Campuses:

<span class=strong>Reception and Poster Session</span>

Monday, April 21, 2008 - 5:00pm - 6:30pm
Lind 400
  • Evolution of song culture in the zebra finch
    Haibin Wang (Cold Spring Harbor Laboratory)
    A number of Oscine songbirds are vocal learners. In these species, song shares a remarkable characteristic with human language: both are acquired through imitative learning. When reared in social and acoustic isolation, the Zebra Finch (the species of songbird under study here) can still sing, revealing the genetically encoded aspect of song. However, the isolate songs usually have longer syllables, and appear to be more variable than the wild type (WT) songs found in the wild or in laboratory colonies.

    In order to understand how the isolate song might evolve over multiple generations, we successively trained naïve juveniles starting with an isolate founding father. The first generation learners are in turn used as tutors to train the next generation, and so on. Thus, tutoring lineages are established through a recursive training processes. We found that small, yet systematic variations accumulate over generations of training. Remarkably, the descendants’ song structures are gradually transformed towards WT songs.
  • The advantage of two step transport problem
    Ezio Marchi (Instituto de Matemática Aplicada)
    Here, we present a transport model which indroduce a variant in
    the transport theory. Here the mass or merchandize in order to
    go from a port to a destination must pass through a deposit,
    without accumulation. It is possible to consider deposit
    constraint. We obtain the corresponding linear program
    associated to it, as well as the dual. The application of this
    model to biological sciences, specially in human body, lungs, blood and biological systems seems promising.
    We obtain the dual, which appear in a natural way from the
    incidence matrix, which has many interesting properties.
    The rank is the number of the ports, deposits plus the
    destination minus on.
    We study and characterize all the extremals extending the ideas
    of Jurkar-Ryser, and von Neumann in the case of the classical
    transpot model. A relation with the material in the papers by
    E. Marchi:Z.Wahrscheinlichtheorie verww. geb,12,220-230
    (1969) and 23,7-17, (1972), is underway.
    We were succesful to extend this theory to mixed model
    considering that in a deposit, there exists the possibility to
    stay or passing. This rich study permits more potentiality to
    the tools. An extension to several steps has been performed and
    its potentiality for applications is vast.
  • Trajectory measures describing the locomotor behavior of Drosophila melanogaster in a circular arena
    Dan Valente (Cold Spring Harbor Laboratory)
    Measuring locomotor behavior of Drosophila in enclosed arenas is a powerful way to obtain a quantitative behavioral phenotype. The measures previously used for this purpose are relatively coarse, thus ignoring fine scale movements of the fly. More importantly, they do not explicitly take into account how the arena shapes the dynamics of the locomotion. We acquired data using a video-tracking system to measure the trajectory of a fly over extended periods as it explores a circular arena. Based on this data, we present some metrics that take into consideration the dynamics of the trajectory, as well as the interactions of the trajectory with the geometry of the arena. The basic idea is to treat the locomotor trajectory of the fly as a stochastic process, and then estimate a set of marginal distributions of the probability measure describing this process. The measures include joint or individual distributions of position, speed, path curvature, inter-event times and re-orientation angles after stopping. These probability measures can be worked into other behavioral setups, are relatively easy to calculate using robust statistical estimation procedures, and can account for environmental effects on the behavior. They also serve as foundation for a quantitative stochastic process model of the walking behavior.
  • Biological project: The construction of the cycle in Lotka-Volterra of n-species
    Ezio Marchi (Instituto de Matemática Aplicada)
    Lotka-Volterra equations are very famous by two biological
    spices. Generally the most common presentations are in ecology
    science. We study this models without considering the
    antisymmetric condition among the parameters.(see Marchi and
    Velasco Revista Mexicana de Fisica,36,No4(1990)665-679).We
    obtain a movement constant for the systems which satisfies the
    Hamilton equation. For more than two interacting species the
    result the Volterra result are biologically improper. This is
    due to the antisymetric conditions. Following Volterra original
    methods combined with the variation of Montroll et. all, who
    applied such equation to maser and laser, we obtain some
    powerful personal procedure that we applied to the three and
    four species obtaining and general condition and build the
    cycle. Moreover this can be extended for an arbitrary number of
    biological species obtaining constructively the cycle. The
    background idea is to delete one variable at that time using
    partial differentials equations of second power of the first
    order. Furthermore we consider the conservation of the density
    of point in the fase space (LIoville theorem) an we postulate
    that the same distributions following the Gibbs Canonical Law.
    By the way Prigogyne at all applied Lotka-Volterra system in
    non-equilibrium thermodynamics. Moreover, there are several
    applications of Lotka-Volterra to the theory of membrane. We
    can show you some of them. Finally, we point out that
    there are about four hundred papers in the subject in the last
    ten years, and non of them apply our methods. The potentiality
    for real application is very important even if the system of
    Lotka-Volterra is asymptotically unstable.
  • A design principle in biochemical reaction networks

    based on realization theory

    Bassam Bamieh (University of California)
    We attempt to address the question of why there are so many intermediate species in biochemical
    reaction networks using an idea from realization theory. We describe how prescribed biological
    function can be designed with very low dimensional models, which are however not implementable
    with the physically allowable biochemical reaction mechanisms. It then becomes apparent that
    the introduction of a large number of intermediate species can be interpreted as a realization technique
    to enable the implementation of prescribed function with the available dynamical building blocks.
    By reversing this realization scheme, we propose a model reduction paradigm for biochemical reaction networks.
  • Architecture and inherent robustness of a bacterial cell cycle control system
    David Dill (Stanford University)
    Joint work with Xiling Shen, Justine Collier, Lucy Shapiro, Mark Horowitz, and Harley H. McAdams.

    We developed a mechanistic model of the cell cycle control of Caulobacter Crescentus. Symbolic model checking reveals that the cell cycle is extremely robust to parameter variations, and that the cell cycle starts and stops reliably to accommodate arbitrary starvation periods.
  • A transcriptional regulatory switch underlying B-cell terminal

    differentiation and its disruption by dioxin

    Sudin Bhattacharya (The Hamner Institutes for Health Sciences)
    Joint work with Qiang Zhang(1), Melvin E. Andersen(1)
    and Rory B.
    Conolly(2).


    The terminal differentiation of B cells in lymphoid organs into
    antibody-secreting plasma cells upon antigen stimulation is a
    crucial
    step in the humoral immune response. The architecture of the
    B-cell
    transcriptional regulatory network consists of coupled
    mutually-repressive feedback loops involving the three
    transcription
    factors Bcl6, Blimp1 and Pax5. This structure forms the basis
    of an
    irreversible bistable switch directing the B-cell to plasma
    cell
    differentiation process - i.e., the switch remains on even
    after the
    activating stimulus (antigen) is removed. The environmental
    contaminant
    2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) is known to suppress
    the
    humoral immune response by interfering with this
    differentiation
    program. We have developed a computational model of the
    biochemical
    pathways that regulate B-cell differentiation, and the
    molecular
    mechanism by which TCDD impairs this process through the action
    of the
    aryl hydrocarbon receptor (AhR). Using a kinetic model and
    bifurcation
    analysis, we propose that TCDD regulates the proportion of
    B-cells that
    differentiate into plasma cells by raising the threshold dose
    of antigen
    lipopolysaccharide (LPS) required to trigger the
    differentiation switch.
    We also show that stochastic modeling of gene expression, which
    allows
    cell-to-cell differences in content of signaling proteins,
    introduces
    distributional characteristics to the timing and probability of
    differentiation among a population of B-cells. This
    cell-to-cell
    variability is likely to be a key determinant of dose-response
    and
    sensitivity of individual cells to differentiation.

    (1) Division of Computational Biology, The Hamner Institutes
    for Health
    Sciences, Research Triangle Park, NC 27709, USA

    (2)
    National Center for Computational Toxicology, U.S.
    Environmental
    Protection Agency, Research Triangle Park, NC 27711, USA
  • Computational hemodynamics analysis in large blood

    vessels: Effects of hematocrit variation on flow stability

    Oluwole Makinde (University of Limpopo)
    Understanding the effects of blood viscosity
    variation plays
    a very crucial role in hemodynamics, thrombosis and
    inflammation and
    could provide useful information for diagnostics and therapy of
    (cardio)
    vascular disease. Blood viscosity, which arises from frictional
    interactions between all major blood constituents, i.e. plasma,
    plasma
    proteins and red blood cells, constitutes blood inherent
    resistance to
    flow in the blood vessel. Because red blood cells (RBCs) are
    the main
    constituent of the cellular phase of blood, white blood cells
    and
    platelets normally do not have a great influence on whole blood
    viscosity. When blood flows through a vessel, it tends to
    separate in
    two different phases. In direct contact with the wall a low
    viscosity
    phase exists, which is deficient in cells and rich in plasma
    and acts as
    a lubricant for the blood transport. In the central core region
    of the
    vessel a high viscosity phase exists, which depends on the
    hematocrit.
    In this paper, the nature and stability of blood flow in a
    large artery
    is investigated numerically using a spectral collocation
    technique with
    expansions in Chebyshev polynomials. The study reveals that a
    rise in
    hematocrit concentration in the central core region of a large
    artery
    has a stabilizing effect on the flow.
    Keywords: Arterial blood flow; Hematocrit; Variable viscosity;
    Temporal
    stability; Chebyshev spectral collocation technique

    References:

    1.) Pedley T. J.: The Fluid Mechanics of Large Blood Vessels.
    Cambridge
    University Press, London, 1980.

    2.) Makinde O. D.: Magneto-Hydromagnetic Stability of plane-
    Poiseuille
    flow using Multi-Deck asymptotic technique. Mathematical &
    Computer
    Modelling Vol. 37, No. 3-4, 251-259, 2003.

    3.) Makinde O. D. and Mhone P. Y.: Temporal stability of small
    disturbances in MHD Jeffery-Hamel flows. Computers and
    Mathematics with
    Applications, Vol. 53, 128–136, 2007.

    4.) Makinde O. D.: Entropy-generation analysis for
    variable-viscosity
    channel flow with non-uniform wall temperature. Applied Energy,
    Vol. 85,
    384-393, 2008.
  • Recurrent and robust patterns underlying human relative preference, and associations with brain circuitry plus genetics
    Hans Breiter MD (Massachusetts General Hospital)
    Joint work with BW Kim.

    The Phenotype Genotype Project on Addiction and Depression (PGP), with support from the Departments of Neurology, Psychiatry, and Radiology, and Center for Human Genetic Research; Massachusetts General Hospital and Harvard Medical School; Boston, MA, USA

    Positive and negative preferences can be assessed by keypress procedures that quantify (i) decision-making regarding approach, avoidance, indifference, and ambivalence responses, and (ii) judgments that determine the magnitude of approach and avoidance. Most prior studies of relative preference have not used keypress procedures, but have used ratings of personal utility, as a composite index of approach and avoidance. Such composite ratings can be calibrated against an absolute framework such as the macroeconomic pricing of commodities, as is done with Prospect Theory. It leaves open questions of whether or not splitting composite ratings of utility into approach and avoidance measures reveals any patterns in behavior, as observed for Prospect Theory. Such patterns might include a trade-off relationship between approach and avoidance, or a value function that might not need an absolute macroeconomic framework. We assessed these questions across multiple sets of healthy control sub
    jects with a keypress procedure, and found a set of patterns for approach and avoidance are (i) recurrent across many stimulus types, and (ii) robust to the injection of noise. These patterns include: (a) a preference trade-off plot that counterbalances approach and avoidance responses and represents biases in preference and consistency/uncertainty of preference, (b) a value function linking preference intensity to uncertainty about preference, and (c) a preference saturation plot that represents how avoidance actions are over-determined relative to approach actions. One can consider this set of patterns to be a form of relative preference theory (RPT), since they meet the same requirements for recurrency and robustness to noise as the Weber-Fechner-Stevens Law. As with the value function for Prospect Theory, the value function in RPT has a steeper slope for negative relative to positive preferences (i.e., loss aversion), and can be described as a power law, or a logarithmic functi
    on. All of these patterns show symmetry between group and individual data in that they have similar mathematical formulations as manifolds or boundary asymptotes for group data, or as fitted functions for individual data across multiple variables. These patterns verify known biases between females and males regarding viewing beautiful and average faces. When used to evaluate cocaine dependent subjects versus healthy controls, these patterns quantify the phenotype of the restricted behavioral repertoire observed in addiction. When used as regressors in the analysis of fMRI data, RPT measures are associated with significant BOLD signal change across a set of reward/aversion brain regions. Both keypress behavior and fMRI BOLD signal can be further associated with polymorphisms is genes such as CREB1 and BDNF. Given RPT scaling between groups of subjects and individuals, further work is warranted to assess if scaling can be achieved to brain circuitry and genetics.
  • Quantitative systems analysis of multicellular morphodynamics
    Anand Asthagiri (California Institute of Technology)
    The goal of my research program is to better understand how biological circuits program multicellular phenotypes. While a major focus of the group involves phenotypes associated with human epithelial systems, we have also drawn upon more tractable model systems, such as C. elegans and yeast, to glean deeper fundamental insights. Each of these three biological systems provides unique advantages that my lab has sought to exploit using a combination of computational and quantitative experimental approaches.