Current approaches to gene regulatory network modelling

Many different approaches have been developed to model and simulate gene regulatory networks. We proposed the following categories for gene regulatory network models: network parts lists, network topology models, network control logic models, and dynamic models. Here we will describe some examples for each of these categories. We will study the topology of gene regulatory networks in yeast in more detail, comparing a direct network derived from transcription factor binding data and an indirect network derived from genome-wide expression data in mutants. Regarding the network dynamics we briefly describe discrete and continuous approaches to network modelling, then describe a hybrid model called Finite State Linear Model and demonstrate that some simple network dynamics can be simulated in this model

Shedding Light on the Galaxy Luminosity Function

From as early as the 1930s, astronomers have tried to quantify the statistical nature of the evolution and large-scale structure of galaxies by studying their luminosity distribution as a function of redshift - known as the galaxy luminosity function (LF). Accurately constructing the LF remains a popular and yet tricky pursuit in modern observational cosmology where the presence of observational selection effects due to e.g. detection thresholds in apparent magnitude, colour, surface brightness or some combination thereof can render any given galaxy survey incomplete and thus introduce bias into the LF. Over the last seventy years there have been numerous sophisticated statistical approaches devised to tackle these issues; all have advantages -- but not one is perfect. This review takes a broad historical look at the key statistical tools that have been developed over this period, discussing their relative merits and highlighting any significant extensions and modifications. In addition, the more generalised methods that have emerged within the last few years are examined. These methods propose a more rigorous statistical framework within which to determine the LF compared to some of the more traditional methods. I also look at how photometric redshift estimations are being incorporated into the LF methodology as well as considering the construction of bivariate LFs. Finally, I review the ongoing development of completeness estimators which test some of the fundamental assumptions going into LF estimators and can be powerful probes of any residual systematic effects inherent magnitude-redshift data.Comment: 95 pages, 23 figures, 3 tables. Now published in The Astronomy & Astrophysics Review. This version: bring in line with A&AR format requirements, also minor typo corrections made, additional citations and higher rez images adde

Keep off the grass?:Cannabis, cognition and addiction

This is the author accepted manuscript. The final version is available from the publisher via the DOI in this record.In an increasing number of states and countries, cannabis now stands poised to join alcohol and tobacco as a legal drug. Quantifying the relative adverse and beneficial effects of cannabis and its constituent cannabinoids should therefore be prioritized. Whereas newspaper headlines have focused on links between cannabis and psychosis, less attention has been paid to the much more common problem of cannabis addiction. Certain cognitive changes have also been attributed to cannabis use, although their causality and longevity are fiercely debated. Identifying why some individuals are more vulnerable than others to the adverse effects of cannabis is now of paramount importance to public health. Here, we review the current state of knowledge about such vulnerability factors, the variations in types of cannabis, and the relationship between these and cognition and addiction.This work was supported by grants from the US National Institutes of Health to L.H.P. (AA020404, AA006420, AA022249 and AA017447) and by grants from the UK Medical Research Council to H.V.C. and C.J.A.M. (G0800268; MR/K015524/1)

J Nutr Health Aging

BACKGROUND: Aim: The aim of this study was to explore whether multidomain intervention (MI) and Omega-3 Polyunsaturated Fatty Acids supplementation can modify the cognitive function on elderly according to frail status. METHOD: Data are from a secondary exploratory analysis of the Multidomain Alzheimer Preventive Trial (MAPT), a French community-dwellers aged 70 or over reporting subjective memory complaints, but free from clinical dementia. The multidomain intervention consisted of 2 hours group sessions focusing on three domains (cognitive stimulation, physical activity, and nutrition) and a preventive consultation (at baseline, 12 months, and 24 months). For Omega-3 Polyunsaturated Fatty Acids supplementation, participants took two capsules of either placebo or polyunsaturated fatty acids daily. Linear mixed-model repeated-measures analyses were used including baseline, 6, 12, 24 and 36-month follow-up data to assess between-group differences in the change in cognitive tests over 36 months. RESULTS: The overall mean age of the MAPT study population was 75.25(+/-4.38). A tend toward significant differences in TMT-A were found for the effect of the multidomain intervention on the prefrail group compared to non-frail group. The MI and n3 PUFA program could not significantly have reduced cognitive function in a sample of pre-frailty elders. CONCLUSION: This population-based study in community-dwellers aged 70 years or over suggested that multidomain intervention and n3 PUFA supplementation have not significant effects on cognitive function change in frail older adults with memory complaints. The beneficial effect of multidomain intervention and n3 PUFA supplementation on cognitive function did not differ between frail and nonfrail participants