The history of development of evolutionary methods in St. Petersburg school of computer simulation in biology

The history of rise and development of evolutionary methods in Saint Petersburg school of biological modelling is traced and analyzed. Some pioneering works in simulation of ecological and evolutionary processes, performed in St.-Petersburg school became an exemplary ones for many followers in Russia and abroad. The individual-based approach became the crucial point in the history of the school as an adequate instrument for construction of models of biological evolution. This approach is natural for simulation of the evolution of life-history parameters and adaptive processes in populations and communities. In some cases simulated evolutionary process was used for solving a reverse problem, i. e., for estimation of uncertain life-history parameters of population. Evolutionary computations is one more aspect of this approach application in great many fields. The problems and vistas of ecological and evolutionary modelling in general are discussed.     

An Evolutionary Firefly Algorithm for the Estimation of Nonlinear Biological Model Parameters

The development of accurate computational models of biological processes is fundamental to computational systems biology. These models are usually represented by mathematical expressions that rely heavily on the system parameters. The measurement of these parameters is often difficult. Therefore, they are commonly estimated by fitting the predicted model to the experimental data using optimization methods. The complexity and nonlinearity of the biological processes pose a significant challenge, however, to the development of accurate and fast optimization methods. We introduce a new hybrid optimization method incorporating the Firefly Algorithm and the evolutionary operation of the Differential Evolution method. The proposed method improves solutions by neighbourhood search using evolutionary procedures. Testing our method on models for the arginine catabolism and the negative feedback loop of the p53 signalling pathway, we found that it estimated the parameters with high accuracy and within a reasonable computation time compared to well-known approaches, including Particle Swarm Optimization, Nelder-Mead, and Firefly Algorithm. We have also verified the reliability of the parameters estimated by the method using an a posteriori practical identifiability test.     

Bayesian Inference of Reticulate Phylogenies under the Multispecies Network Coalescent

The multispecies coalescent (MSC) is a statistical framework that models how gene genealogies grow within the branches of a species tree. The field of computational phylogenetics has witnessed an explosion in the development of methods for species tree inference under MSC, owing mainly to the accumulating evidence of incomplete lineage sorting in phylogenomic analyses. However, the evolutionary history of a set of genomes, or species, could be reticulate due to the occurrence of evolutionary processes such as hybridization or horizontal gene transfer. We report on a novel method for Bayesian inference of genome and species phylogenies under the multispecies network coalescent (MSNC). This framework models gene evolution within the branches of a phylogenetic network, thus incorporating reticulate evolutionary processes, such as hybridization, in addition to incomplete lineage sorting. As phylogenetic networks with different numbers of reticulation events correspond to points of different dimensions in the space of models, we devise a reversible-jump Markov chain Monte Carlo (RJMCMC) technique for sampling the posterior distribution of phylogenetic networks under MSNC. We implemented the methods in the publicly available, open-source software package PhyloNet and studied their performance on simulated and biological data. The work extends the reach of Bayesian inference to phylogenetic networks and enables new evolutionary analyses that account for reticulation.     

Computational Modeling,Formal Analysis,and Tools for Systems Biology

As the amount of biological data in the public domain grows, so does the range of modeling and analysis techniques employed in systems biology. In recent years, a number of theoretical computer science developments have enabled modeling methodology to keep pace. The growing interest in systems biology in executable models and their analysis has necessitated the borrowing of terms and methods from computer science, such as formal analysis, model checking, static analysis, and runtime verification. Here, we discuss the most important and exciting computational methods and tools currently available to systems biologists. We believe that a deeper understanding of the concepts and theory highlighted in this review will produce better software practice, improved investigation of complex biological processes, and even new ideas and better feedback into computer science.     

模型分析在动物进化生物学研究中的应用

早期的生态学研究往往局限于对野外观察现象的基本描述。随着模型分析方法的引入,可以通过建立数学模型寻找描述性材料中蕴藏的一般性规律,探讨某一现象产生的原因及其制约因素。近年,随着计算机技术的飞速发展和普及,模型分析方法应用越来越广泛。动物行为的进化及其对环境的适应性一直以来都是生态学研究的热点,根据应用不同的理论基础,人们发展了许多不同的建模方法,主要包括种群遗传学模型、最优化模型、博弈模型、基于个体的模拟模型和系统发育对比分析模型等。本文主要介绍了以上5种模型方法,及其在动物进化生物学研究中的应用现状。     

Inferring evolutionary processes from phylogenies

Evolutionary processes shape the regular trends of evolution and are responsible for the diversity and distribution of contemporary species. They include correlated evolutionary change and trajectories of trait evolution, convergent and parallel evolution, differential rates of evolution, speciation and extinction, the order and direction of change in characters, and the nature of the evolutionary process itself—does change accumulate gradually, episodically, or in punctuational bursts. Phylogenies, in combination with information on species, contain the imprint of these historical evolutionary processes. By applying comparative methods based upon statistical models of evolution to well resolved phylogenies, it is possible to infer the historical evolutionary processes that must have existed in the past, given the patterns of diversity seen in the present. I describe a set of maximum likelihood statistical methods for inferring such processes. The methods estimate parameters of statistical models for inferring correlated evolutionary change in continuously varying characters, for detecting correlated evolution in discrete characters, for estimating rates of evolution, and for investigating the nature of the evolutionary process itself. They also anticipate the wealth of information becoming available to biological scientists from genetic studies that pin down relationships among organisms with unprecedented accuracy.     

Recent developments in the monitoring,modeling and control of biological production systems

Current trends in the development of methods for monitoring, modeling and controlling biological production systems are reviewed from a bioengineering perspective. The ability to measure intracellular conditions in bioprocesses using genomics and other bioinformatics tools is addressed. Devices provided via micromachining techniques and new real-time optical technology are other novel methods that may facilitate biosystem engineering. Mathematical modeling of data obtained from bioinformatics or real-time monitoring methods are necessary in order to handle the dense flows of data that are generated. Furthermore, control methods must be able to cope with these data flows in efficient ways that can be implemented in plant-wide computer communication systems.Mini-review for the proceedings of the M3C conference     

Invasion genetics of the introduced black rat (Rattus rattus) in Senegal,West Africa

An understanding of the evolutionary history and dynamics of invasive species is required for the construction of predictive models of future spread and the design of biological management measures. The black rat (Rattus rattus) is a major vertebrate invader with a worldwide distribution. Despite the severe ecological, economic and health impacts of this species, its evolutionary history has been little studied. We carried out extensive specimen sampling in Senegal, West Africa, and used microsatellite markers to describe the pattern and processes of invasion in this large continental area. The genetic data obtained were combined with historical knowledge concerning the presence of this species in Senegal. Data were analysed by a combination of Bayesian clustering and approximate Bayesian computation methods. The invasion pathways closely paralleled the history of human trade routes in Senegal. In several places, we detected the occurrence of multiple introductions from genetically different sources. Long‐distance migration between towns and villages was also observed. Our findings suggest that genetic bottlenecks and admixture have played a major role in shaping the genetics of invasive black rats. These two processes may generate genetic novelty and favour rapid evolution along the invasion pathways.     

Individual heterogeneity in life histories and eco‐evolutionary dynamics

Individual heterogeneity in life history shapes eco‐evolutionary processes, and unobserved heterogeneity can affect demographic outputs characterising life history and population dynamical properties. Demographic frameworks like matrix models or integral projection models represent powerful approaches to disentangle mechanisms linking individual life histories and population‐level processes. Recent developments have provided important steps towards their application to study eco‐evolutionary dynamics, but so far individual heterogeneity has largely been ignored. Here, we present a general demographic framework that incorporates individual heterogeneity in a flexible way, by separating static and dynamic traits (discrete or continuous). First, we apply the framework to derive the consequences of ignoring heterogeneity for a range of widely used demographic outputs. A general conclusion is that besides the long‐term growth rate lambda, all parameters can be affected. Second, we discuss how the framework can help advance current demographic models of eco‐evolutionary dynamics, by incorporating individual heterogeneity. For both applications numerical examples are provided, including an empirical example for pike. For instance, we demonstrate that predicted demographic responses to climate warming can be reversed by increased heritability. We discuss how applications of this demographic framework incorporating individual heterogeneity can help answer key biological questions that require a detailed understanding of eco‐evolutionary dynamics.     

Diversification within glacial refugia: tempo and mode of evolution of the polytypic fish Barbus sclateri

A diversity of evolutionary processes can be responsible for generating and maintaining biodiversity. Molecular markers were used to investigate the influence of Plio-Pleistocene climatic oscillations on the evolutionary history of taxa restricted to the freshwaters of a classical glacial refugium. Population genetic, phylogenetic and phylogeographical methods allowed the inference of temporal dynamics of cladogenesis and processes shaping present-day genetic constitution of Barbus sclateri , a polytypic taxon found in several independent river drainages in southern Iberian Peninsula. Results from different analyses consistently indicate several range expansions, high levels of allopatric fragmentation, and admixture following secondary contacts throughout its evolutionary history. Using a Bayesian demographical coalescent model on mitochondrial DNA sequences calibrated with fossil evidence, all cladogenetic events within B. sclateri are inferred to have occurred during the Pleistocene and were probably driven by environmental factors. Our results suggest that glaciation cycles did not inhibit cladogenesis and probably interacted with regional geomorphology to promote diversification. We conclude that this polytypic taxon is a species complex that recently diversified in allopatry, and that Pleistocene glaciation–deglaciation cycles probably contributed to the generation of biological diversity in a classical glacial refugium with high endemicity.     

Integrating Interactive Computational Modeling in Biology Curricula

While the use of computer tools to simulate complex processes such as computer circuits is normal practice in fields like engineering, the majority of life sciences/biological sciences courses continue to rely on the traditional textbook and memorization approach. To address this issue, we explored the use of the Cell Collective platform as a novel, interactive, and evolving pedagogical tool to foster student engagement, creativity, and higher-level thinking. Cell Collective is a Web-based platform used to create and simulate dynamical models of various biological processes. Students can create models of cells, diseases, or pathways themselves or explore existing models. This technology was implemented in both undergraduate and graduate courses as a pilot study to determine the feasibility of such software at the university level. First, a new (In Silico Biology) class was developed to enable students to learn biology by “building and breaking it” via computer models and their simulations. This class and technology also provide a non-intimidating way to incorporate mathematical and computational concepts into a class with students who have a limited mathematical background. Second, we used the technology to mediate the use of simulations and modeling modules as a learning tool for traditional biological concepts, such as T cell differentiation or cell cycle regulation, in existing biology courses. Results of this pilot application suggest that there is promise in the use of computational modeling and software tools such as Cell Collective to provide new teaching methods in biology and contribute to the implementation of the “Vision and Change” call to action in undergraduate biology education by providing a hands-on approach to biology.     

分子进化研究中系统发生树的重建

在现代分子进化研究中,根据现有生物基因或物种多样性来重建生物的进化史是一个非常重要的问题。一个可靠的系统发生的推断,将揭示出有关生物进化过程的顺序,有助于我们了解生物进化的历史和进化机制。本文简要介绍了系统发生树推断的几个重要问题：建树方法、数据转换、树的可靠性及目前使用较多的几种分析软件。     

Evolutionary history and stress regulation of the lectin superfamily in higher plants

Background  

Lectins are a class of carbohydrate-binding proteins. They play roles in various biological processes. However, little is known about their evolutionary history and their functions in plant stress regulation. The availability of full genome sequences from various plant species makes it possible to perform a whole-genome exploration for further understanding their biological functions.     

Computational intelligence approaches for pattern discovery in biological systems

Biology, chemistry and medicine are faced by tremendous challenges caused by an overwhelming amount of data and the need for rapid interpretation. Computational intelligence (CI) approaches such as artificial neural networks, fuzzy systems and evolutionary computation are being used with increasing frequency to contend with this problem, in light of noise, non-linearity and temporal dynamics in the data. Such methods can be used to develop robust models of processes either on their own or in combination with standard statistical approaches. This is especially true for database mining, where modeling is a key component of scientific understanding. This review provides an introduction to current CI methods, their application to biological problems, and concludes with a commentary about the anticipated impact of these approaches in bioinformatics.     

Haploid evolutionary constructor: new features and further challenges

In this paper we consider the recent advances in methodology for modeling of prokaryotic communities evolution and new features of the software package "Haploid evolutionary constructor" (http://evol-constructor.bionet.nsc.ru). We show the principles of building complex computer models in our software tool. These models describe several levels of biological organization: genetic, metabolic, population, ecological. New features of the haploid evolutionary constructor include the modeling of gene networks and phage infections.     

INVESTIGATING EVOLUTIONARY TRADE‐OFFS IN WILD POPULATIONS OF ATLANTIC SALMON (SALMO SALAR): INCORPORATING DETECTION PROBABILITIES AND INDIVIDUAL HETEROGENEITY

Evolutionary trade‐offs among demographic parameters are important determinants of life‐history evolution. Investigating such trade‐offs under natural conditions has been limited by inappropriate analytical methods that fail to address the bias in demographic estimates that can result when issues of detection (uncertain detection of individual) are ignored. We propose a new statistical approach to quantify evolutionary trade‐offs in wild populations. Our method is based on a state‐space modeling framework that focuses on both the demographic process of interest as well as the observation process. As a case study, we used individual mark–recapture data for stream‐dwelling Atlantic salmon juveniles in the Scorff River (Southern Brittany, France). In freshwater, juveniles face two life‐history choices: migration to the ocean and sexual maturation (for males). Trade‐offs may appear with these life‐history choices and survival, because all are energy dependent. We found a cost of reproduction on survival for fish staying in freshwater and a survival advantage associated with the “decision” to migrate. Our modeling framework opens up promising prospects for the study of evolutionary trade‐offs when some life‐history traits are not, or only partially, observable.     

Computer simulation of the cellular arrangement using physical model in early cleavage of the nematode Caenorhabditis elegans

MOTIVATION: The ultimate goal of bioinformatics is to reconstruct biological systems in the computer. Since biological systems have many levels, it is important to focus on an appropriate level. In our first application of computer modeling to the early development of the nematode Caenorhabditis elegans, we focus on the cellular arrangement in early embryos. This plays a very important role in cell fate determination by cell-cell interaction, and is regarded as a system, one level higher than the system of gene regulation within cells. It is largely restricted by physical conditions that seemed feasible to model by computer. RESULTS: We constructed a computer model of the C.elegans embryo, currently up to the 4-cell stage, using a deformable and dividable triangulated network. The model is based solely on cellular-level dynamics. We found that the optimal ranges of three parameters that affect the elongation of dividing cells led, in computer simulations, to almost the same cellular arrangements as in real embryos. The nature of the model and the relationship with real embryos are discussed.     

Inferring population history with DIY ABC: a user-friendly approach to approximate Bayesian computation

Genetic data obtained on population samples convey information about their evolutionary history. Inference methods can extract part of this information but they require sophisticated statistical techniques that have been made available to the biologist community (through computer programs) only for simple and standard situations typically involving a small number of samples. We propose here a computer program (DIY ABC) for inference based on approximate Bayesian computation (ABC), in which scenarios can be customized by the user to fit many complex situations involving any number of populations and samples. Such scenarios involve any combination of population divergences, admixtures and population size changes. DIY ABC can be used to compare competing scenarios, estimate parameters for one or more scenarios and compute bias and precision measures for a given scenario and known values of parameters (the current version applies to unlinked microsatellite data). This article describes key methods used in the program and provides its main features. The analysis of one simulated and one real dataset, both with complex evolutionary scenarios, illustrates the main possibilities of DIY ABC. AVAILABILITY: The software DIY ABC is freely available at http://www.montpellier.inra.fr/CBGP/diyabc.