Inferring robust gene networks from expression data by a sensitivity-based incremental evolution method

<p>Abstract</p> <p>Background</p> <p>Reconstructing gene regulatory networks (GRNs) from expression data is one of the most important challenges in systems biology research. Many computational models and methods have been proposed to automate the process of network reconstruction. Inferring robust networks with desired behaviours remains challenging, however. This problem is related to network dynamics but has yet to be investigated using network modeling.</p> <p>Results</p> <p>We propose an incremental evolution approach for inferring GRNs that takes network robustness into consideration and can deal with a large number of network parameters. Our approach includes a sensitivity analysis procedure to iteratively select the most influential network parameters, and it uses a swarm intelligence procedure to perform parameter optimization. We have conducted a series of experiments to evaluate the external behaviors and internal robustness of the networks inferred by the proposed approach. The results and analyses have verified the effectiveness of our approach.</p> <p>Conclusions</p> <p>Sensitivity analysis is crucial to identifying the most sensitive parameters that govern the network dynamics. It can further be used to derive constraints for network parameters in the network reconstruction process. The experimental results show that the proposed approach can successfully infer robust GRNs with desired system behaviors.</p

Invasion success of a widespread invasive predator may be explained by a high predatory efficacy but may be influenced by pathogen infection

Invasive alien species (IAS) can drive community change through ecological interactions. Parasites and pathogens can play an important role in community function including mitigating or enhancing IAS impacts. Despite this, the degree to which pathogen pressure influences IAS impacts remains poorly understood. We quantified the predatory behaviour of the highly invasive alien harlequin ladybird (Harmonia axyridis) and two UK native species, the 7-spot (Coccinella septempunctata) and 2-spot (Adalia bipunctata) ladybirds, using comparative functional response experiments. We investigated the impacts of pathogen infection on the predatory ability of the ladybirds by exposing individuals to Beauveria bassiana, a widespread entomopathogen. Invasive H. axyridis was a more efficient predator than both the native A. bipunctata and C. septempunctata, often having higher attack and/or lower prey handling time coefficients, whereas native A. bipunctata were the least efficient predators. These differences were found in both adult and larval life-stages. Beauveria bassiana infection significantly altered the predatory efficiency of adult and larval ladybird predators. The effects of pathogenic infection differed between species and life-stage but in many cases infection resulted in a reduced predatory ability. We suggest that the interactions between IAS and pathogens are integral to determining invasion success and impact

Invasion success of a widespread invasive predator may be explained by a high predatory efficacy but may be influenced by pathogen infection

Invasive alien species (IAS) can drive community change through ecological interactions. Parasites and pathogens can play an important role in community function including mitigating or enhancing IAS impacts. Despite this, the degree to which pathogen pressure influences IAS impacts remains poorly understood. We quantified the predatory behaviour of the highly invasive alien harlequin ladybird (Harmonia axyridis) and two UK native species, the 7-spot (Coccinella septempunctata) and 2-spot (Adalia bipunctata) ladybirds, using comparative functional response experiments. We investigated the impacts of pathogen infection on the predatory ability of the ladybirds by exposing individuals to Beauveria bassiana, a widespread entomopathogen. Invasive H. axyridis was a more efficient predator than both the native A. bipunctata and C. septempunctata, often having higher attack and/or lower prey handling time coefficients, whereas native A. bipunctata were the least efficient predators. These differences were found in both adult and larval life-stages. Beauveria bassiana infection significantly altered the predatory efficiency of adult and larval ladybird predators. The effects of pathogenic infection differed between species and life-stage but in many cases infection resulted in a reduced predatory ability. We suggest that the interactions between IAS and pathogens are integral to determining invasion success and impact

An analysis of carriers’ selection criteria when choosing container terminals in Pakistan

This paper presents the results of an empirical study conducted by distributing questionnaires to shipping agents working for foreign principals in Karachi, Pakistan. In Part A of the questionnaire, respondents gave a score reflecting the importance of 13 factors affecting terminal selection. Their responses indicate that service quality, loading/discharging rate and handling charges are the most important selection factors. A linear model is developed in which the dependent variable is total stay (in hours). The independent variables are vessel type, vessel size, total TEUs (twenty-foot equivalent units), vessel frequency and past visits of the shipping line. All the coefficients are significant. In the second section (that is, Part B of the questionnaire), respondents gave scores reflecting the quality of different attributes and how they affect the attractiveness of four specific container terminals. One-way ANOVA was used to test whether respondents have significant opinion differences. The result indicated that respondents do differ in opinions. Moreover, factor analysis of the aggregate data produced two factors with strong loading of six attributes in one factor and two attributes in the second. Maritime Economics & Logistics (2009) 11, 270–288. doi:10.1057/mel.2009.8