Biblioteca Digital

Detecting genomic footprints of selection is an important step in the understanding of evolution. Accounting for linkage disequilibrium in genome scans allows increasing the detection power, but haplotype-based methods require individual genotypes and are not applicable on pool-sequenced samples. We propose to take advantage of the local score approach to account for linkage disequilibrium, accumulating (possibly small) signals from single markers over a genomic segment, to clearly pinpoint a selection signal, avoiding windowing methods. This method provided results similar to haplotype-based methods on two benchmark data sets with individual genotypes. Results obtained for a divergent selection experiment on behavior in quail, where two lines were sequenced in pools, are precise and biologically coherent, while competing methods failed: our approach led to the detection of signals involving genes known to act on social responsiveness or autistic traits. This local score approach is general and can be applied to other genome-wide analyzes such as GWAS or genome scans for selection.; Comment: 32 pages, 4 figures

L\'evy flights represent the best strategy to randomly search for a target in an unknown environment, and have been widely observed in many animal species. Here, we inspect and discuss recent results concerning human behavior and cognition. Different studies have shown that human mobility can be described in terms of L\'evy flights, while fresh evidence indicates that the same pattern accounts for human mental searches in online gambling sites. Thus, L\'evy flights emerge as a unifying concept with broad cross-disciplinary implications. We argue that the ubiquity of such a pattern, both in behavior and cognition, suggests that the brain regions responsible for this behavior are likely to be evolutionarily old (i.e. no frontal cortex is involved), and that fMRI techniques might help to confirm this hypothesis.

Building circuits and studying their behavior in cells is a major goal of systems and synthetic biology. Synthetic biology enables the precise control of cellular states for systems studies, the discovery of novel parts, control strategies, and interactions for the design of robust synthetic systems. To the best of our knowledge,there are no literature reports for the synthetic circuit construction for protozoan parasites. This paper describes the construction of genetic circuit for the targeted enzyme inositol phosphorylceramide synthase belonging to the protozoan parasite Leishmania. To explore the dynamic nature of the circuit designed, simulation was done followed by circuit validation by qualitative and quantitative approaches. The genetic circuit designed for inositol phosphorylceramide synthase shows responsiveness, oscillatory and bistable behavior, together with intrinsic robustness.; Comment: This is Master of Science thesis from Sardar Patel university. Part of the thesis has been published as the following paper: "Mandlik, Vineetha, Dixita Limbachiya, Sonali Shinde, Milsee Mol, and Shailza Singh. "Synthetic circuit of inositol phosphorylceramide synthase in Leishmania: a chemical biology approach." Journal of Chemical Biology (2012): 1-12" in the Journal of Chemical Biology

We investigate the macroscopic effects of the ingredients that drive the origin of species through sympatric speciation. In our model, sympatric speciation is obtained as we tune up the strength of competition between individuals with different phenotypes. As a function of this control parameter, we can characterize, through the behavior of a macroscopic order parameter, a phase transition from a non-speciation to a speciation state of the system. The behavior of the first derivative of the order parameter with respect to the control parameter is consistent with a phase transition and exhibits a sharp peak at the transition point. For different resources distribution, the transition point is shifted, an effect similar to pressure in PVT system. The inverse of the parameter related to sexual selection strength behaves like an external field in the system and, as thus, is also a control parameter. The macroscopic effects of the biological parameters used in our model reveal thus fingerprints typical of thermodynamic quantities in a phase transition of an equilibrium physical system.; Comment: 4 pages and 10 figures

Animals living in groups make movement decisions that depend, among other factors, on social interactions with other group members. Our present understanding of social rules in animal collectives is mainly based on empirical fits to observations, with less emphasis in obtaining first-principles approaches that allow their derivation. Here we show that patterns of collective decisions can be derived from the basic ability of animals to make probabilistic estimations in the presence of uncertainty. We build a decision-making model with two stages: Bayesian estimation and probabilistic matching. In the first stage, each animal makes a Bayesian estimation of which behavior is best to perform taking into account personal information about the environment and social information collected by observing the behaviors of other animals. In the probability matching stage, each animal chooses a behavior with a probability equal to the Bayesian-estimated probability that this behavior is the most appropriate one. This model derives very simple rules of interaction in animal collectives that depend only on two types of reliability parameters, one that each animal assigns to the other animals and another given by the quality of the non-social information. We test our model by obtaining theoretically a rich set of observed collective patterns of decisions in three-spined sticklebacks...

The transmission through contacts among MSM (men who have sex with men) is one of the dominating contributors to HIV prevalence in industrialized countries. In Amsterdam, the capital of the Netherlands, the MSM risk group has been traced for decades. This has motivated studies which provide detailed information about MSM's risk behavior statistically, psychologically and sociologically. Despite the era of potent antiretroviral therapy, the incidence of HIV among MSM increases. In the long term the contradictory effects of risk behavior and effective therapy are still poorly understood. Using a previously presented Complex Agent Network model, we describe steady and casual partnerships to predict the HIV spreading among MSM. Behavior-related parameters and values, inferred from studies on Amsterdam MSM, are fed into the model; we validate the model using historical yearly incidence data. Subsequently, we study scenarios to assess the contradictory effects of risk behavior and effective therapy, by varying corresponding values of parameters. Finally, we conduct quantitative analysis based on the resulting incidence data. The simulated incidence reproduces the ACS historical incidence well and helps to predict the HIV epidemic among MSM in Amsterdam. Our results show that in the long run the positive influence of effective therapy can be outweighed by an increase in risk behavior of at least 30% for MSM. Conclusion: We recommend...

Weakly electric fish are unique models in Neuroscience allowing experimentalists to access, with non invasive techniques,a central nervous system generated spatio-temporal electric pattern of pulses with roles in at least two complex and not yet completely understood abilities:electrocommunication and electrolocation. We developed an apparatus to allow realistic stimulation and simultaneous recording of electric pulses in freely moving Gymnotus carapo for very long periods-several days. Voltage time series from a 3dimensional array of sensitive dipoles that detects electric field in several positions underwater were digitized and home made real-time software allowed reliable recording of pulse timestamps,independently of the fish's position,and also to infer fish movement. A stimulus fish was mimicked by a dipole electrode that reproduced the voltage time series of real conspecific pulses,but according to timestamp sequences previously recorded that could be chosen by the experimenter. Two independent variables were used to analyze fish behavior:the entropy of the recorded timestamp sequences and the movement of the fish inferred from pulse amplitude variability at each detection dipole. All fish presented very long transient exploratory behavior (about 8hours) when exposed to a new environment in the absence of stimuli. After the transient there were several intervals(5min-2hours)...

Several models of flocking have been promoted based on simulations with qualitatively naturalistic behavior. In this paper we provide the first direct application of computational modeling methods to infer flocking behavior from experimental field data. We show that this approach is able to infer general rules for interaction, or lack of interaction, among members of a flock or, more generally, any community. Using experimental field measurements of homing pigeons in flight we demonstrate the existence of a basic distance dependent attraction/repulsion relationship and show that this rule is sufficient to explain collective behavior observed in nature. Positional data of individuals over time are used as input data to a computational algorithm capable of building complex nonlinear functions that can represent the system behavior. Topological nearest neighbor interactions are considered to characterize the components within this model. The efficacy of this method is demonstrated with simulated noisy data generated from the classical (two dimensional) Vicsek model. When applied to experimental data from homing pigeon flights we show that the more complex three dimensional models are capable of predicting and simulating trajectories, as well as exhibiting realistic collective dynamics. The simulations of the reconstructed models are used to extract properties of the collective behavior in pigeons...

Synthetic biology is the engineering of cellular networks. It combines principles of engineering and the knowledge of biological networks to program the behavior of cells. Computational modeling techniques in conjunction with molecular biology techniques have been successful in constructing biological devices such as switches, oscillators, and gates. The ambition of synthetic biology is to construct complex systems from such fundamental devices, much in the same way electronic circuits are built from basic parts. As this ambition becomes a reality, engineering concepts such as interchangeable parts and encapsulation will find their way into biology. We realize that there is a need for computational tools that would support such engineering concepts in biology. As a solution, we have developed the software Athena that allows biological models to be constructed as modules. Modules can be connected to one another without altering the modules themselves. In addition, Athena houses various tools useful for designing synthetic networks including tools to perform simulations, automatically derive transcription rate expressions, and view and edit synthetic DNA sequences. New tools can be incorporated into Athena without modifying existing program via a plugin interface...

Polymorphism in the peripheral sensory system (e.g., congenital individual differences in photopigment configuration) is important in diverse research fields, ranging from evolutionary biology to engineering, because of its potential relationship to the cognitive and behavioral variability among individuals. However, there is a gap between the current understanding of sensory polymorphism and the behavioral variability that is an outcome of potentially complex cognitive processes in natural environments. Linking peripheral sensor properties to behavior requires computational models of nervous processes transforming sensory representation into action, which are constrained by quantitative data based on physiological and behavioral studies. Recently, studies based on machine vision approaches are shedding light on the quantitative relationships between sensory polymorphism and the resulting behavioral variability. To gain a convergent understanding of the functional impact of sensory polymorphism in realistic environments, a close coordination among physiological, behavioral, and computational approaches is required. At the same time, such an interdisciplinary approach yields broad insights into the universal mechanisms in our cognitive processes and effective strategies to compensate for individual differences in daily life.

A key aim in biology and psychology is to identify fundamental principles underpinning the behavior of animals, including humans. Analyses of human language and the behavior of a range of non-human animal species have provided evidence for a common pattern underlying diverse behavioral phenomena: words follow Zipf's law of brevity (the tendency of more frequently used words to be shorter), and conformity to this general pattern has been seen in the behavior of a number of other animals. It has been argued that the presence of this law is a sign of efficient coding in the information theoretic sense. However, no strong direct connection has been demonstrated between the law and compression, the information theoretic principle of minimizing the expected length of a code. Here we show that minimizing the expected code length implies that the length of a word cannot increase as its frequency increases. Furthermore, we show that the mean code length or duration is significantly small in human language, and also in the behavior of other species in all cases where agreement with the law of brevity has been found. We argue that compression is a general principle of animal behavior, that reflects selection for efficiency of coding.; Comment: This is the pre-proofed version. The published version will be available at http://onlinelibrary.wiley.com/journal/10.1111/%28ISSN%291551-6709

We present a simple algorithm for detecting oscillatory behavior in discrete data. The data is used as an input driving force acting on a set of simulated damped oscillators. By monitoring the energy of the simulated oscillators, we can detect oscillatory behavior in data. In application to in vivo deep brain basal ganglia recordings, we found sharp peaks in the spectrum at 20 and 70 Hz. The algorithm is also compared to the conventional fast Fourier transform and circular statistics techniques using computer generated model data, and is found to be comparable to or better than fast Fourier transform in test cases. Circular statistics performed poorly in our tests.; Comment: 20 pages, 6 figures

While designing oligonucleotide-based microarrays, cross-hybridization between surface-bound oligos and non-intended labeled targets is probably the most difficult parameter to predict. Although literature describes rules-of-thumb concerning oligo length, overall similarity, and continuous stretches, the final behavior is difficult to predict. The aim of this study was to investigate the effect of well-defined mismatches on hybridization specificity using CodeLink Activated Slides, and to study quantitatively the relation between hybridization intensity and Gibbs free energy (Delta G), taking the mismatches into account. Our data clearly showed a correlation between the hybridization intensity and Delta G of the oligos over three orders of magnitude for the hybridization intensity, which could be described by the Langmuir model. As Delta G was calculated according to the nearest-neighbor model, using values related to DNA hybridizations in solution, this study clearly shows that target-probe hybridizations on microarrays with a three-dimensional coating are in quantitative agreement with the corresponding reaction in solution. These results can be interesting for some practical applications. The correlation between intensity and Delta G can be used in quality control of microarray hybridizations by designing probes and corresponding RNA spikes with a range of Delta G values. Furthermore...

It is the goal of systems biology to understand the behavior of the whole in terms of the knowledge of the parts. This is hard to achieve in many cases due to the difficulty of characterizing the many constituents and their complex web of interactions involved in a biological system. The lac promoter of E. coli offers a possibility of confronting system-leve properties of transcriptional regulation with the known biochemistry of the molecular constituents and their mutual interactions. Such confrontations can reveal previously unknown constituents and interactions, as well as offering new insight into how the components work together as a whole. Here we study the combinatorial control of the lac promoter by the regulators LacR and CRP. A previous in vivo study [Setty et al., PNAS 100: 7702-7 (2003)] found gross disagreement between the observed promoter activites and the expected behavior based on the known molecular mechanisms. We repeated the study by identifying and removing several extraneous factors which significantly modulated the expression of the lac promoter. Through quantitative, systematic characterization of promoter activity for a number of key mutants and guided by the thermodynamic model of transcriptional gene regulation...

In this paper, we perform a complete analysis of the kinetic behavior of the general modifier mechanism of Botts and Morales in both equilibrium steady states and non-equilibrium steady states (NESS). Enlightened by the non-equilibrium theory of Markov chains, we introduce the net flux into discussion and acquire an expression of product rate in NESS, which has clear biophysical significance. Up till now, it is a general belief that being an activator or an inhibitor is an intrinsic property of the modifier. However, we reveal that this traditional point of view is based on the equilibrium assumption. A modifier may no longer be an overall activator or inhibitor when the reaction system is not in equilibrium. Based on the regulation of enzyme activity by the modifier concentration, we classify the kinetic behavior of the modifier into three categories, which are named hyperbolic behavior, bell-shaped behavior, and switching behavior, respectively. We show that the switching phenomenon, in which a modifier may convert between an activator and an inhibitor when the modifier concentration varies, occurs only in NESS. Effects of drugs on the Pgp ATPase activity, where drugs may convert from activators to inhibitors with the increase of the drug concentration...

Control theory arose from a need to control synthetic systems. From regulating steam engines to tuning radios to devices capable of autonomous movement, it provided a formal mathematical basis for understanding the role of feedback in the stability (or change) of dynamical systems. It provides a framework for understanding any system with feedback regulation, including biological ones such as regulatory gene networks, cellular metabolic systems, sensorimotor dynamics of moving animals, and even ecological or evolutionary dynamics of organisms and populations. Here we focus on four case studies of the sensorimotor dynamics of animals, each of which involves the application of principles from control theory to probe stability and feedback in an organism's response to perturbations. We use examples from aquatic (electric fish station keeping and jamming avoidance), terrestrial (cockroach wall following) and aerial environments (flight control in moths) to highlight how one can use control theory to understand how feedback mechanisms interact with the physical dynamics of animals to determine their stability and response to sensory inputs and perturbations. Each case study is cast as a control problem with sensory input, neural processing...

Swarming behaviors in animals have been extensively studied due to their implications for the evolution of cooperation, social cognition, and predator-prey dynamics. An important goal of these studies is discerning which evolutionary pressures favor the formation of swarms. One hypothesis is that swarms arise because the presence of multiple moving prey in swarms causes confusion for attacking predators, but it remains unclear how important this selective force is. Using an evolutionary model of a predator-prey system, we show that predator confusion provides a sufficient selection pressure to evolve swarming behavior in prey. Furthermore, we demonstrate that the evolutionary effect of predator confusion on prey could in turn exert pressure on the structure of the predator's visual field, favoring the frontally oriented, high-resolution visual systems commonly observed in predators that feed on swarming animals. Finally, we provide evidence that when prey evolve swarming in response to predator confusion, there is a change in the shape of the functional response curve describing the predator's consumption rate as prey density increases. Thus, we show that a relatively simple perceptual constraint--predator confusion--could have pervasive evolutionary effects on prey behavior...

What fascinates us about animal behavior is its richness and complexity, but understanding behavior and its neural basis requires a simpler description. Traditionally, simplification has been imposed by training animals to engage in a limited set of behaviors, by hand scoring behaviors into discrete classes, or by limiting the sensory experience of the organism. An alternative is to ask whether we can search through the dynamics of natural behaviors to find explicit evidence that these behaviors are simpler than they might have been. We review two mathematical approaches to simplification, dimensionality reduction and the maximum entropy method, and we draw on examples from different levels of biological organization, from the crawling behavior of C. elegans to the control of smooth pursuit eye movements in primates, and from the coding of natural scenes by networks of neurons in the retina to the rules of English spelling. In each case, we argue that the explicit search for simplicity uncovers new and unexpected features of the biological system, and that the evidence for simplification gives us a language with which to phrase new questions for the next generation of experiments. The fact that similar mathematical structures succeed in taming the complexity of very different biological systems hints that there is something more general to be discovered.

Mimicry is a resemblance between species that benefits at least one of the species. It is a ubiquitous evolutionary phenomenon particularly common among prey species, in which case the advantage involves better protection from predation. We formulate a mathematical description of mimicry among prey species, to investigate benefits and disadvantages of mimicry. The basic setup involves differential equations for quantities representing predator behavior, namely, the probabilities for attacking prey at the next encounter. Using this framework, we present new quantitative results, and also provide a unified description of a significant fraction of the quantitative mimicry literature. The new results include `temporary' mutualism between prey species, and an optimal density at which the survival benefit is greatest for the mimic. The formalism leads naturally to extensions in several directions, such as the evolution of mimicry, the interplay of mimicry with population dynamics, etc. We demonstrate this extensibility by presenting some explorations on spatiotemporal pattern dynamics.; Comment: 9 pages, 7 figures

Small, non-coding RNAs (sRNAs) play important roles as genetic regulators in prokaryotes. sRNAs act post-transcriptionally via complementary pairing with target mRNAs to regulate protein expression. We use a quantitative approach to compare and contrast sRNAs with conventional transcription factors (TFs) to better understand the advantages of each form of regulation. In particular, we calculate the steady-state behavior, noise properties, frequency-dependent gain (amplification), and dynamical response to large input signals of both forms of regulation. While the mean steady-state behavior of sRNA-regulated proteins exhibits a distinctive tunable threshold-linear behavior, our analysis shows that transcriptional bursting leads to significantly higher intrinsic noise in sRNA-based regulation than in TF-based regulation in a large range of expression levels and limits the ability of sRNAs to perform quantitative signaling. Nonetheless, we find that sRNAs are better than TFs at filtering noise in input signals. Additionally, we find that sRNAs allow cells to respond rapidly to large changes in input signals. These features suggest a niche for sRNAs in allowing cells to transition quickly yet reliably between distinct states. This functional niche is consistent with the widespread appearance of sRNAs in stress-response and quasi-developmental networks in prokaryotes.; Comment: 26 pages...