcriptional systems to be globally entrained to external periodic inputs. By using contraction theory, a powerful tool from dynamical systems theory, it is shown that certain systems driven by external periodic signals have the property that all solutions converge to fixed limit cycles. General results are proved, and the properties are verified in the specific case of some models of transcriptional systems.

  6. L. Scardovi, M. Arcak, and E.D. Sontag. Synchronization of interconnected systems with applications to biochemical networks: an input-output approach. IEEE Transactions Autom. Control, 55:1367-1379, 2010. [PDF]
    This paper provides synchronization conditions for networks of nonlinear systems, where each component of the network itself consists of subsystems represented as operators in the extended L2 space. The synchronization conditions are provided by combining the input-output properties of the subsystems with information about the structure of network. The paper also explores results for state-space models as well as biochemical applications. The work is motivated by cellular networks where signaling occurs both internally, through interactions of species, and externally, through intercellular signaling.

  7. O. Shoval, L. Goentoro, Y. Hart, A. Mayo, E.D. Sontag, and U. Alon. Fold change detection and scalar symmetry of sensory input fields. Proc Natl Acad Sci USA, 107:15995-16000, 2010. [PDF] Keyword(s): identifiability, adaptation, biological adaptation, perfect adaptation, adaptation, feedforward loops, integral feedback, scale invariance, systems biology, transient behavior, symmetries, fcd, fold-change detection, incoherent feedforward loop, feedforward, IFFL.
    Certain cellular sensory systems display fold-change detection (FCD): a response whose entire shape, including amplitude and duration, depends only on fold-changes in input, and not on absolute changes. Thus, a step change in input from, say, level 1 to 2, gives precisely the same dynamical output as a step from level 2 to 4, since the steps have the same fold-change. We ask what is the benefit of FCD, and show that FCD is necessary and sufficient for sensory search to be independent of multiplying the input-field by a scalar. Thus the FCD search pattern depends only on the spatial profile of the input, and not on its amplitude. Such scalar symmetry occurs in a wide range of sensory inputs, such as source strength multiplying diffusing/convecting chemical fields sensed in chemotaxis, ambient light multiplying the contrast field in vision, and protein concentrations multiplying the output in cellular signaling-systems.Furthermore, we demonstrate that FCD entails two features found across sensory systems, exact adaptation and Weber's law, but that these two features are not sufficient for FCD. Finally, we present a wide class of mechanisms that have FCD, including certain non-linear feedback and feedforward loops.. We find that bacterial chemotaxis displays feedback within the present class, and hence is expected to show FCD. This can explain experiments in which chemotaxis searches are insensitive to attractant source levels. This study thus suggests a connection between properties of biological sensory systems and scalar symmetry stemming from physical properties of their input-fields.

  8. E.D. Sontag. Remarks on Feedforward Circuits, Adaptation, and Pulse Memory. IET Systems Biology, 4:39-51, 2010. [PDF] Keyword(s): adaptation, feedforward loops, integral feedback, systems biology, transient behavior, incoherent feedforward loop, feedforward, IFFL.
    This note studies feedforward circuits as models for perfect adaptation to step signals in biological systems. A global convergence theorem is proved in a general framework, which includes examples from the literature as particular cases. A notable aspect of these circuits is that they do not adapt to pulse signals, because they display a memory phenomenon. Estimates are given of the magnitude of this effect.

  9. E.D. Sontag. Rudolf E. Kalman and his students. Control Systems Magazine, 30:87-103, 2010. [PDF]
    An edited set of articles about Rudolf Kalman's legacy through his Ph.D. students.

  10. E.D. Sontag and D. Zeilberger. A symbolic computation approach to a problem involving multivariate Poisson distributions. Advances in Applied Mathematics, 44:359-377, 2010. Note: There are a few typos in the published version. Please see this file for corrections: [PDF] Keyword(s): probability theory, stochastic systems, systems biology, biochemical networks, chemical master equation.
    Multivariate Poisson random variables subject to linear integer constraints arise in several application areas, such as queuing and biomolecular networks. This note shows how to compute conditional statistics in this context, by employing WZ Theory and associated algorithms. A symbolic computation package has been developed and is made freely available. A discussion of motivating biomolecular problems is also provided.

  11. L. Wang, P. de Leenheer, and E.D. Sontag. Conditions for global stability of monotone tridiagonal systems with negative feedback. Systems and Control Letters, 59:138-130, 2010. [PDF] Keyword(s): systems biology, monotone systems, tridiagonal systems, global stability.
    This paper studies monotone tridiagonal systems with negative feedback. These systems possess the Poincar{\'e}-Bendixson property, which implies that, if orbits are bounded, if there is a unique steady state and this unique equilibrium is asymptotically stable, and if one can rule out periodic orbits, then the steady state is globally asymptotically stable. Different approaches are discussed to rule out period orbits. One is based on direct linearization, while the other uses the theory of second additive compound matrices. Among the examples that will illustrate our main theoretical results is the classical Goldbeter model of circadian rhythms.

Conference articles
  1. G. Russo, M. di Bernardo, and E.D. Sontag. Stability of networked systems: a multi-scale approach using contraction. In Proc. IEEE Conf. Decision and Control, Atlanta, Dec. 2010, pages FrB14.3, 2010. Keyword(s): contractive systems, contractions, systems biology, biochemical networks, synchronization.
    Preliminary conference version of ''A contraction approach to the hierarchical analysis and design of networked systems''.

  2. E.D. Sontag. Remarks on structural identification, modularity, and retroactivity. In Proc. IEEE Conf. Decision and Control, Atlanta, Dec. 2010, pages ThA23.1, 2010. [PDF] Keyword(s): modularity, retroactivity, identification.
    Summarized conference version of ``Modularity, retroactivity, and structural identification''.

  3. A. White, P.G. Cipriani, H.-L. Kao, B. Lees, D. Geiger, E.D. Sontag, K. Gunsalus, and F. Piano. Rapid and accurate developmental stage recognition of C. elegans from high-throughput image data. In 2010 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pages 3089-3096, 2010. [PDF]
    This paper presents a hierarchical principle for object recognition and its application to automatically classify developmental stages of C. elegans animals from a population of mixed stages. The system is in current use in a functioning C. elegans laboratory and has processed over two hundred thousand images for lab users.



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