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arXiv2011

Dynamics of glucose-lactose diauxic growth in E. coli

We present a mathematical model of glucose-lactose diauxic growth in Escherichia coli including both the postive and negative regulation mechanisms of the lactose operon as well as the inducer exclusion. To validate this model, we first calculated the time evolution of beta-galactosidase for only the lactose nutrient and compared the numerical results with experimental data. Second, we compared the calculated cell biomass of the glucose-lactose diauxic growth with the experimental optical density of the diauxic growth for a particular E. coli MG 1655. For both cases, the numerical calculations from this model are in good agreement with these two experiments' data. The diauxic growth pattern of a wild type E. coli was also investigated.

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arXiv2007

A model for exploring bird morphology

A simplified model of the bird skeleton along with elongation parameters for the flight feathers is used to explore the diversity of bird shapes. Varying a small number of parameters simulates a wide range of observed bird silhouettes. The model may serve to examine developmental factors involved, help museum curators develop computational approaches to bird morphometry and has applications in computer generated illustration.

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arXiv2007

Borges Dilemma, Fundamental Laws, and Systems Biology

I reason here that the known folk law in biology that there is no general law in biology because of exceptions is false. The (quantitative) systems biology offers the potential to solve the Borges Dilemma, by transcending it. There have already a plenty of indications on this trend.

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arXiv2008

Efficient Implementation of the AI-REML Iteration for Variance Component QTL Analysis

Regions in the genome that affect complex traits, quantitative trait loci (QTL), can be identified using statistical analysis of genetic and phenotypic data. When restricted maximum-likelihood (REML) models are used, the mapping procedure is normally computationally demanding. We develop a new efficient computational scheme for QTL mapping using variance component analysis and the AI-REML algorithm. The algorithm uses an exact or approximative low-rank representation of the identity-by-descent matrix, which combined with the Woodbury formula for matrix inversion results in that the computations in the AI-REML iteration body can be performed more efficiently. For cases where an exact low-rank representation of the IBD matrix is available a-priori, the improved AI-REML algorithm normally runs almost twice as fast compared to the standard version. When an exact low-rank representation is not available, a truncated spectral decomposition is used to determine a low-rank approximation. We show that also in this case, the computational efficiency of the AI-REML scheme can often be significantly improved.

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arXiv2007

Effect of THz-radiation on Behavior of Male Mice

Effect of terahertz radiation (3.6 THz, 81.5 mkm,15 mV) on some behavioral patterns of intact mice has been investigated. In home cage mice demonstrated avoidance of laser ray and enhanced replacement activity in free behavior. Animals irradiated during 30 minutes manifested an increased level of anxiety, which was evaluated in the plus maze test on the day following the radiation.

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arXiv2007

Complexity, Collective Effects and Modelling of Ecosystems: formation, function and stability

We discuss the relevance of studying ecology within the framework of Complexity Science from a statistical mechanics approach. Ecology is concerned with understanding how systems level properties emerge out of the multitude of interactions amongst large numbers of components, leading to ecosystems that possess the prototypical characteristics of complex systems. We argue that statistical mechanics is at present the best methodology available to obtain a quantitative description of complex systems, and that ecology is in urgent need of ``integrative'' approaches that are quantitative and non-stationary. We describe examples where combining statistical mechanics and ecology has led to improved ecological modelling and, at the same time, broadened the scope of statistical mechanics.

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arXiv2008

Top-Down Causation by Information Control: From a Philosophical Problem to a Scientific Research Program

It has been claimed that different types of causes must be considered in biological systems, including top-down as well as same-level and bottom-up causation, thus enabling the top levels to be causally efficacious in their own right. To clarify this issue, important distinctions between information and signs are introduced here and the concepts of information control and functional equivalence classes in those systems are rigorously defined and used to characterise when top down causation by feedback control happens, in a way that is testable. The causally significant elements we consider are equivalence classes of lower level processes, realised in biological systems through different operations having the same outcome within the context of information control and networks.

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arXiv2008

The immune system: look who's talking

Human language and its governing rules present a number of analogies with the organization and structure of communication and information management in living organisms. This chapter will provide a short general introduction about grammar, as well as a brief explanation on how linguistic approaches effectively contaminate scientific practice, and, finally, how they can also provide systems biology with further tools and paradigms to analyse emergent behaviours and interactions among the components of a biological system.

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arXiv2009

Imposition of Different Optimizing Object with Non-Linear Constraints on Flux Sampling and Elimination of Free Futile Pathways

Constraint-based modeling has been widely used on metabolic networks analysis, such as biosynthetic prediction and flux optimization. The linear constraints, like mass conservation constraint, reversibility constraint, biological capacity constraint, can be imposed on linear algorithms. However, recently a non-linear constraint based on the second thermodynamic law, known as "loop law", has emerged and challenged the existing algorithms. Proven to be unfeasible with linear solutions, this non-linear constraint has been successfully imposed on the sampling process. In this place, Monte - Carlo sampling with Metropolis criterion and Simulated Annealing has been introduced to optimize the Biomass synthesis of genome scale metabolic network of Helicobacter pylori (iIT341 GSM / GPR) under mass conservation constraint, biological capacity constraint, and thermodynamic constraints including reversibility and "loop law". The sampling method has also been employed to optimize a non-linear objective function, the Biomass synthetic rate, which is unified by the total income number of reducible electrons. To verify whether a sample contains internal loops, an automatic solution has been developed based on solving a set of inequalities. In addition, a new type of pathway has been proposed here, the Futile Pathway, which has three properties: 1) its mass flow could be self-balanced; 2) it has exchange reactions; 3) it is independent to the biomass synthesis. To eliminate the fluxes of the Futile Pathways in the sampling results, a linear programming based method has been suggested and the results have showed improved correlations among the reaction fluxes in the pathways related to Biomass synthesis.

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arXiv2007

Newton-type Methods for REML Estimation in Genetic Analysis of Quantitative Traits

Robust and efficient optimization methods for variance component estimation using Restricted Maximum Likelihood (REML) models for genetic mapping of quantitative traits are considered. We show that the standard Newton-AI scheme may fail when the optimum is located at one of the constraint boundaries, and we introduce different approaches to remedy this by taking the constraints into account. We approximate the Hessian of the objective function using the average information matrix and also by using an inverse BFGS formula. The robustness and efficiency is evaluated for problems derived from two experimental data from the same animal populations.

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arXiv2007

Nucleosome shape dictates chromatin-fiber structure

Apart from being the gateway for all access to the eukaryotic genome, chromatin has in recent years been identified as carrying an epigenetic code regulating transcriptional activity. The detailed knowledge of this code contrasts the ignorance of the fiber structure which it regulates, and none of the suggested fiber models are capable of predicting the most basic quantities of the fiber (diameter, nucleosome line density, etc.). We address this three-decade-old problem by constructing a simple geometrical model based on the nucleosome shape alone. Without fit parameters we predict the observed properties of the condensed chromatin fiber (e.g. its 30 nm diameter), the structure, and how the fiber changes with varying nucleosome repeat length. Our approach further puts the plethora of previously suggested models within a coherent framework, and opens the door to detailed studies of the interplay between chromatin structure and function.

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arXiv2007

Constructing Bio-molecular Databases on a DNA-based Computer

Codd [Codd 1970] wrote the first paper in which the model of a relational database was proposed. Adleman [Adleman 1994] wrote the first paper in which DNA strands in a test tube were used to solve an instance of the Hamiltonian path problem. From [Adleman 1994], it is obviously indicated that for storing information in molecules of DNA allows for an information density of approximately 1 bit per cubic nm (nanometer) and a dramatic improvement over existing storage media such as video tape which store information at a density of approximately 1 bit per 1012 cubic nanometers. This paper demonstrates that biological operations can be applied to construct bio-molecular databases where data records in relational tables are encoded as DNA strands. In order to achieve the goal, DNA algorithms are proposed to perform eight operations of relational algebra (calculus) on bio-molecular relational databases, which include Cartesian product, union, set difference, selection, projection, intersection, join and division. Furthermore, this work presents clear evidence of the ability of molecular computing to perform data retrieval operations on bio-molecular relational databases.

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arXiv2007

Information retrieval from a phoneme time series database

Developing fast and efficient algorithms for retrieval of objects to a given user query is an area of active research. The present study investigates retrieval of time series objects from a phoneme database to a given user pattern or query. The proposed method maps the one-dimensional time series retrieval into a sequence retrieval problem by partitioning the multi-dimensional phase-space using k-means clustering. The problem of whole sequence as well as subsequence matching is considered. Robustness of the proposed technique is investigated on phoneme time series corrupted with additive white Gaussian noise. The shortcoming of classical power-spectral techniques for time series retrieval is also discussed.

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arXiv2007

Simulating Genomes and Populations in the Mutation Space: An example with the evolution of HIV drug resistance

When simulating biological populations under different evolutionary genetic models, backward or forward strategies can be followed. Backward simulations, also called coalescent-based simulations, are computationally very efficient. However, this framework imposes several limitations that forward simulation does not. In this work, a new simple and efficient model to perform forward simulation of populations and/or genomes is proposed. The basic idea considers an individual as the differences (mutations) between this individual and a reference or consensus genotype. Thus, this individual is no longer represented by its complete sequence or genotype. An example of the efficiency of the new model with respect to a more classical forward one is demonstrated. This example models the evolution of HIV resistance using the B_FR.HXB2 reference sequence to study the emergence of known resistance mutants to Zidovudine and Didanosine drugs

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arXiv2008

Size-independent differences between the mean of discrete stochastic systems and the corresponding continuous deterministic systems

In this paper I show that, for a class of reaction networks, the discrete stochastic nature of the reacting species and reactions results in qualitative and quantitative differences between the mean of exact stochastic simulations and the prediction of the corresponding deterministic system. The differences are independent of the number of molecules of each species in the system under consideration. These reaction networks are open systems of chemical reactions with no zero-order reaction rates systems. They are characterized by at least two stationary points, one of which is a nonzero stable point, and one unstable trivial solution (stability based on a linear stability analysis of the deterministic system). Starting from a nonzero initial condition, the deterministic system never reaches the zero stationary point due to its unstable nature. In contrast, the result presented here proves that this zero-state is the only stable stationary state for the discrete stochastic system. This result generalizes previous theoretical studies and simulations of specific systems and provides a theoretical basis for analyzing a class of systems that exhibit such inconsistent behavior. This result has implications in the simulation of infection, apoptosis, and population kinetics, as it can be shown that for certain models the stochastic simulations will always yield different predictions for the mean behavior than the deterministic simulations.

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arXiv2008

Nemo: a computational tool for analyzing nematode locomotion

The nematode Caenorhabditis elegans responds to an impressive range of chemical, mechanical and thermal stimuli and is extensively used to investigate the molecular mechanisms that mediate chemosensation, mechanotransduction and thermosensation. The main behavioral output of these responses is manifested as alterations in animal locomotion. Monitoring and examination of such alterations requires tools to capture and quantify features of nematode movement. In this paper, we introduce Nemo (nematode movement), a computationally efficient and robust two-dimensional object tracking algorithm for automated detection and analysis of C. elegans locomotion. This algorithm enables precise measurement and feature extraction of nematode movement components. In addition, we develop a Graphical User Interface designed to facilitate processing and interpretation of movement data. While, in this study, we focus on the simple sinusoidal locomotion of C. elegans, our approach can be readily adapted to handle complicated locomotory behaviour patterns by including additional movement characteristics and parameters subject to quantification. Our software tool offers the capacity to extract, analyze and measure nematode locomotion features by processing simple video files. By allowing precise and quantitative assessment of behavioral traits, this tool will assist the genetic dissection and elucidation of the molecular mechanisms underlying specific behavioral responses.

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arXiv2008

Study Of Spatial Biological Systems Using a Graphical User Interface

In this paper, we describe a Graphical User Interface (GUI) designed to manage large quantities of image data of a biological system. After setting the design requirements for the system, we developed an ecology quantification GUI that assists biologists in analysing data. We focus on the main features of the interface and we present the results and an evaluation of the system. Finally, we provide some directions for some future work.

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arXiv2008

Biological Organization and Negative Entropy: Based on Schroedinger's reflections

This paper proposes a systemic perspective for some aspects of both phylogenesis and ontogenesis, in the light of the notion of biological organization as negative entropy, following some hints by Schroedinger. To this purpose, we introduce two extra principles to the thermodynamic ones, which are (mathematically) compatible with the traditional principles, but have no meaning in inert matter. A traditional balance equation for metabolism will be then extended to the new notion as specified by these principles. We consider far from equilibrium systems and we focus in particular on the production of global entropy associated to the irreversible character of the processes. A close analysis of this term will be carried on, both in terms of a diffusion equation of biomass over complexity and, as a complementary approach and as a tool for specifying a source term, in connection to Schroedinger's method for his equation in Quantum Mechanics. We borrow from this equation just the operatorial approach and, this, in a classical frame, as we use real coefficients instead of complex ones, away thus from the mathematical frame of quantum theories. The first application of our proposal is a simple mathematical reconstruction of Gould's complexity curve of biomass over complexity, as for evolution. We then elaborate, from the existence of different time scales, a partition of ontogenetic time, in reference to entropy and negative entropy variation. On the grounds of this approach, we analyze metabolism and scaling laws. This allows to compare various relevant coefficients appearing in these scaling laws, which seem to fit empirical data. Finally, a tentative and quantitative evaluation of complexity is proposed, also in relation to some empirical data (caenorhabditis elegans).

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