TY - JOUR AB - Continuous-time Markov chains are commonly used in practice for modeling biochemical reaction networks in which the inherent randomness of themolecular interactions cannot be ignored. This has motivated recent research effort into methods for parameter inference and experiment design for such models. The major difficulty is that such methods usually require one to iteratively solve the chemical master equation that governs the time evolution of the probability distribution of the system. This, however, is rarely possible, and even approximation techniques remain limited to relatively small and simple systems. An alternative explored in this article is to base methods on only some low-order moments of the entire probability distribution. We summarize the theory behind such moment-based methods for parameter inference and experiment design and provide new case studies where we investigate their performance. AU - Ruess, Jakob AU - Lygeros, John ID - 1861 IS - 2 JF - ACM Transactions on Modeling and Computer Simulation TI - Moment-based methods for parameter inference and experiment design for stochastic biochemical reaction networks VL - 25 ER - TY - JOUR AU - Henzinger, Thomas A AU - Raskin, Jean ID - 1866 IS - 2 JF - Communications of the ACM TI - The equivalence problem for finite automata: Technical perspective VL - 58 ER - TY - JOUR AB - The plant hormone auxin is a key regulator of plant growth and development. Differences in auxin distribution within tissues are mediated by the polar auxin transport machinery, and cellular auxin responses occur depending on changes in cellular auxin levels. Multiple receptor systems at the cell surface and in the interior operate to sense and interpret fluctuations in auxin distribution that occur during plant development. Until now, three proteins or protein complexes that can bind auxin have been identified. SCFTIR1 [a SKP1-cullin-1-F-box complex that contains transport inhibitor response 1 (TIR1) as the F-box protein] and S-phase-kinaseassociated protein 2 (SKP2) localize to the nucleus, whereas auxinbinding protein 1 (ABP1), predominantly associates with the endoplasmic reticulum and cell surface. In this Cell Science at a Glance article, we summarize recent discoveries in the field of auxin transport and signaling that have led to the identification of new components of these pathways, as well as their mutual interaction. AU - Grones, Peter AU - Friml, Jirí ID - 1871 IS - 1 JF - Journal of Cell Science TI - Auxin transporters and binding proteins at a glance VL - 128 ER - TY - JOUR AB - The hippocampal region, comprising the hippocampal formation and the parahippocampal region, has been one of the most intensively studied parts of the brain for decades. Better understanding of its functional diversity and complexity has led to an increased demand for specificity in experimental procedures and manipulations. In view of the complex 3D structure of the hippocampal region, precisely positioned experimental approaches require a fine-grained architectural description that is available and readable to experimentalists lacking detailed anatomical experience. In this paper, we provide the first cyto- and chemoarchitectural description of the hippocampal formation and parahippocampal region in the rat at high resolution and in the three standard sectional planes: coronal, horizontal and sagittal. The atlas uses a series of adjacent sections stained for neurons and for a number of chemical marker substances, particularly parvalbumin and calbindin. All the borders defined in one plane have been cross-checked against their counterparts in the other two planes. The entire dataset will be made available as a web-based interactive application through the Rodent Brain WorkBench (http://www.rbwb.org) which, together with this paper, provides a unique atlas resource. AU - Boccara, Charlotte AU - Kjønigsen, Lisa AU - Hammer, Ingvild AU - Bjaalie, Jan AU - Leergaard, Trygve AU - Witter, Menno ID - 1874 IS - 7 JF - Hippocampus TI - A three-plane architectonic atlas of the rat hippocampal region VL - 25 ER - TY - JOUR AB - We consider partially observable Markov decision processes (POMDPs) with limit-average payoff, where a reward value in the interval [0,1] is associated with every transition, and the payoff of an infinite path is the long-run average of the rewards. We consider two types of path constraints: (i) a quantitative constraint defines the set of paths where the payoff is at least a given threshold λ1ε(0,1]; and (ii) a qualitative constraint which is a special case of the quantitative constraint with λ1=1. We consider the computation of the almost-sure winning set, where the controller needs to ensure that the path constraint is satisfied with probability 1. Our main results for qualitative path constraints are as follows: (i) the problem of deciding the existence of a finite-memory controller is EXPTIME-complete; and (ii) the problem of deciding the existence of an infinite-memory controller is undecidable. For quantitative path constraints we show that the problem of deciding the existence of a finite-memory controller is undecidable. We also present a prototype implementation of our EXPTIME algorithm and experimental results on several examples. AU - Chatterjee, Krishnendu AU - Chmelik, Martin ID - 1873 JF - Artificial Intelligence TI - POMDPs under probabilistic semantics VL - 221 ER -