Common inaccuracies and errors in the application of statistical methods in soil science

The most common inaccuracies and errors in the application of statistical methods found in Russian publications on soil science are considered. When designating random variables and distribution parameters in Greek letters, it is necessary to designate those that refer to general populations, and Latin letters – to sampling ones. A detailed description of the experiment and what the replications relate to allows you to draw correct conclusions from the study. It is necessary to avoid pseudoreplication when results at closely located sampling points are considered as characteristics of soil variability over large distances. Expanding the list of descriptive statistics will allow you to use a specific study in meta-analysis. Calculating the confidence interval for the average using the Student's test at different significance levels expands the scope of possible values of the average, but this approach is justified only if the indicator does not differ too much from the normal distribution. When testing statistical hypotheses, it is necessary to pay attention not only to the level of significance, but also to the power of the criterion. The normality distribution hypothesis can be tested using various criteria. The success of applying the criterion depends not only on the validity of the null hypothesis (a truly normal distribution), but also on other reasons: on the sample size and on the alternatives for which the criterion tests the hypothesis. Any statement about the type of relationship between features based on the correlation coefficient (Pearson or Spearman) is meaningless without specifying the number of replicates, since it is the number of replicates that determines the significance of the difference between the correlation coefficient and zero. It is proposed that authors and reviewers pay closer attention to such errors

A User-centric Framework for Accessing Biological Sources and Tools

Biologists face two problems in interpreting their experiments: the integration of their data with information from multiple heterogeneous sources and data analysis with bioinformatics tools. It is difficult for scientists to choose between the numerous sources and tools without assistance. Following a thorough analysis of scientists’ needs during the querying process, we found that biologists express preferences concerning the sources to be queried and the tools to be used. Interviews also showed that the querying process itself – the strategy followed – differs between scientists. In response to these findings, we have introduced a user-centric framework allowing to specify various querying processes. Then we have developed the BioGuide system which helps the scientists to choose suitable sources and tools, find complementary information in sources, and deal with divergent data. It is generic in that it can be adapted by each user to provide answers respecting his/her preferences, and obtained following his/her strategies

FlyEx, the quantitative atlas on segmentation gene expression at cellular resolution

The datasets on gene expression are the valuable source of information about the functional state of an organism. Recently, we have acquired the large dataset on expression of segmentation genes in the Drosophila blastoderm. To provide efficient access to the data, we have developed the FlyEx database (http://urchin.spbcas.ru/flyex). FlyEx contains 4716 images of 14 segmentation gene expression patterns obtained from 1579 embryos and 9 500 000 quantitative data records. Reference data are available for all segmentation genes in cycles 11–13 and all temporal classes of cycle 14A. FlyEx supports operations on images of gene expression patterns. The database can be used to examine the quality of data, analyze the dynamics of formation of segmentation gene expression domains, as well as to estimate the variability of gene expression patterns. Currently, a user is able to monitor and analyze the dynamics of formation of segmentation gene expression domains over the whole period of segment determination, that amounts to 1.5 h of development. FlyEx supports the data downloads and construction of personal reference datasets, that makes it possible to more effectively use and analyze data

Promiscuous targeting of bromodomains by bromosporine identifies BET proteins as master regulators of primary transcription response in leukemia

Bromodomains (BRDs) have emerged as compelling targets for cancer therapy. The development of selective and potent BET (bromo and extra-terminal) inhibitors and their significant activity in diverse tumor models have rapidly translated into clinical studies and have motivated drug development efforts targeting non-BET BRDs. However, the complex multidomain/subunit architecture of BRD protein complexes complicates predictions of the consequences of their pharmacological targeting. To address this issue, we developed a promiscuous BRD inhibitor [bromosporine (BSP)] that broadly targets BRDs (including BETs) with nanomolar affinity, creating a tool for the identification of cellular processes and diseases where BRDs have a regulatory function. As a proof of principle, we studied the effects of BSP on leukemic cell lines known to be sensitive to BET inhibition and found, as expected, strong antiproliferative activity. Comparison of the modulation of transcriptional profiles by BSP after a short exposure to the inhibitor resulted in a BET inhibitor signature but no significant additional changes in transcription that could account for inhibition of other BRDs. Thus, nonselective targeting of BRDs identified BETs, but not other BRDs, as master regulators of context-dependent primary transcription response.The Structural Genomics Consortium is a registered charity (no. 1097737) that receives funds from AbbVie, Bayer Pharma AG, Boehringer Ingelheim, Canada Foundation for Innovation, Eshelman Institute for Innovation, Genome Canada, Innovative Medicines Initiative (EU/EFPIA) (ULTRA-DD grant 115766), Janssen, Merck & Co., Novartis Pharma AG, Ontario Ministry of Economic Development and Innovation, Pfizer, São Paulo Research Foundation (FAPESP), Takeda, and Wellcome Trust (092809/Z/10/Z). P.F., S.P., and C.-Y.W. were supported by a Wellcome Career Development Fellowship (095751/Z/11/Z). A.-C.G. is the Canada Research Chair in Functional Proteomics and the Lea Reichmann Chair in Cancer Proteomics and was supported by the Canadian Institutes of Health Research (foundation grant FDN143301). J.-P.L. was supported by a Cancer Research Society (Canada) Scholarship for the Next Generation of Scientists

Mechanisms of gap gene expression canalization in the Drosophila blastoderm

<p>Abstract</p> <p>Background</p> <p>Extensive variation in early gap gene expression in the <it>Drosophila </it>blastoderm is reduced over time because of gap gene cross regulation. This phenomenon is a manifestation of canalization, the ability of an organism to produce a consistent phenotype despite variations in genotype or environment. The canalization of gap gene expression can be understood as arising from the actions of attractors in the gap gene dynamical system.</p> <p>Results</p> <p>In order to better understand the processes of developmental robustness and canalization in the early <it>Drosophila </it>embryo, we investigated the dynamical effects of varying spatial profiles of Bicoid protein concentration on the formation of the expression border of the gap gene <it>hunchback</it>. At several positions on the anterior-posterior axis of the embryo, we analyzed attractors and their basins of attraction in a dynamical model describing expression of four gap genes with the Bicoid concentration profile accounted as a given input in the model equations. This model was tested against a family of Bicoid gradients obtained from individual embryos. These gradients were normalized by two independent methods, which are based on distinct biological hypotheses and provide different magnitudes for Bicoid spatial variability. We showed how the border formation is dictated by the biological initial conditions (the concentration gradient of maternal Hunchback protein) being attracted to specific attracting sets in a local vicinity of the border. Different types of these attracting sets (point attractors or one dimensional attracting manifolds) define several possible mechanisms of border formation. The <it>hunchback </it>border formation is associated with intersection of the spatial gradient of the maternal Hunchback protein and a boundary between the attraction basins of two different point attractors. We demonstrated how the positional variability for <it>hunchback </it>is related to the corresponding variability of the basin boundaries. The observed reduction in variability of the <it>hunchback </it>gene expression can be accounted for by specific geometrical properties of the basin boundaries.</p> <p>Conclusion</p> <p>We clarified the mechanisms of gap gene expression canalization in early <it>Drosophila </it>embryos. These mechanisms were specified in the case of <it>hunchback </it>in well defined terms of the dynamical system theory.</p

Canalization of Gene Expression and Domain Shifts in the Drosophila Blastoderm by Dynamical Attractors

The variation in the expression patterns of the gap genes in the blastoderm of the fruit fly Drosophila melanogaster reduces over time as a result of cross regulation between these genes, a fact that we have demonstrated in an accompanying article in PLoS Biology (see Manu et al., doi:10.1371/journal.pbio.1000049). This biologically essential process is an example of the phenomenon known as canalization. It has been suggested that the developmental trajectory of a wild-type organism is inherently stable, and that canalization is a manifestation of this property. Although the role of gap genes in the canalization process was established by correctly predicting the response of the system to particular perturbations, the stability of the developmental trajectory remains to be investigated. For many years, it has been speculated that stability against perturbations during development can be described by dynamical systems having attracting sets that drive reductions of volume in phase space. In this paper, we show that both the reduction in variability of gap gene expression as well as shifts in the position of posterior gap gene domains are the result of the actions of attractors in the gap gene dynamical system. Two biologically distinct dynamical regions exist in the early embryo, separated by a bifurcation at 53% egg length. In the anterior region, reduction in variation occurs because of stability induced by point attractors, while in the posterior, the stability of the developmental trajectory arises from a one-dimensional attracting manifold. This manifold also controls a previously characterized anterior shift of posterior region gap domains. Our analysis shows that the complex phenomena of canalization and pattern formation in the Drosophila blastoderm can be understood in terms of the qualitative features of the dynamical system. The result confirms the idea that attractors are important for developmental stability and shows a richer variety of dynamical attractors in developmental systems than has been previously recognized