Providing SSPCO Algorithm to Construct Static Protein-Protein Interaction (PPI) Networks

Protein-Protein Inter-action Networks are dynamic in reality; i.e. Inter-actions among different proteins may be ineffective in different circumstances and times. One of the most crucial parameters in the conversion of a static network into a temporal graph is the well-tuning of transformation threshold. In this part of the article, using additional data, like gene expression data in different times and circumstances and well-known protein complexes, it is tried to determine an appropriate threshold. To accomplish this task, we transform the problem into an optimization one and then we solve it using a meta-heuristic algorithm, named Particle Swarm Optimization (SSPCO). One of the most important parts in our work is the determination of interestingness function in the SSPCO. It is defined as a function of standard complexes and gene co-expression data. After producing a threshold per each gene, in the following section we will discuss how using these thresholds, active proteins are determined and then temporal graph is created. For final assessment of the produced graph quality, we use graph clustering algorithms and protein complexes determination algorithms. For accomplishing this task, we use MCL, Cluster One, MCODE algorithms. Due to high number of the obtained clusters, the obtained results, if they have some special conditions, will filter out or be merged with each other. Standard performance criteria like Recal, Precision, and F-measure are employed. There is a new proposed criterion named Smoothness. Our experimental results show that the graphs produced by the proposed method outperform the previous methods

Comprehensive Taxonomies of Nature- and Bio-inspired Optimization: Inspiration Versus Algorithmic Behavior, Critical Analysis Recommendations

In recent algorithmic family simulates different biological processes observed in Nature in order to efficiently address complex optimization problems. In the last years the number of bio-inspired optimization approaches in literature has grown considerably, reaching unprecedented levels that dark the future prospects of this field of research. This paper addresses this problem by proposing two comprehensive, principle-based taxonomies that allow researchers to organize existing and future algorithmic developments into well-defined categories, considering two different criteria: the source of inspiration and the behavior of each algorithm. Using these taxonomies we review more than three hundred publications dealing with nature- inspired and bio-inspired algorithms, and proposals falling within each of these categories are examined, leading to a critical summary of design trends and similarities between them, and the identification of the most similar classical algorithm for each reviewed paper. From our analysis we conclude that a poor relationship is often found between the natural inspiration of an algorithm and its behavior. Furthermore, similarities in terms of behavior between different algorithms are greater than what is claimed in their public disclosure: specifically, we show that more than one-third of the reviewed bio-inspired solvers are versions of classical algorithms. Grounded on the conclusions of our critical analysis, we give several recommendations and points of improvement for better methodological practices in this active and growing research field

Building a Bird: Musculoskeletal Modeling and Simulation of Wing-Assisted Incline Running during Avian Ontogeny

Flapping flight is the most power-demanding mode of locomotion, associated with a suite of anatomical specializations in extant adult birds. In contrast, many developing birds use their forelimbs to negotiate environments long before acquiring “flight adaptations,” recruiting their developing wings to continuously enhance leg performance and, in some cases, fly. How does anatomical development influence these locomotor behaviors? Isolating morphological contributions to wing performance is extremely challenging using purely empirical approaches. However, musculoskeletal modeling and simulation techniques can incorporate empirical data to explicitly examine the functional consequences of changing morphology by manipulating anatomical parameters individually and estimating their effects on locomotion. To assess how ontogenetic changes in anatomy affect locomotor capacity, we combined existing empirical data on muscle morphology, skeletal kinematics, and aerodynamic force production with advanced biomechanical modeling and simulation techniques to analyze the ontogeny of pectoral limb function in a precocial ground bird (Alectoris chukar). Simulations of wing-assisted incline running (WAIR) using these newly developed musculoskeletal models collectively suggest that immature birds have excess muscle capacity and are limited more by feather morphology, possibly because feathers grow more quickly and have a different style of growth than bones and muscles. These results provide critical information about the ontogeny and evolution of avian locomotion by (i) establishing how muscular and aerodynamic forces interface with the skeletal system to generate movement in morphing juvenile birds, and (ii) providing a benchmark to inform biomechanical modeling and simulation of other locomotor behaviors, both across extant species and among extinct theropod dinosaurs

Comprehensive Taxonomies of Nature- and Bio-inspired Optimization: Inspiration versus Algorithmic Behavior, Critical Analysis and Recommendations

In recent years, a great variety of nature- and bio-inspired algorithms has been reported in the literature. This algorithmic family simulates different biological processes observed in Nature in order to efficiently address complex optimization problems. In the last years the number of bio-inspired optimization approaches in literature has grown considerably, reaching unprecedented levels that dark the future prospects of this field of research. This paper addresses this problem by proposing two comprehensive, principle-based taxonomies that allow researchers to organize existing and future algorithmic developments into well-defined categories, considering two different criteria: the source of inspiration and the behavior of each algorithm. Using these taxonomies we review more than three hundred publications dealing with nature-inspired and bio-inspired algorithms, and proposals falling within each of these categories are examined, leading to a critical summary of design trends and similarities between them, and the identification of the most similar classical algorithm for each reviewed paper. From our analysis we conclude that a poor relationship is often found between the natural inspiration of an algorithm and its behavior. Furthermore, similarities in terms of behavior between different algorithms are greater than what is claimed in their public disclosure: specifically, we show that more than one-third of the reviewed bio-inspired solvers are versions of classical algorithms. Grounded on the conclusions of our critical analysis, we give several recommendations and points of improvement for better methodological practices in this active and growing research field.Comment: 76 pages, 6 figure

Relationship of landscape structure to ring-necked pheasant population dynamics in northern Iowa

I studied demographic processes that operate on individual animals as a means to understand the relationship of landscape structure to population size and survival. I applied the idea of risk-sensitivity to habitat selection by examining the demographic effects on an animal population in which individuals select from two habitats that have similar mean values for reproductive output but differ in the variance of reproductive output. I conducted simulations using a source-sink population model to show that population size increased with increased variation in habitat quality. I then looked at how landscape heterogeneity was related to ring-necked pheasant (Phasianus colchicus) demography. Although wildlife ecologists suggest that the period of settling movements during spring is a time of high mortality, there are few data to quantify the impact on demographics. Most often, the proximate cause of mortality is predation. However, ecologists presume that landscape pattern is strongly correlated with survival. I used radio-tracking data from April-May 1992 and 1993 on hen pheasants in an agricultural landscape in northern Iowa to determine factors related to survival. I measured covariates to quantify habitat selection, individual movement rates, and landscape patterns, and evaluated these using Cox\u27s proportional hazards model. I used a geographical information system to map hen use of habitat, calculated movement rates, and quantified landscape patterns within areas selected by hens. Edge density (m/ha) was predictive of mortality whereas movement rates were not. I linked this landscape factor to pheasant population dynamics by developing a spatially-explicit, individually-based model. I examined both parametric and nonparametric means of specifying the underlying instantaneous hazard, and simulated time- and location-specific survival as a function of landscape features, including edge density. Modeling the distribution of settling movements including habitat selection, and the predicted effects on mortality, enabled me to combine activities and fates of individual animals and to simulate population-wide demographic responses to landscape attributes. I conducted a simulation experiment that tested the effect of changes in the configuration (edge density) and composition (% grassland) of the landscapes used as input for the simulations. Simulated population survival was lowest in landscapes with low proportions of grassland and high measures of edge density

Macroevolutionary outcomes of coevolution between avian brood parasites and their hosts

Almost one hundred bird species in the world are known to be obligate interspecific brood parasites. These lay their eggs in the nests of other species, their hosts, which take care of a usually larger parasitic chick. Brood parasitism constitutes one of the best examples of coevolution in the animal kingdom. This strategy is usually costly to the host, and has led to the evolution of a suite of adaptations in hosts, in order to defend themselves against parasitism, and in parasites, in order to effectively parasitize their hosts. In this thesis I explore the effects of brood parasitism on macro-evolutionary patterns in both hosts and parasites. In the first six chapters of my thesis I explore how defences evolve in hosts. First I present a literature review about the evolution of egg acceptance and tolerance mechanisms in hosts of brood parasites, in which I discuss how other co-evolutionary interactions, such as those between plants and herbivores, may be informative for understanding brood parasitic systems. In the second chapter I perform a large-scale comparative analysis on the evolution of clutch size as a tolerance mechanism in hosts. This chapter also incorporates a mathematical model and a field experiment on the Horsfield’s bronze-cuckoo Chalcites basalis. In the third chapter I investigate why one type of defence, egg rejection, evolves in some host species and not in others. In the fourth chapter I present a comparative analysis which tests the idea that the benefits of group defence against brood parasites has led to the evolution of cooperative breeding in hosts. For the fifth and sixth chapters, I describe field experiments to test the evolution of defences in the yellow-rumped thornbill (Acanthiza chrysorrhoa), the main host of the shining bronze-cuckoo (Chalcites lucidus) in Australia. My main aim is to understand which types of defences have evolved in this major host. I also perform field experiments to understand which factors constrain the evolution of defences in this species. In the second part of my thesis I study how brood parasitism can be associated with the evolution of diversity in both hosts and parasites, especially in traits that are likely to be under selective pressures, such as the egg phenotype. In chapter 7 I study how egg phenotype has evolved to be more diverse within and among species that are hosts of brood parasites. In chapter 8 I explore whether a brood parasitic breeding strategy promotes the generation of new species and phenotypic diversity. Specifically, I test whether brood parasitic lineages have faster rates of speciation and phenotypic evolution. Finally, in chapter 9, I discuss how together, these chapters offer a broad evolutionary landscape that demonstrate the diverse impacts of brood parasitism as a co-evolutionary interaction. I provide evidence that brood parasitism, besides driving the evolution of defenses, is linked to trait diversity, and may be an important force behind the evolution of clutch size, cooperative breeding, egg pattern, egg size and plumage diversity

Explaining patterns of age-specific performance

Individual life histories are frequently studied to gain insight into the mechanisms of ageing. However, various challenges complicate the accurate quantification of age-specific variation in fitness. In this thesis I develop and apply methods to accurately characterise patterns of ageing, and to explain why such patterns arise. All mammals and birds have an upper bound on litter size, and for many species this limit is quite low. In addition, in many species, not all individuals breed at every possible opportunity. Reproduction should consequently be considered as two processes: whether an individual breeds or not and the number of offspring produced. These processes mean that reproduction in many species does not follow a Poisson process as is often assumed in analyses of breeding performance. A more appropriate model for a repeated ordinal response like annual reproductive success is a proportional odds model with a random intercept for individuals. Such a model has not previously been used in ecology or evolutionary biology. I apply this model to analyse age and temporal variation in the number of fledglings produced annually by male and female common terns (Sterna hirundo). I use data collected from this intensively studied, long-lived species, repeatedly throughout the thesis. The proportional odds analysis reveal that reproductive performance in females initially increased with age, before declining as individuals began to senesce. But why does this pattern arise? Is it purely an effect of getting physiologically older or are other processes involved? I estimate the effect of the length of time spent with the current partner using the common tern data. Despite the quality of the data, it is not always obvious if unmarked partners are new or not. I use a hierarchical Bayesian model of the steps that lead to the number of fledglings. Modelling this complicated process requires a complex model, but results show that no substantial amount of observed age-related patterns in reproductive performance can be attributed to length of pair bond. While the proportional odds and Bayesian analyses account for repeated measures on individuals they do not account for compositional change. Such a change in the composition of the population caused by heterogeneity between individuals can mask true rates of individual change. I develop a novel retrospective decomposition method related to the Price equation to address this issue. The equation gives the exact contributions of selective disappearance and average change in individual performance among survivors to the aggregate change at the level of the population. This equation can be extended by including a term for the compositional change due to selective appearance of individuals in the study population. I apply this decomposition to the common tern dataset to disentangle whether apparent increases and decreases in reproductive performance with age reflect genuine changes within individuals or are an artefact of compositional change in a heterogeneous population. I show an improvement in average reproductive performance of individuals over most of adult life and give support for reproductive senescence at old ages. I show that the contribution of compositional change is of minor importance, suggesting that population-level averages accurately capture the individual-level ageing process well. Can the decomposition method I develop be applied to other systems? Does it lead to similar conclusions? I apply it to two different datasets dealing with functioning at old age in humans: the ability to live independently in the Danish 1905-cohort, and cognitive functioning for people aged 80 and older participating in the Chinese Longitudinal Health and Longevity Survey. In both studies I reveal that average individual functioning declines at old ages. Although the decline is also apparent at the population level it is less strong due to the tendency of individuals with lower functioning to drop out earlier. Finally, I illustrate the general use of the decomposition by applying it to epidemiological and economic studies in the appendix. Overall, I find that reproductive performance improves over many age classes before senescence begins. Numerous processes can influence rates of age-related change, with results apparently specific to the trait and population under study