With the declining interest among incoming college students and the nationwide drop in computer science (CS) enrollments ([2, 1]), many CS departments would like to broaden participation in computing by reaching out to other departments on their campuses. One tactic is to encourage interdisciplinary work that has computing as a significant component. These efforts may result in more CS majors, increased enrollments in certain CS courses, and a student population that is better equipped to utilize computing within the contexts of their disciplines.

No abstract available.

Students of Computer Organization should be able to "learn by doing" at all levels of computer design. Digital logic circuitry is frequently taught using simulation software, however such platforms are often limited to exposing only a narrow range of design levels. This paper describes how, in the new multilevel simulation system DLSim 3, we are able to incorporate abstraction and extensibility to present the many levels of complex circuit designs in a single environment: from low level combinational and sequential circuits, through models of complete CPUs. Among other features, DLSim 3 is able to accomplish this by providing three different types of circuit abstraction: cards, chips, and plug-ins. Using DLSim 3, students recognize the uniformity of system structure, as well as the principles of abstraction that link the various levels of design.

Students of Computer Organization should be able to "learn by doing" at all levels of computer design. DLSim 3 is a multilevel simulation system that provides a unified platform for studying system structure, from low level combinational and sequential circuits, through design of a complete CPU. Using DLSim 3, students recognize the uniformity of system structure, as well as the principles of abstraction that link the various levels of design.

Chemical reaction networks by which individual cells gather and process information about their chemical environments have been dubbed "signal transduction" networks. Despite this suggestive terminology, there have been few attempts to analyze chemical signaling systems with the quantitative tools of information theory. Gradient sensing in the social amoeba Dictyostelium discoideum is a well characterized signal transduction system in which a cell estimates the direction of a source of diffusing chemoattractant molecules based on the spatiotemporal sequence of ligand-receptor binding events at the cell membrane. Using Monte Carlo techniques (MCell) we construct a simulation in which a collection of individual ligand particles undergoing Brownian diffusion in a three-dimensional volume interact with receptors on the surface of a static amoeboid cell. Adapting a method for estimation of spike train entropies described by Victor (originally due to Kozachenko and Leonenko), we estimate lower bounds on the mutual information between the transmitted signal (direction of ligand source) and the received signal (spatiotemporal pattern of receptor binding/unbinding events). Hence we provide a quantitative framework for addressing the question: how much could the cell know, and when could it know it? We show that the time course of the mutual information between the cell's surface receptors and the (unknown) gradient direction is consistent with experimentally measured cellular response times. We find that the acquisition of directional information depends strongly on the time constant at which the intracellular response is filtered. 1 Introduction: gradient sensing in eukaryotes Biochemical signal transduction networks provide the computational machinery by which neurons, amoebae or other single cells sense and react to their chemical environments. The precision of this chemical sensing is limited by fluctuations inherent in reaction and diffusion processes involving a Current address: Computational Neuroscience Graduate Program, The University of Chicago. Oberlin Center for Computation and Modeling, http://occam.oberlin.edu/. To whom correspondence should be addressed. http://www.case.edu/artsci/math/thomas/thomas.html; Oberlin College Research Associate. finite quantity of molecules [1, 2]. The theory of communication provides a framework that makes explicit the noise dependence of chemical signaling. For example, in any reaction A + B C , we may view the time varying reactant concentrations A(t) and B (t) as input signals to a noisy channel, and the product concentration C (t) as an output signal carrying information about A(t) and B (t). In the present study we show that the mutual information between the (known) state of the cell's surface receptors and the (unknown) gradient direction follows a time course consistent with experimentally measured cellular response times, reinforcing earlier claims that information theory can play a role in understanding biochemical cellular communication [3, 4]. Dictyostelium is a soil dwelling amoeba that aggregates into a multicellular form in order to survive conditions of drought or starvation. During aggregation individual amoebae perform chemotaxis, or chemically guided movement, towards sources of the signaling molecule cAMP, secreted by nearby amoebae. Quantitive studies have shown that Dictyostelium amoebae can sense shallow, static gradients of cAMP over long time scales (30 minutes), and that gradient steepness plays a crucial role in guiding cells [5]. The chemotactic efficiency (CE), the population average of the cosine between the cell displacement directions and the true gradient direction, peaks at a cAMP concentration of 25 nanoMolar, similar to the equilibrium constant for the cAMP receptor (the Keq is the concentration of cAMP at which the receptor has a 50% chance of being bound or unbound, respectively). For smaller or larger concentrations the CE dropped rapidly. Nevertheless over long times cells were able (on average) to detect gradients as small as 2% change in [cAMP] per cell length. At an early stage of development when the pattern of chemotactic centers and spirals is still forming, individual amoebae presumably experience an inchoate barrage of weak, noisy and conflicting directional signals. When cAMP binds receptors on a cell's surface, second messengers trigger a chain of subsequent intracellular events including a rapid spatial reorganization of proteins involved in cell motility. Advances in fluorescence microscopy have revealed that the oriented subcellular response to cAMP stimulation is already well underway within two seconds [6, 7]. In order to understand the fundamental limits to communication in this cell signaling process we abstract the problem faced by a cell to that of rapidly identifying the direction of origin of a stimulus gradient superimposed on an existing mean background concentration. We model gradient sensing as an information channel in which an input signal the direction of a chemical source is noisily transmitted via a gradient of diffusing signaling molecules; and the "received signal" is the spatiotemporal pattern of binding events between cAMP and the cAMP receptors [8]. We neglect downstream intracellular events, which cannot increase the mutual information between the state of the cell and the direction of the imposed extracellular gradient [9]. The analysis of any signal transmission system depends on precise representation of the noise corrupting transmitted signals. We develop a Monte Carlo simulation (MCell, [10, 11]) in which a simulated cell is exposed to a cAMP distribution that evolves from a uniform background to a gradient at low (1 nMol) average concentration. The noise inherent in the communication of a diffusionmediated signal is accurately represented by this method. Our approach bridges both the transient and the steady state regimes and allows us to estimate the amount of stimulus-related information that is in principle available to the cell through its receptors as a function of time after stimulus initiation. Other efforts to address aspects of cell signaling using the conceptual tools of information theory have considered neurotransmitter release [3] and sensing temporal signals [4], but not gradient sensing in eukaryotic cells. A typical natural habitat for social amoebae such as Dictyostelium is the complex anisotropic threedimensional matrix of the forest floor. Under experimental conditions cells typically aggregate on a flat two-dimensional surface. We approach the problem of gradient sensing on a sphere, which is both harder and more natural for the ameoba, while still simple enough for us analytically and numerically. Directional data is naturally described using unit vectors in spherical coordinates, but the ameobae receive signals as binding events involving intramembrane protein complexes, so we have developed a method for projecting the ensemble of receptor bindings onto coordinates in R3 . In loose analogy with the chemotactic efficiency [5], we compare the projected directional estimate with the true gradient direction represented as a unit vector on S2 . Consistent with observed timing of the cell's response to cAMP stimulation, we find that the directional signal converges quickly enough for the cell to make a decision about which direction to move within the first two seconds following stimulus onset. 2 Methods 2.1 Monte Carlo simulations Using MCell and DReAMM [10, 11] we construct a spherical cell (radius R = 7.5m, [12]) centered in a cubic volume (side length L = 30m). N = 980 triangular tiles partition the surface (mesh generated by DOME1 ); each contained one cell surface receptor for cAMP with binding rate k+ = 4.4 107 sec-1 M-1 , first-order cAMP unbinding rate k- = 1.1 sec-1 [12] and Keq = k- /k+ = 25nMol cAMP. We established a baseline concentration of approximately 1nMol by releasing a cAMP bolus at time 0 inside the cube with zero-flux boundary conditions imposed on each wall. At t = 2 seconds we introduced a steady flux at the x = -L/2 wall of 1 molecule of cAMP per square micron per msec, adding signaling molecules from the left. Simultaneously, the x = +L/2 wall of the cube assumes absorbing boundary conditions. The new boundary conditions lead (at equilibrium) to a linear gradient of 2 nMol/30m, ranging from 2.0 nMol at the flux source wall to 0 nMol at the absorbing wall (see Figure 1); the concentration profile approaches this new steady state with time constant of approximately 1.25 msec. Sampling boxes centered along the planes x = 13.5m measured the local concentration, allowing us to validate the expected model behavior. Figure 1: Gradient sensing simulations performed with MCell (a Monte Carlo simulator of cellular microphysiology, http://www.mcell.cnl.salk.edu/) and rendered with DReAMM (Design, Render, and Animate MCell Models, http://www.mcell.psc.edu/). The model cell comprised a sphere triangulated with 980 tiles with one cAMP receptor per tile. Cell radius R = 7.5m; cube side L = 30m. Left: Initial equilibrium condition, before imposition of gradient. [cAMP] 1nMol (c. 15,000 molecules in the volume outside the sphere). Right: Gradient condition after transient (c. 15,000 molecules; see Methods for details).

In order to be effective, the content of the introductory curriculum must strike a proper balance between the highly motivating (i.e. "fun") aspects of programming and the development of sound scientific background and analytical thinking. As part of an NSF-funded Education Infrastructure project at Oberlin College, we have developed a curriculum that maintains a high level of scientific rigor, while making use of the new technology of HTML and the World Wide Web to instruct and motivate. We provide our students with an integrated experience which includes web-based guided-study laboratory materials, an interactive programming environment and a syllabus which emphasizes the interplay between abstract and formal concepts on the one hand, and concrete implementations and experimental investigations on the other. Scheme is used as the primary programming environment, to illustrate the salient features of the imperative and the object-oriented paradigms, along with the functional paradigm with which it is usually associated. We believe that our approach: 1) revitalizes the material for students who expect a more modern presentation; 2) provides a balanced view of competing perspectives on programming style and methodology; and 3) provides a well-balanced mixture of formal analysis and experimental measurement.In order to produce laboratory materials without the overhead entailed by creating them directly in HTML, we have developed a tool capable of abstracting the functionality and style of HTML documents; thus we can engage both faculty and student authors in the development of laboratories with a uniform style. The very tools used to develop the online materials are themselves an excellent illustration of the empowerment which results from a thorough understanding of the principles of abstraction.

No abstract available.