Weighted k-Nearest-Neighbor Techniques and Ordinal Classification

In the field of statistical discrimination k-nearest neighbor classification is a well-known, easy and successful method. In this paper we present an extended version of this technique, where the distances of the nearest neighbors can be taken into account. In this sense there is a close connection to LOESS, a local regression technique. In addition we show possibilities to use nearest neighbor for classification in the case of an ordinal class structure. Empirical studies show the advantages of the new techniques

Rapid Determination of Proteins in Serum and Cerebrospinal Fluid by Laser-Nephelometry

Peer Reviewe

apex: phylogenetics with multiple genes.

Genetic sequences of multiple genes are becoming increasingly common for a wide range of organisms including viruses, bacteria and eukaryotes. While such data may sometimes be treated as a single locus, in practice, a number of biological and statistical phenomena can lead to phylogenetic incongruence. In such cases, different loci should, at least as a preliminary step, be examined and analysed separately. The r software has become a popular platform for phylogenetics, with several packages implementing distance-based, parsimony and likelihood-based phylogenetic reconstruction, and an even greater number of packages implementing phylogenetic comparative methods. Unfortunately, basic data structures and tools for analysing multiple genes have so far been lacking, thereby limiting potential for investigating phylogenetic incongruence. In this study, we introduce the new r package apex to fill this gap. apex implements new object classes, which extend existing standards for storing DNA and amino acid sequences, and provides a number of convenient tools for handling, visualizing and analysing these data. In this study, we introduce the main features of the package and illustrate its functionalities through the analysis of a simple data set

Asymmetric Biotic Interactions and Abiotic Niche Differences Revealed by a Dynamic Joint Species Distribution Model

A species’ distribution and abundance are determined by abiotic conditions and biotic interactions with other species in the community. Most species distribution models correlate the occurrence of a single species with environmental variables only, and leave out biotic interactions. To test the importance of biotic interactions on occurrence and abundance, we compared a multivariate spatiotemporal model of the joint abundance of two invasive insects that share a host plant, hemlock woolly adelgid (HWA; Adelges tsugae) and elongate hemlock scale (EHS; Fiorina externa), to independent models that do not account for dependence among co‐occurring species. The joint model revealed that HWA responded more strongly to abiotic conditions than EHS. Additionally, HWA appeared to predispose stands to subsequent increase of EHS, but HWA abundance was not strongly dependent on EHS abundance. This study demonstrates how incorporating spatial and temporal dependence into a species distribution model can reveal the dependence of a species’ abundance on other species in the community. Accounting for dependence among co‐occurring species with a joint distribution model can also improve estimation of the abiotic niche for species affected by interspecific interactions

Photosynthetic acclimation of Nannochloropsis oculata investigated by multi-wavelength chlorophyll fluorescence analysis

Multi-wavelength chlorophyll fluorescence analysis was utilised to examine the photosynthetic efficiency of the biofuel-producing alga Nannochloropsis oculata, grown under two light regimes; low (LL) and high (HL) irradiance levels. Wavelength dependency was evident in the functional absorption cross-section of Photosystem II (σII(λ)), absolute electron transfer rates (ETR(II)), and non-photochemical quenching (NPQ) of chlorophyll fluorescence in both HL and LL cells. While σII(λ) was not significantly different between the two growth conditions, HL cells upregulated ETR(II) 1.6-1.8-fold compared to LL cells, most significantly in the wavelength range of 440-540nm. This indicates preferential utilisation of blue-green light, a highly relevant spectral region for visible light in algal pond conditions. Under these conditions, the HL cells accumulated saturated fatty acids, whereas polyunsaturated fatty acids were more abundant in LL cells. This knowledge is of importance for the use of N. oculata for fatty acid production in the biofuel industry. © 2014 Elsevier Ltd

Accelerating Bayesian hierarchical clustering of time series data with a randomised algorithm

We live in an era of abundant data. This has necessitated the development of new and innovative statistical algorithms to get the most from experimental data. For example, faster algorithms make practical the analysis of larger genomic data sets, allowing us to extend the utility of cutting-edge statistical methods. We present a randomised algorithm that accelerates the clustering of time series data using the Bayesian Hierarchical Clustering (BHC) statistical method. BHC is a general method for clustering any discretely sampled time series data. In this paper we focus on a particular application to microarray gene expression data. We define and analyse the randomised algorithm, before presenting results on both synthetic and real biological data sets. We show that the randomised algorithm leads to substantial gains in speed with minimal loss in clustering quality. The randomised time series BHC algorithm is available as part of the R package BHC, which is available for download from Bioconductor (version 2.10 and above) via http://bioconductor.org/packages/2.10/bioc/html/BHC.html. We have also made available a set of R scripts which can be used to reproduce the analyses carried out in this paper. These are available from the following URL. https://sites.google.com/site/randomisedbhc/

Turnip mosaic potyvirus probably first spread to Eurasian brassica crops from wild orchids about 1000 years ago

Turnip mosaic potyvirus (TuMV) is probably the most widespread and damaging virus that infects cultivated brassicas worldwide. Previous work has indicated that the virus originated in western Eurasia, with all of its closest relatives being viruses of monocotyledonous plants. Here we report that we have identified a sister lineage of TuMV-like potyviruses (TuMV-OM) from European orchids. The isolates of TuMV-OM form a monophyletic sister lineage to the brassica-infecting TuMVs (TuMV-BIs), and are nested within a clade of monocotyledon-infecting viruses. Extensive host-range tests showed that all of the TuMV-OMs are biologically similar to, but distinct from, TuMV-BIs and do not readily infect brassicas. We conclude that it is more likely that TuMV evolved from a TuMV-OM-like ancestor than the reverse. We did Bayesian coalescent analyses using a combination of novel and published sequence data from four TuMV genes [helper component-proteinase protein (HC-Pro), protein 3(P3), nuclear inclusion b protein (NIb), and coat protein (CP)]. Three genes (HC-Pro, P3, and NIb), but not the CP gene, gave results indicating that the TuMV-BI viruses diverged from TuMV-OMs around 1000 years ago. Only 150 years later, the four lineages of the present global population of TuMV-BIs diverged from one another. These dates are congruent with historical records of the spread of agriculture in Western Europe. From about 1200 years ago, there was a warming of the climate, and agriculture and the human population of the region greatly increased. Farming replaced woodlands, fostering viruses and aphid vectors that could invade the crops, which included several brassica cultivars and weeds. Later, starting 500 years ago, inter-continental maritime trade probably spread the TuMV-BIs to the remainder of the world

Life history linked to immune investment in developing amphibians

The broad diversity of amphibian developmental strategies has been shaped, in part, by pathogen pressure, yet trade-offs between the rate of larval development and immune investment remain poorly understood. The expression of antimicrobial peptides (AMPs) in skin secretions is a crucial defense against emerging amphibian pathogens and can also indirectly affect host defense by influencing the composition of skin microbiota. We examined the constitutive or induced expression of AMPs in 17 species at multiple life-history stages. We found that AMP defenses in tadpoles of species with short larval periods (fast pace of life) were reduced in comparison with species that overwinter as tadpoles and grow to a large size. A complete set of defensive peptides emerged soon after metamorphosis. These findings support the hypothesis that species with a slow pace of life invest energy in AMP production to resist potential pathogens encountered during the long larval period, whereas species with a fast pace of life trade this investment in defense for more rapid growth and development