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Several tests of neutral evolution employ the observed number of segregating sites and properties of the haplotype frequency distribution as summary statistics and use simulations to obtain rejection probabilities. Here we develop a "haplotype configuration test" of neutrality (HCT) based on the full haplotype frequency distribution. To enable exact computation of rejection probabilities for small samples, we derive a recursion under the standard coalescent model for the joint distribution of the haplotype frequencies and the number of segregating sites. For larger samples, we consider simulation-based approaches. The utility of the HCT is demonstrated in simulations of alternative models and in application to data from Drosophila melanogaster.S ELECTIVELY neutral models of within-species evo- (Hudson et al. 1994). Alternatively, because haplotype frequency distributions may differ greatly across demolution consist of a model that describes the genealgraphic scenarios (Nei et al. 1975;Donnelly 1996), ogy of sampled DNA sequences and a model for the haplotype tests can also help to identify deviations from stochastic process of mutation along the branches of the the demographic assumptions of the standard neutral genealogy. Typical neutral models use the coalescent model. process (Nordborg 2001, for example) to describe the Some of the first haplotype tests, such as the Ewensgenealogy and the infinitely many sites model (WattWatterson homozygosity test, were based on the Ewens erson, 1975) for the mutation process. Many theoretical (1972) sampling theory for the infinitely many alleles predictions have been made under the standard neutral mutation model. Because "allele" in this model and model, in which the particular coalescent model chosen "haplotype" in the infinitely many sites model have the is the one with constant population size. same meaning, the Ewens (1972) theory provides the As an alternative to computationally intensive compariconditional distribution of the haplotype frequency vecsons of likelihoods of DNA sequence data under null and tor C given the sample size n and the number of distinct alternative models (Griffiths and Tavaré 1994; Kuhner haplotypes K, under the standard neutral model (Tavaré et al.

Rice is one of the most important crops in the world; meanwhile, the rice field is also an important contributor to greenhouse gas methane emission. Therefore, it is important to get an accurate estimation of rice acreage for both food production and climate change related studies. The eastern plain region is one of the major single-cropped rice (SCR) growing areas in China. Subjected to the topography and intensified human activities, the rice fields are generally fragmented and irregular. How remote sensing can meet this challenge to accurately estimate the acreage of the rice in this region using medium-resolution imagery is the topic of this study. In this study, the applicability of the Chinese HJ-1A/B satellites and a two-band enhanced vegetation index (EVI2) was investigated. Field campaigns were carried out during the rice growing season and ground-truth data were collected for classification accuracy assessments in 2012. A stepwise classification strategy utilizing the EVI2 signatures during key phenology stages, i.e., the transplanting and the vegetative to reproductive transition phases, of the SCR was proposed, and the overall classification accuracy was 91.7%. The influence of the mixed pixel and boundary effects to classification accuracy was also investigated. This work demonstrates OPEN ACCESSRemote Sens. 2015, 7 3468 that the Chinese HJ-1A/B data are suitable data source to estimating SCR cropping area under complex land cover composition.

Background: Identification of novel cancer-causing genes is one of the main goals in cancer research. The rapid accumulation of genome-wide protein-protein interaction (PPI) data in humans has provided a new basis for studying the topological features of cancer genes in cellular networks. It is important to integrate multiple genomic data sources, including PPI networks, protein domains and Gene Ontology (GO) annotations, to facilitate the identification of cancer genes.

The PROSPECT leaf optical model has, to date, well-separated the effects of total chlorophyll and carotenoids on leaf reflectance and transmittance in the 400–800 nm. Considering variations in chlorophyll a:b ratio with leaf age and physiological stress, a further separation of total plant-based chlorophylls into chlorophyll a and chlorophyll b is necessary for advanced monitoring of plant growth. In this study, we present an extended version of PROSPECT model (hereafter referred to as PROSPECT-MP) that can combine the effects of chlorophyll a, chlorophyll b and carotenoids on leaf directional hemispherical reflectance and transmittance (DHR and DHT) in the 400–800 nm. The LOPEX93 dataset was used to evaluate the capabilities of PROSPECT-MP for spectra modelling and pigment retrieval. The results show that PROSPECT-MP can both simultaneously retrieve leaf chlorophyll a and b, and also performs better than PROSPECT-5 in retrieving carotenoids concentrations. As for the simulation of DHR and DHT, the performances of PROSPECT-MP are similar to that of PROSPECT-5. This study demonstrates the potential of PROSPECT-MP for improving capabilities of remote sensing of leaf photosynthetic pigments (chlorophyll a, chlorophyll b and carotenoids) and for providing a framework for future refinements in the modelling of leaf optical properties.