Spread of new mutations through space

The terms population size and population density are often used interchangeably, when in fact they are quite different. When viewed in a spatial landscape, density is defined as the number of individuals within a square unit of distance, while population size is simply the total count of a population. In discrete population genetics models, the effective population size is known to influence the interaction between selection and random drift with selection playing a larger role in large populations while random drift has more influence in smaller populations. Using a spatially explicit simulation software we investigate how population density affects the flow of new mutations through a geographical space. Using population density, selectional advantage, and dispersal distributions, a model is developed to predict the speed at which the new allele will travel, obtaining more accurate results than current diffusion approximations provide. We note that the rate at which a neutral mutation spreads begins to decay over time while the rate of spread of an advantageous allele remains constant. We also show that new advantageous mutations spread faster in dense populations.

The Implementation of Habitat Destruction Methods That Promote Native Survival Under Invasion

Controlling invasive alien species invasion and maintaining the survival of native species have attracted increasing attention, and habitat destruction can be used to achieve these aims. However, it remains unclear whether and how to promote the long-term survival of indigenous species facing invaders through the use of habitat destruction. In this study, we developed a spatially explicit simulation model and exposed invaders and residents from this model to habitat destruction with different properties. The results showed that (1) introducing habitat destruction could promote the long-term survival of native species facing invaders; however, the promoting effect of habitat destruction occurred only over a period of time after introduction, and habitat destruction substantially weakened indigenous species before that. (2) Intermediate levels of habitat destruction were the most beneficial to the protection of native species. (3) Even if not considering the proportion of destroyed habitats, introducing spatially dispersed habitat destruction at an earlier time and shortening the interval between two habitat destruction events were very beneficial to the protection of residents. These insights can help facilitate the protection of residents under invasion by adjusting the implementation method of habitat destruction.

Testing the Performance of Some Competition Indices against Experimental Data and Outputs of Spatially Explicit Simulation Models

Three competition indices were tested against experimental data on the growth of individual trees in mapped forest stands and outputs of spatially explicit, process-based models of competition. The comparison showed the fundamental importance of taking into account the spatial structure of stands and, particularly, the relative spatial locations of individual trees (spatial asymmetry) when calculating the competition between trees. Although none of the competition indices are able to take into account the specific processes affecting the development of individual trees, these indices can be used in forest dynamics modeling as a simplified representation of competition between trees for resources.

Urban Pit-Building Insects Are Attracted to Walls for Multiple Reasons

Whereas most animals find urban habitats to be inferior to natural habitats, some “urban specialist” species thrive there. Wormlions present such an example. Common in Mediterranean cities, they cluster in thin layers of loose soil below man-made shelters. Wormlions are fly larvae that dig pit-traps in loose soil and hunt small arthropods. Our first aim was to determine whether wormlion pits accumulate next to walls. Wormlion pits were indeed closer to walls than expected by chance at most of the study sites. We examined possible factors behind this apparent preference, combining field observations and experiments, laboratory work, and theoretical analysis. We examined the effect of soil depth, particle size, shade, and prey abundance. Each factor provided a partial explanation for the wormlions’ proximity to walls, but none provided an overall explanation. We developed a spatially explicit simulation model, demonstrating under which conditions wall-adjacent positions are favored. Finally, we created artificial microhabitats, and placed wormlions either in the center or next to the wall. The wormlions in the center moved over longer distances than those next to the wall and did so more in the wall’s direction. The abundance of walls may help to explain the success of wormlions in urban habitats.

An Efficient Tau-Leaping Simulation Method for Stochastic Biochemical Kinetics

Stochastic modeling and simulation of biochemical systems are topics of high interest in Computational Biology. Stochastic mathematical models are critical in accurately capturing the variability observed experimentally in cellular processes, in particular when some species have low molecular numbers. Many, realistic biochemical networks exhibit stiffness, due to the presence of multiple time-scales. For such networks explicit simulation methods are computationally quite intensive. In this thesis, we introduce an improved implicit tau-leaping strategy for the simulation of stochastic biochemical kinetic models. Numerical tests on various biochemical systems of interest in applications show the efficiency of our method.

An Efficient Tau-Leaping Simulation Method for Stochastic Biochemical Kinetics

Stochastic modeling and simulation of biochemical systems are topics of high interest in Computational Biology. Stochastic mathematical models are critical in accurately capturing the variability observed experimentally in cellular processes, in particular when some species have low molecular numbers. Many, realistic biochemical networks exhibit stiffness, due to the presence of multiple time-scales. For such networks explicit simulation methods are computationally quite intensive. In this thesis, we introduce an improved implicit tau-leaping strategy for the simulation of stochastic biochemical kinetic models. Numerical tests on various biochemical systems of interest in applications show the efficiency of our method.

Learning to Model G-Quadruplexes: Current Methods and Perspectives

G-quadruplexes have raised considerable interest during the past years for the development of therapies against cancer. These noncanonical structures of DNA may be found in telomeres and/or oncogene promoters, and it has been observed that the stabilization of such G-quadruplexes may disturb tumor cell growth. Nevertheless, the mechanisms leading to folding and stabilization of these G-quadruplexes are still not well established, and they are the focus of much current work in this field. In seminal works, stabilization was observed to be produced by cations. However, subsequent studies showed that different kinds of small molecules, from planar and nonplanar organic molecules to square-planar and octahedral metal complexes, may also lead to the stabilization of G-quadruplexes. Thus, the comprehension and rationalization of the interaction of these small molecules with G-quadruplexes are also important topics of current interest in medical applications. To shed light on the questions arising from the literature on the formation of G-quadruplexes, their stabilization, and their interaction with small molecules, synergies between experimental studies and computational works are needed. In this review, we mainly focus on in silico approaches and provide a broad compilation of different leading studies carried out to date by different computational methods. We divide these methods into two main categories: ( a) classical methods, which allow for long-timescale molecular dynamics simulations and the corresponding analysis of dynamical information, and ( b) quantum methods (semiempirical, quantum mechanics/molecular mechanics, and density functional theory methods), which allow for the explicit simulation of the electronic structure of the system but, in general, are not capable of being used in long-timescale molecular dynamics simulations and, therefore, give a more static picture of the relevant processes. Expected final online publication date for the Annual Review of Biophysics, Volume 50 is May 2021. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.