A mixture of shifted asymmetric Laplace distributions is introduced and used for clustering and classification. A variant of the EM algorithm is developed for parameter estimation by exploiting the relationship with the generalized inverse Gaussian distribution. This approach is mathematically elegant and relatively computationally straightforward. Our novel mixture modelling approach is demonstrated on both simulated and real data to illustrate clustering and classification applications. In these analyses, our mixture of shifted asymmetric Laplace distributions performs favourably when compared to the popular Gaussian approach. This work, which marks an important step in the non-Gaussian model-based clustering and classification direction, concludes with discussion as well as suggestions for future work.

Natural products represent a prominent source of pharmaceutically and industrially important agents. Calculating the chemical similarity of two molecules is a central task in cheminformatics, with applications at multiple stages of the drug discovery pipeline. Quantifying the similarity of natural products is a particularly important problem, as the biological activities of these molecules have been extensively optimized by natural selection. The large and structurally complex scaffolds of natural products distinguish their physical and chemical properties from those of synthetic compounds. However, no analysis of the performance of existing methods for molecular similarity calculation specific to natural products has been reported to date. Here, we present LEMONS, an algorithm for the enumeration of hypothetical modular natural product structures. We leverage this algorithm to conduct a comparative analysis of molecular similarity methods within the unique chemical space occupied by modular natural products using controlled synthetic data, and comprehensively investigate the impact of diverse biosynthetic parameters on similarity search. We additionally investigate a recently described algorithm for natural product retrobiosynthesis and alignment, and find that when rule-based retrobiosynthesis can be applied, this approach outperforms conventional two-dimensional fingerprints, suggesting it may represent a valuable approach for the targeted exploration of natural product chemical space and microbial genome mining. Our open-source algorithm is an extensible method of enumerating hypothetical natural product structures with diverse potential applications in bioinformatics.Electronic supplementary materialThe online version of this article (doi:10.1186/s13321-017-0234-y) contains supplementary material, which is available to authorized users.

A mixture of multiple scaled generalized hyperbolic distributions (MMSGHDs) is introduced. Then, a coalesced generalized hyperbolic distribution (CGHD) is developed by joining a generalized hyperbolic distribution with a multiple scaled generalized hyperbolic distribution. After detailing the development of the MMSGHDs, which arises via implementation of a multi-dimensional weight function, the density of the mixture of CGHDs is developed. A parameter estimation scheme is developed using the everexpanding class of MM algorithms and the Bayesian information criterion is used for model selection. The issue of cluster convexity is examined and a special case of the MMSGHDs is developed that is guaranteed to have convex clusters. These approaches are illustrated and compared using simulated and real data. The identifiability of the MMSGHDs and the mixture of CGHDs is discussed in an appendix.

Nicotine is an addictive compound that activates neuronal nicotinic acetylcholine receptors (nAChRs) and causes behavioural effects that vary with dose, schedule of administration, and animal model. In zebrafish (Danio rerio), acute doses of nicotine have been consistently found to have anxiolytic properties, whereas, chronic exposure elicits anxiogenic effects. To date, however, studies on repeated nicotine administration and the effects of nicotine withdrawal have not been well explored using this model. In this study, we administered nicotine with three different dosing regimens: 1. Single exposures of a "high" dose (25, 50, 100, or 400 mg/L) for 3 minutes. 2. Single exposures to a "low" dose (2.5, 5, or 20 mg/L) for one hour. 3. Repeated one-hour exposure to a "low" dose (2.5, 5, or 20 mg/L) for 21 days. The novel object approach test was used to examine boldness based on the tendency of the fish to explore a novel object. Acutely, nicotine significantly increased the time spent approaching the object with both three-minute and onehour durations of exposure, indicating increased boldness. Conversely, after repeated nicotine exposure for 21 days, fish spent less time approaching the object suggesting a decrease in boldness. Distance moved was unaffected one hour after repeated nicotine exposure, yet decreased after a two-day withdrawal period. Our work suggests that nicotine can have opposing effects on boldness that vary based on dosage and schedule of exposure. The global prevalence of tobacco smoking among adults has declined in recent decades, however, the number of daily smokers has increased due to population growth 1. The harmful effects of repeated tobacco use (e.g. cancer, stroke and heart disease) result in tobacco use being the leading cause of preventable deaths worldwide 2 at about 7 million per year 3. When tobacco is consumed, most commonly by smoking, nicotine enters the central nervous system and binds to neuronal nicotinic acetylcholine receptors (nAChRs) that are normally activated by endogenous acetylcholine 4. Repeated nicotine use results in modifications to dopamine and acetylcholine pathways on reinforcement circuits in the midbrain and cortex 5 and causes a pleasurable experience via the activation of these circuits which reinforces self-administration 6. Contributing to the addictive nature of nicotine is the effect it has on emotion in humans 7,8. The acute effect of nicotine on anxiety, however, seems to depend on dose and varies across animal models. In rodent models, low doses of nicotine have anxiolytic effects on social interaction, whereas, high doses have an anxiogenic effect 7. Low doses of nicotine have also been shown to increase the amount of time some strains of mice spend in a mirrored chamber 9 as well as the time they spend in the white side of a white/black test box 10 , supporting an increase in boldness at low doses. Other studies, however, have failed to produce evidence that nicotine impacts anxiety and/ or boldness levels. For example, mice tested in an elevated ...