Characterization of ecosystem responses to climatic controls using artificial neural networks

Understanding and modeling ecosystem responses to their climatic controls is one of the major challenges for predicting the effects of global change. Usually, the responses are implemented in models as parameterized functional relationships of a fixed type. In contrast, the inductive approach presented here based on artificial neural networks (ANNs) allows the relationships to be extracted directly from the data. It has been developed to explore large, fragmentary, noisy, and multidimensional datasets, such as the carbon fluxes measured at the ecosystem level with the eddy covariance technique. To illustrate this, our approach has been systematically applied to the daytime carbon flux dataset of the deciduous broadleaf forest Hainich in Germany. The total explainable variability of the half‐hourly carbon fluxes from the driving climatic variables was 93.1%, showing the excellent data mining capability of the ANNs. Total photosynthetic photon flux density was identified as the dominant control of the daytime response, followed by the diffuse radiation. The vapor pressure deficit was the most important nonradiative control. From the ANNs, we were also able to deduce and visualize the dependencies and sensitivities of the response to its climatic controls. With respect to diffuse radiation, the daytime carbon response showed no saturation and the light use efficiency was three times greater for diffuse compared with direct radiation. However, with less potential radiation reaching the forest, the overall effect of diffuse radiation was slightly negative. The optimum uptake of carbon occurred at diffuse fractions between 30% and 40%. By identifying the hierarchy of the climatic controls of the ecosystem response as well as their multidimensional functional relationships, our inductive approach offers a direct interface to the data. This provides instant insight in the underlying ecosystem physiology and links the observational relationships to their representation in the modeling world.     

European Vegetation Survey: update on progress

Abstract. Progress in the European Vegetation Survey is described. 25 countries are now represented in a network committed to common data standards in phytosociological survey, the development of compatible software for data analysis and mapping, the encouragement of national programmes and the development of an overview of European plant communities. Advances in each of these areas of activity is summarised and plans for the future are outlined, most notably the production of a book ‘The Vegetation of Europe’.     

Identification of the Fluvirucin B2 (Sch 38518) Biosynthetic Gene Cluster from Actinomadura fulva subsp. indica ATCC 53714: substrate Specificity of the β-Amino Acid Selective Adenylating Enzyme FlvN

Fluvirucins are 14-membered macrolactam polyketides that show antifungal and antivirus activities. Fluvirucins have the β-alanine starter unit at their polyketide skeletons. To understand the construction mechanism of the β-alanine moiety in fluvirucin biosyntheses, we have identified the biosynthetic cluster of fluvirucin B₂ produced from Actinomadura fulva subsp. indica ATCC 53714. The identified gene cluster contains three polyketide synthases, four characteristic β-amino acid-carrying enzymes, one decarboxylase, and one amidohydrolase. We next investigated the activity of the adenylation enzyme FlvN, which is a key enzyme for the selective incorporation of a β-amino acid substrate. FlvN showed strong preference for l-aspartate over other amino acids such as β-alanine. Based on these results, we propose a biosynthetic pathway for fluvirucin B₂.     

肿瘤精准医学知识数据库的设计与构建

目的:整合现有前沿的大量而分散的精准医学知识以形成系统完整的知识数据库,为个体组学数据的临床应用提供依据,旨在最终实现基于组学特征的精准用药推荐。方法:采用MySQL数据库管理系统构建数据库,从FDA伴随诊断、NCCN指南、My Cancer Genome、GDSC四大权威医学资源中手动收集精准用药知识,并将原始数据标准化、结构化后以统一的格式存储。结果:成功设计并构建了肿瘤精准医学知识库,目前共收录1 940条精准用药指导,涵盖了基因突变等14种不同类型的组学特征。结论:精准医学知识数据库收录了肿瘤分子组学特征和治疗策略的关联信息,可为临床上个体化治疗方案的制订提供参考依据。数据库的建立为精准医疗临床决策支持系统的开发奠定了基础。     

重金属胁迫对真菌生长及发酵液pH的影响

[背景]矿区废渣堆重金属污染严重,废渣堆分布着一些耐重金属的微生物.[目标]探究重金属胁迫对真菌生长及发酵液pH的影响.[方法]从金川矿区废渣堆采集土样,分离培养具有产酸能力的真菌,采用形态学与分子生物学技术鉴定这些菌株,并测定其产酸能力及其对pb2+、Cd2+和Zn2+的耐受性.[结果]形态学及18S rRNA基因序...     

蛋白质折叠类型分类方法及分类数据库

蛋白质折叠规律研究是生命科学重大前沿课题,折叠分类是蛋白质折叠研究的基础。目前的蛋白质折叠类型分类基本上靠专家完成,不同的库分类并不相同,迫切需要一个建立在统一原理基础上的蛋白质折叠类型数据库。本文以ASTRAL-1.65数据库中序列同源性在25%以下、分辨率小于2.5的蛋白为基础,通过对蛋白质空间结构的观察及折叠类型特征的分析,提出以蛋白质折叠核心为中心、以蛋白质结构拓扑不变性为原则、以蛋白质折叠核心的规则结构片段组成、连接和空间排布为依据的蛋白质折叠类型分类方法,建立了低相似度蛋白质折叠分类数据库——LIFCA,包含259种蛋白质折叠类型。数据库的建立,将为进一步的蛋白质折叠建模及数据挖掘、蛋白质折叠识别、蛋白质折叠结构进化研究奠定基础。