1980 Preface * 1999 Preface * 1999 Acknowledgements * Introduction * 1 Circular Logic * 2 Phase Singularities (Screwy Results of Circular Logic) * 3 The Rules of the Ring * 4 Ring Populations * 5 Getting Off the Ring * 6 Attracting Cycles and Isochrons * 7 Measuring the Trajectories of a Circadian Clock * 8 Populations of Attractor Cycle Oscillators * 9 Excitable Kinetics and Excitable Media * 10 The Varieties of Phaseless Experience: In Which the Geometrical Orderliness of Rhythmic Organization Breaks Down in Diverse Ways * 11 The Firefly Machine 12 Energy Metabolism in Cells * 13 The Malonic Acid Reagent ('Sodium Geometrate') * 14 Electrical Rhythmicity and Excitability in Cell Membranes * 15 The Aggregation of Slime Mold Amoebae * 16 Numerical Organizing Centers * 17 Electrical Singular Filaments in the Heart Wall * 18 Pattern Formation in the Fungi * 19 Circadian Rhythms in General * 20 The Circadian Clocks of Insect Eclosion * 21 The Flower of Kalanchoe * 22 The Cell Mitotic Cycle * 23 The Female Cycle * References * Index of Names * Index of Subjects

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The geometry of biological time , by A. T. Winfree. Pp 544. DM68. Corrected Second Printing 1990. ISBN 3-540-52528-9 (Springer)

to be done in this area. Face recognition is a problem that scarcely clamoured for attention before the computer age but, having surfaced, has involved a wide range of techniques and has attracted the attention of some fine minds (David Mumford was a Fields Medallist in 1974). This singular application of mathematical modelling to a messy applied problem of obvious utility and importance but with no unique solution is a pretty one to share with students: perhaps, returning to the source of our opening quotation, we may invert Duncan's earlier observation, 'There is an art to find the mind's construction in the face!'.

Linear and nonlinear waves, by G. B. Whitham. Pp.636. £50. 1999. ISBN 0 471 35942 4 (Wiley).

Statistical physics of vehicular traffic and some related systems

Random-matrix theories in quantum physics : common concepts

Extraction and Solubilization of Proteins for Proteomic Studies Richard M. Leimgruber Preparation of Bacterial Samples for 2-D PAGE Brian Berg Vandahl, Gunna Christiansen, and Svend Birkelund Preparation of Yeast Samples for 2-D PAGE Joakim Norbeck Preparation of Mammalian Tissue Samples for Two-Dimensional Electrophoresis Frank A. Witzmann Differential Detergent Fractionation of Eukaryotic Cells Melinda L. Ramsby and Gregory S. Makowski Serum or Plasma Sample Preparation for Two-Dimensional Gel Electrophoresis Anthony G. Sullivan, Stephen Russell, Henry Brzeski, Richard I. Somiari, and Craig D. Shriver Preparation of Plant Protein Samples for 2-D PAGE David W. M. Leung Laser-Assisted Microdissection in Proteomic Analyses Darrell L. Ellsworth, Stephen Russell, Brenda Deyarmin, Anthony G. Sullivan, Henry Brzeski, Richard I. Somiari, and Craig D. Shriver Purification of Cellular and Organelle Populations by Fluorescence-Activated Cell Sorting for Proteome Analysis William L. Godfrey, Colette J. Rudd, Sujata Iyer, and Diether Recktenwald Purification of Nucleoli From Lymphoma Cells and Solubilization of Nucleolar Proteins for 2-DE Separation Regis Dieckmann, Yohann Coute, Denis Hochstrasser, Jean-Jacques Diaz, and Jean-Charles Sanchez Prefractionation of Complex Protein Mixture for 2-D PAGE Using Reversed-Phase Liquid Chromatography Volker Badock and Albrecht Otto Fractionation of Complex Proteomes by Microscale Solution Isoelectrofocusing Using ZOOM(TM) IEF Fractionators to Improve Protein Profiling Xun Zuo, Ki-Boom Lee, and David W. Speicher Large-Format 2-D Polyacrylamide Gel Electrophoresis Henry Brzeski, Stephen Russell, Anthony G. Sullivan, Richard I. Somiari, and Craig D. Shiver Analysis of Membrane Proteins by Two-Dimensional Gels MichaelFountoulakis 2-D PAGE of High-Molecular-Mass Proteins Masamichi Oh-Ishi and Tadakazu Maeda Using Ultra-Zoom Gels for High-Resolution Two-Dimensional Polyacrylamide Gel Electrophoresis Sjouke Hoving, Hans Voshol, and Jan van Oostrum NEpHGE and pI Strip Proteomic 2-D Gel Electrophoretic Mapping of Lipid-Rich Membranes Steven E. Pfeiffer, Yoshihide Yamaguchi, Cecilia B. Marta, Rashmi Bansal, and Christopher M. Taylor Silver Staining of 2-D Gels Julia Poland, Thierry Rabilloud, and Pranav Sinha Zn2+ Reverse Staining Technique Carlos Fernandez-Patron Multiplexed Proteomics Technology for the Fluorescence Detection of Glycoprotein Levels and Protein Expression Levels Using Pro-Q(R) Emerald and SYPRO(R) Ruby Dyes Birte Schulenberg and Wayne F. Patton Multiplexed Proteomics Technology for the Fluorescence Detection of Phosphorylation and Protein Expression Levels Using Pro-Q(R) Diamond and SYPRO(R) Ruby Dyes Birte Schulenberg, Terrie Goodman, Thomas H. Steinberg, and Wayne F. Patton Sensitive Quantitative Fluorescence Detection of Proteins in Gels Using SYPRO(R) Ruby Protein Gel Stain Birte Schulenberg, Nancy Ahnert, and Wayne F. Patton Rapid, Sensitive Detection of Proteins in Minigels With Fluorescent Dyes: Coomassie Fluor Orange, SYPRO(R) Orange, SYPRO Red, and SYPRO Tangerine Protein Gel Stains Thomas H. Steinberg, Courtenay R. Hart, and Wayne F. Patton Differential In-Gel Electrophoresis in a High-Throughput Environment Richard I. Somiari, Stephen Russell, Stella B. Somiari, Anthony G. Sullivan, Darrell L. Ellsworth, Henry Brzeski, and Craig D. Shriver Statistical Analysis of 2-D Gel Patterns Francoise Seillier-Moiseiwitsch 2-DE Databases on the World Wide Web Christine Hoogland, Khaled Mostaguir, and Ron D. Appel Computer Analysis of 2-D Images Patricia M. Palagi,

The proteomics protocols handbook

The power spectrum of the potential energy fluctuation of liquid water is examined and found to yield so‐called 1/f frequency dependence (f is frequency). This is in sharp contrast to spectra of simple liquids (e.g., liquid argon), which exhibit a near white spectrum. This indicates that there exists an extended multiplicity of hydrogen bond network relaxations in liquid water. A simple model of cellular dynamics is proposed to explain this frequency dependence. On the other hand, the cluster dynamics of argon also involves energy fluctuations of a 1/f type, resulting from various relaxation processes at core and surface.

Long time fluctuation of liquid water: 1/f spectrum of energy fluctuation in hydrogen bond network rearrangement dynamics

We compare the annotation of three complete genomes using theab initio methods of gene identification GeneScan and GLIMMER. The annotation given in GenBank, the standard against which these are compared, has been made using GeneMark. We find a number of novel genes which are predicted by both methods used here, as well as a number of genes that are predicted by GeneMark, but are not identified by either of the nonconsensus methods that we have used. The three organisms studied here are all prokaryotic species with fairly compact genomes. The Fourier measure forms the basis for an efficient non-consensus method for gene prediction, and the algorithm GeneScan exploits this measure. We have bench-marked this program as well as GLIMMER using 3 complete prokaryotic genomes. An effort has also been made to study the limitations of these techniques for complete genome analysis. GeneScan and GLIMMER are of comparable accuracy insofar as gene-identification is concerned, with sensitivities and specificities typically greater than 0.9. The number of false predictions (both positive and negative) is higher for GeneScan as compared to GLIMMER, but in a significant number of cases, similar results are provided by the two techniques. This suggests that there could be some as-yet unidentified additional genes in these three genomes, and also that some of the putative identifications made hitherto might require re-evaluation. All these cases are discussed in detail.

/pdf/ab-initio-gene-identification-prokaryote-genome-annotation-3wurxhbaip.pdf

Ab initio gene identification: prokaryote genome annotation with GeneScan and GLIMMER.

We characterize the steady state of a driven diffusive lattice gas in which each site holds several particles, and the dynamics is activated and asymmetric. Using a quantum Hamiltonian formalism, we show that for arbitrary transition rates the model has product invariant measure. In the steady state, a pairwise balance condition is shown to hold. Configurations n 00 and n 0 leading respectively into and out of a given configuration n are matched in pairs so that the flux of transitions from n 00 to n is equal to the flux from n to n 0 . Pairwise balance is more general than the condition of detailed balance and holds in the non-equilibrium steady state of a number of stochastic models.

Pairwise balance and invariant measures for generalized exclusion processes

We study the probability densities of finite-time or local Lyapunov exponents in low-dimensional chaotic systems. While the multifractal formalism describes how these densities behave in the asymptotic or long-time limit, there are significant finite-size corrections, which are coordinate dependent. Depending on the nature of the dynamical state, the distribution of local Lyapunov exponents has a characteristic shape. For intermittent dynamics, and at crises, dynamical correlations lead to distributions with stretched exponential tails, while for fully developed chaos the probability density has a cusp. Exact results are presented for the logistic map, $\stackrel{\ensuremath{\rightarrow}}{x}4x(1\ensuremath{-}x).$ At intermittency the density is markedly asymmetric, while for ``typical'' chaos, it is known that the central limit theorem obtains and a Gaussian density results. Local analysis provides information on the variation of predictability on dynamical attractors. These densities, which are used to characterize the nonuniform spatial organization on chaotic attractors, are robust to noise and can, therefore, be measured from experimental data.

Characteristic distributions of finite-time Lyapunov exponents.

Recently, the phase-flip bifurcation has been described as a fundamental transition in time-delay coupled, phase-synchronized nonlinear dynamical systems. The bifurcation is characterized by a change of the synchronized dynamics from being in-phase to antiphase, or vice versa; the phase-difference between the oscillators undergoes a jump of pi as a function of the coupling strength or the time delay. This phase-flip is accompanied by discontinuous changes in the frequency of the synchronized oscillators, and in the largest negative Lyapunov exponent or its derivative. Here we illustrate the phenomenology of the bifurcation for several classes of nonlinear oscillators, in the regimes of both periodic and chaotic dynamics. We present extensive numerical simulations and compute the oscillation frequencies and the Lyapunov spectra as a function of the coupling strength. In particular, our simulations provide clear evidence of the phase-flip bifurcation in excitable laser and Fitzhugh-Nagumo neuronal models, and in diffusively coupled predator-prey models with either limit cycle or chaotic dynamics. Our analysis demonstrates marked jumps of the time-delayed and instantaneous fluxes between the two interacting oscillators across the bifurcation; this has strong implications for the performance of the system as well as for practical applications. We further construct an electronic circuit consisting of two coupled Chua oscillators and provide the first formal experimental demonstration of the bifurcation. In totality, our study demonstrates that the phase-flip phenomenon is of broad relevance and importance for a wide range of physical and natural systems.

Ramakrishna Ramaswamy

Papers

Long time fluctuation of liquid water: 1/f spectrum of energy fluctuation in hydrogen bond network rearrangement dynamics

Ab initio gene identification: prokaryote genome annotation with GeneScan and GLIMMER.

Pairwise balance and invariant measures for generalized exclusion processes

Characteristic distributions of finite-time Lyapunov exponents.

Universal occurrence of the phase-flip bifurcation in time-delay coupled systems