Blurry artifacts: a retraction

Abstract. This note is to apologize for an error in the computer program used to evaluate the random data used in Fuzzy Set Ordination according to Zhang & Oxley. After correction of this error no artifacts could be detected any longer. However, the basic conclusion of the earlier critical note still stands: if one selects environmental variables after analyzing the results of a multivariate gradient analysis, and then uses these variables as input into a multiple univariate gradient analysis, the results are expected to be comparable.     

国家自然科学基金评审程序剖析──1993年和1994年植物学科面上基金项目分析

国家自然科学基金评审程序剖析──１９９３年和１９９４年植物学科面上基金项目分析陈峰,朱大保（中国科学院武汉植物研究所武汉４３００７４）（国家自然科学基金委员会生命科学部北京１０００８３）关键词基金,评审,科研立项,学科ＡＮＡＬＹＳＬＳＦＯＲＪＵＤＧＥ...     

Methylation of histone H3 at lysine 37 by Set1 and Set2 prevents spurious DNA replication

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Prediction of shape and internal structure of the proximal femur using a modified level set method for structural topology optimisation

A computational framework was developed to simulate the bone remodelling process as a structural topology optimisation problem. The mathematical formulation of the Level Set technique was extended and then implemented into a coronal plane model of the proximal femur to simulate the remodelling of internal structure and external geometry of bone into the optimal state. Results indicated that the proposed approach could reasonably mimic the major geometrical and material features of the natural bone. Simulation of the internal bone remodelling on the typical gross shape of the proximal femur, resulted in a density distribution pattern with good consistency with that of the natural bone. When both external and internal bone remodelling were simulated simultaneously, the initial rectangular design domain with a regularly distributed mass reduced gradually to an optimal state with external shape and internal structure similar to those of the natural proximal femur.     

Scale matters

During meiosis in many organisms, homologous chromosomes engage in numerous recombination events initiated by DNA double-strand breaks (DSBs) formed by the Spo11 protein. DSBs are distributed nonrandomly, which governs how recombination influences inheritance and genome evolution. The chromosomal features that shape DSB distribution are not well understood. In the budding yeast Saccharomyces cerevisiae, trimethylation of lysine 4 of histone H3 (H3K4me3) has been suggested to play a causal role in targeting Spo11 activity to small regions of preferred DSB formation called hotspots. The link between H3K4me3 and DSBs is supported in part by a genome-wide spatial correlation between the two. However, this correlation has only been evaluated using relatively low-resolution maps of DSBs, H3K4me3 or both. These maps illuminate chromosomal features that influence DSB distributions on a large scale (several kb and greater) but do not adequately resolve features, such as chromatin structure, that act on finer scales (kb and shorter). Using recent nucleotide-resolution maps of DSBs and meiotic chromatin structure, we find that the previously described spatial correlation between H3K4me3 and DSB hotspots is principally attributable to coincident localization of both to gene promoters. Once proximity to the nucleosome-depleted regions in promoters is accounted for, H3K4me3 status has only modest predictive power for determining DSB frequency or location. This analysis provides a cautionary tale about the importance of scale in genome-wide analyses of DSB and recombination patterns.     

On statistical inference for the random set generated Cox process with set-marking

Cox point process is a process class for hierarchical modelling of systems of non-interacting points in Rd under environmental heterogeneity which is modelled through a random intensity function. In this work a class of Cox processes is suggested where the random intensity is generated by a random closed set. Such heterogeneity appears for example in forestry where silvicultural treatments like harvesting and site-preparation create geometrical patterns for tree density variation in two different phases. In this paper the second order property, important both in data analysis and in the context of spatial sampling, is derived. The usefulness of the random set generated Cox process is highly increased, if for each point it is observed whether it is included in the random set or not. This additional information is easy and economical to obtain in many cases and is hence of practical value; it leads to marks for the points. The resulting random set marked Cox process is a marked point process where the marks are intensity-dependent. The problem with set-marking is that the marks are not a representative sample from the random set. This paper derives the second order property of the random set marked Cox process and suggests a practical estimation method for area fraction and covariance of the random set and for the point densities within and outside the random set. A simulated example and a forestry example are given.