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arXiv1997

Testing a new Monte Carlo Algorithm for Protein Folding

We demonstrate that the recently proposed pruned-enriched Rosenbluth method PERM (P. Grassberger, Phys. Rev. E, in press (1997)) leads to extremely efficient algorithms for the folding of simple model proteins. We test it on several models for lattice heteropolymers, and compare to published Monte Carlo studies of the properties of particular sequences. In all cases our method is faster than the previous ones, and in several cases we find new minimal energy states. In addition to producing more reliable candidates for ground states, our method gives detailed information about the thermal spectrum and, thus, allows to analyze static aspects of the folding behavior of arbitrary sequences.

cond-mat.stat-mech↗

arXiv1998

The Lack of Long Range Correlations is a Necessary Condition for a Functional Biologically Active Protein

We study random heteropolymer chain with gaussian distribution of kinds of monomers. The long-range correlations between kinds of monomers were introduce. The mean-field analysis of such heteropolymer indicates the existence of infinite energetic barrier between heteropolymer random coil and frozen states. Thus, the frozen state is kinetically unavailable for the random heteropolymer with power-law correlations in monomers' sequence. The relationship between our results and some early obtained results for the DNA intrones sequences are discussed.

cond-mat.soft↗

arXiv1998

Cooperativity in Protein Folding: From Lattice Models with Side Chains to Real Proteins

We consider equilibrium folding transitions in lattice protein models with and without side chains. A dimensionless measure, $Omega_{c}$, is introduced to quantitatively assess the degree of cooperativity in lattice models and in real proteins. We show that larger values of $Ω_{c}$ resembling those seen in proteins are obtained in lattice models with side chains (LMSC). The enhanced cooperativity in LMSC is due to the possibility of denser packing of side chains in the interior of the model protein. We also establish that $Ω_{c}$ correlates extremely well with (σ= (T_θ -T_{f} )/T_θ), where (T_θ) and (T_{f}) are collapse and folding transition temperatures, respectively. These theoretical ideas are used to analyze folding transitions in various real proteins. The values of $Ω_{c}$ extracted from experiments show a correlation with $σ$. We conclude that the degree of cooperativity can be expressed in terms of the single parameter $σ$, which can be estimated from experimental data.

cond-mat.soft↗

arXiv2000

Mutual Information of Three-State Low Activity Diluted Neural Networks with Self-Control

The influence of a macroscopic time-dependent threshold on the retrieval process of three-state extremely diluted neural networks is examined. If the threshold is chosen appropriately in function of the noise and the pattern activity of the network, adapting itself in the course of the time evolution, it guarantees an autonomous functioning of the network. It is found that this self-control mechanism considerably improves the retrieval quality, especially in the limit of low activity, including the storage capacity, the basins of attraction and the information content. The mutual information is shown to be the relevant parameter to study the retrieval quality of such low activity models. Numerical results confirm these observations.

cond-mat.stat-mech↗

arXiv1999

Master equation approach to protein folding

The dynamics of two 12-monomer heteropolymers on the square lattice is studied exactly within the master equation approach. The time evolution of the occupancy of the native state is determined. At low temperatures, the median folding time follows the Arrhenius law and is governed by the longest relaxation time. For good folders, significant kinetic traps appear in the folding funnel whereas for bad folders, the traps also occur in non-native energy valleys.

cond-mat.stat-mech↗

arXiv1998

The role of the energy gap in protein folding dynamics

The dynamics of folding of proteins is studied by means of a phenomenological master equation. The energy distribution is taken as a truncated exponential for the misfolded states plus a native state sitting below the continuum. The influence of the gap on the folding dynamics is studied, for various models of the transition probabilities between the different states of the protein. We show that for certain models, the relaxation to the native state is accelerated by increasing the gap, whereas for others it is slowed down .

cond-mat.soft↗

arXiv1998

Identifying the protein folding nucleus using molecular dynamics

Molecular dynamics simulations of folding in an off-lattice protein model reveal a nucleation scenario, in which a few well-defined contacts are formed with high probability in the transition state ensemble of conformations. Their appearance determines folding cooperativity and drives the model protein into its folded conformation.

cond-mat.stat-mech↗

arXiv1999

Collectivity in the Brain Sensory Response

A question of cooperative effects in auditory brain processing on various space- and time-scales is addressed. The experimental part of our study is based on Multichannel Magnetoencephalography recordings in normal human subjects. Left, right and binaural stimulations were used, in separate runs, for each subject. The resulting time-series representing left and right auditory cortex activity provide a clear evidence for two levels of neuronal cooperation. One is the local hemispheric collective response, termed M100 for its maximum at around 100ms after a stimulus onset. Its only global characteristics turn out to be time-locked to a stimulus, however, which means that the detailed neuronal evolution is largely stochastic. This, together with the $1/f$ character of the corresponding power spectrum indicates self-organized criticality as an underlying mechanism. The second level is communication between the two hemispheres with clear laterality effects: as a rule, the contralateral hemisphere leads by $\sim$10ms. Mutual information analysis points to a direct information transport as a way of this communication.

cond-mat↗

arXiv1999

Cortical Potential Distributions and Cognitive Information Processing

The use of cortical field potentials rather than the details of spike trains as the basis for cognitive information processing is proposed. This results in a space of cognitive elements with natural metrics. Sets of spike trains may also be considered to be points in a multidimensional metric space. The closeness of sets of spike trains in such a space implies the closeness of points in the resulting function space of potential distributions.

cond-mat.dis-nn↗

arXiv1999

Evolution of Fragments Formed at the Rupture of a Knotted Alkane Molecule

Common experience tells us that a knot significantly weakens the polymer strand in which it is tied, which in turn leads to more facile chain rupture under tensile loading. Using first-principles molecular dynamics calculations we describe the dynamical evolution of the radicals that form after chain rupture of a single knotted alkane molecule in their very early stages of life. They are able to recombine, to form cyclic alkanes and to undergo disproportionation phenomena with nearby chain segments. The breaking of a single knotted polymer chain under mechanical loading is thus predicted to reveal phenomena falling in the domain of ultrafast spectroscopy.

cond-mat.mtrl-sci↗

arXiv1999

Self-localization of directed polymers and oppressive population control

We construct a phenomenological theory of self-localization of directed polymers in d+1 dimensions. In d=1 we show that the polymer is always self-localized, whereas in d=2 there is a phase transition between localized and free states. We also map this system to a model of population dynamics with fixed total population. Our previous results translate to static and expanding population clusters, depending on the birth and death rates. A novel ``pseudo-travelling wave'' is observed in some sectors of parameter space.

cond-mat.stat-mech↗

arXiv2003

Barnacle: An Assembly Algorithm for Clone-based Sequences of Whole Genomes

We propose an assembly algorithm {\sc Barnacle} for sequences generated by the clone-based approach. We illustrate our approach by assembling the human genome. Our novel method abandons the original physical-mapping-first framework. As we show, {\sc Barnacle} more effectively resolves conflicts due to repeated sequences. The latter is the main difficulty of the sequence assembly problem. Inaddition, we are able to detect inconsistencies in the underlying data. We present and compare our results on the December 2001 freeze of the public working draft of the human genome with NCBI's assembly (Build 28). The assembly of December 2001 freeze of the public working draft generated by {\sc Barnacle} and the source code of {\sc Barnacle} are available at (http://www.cs.rutgers.edu/~vchoi).

cs.DS↗

arXiv1995

On the Informativeness of the DNA Promoter Sequences Domain Theory

The DNA promoter sequences domain theory and database have become popular for testing systems that integrate empirical and analytical learning. This note reports a simple change and reinterpretation of the domain theory in terms of M-of-N concepts, involving no learning, that results in an accuracy of 93.4% on the 106 items of the database. Moreover, an exhaustive search of the space of M-of-N domain theory interpretations indicates that the expected accuracy of a randomly chosen interpretation is 76.5%, and that a maximum accuracy of 97.2% is achieved in 12 cases. This demonstrates the informativeness of the domain theory, without the complications of understanding the interactions between various learning algorithms and the theory. In addition, our results help characterize the difficulty of learning using the DNA promoters theory.

cs.AI↗

arXiv1997

Analysis of Three-Dimensional Protein Images

A fundamental goal of research in molecular biology is to understand protein structure. Protein crystallography is currently the most successful method for determining the three-dimensional (3D) conformation of a protein, yet it remains labor intensive and relies on an expert's ability to derive and evaluate a protein scene model. In this paper, the problem of protein structure determination is formulated as an exercise in scene analysis. A computational methodology is presented in which a 3D image of a protein is segmented into a graph of critical points. Bayesian and certainty factor approaches are described and used to analyze critical point graphs and identify meaningful substructures, such as alpha-helices and beta-sheets. Results of applying the methodologies to protein images at low and medium resolution are reported. The research is related to approaches to representation, segmentation and classification in vision, as well as to top-down approaches to protein structure prediction.

cs.AI↗

arXiv1994

Gauge theory of things alive and universal dynamics

Positing complex adaptive systems made of agents with relations between them that can be composed, it follows that they can be described by gauge theories similar to elementary particle theory and general relativity. By definition, a universal dynamics is able to determine the time development of any such system without need for further specification. The possibilities are limited, but one of them - reproduction fork dynamics - describes DNA replication and is the basis of biological life on earth. It is a universal copy machine and a renormalization group fixed point. A universal equation of motion in continuous time is also presented.

hep-lat↗

arXiv1999

A Modified Equation for Neural Conductance and Resonance

A modified equation, the S-K equation, fits data that the current neural conduction equation, the K-R equation, does not. The S-K equation is a modified Heaviside equation, based on a new interpretation of cross terms. Elements of neural anatomy and function are reviewed to put the S-K equation into context. The fit between S-K and resonance-like neural data is then shown. Appendix 1: Derivation of crossterms that represent combinations of physical laws for a line conductor of finite length. Appendix 2: Evaluation of crossterms that represent combinations of physical laws according to consistency arguments. Appendix 3: Some background on resonance. Appendix 4: Web access to some brain modeling, correspondence with NATURE, and discussion of the work in George Johnson's New York Times forums.

math-ph↗

arXiv2000

Destruction of CD4 T Lymphocytes Alone Cannot Account for their Long-term Decrease in AIDS

Following previous models describing a quasi steady state (QSS) for the evolution of HIV infection and AIDS, we have developed a larger formalism simulating the long-term evolution of the QSS We show that the long-term evolution of AIDS cannot be explained by the destruction alone of CD4 T cells, either directly or indirectly. The destruction of CD4 T cells can lead only to a QSS with a lower concentration of CD4 T cells, but CD4 destruction cannot generate the sustained long-term decrease in T cells leading to AIDS. We here suggest some workable explanations.

math.DS↗

arXiv2001

In search of an evolutionary coding style

In the near future, all the human genes will be identified. But understanding the functions coded in the genes is a much harder problem. For example, by using block entropy, one has that the DNA code is closer to a random code then written text, which in turn is less ordered then an ordinary computer code; see \cite{schmitt}. Instead of saying that the DNA is badly written, using our programming standards, we might say that it is written in a different style -- an evolutionary style. We will suggest a way to search for such a style in a quantified manner by using an artificial life program, and by giving a definition of general codes and a definition of style for such codes.

math.NA↗