基于过程模型CROBAS的全局灵敏度分析方法比较

过程机理模型在开发过程中常受限于生理学参数无法直接或准确测量.全局灵敏度分析可以评估模型预测结果对于生理学参数变化的响应,为模型结构改进、数据收集和参数校准提供参考.本研究基于过程模型CROBAS,以华山松为例,选取模型中描述树木结构关系的10个参数,以树高和各器官生物量的Nash-Sutcliffe效率(NSE)为目...     

Lower Statistical Support with Larger Data Sets: Insights from the Ochrophyta Radiation

It is commonly assumed that increasing the number of characters has the potential to resolve evolutionary radiations. Here, we studied photosynthetic stramenopiles (Ochrophyta) using alignments of heterogeneous origin mitochondrion, plastid, and nucleus. Surprisingly while statistical support for the relationships between the six major Ochrophyta lineages increases when comparing the mitochondrion (6,762 sites) and plastid (21,692 sites) trees, it decreases in the nuclear (209,105 sites) tree. Statistical support is not simply related to the data set size but also to the quantity of phylogenetic signal available at each position and our ability to extract it. Here, we show that this ability for current phylogenetic methods is limited, because conflicting results were obtained when varying taxon sampling. Even though the use of a better fitting model improved signal extraction and reduced the observed conflicts, the plastid data set provided higher statistical support for the ochrophyte radiation than the larger nucleus data set. We propose that the higher support observed in the plastid tree is due to an acceleration of the evolutionary rate in one short deep internal branch, implying that more phylogenetic signal per position is available to resolve the Ochrophyta radiation in the plastid than in the nuclear data set. Our work therefore suggests that, in order to resolve radiations, beyond the obvious use of data sets with more positions, we need to continue developing models of sequence evolution that better extract the phylogenetic signal and design methods to search for genes/characters that contain more signal specifically for short internal branches.     

数字细胞模型的研究及应用

组学分析技术的发展推动生物学逐渐成为一门以数据分析为中心的科学。依托生物数据在细胞整体系统水平建立数字细胞模型,对于理解细胞系统组织原理和生命产生进化规律,预测各种环境和基因扰动对细胞功能的影响并指导设计人工生命具有重要意义,因此数字细胞的构建模拟设计已成为合成生物学的核心研究内容与底层支撑技术。本文重点对天津工业生物技术研究所创立十年来在数字细胞研究方面的进展进行回顾介绍,重点包括基因组尺度代谢网络模型的构建、质控以及其在途径设计和指导菌种代谢工程改造方面的应用,进一步结合近年来细胞模型研究的前沿趋势,对整合多种约束的模型的构建和分析研究方面的最新成果进行了介绍,最后对数字细胞研究的未来发展方向进行展望。数字细胞技术将与基因组测序、合成和编辑等合成生物学前沿技术一起提升人们对生命进行读写改创的能力。     

Comments on the manna model

WANGERSKY and WANGERSKY'S (1980, 1981, 1983) Manna models on algal patchiness and competition are essentially stochastic models. Analysis of their phase-spatial properties, however, reveals complementary, deterministic features: interspecific competition is relatively ineffective because of the high degree of compartmentalization of resource supply and consumption; the probability of consumption in a given place at a given time is largely independent of the rate of consumption in other places.     

Organoids in recapitulating tumorigenesis driven by risk factors: Current trends and future perspectives

Environmental and exogenous/ endogenous factors, in a setting of individual genetic predisposition, contribute to the cancer development. Over the years, epidemical evidence increasingly highlights the correlations of multiple cancer incentives and genetic alterations with cancer incidence. Unraveling the pivotal carcinogenesis events prompted by particular risk factors remarkably advances early surveillance and oncogenesis intervening. Traditional cell-based models and animal-based models are unrealistic and unreliable for translational study, respectively ascribing to the limited tumor heterogeneity and species-related variation. Organoid emerged as a fidelity model that well preserves the properties of its origin. With inherent quality of holistic perspective, organoid is therefore ideally suited for delineating the carcinogenesis under risk exposure, in favor of understanding pathogen-host interactions and alleviating cancer initiation. In this review, we have summarized the organoid model-based evidence that identified or validated carcinogenic risks, mainly including diet, aging, microbial infection, and chemical exposure. In addition, we envisioned the exciting prospect of organoid model in screening promising treatment and/or prevention during tumorigenesis. As a robust 3D in vitro system, organoid has been widespread applied in basial and clinical cancer research, which may elucidate crucial mechanisms of oncogenesis and develop novel targeting strategies.     

The effect of past changes in inter‐annual temperature variability on tree distribution limits

Aim The northern limits of temperate broadleaved species in Fennoscanndia are controlled by their requirements for summer warmth for successful regeneration and growth as well as by the detrimental effects of winter cold on plant tissue. However, occurrences of meteorological conditions with detrimental effects on individual species are rare events rather than a reflection of average conditions. We explore the effect of changes in inter‐annual temperature variability on the abundances of the tree species Tilia cordata, Quercus robur and Ulmus glabra near their distribution limits using a process‐based model of ecosystem dynamics. Location A site in central Sweden and a site in southern Finland were used as examples for the ecotone between boreal and temperate forests in Fennoscandia. The Finnish site was selected because of the availability of varve‐thickness data. Methods The dynamic vegetation model LPJ‐GUESS was run with four scenarios of inter‐annual temperature forcing for the last 10,000 years. In one scenario the variability in the thickness of summer and winter varves from the annually laminated lake in Finland was used as a proxy for past inter‐annual temperature variability. Two scenarios were devised to explore systematically the effect of stepwise changes in the variance and shape parameter of a probability distribution. All variability scenarios were run both with and without the long‐term trend in Holocene temperature change predicted by an atmospheric general circulation model. Results Directional changes in inter‐annual temperature variability have significant effects on simulated tree distribution limits through time. Variations in inter‐annual temperature variability alone are shown to alter vegetation composition by magnitudes similar to the magnitude of changes driven by variation in mean temperatures. Main conclusions The varve data indicate that inter‐annual climate variability has changed in the past. The model results show that past changes in species abundance can be explained by changes in the inter‐annual variability of climate parameters as well as by mean climate. Because inter‐annual climatic variability is predicted to change in the future, this component of climate change should be taken into account both when making projections of future plant distributions and when interpreting vegetation history.     

Score Tests for Exploring Complex Models: Application to HIV Dynamics Models

In biostatistics, more and more complex models are being developed. This is particularly the case in system biology. Fitting complex models can be very time‐consuming, since many models often have to be explored. Among the possibilities are the introduction of explanatory variables and the determination of random effects. The particularity of this use of the score test is that the null hypothesis is not itself very simple; typically, some random effects may be present under the null hypothesis. Moreover, the information matrix cannot be computed, but only an approximation based on the score. This article examines this situation with the specific example of HIV dynamics models. We examine the score test statistics for testing the effect of explanatory variables and the variance of random effect in this complex situation. We study type I errors and the statistical powers of this score test statistics and we apply the score test approach to a real data set of HIV‐infected patients.     

An Efficient Timer and Sizer of Biomacromolecular Motions

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