网络分析法在动物声音通讯及生物声学研究中的应用与前景

动物社会网络分析法(animal social network analysis,ASNA)是一套用于研究动物社会性、量化个体间各种社会关系、揭示个体行为与社会结构动态之间联系的工具,被广泛应用于多种动物类群的行为学研究。该分析方法所提供的一系列指标也非常适用于探究动物的声音交流及鸣声结构。在此,本文首先简要介绍了网络分析法的基本概念及一些常用的指标;然后基于野外和室内研究实例,阐述了如何利用ASNA建立声音通讯网络、量化声音交流,以及将ASNA与被动声学监测技术相结合的应用前景;随后探讨了ASNA在分析鸣声相似性及鸣声地理变异中的优势;最后概述了ASNA在解析鸣声结构和句法规则中的应用。ASNA为研究动物通讯网络以及声音信号的适应性进化提供了新的视角和新的思路。     

浅谈网络分析法及其在古生物学中的应用

网络分析作为一种新的数据可视化途径和定量方法,能简化复杂系统而发现元素间的关系模式。它在定量社会科学、计算机科学与机器学习等领域均有众多应用实例。近年来,在古生物学,特别是古生物地理学相关研究中逐渐受到关注。本文介绍了网络的基本构成、常见网络类型及其数据储存方式、以及网络分析中的重要参数及其定义,同时给出了两种实现网络分析的方法及相关工具,即Gephi软件与R语言平台。通过分析比较两种方法的步骤及结果,发现Gephi虽成图简洁美观,但算法功能有限,且无法完成成图前的数据处理以及成图后的多元分析,因而最终推荐使用R语言编程进行网络分析。本文以奥陶纪末大灭绝后复苏期全球腕足动物数据为例,详细展现了利用R语言及其应用包"igraph"编程进行网络分析的过程,并实现了古生物地理学数据资料的处理以及网络分析图件的绘制。希望对即将接触此类工具的古生物学科研人员在进行网络分析时提供借鉴与参考。     

DNA指纹图谱技术在动物行为学研究上的应用

ＤＮＡ指纹图谱技术于８０年代末在国外已被广泛应用于行为学尤其是动物繁殖行为学研究中,国内在此方面的应用尚少。综述了ＤＮＡ指纹图谱技术在动物行为学研究中的作用,介绍了ＤＮＡ指纹图谱的产生、实验操作方法、应用实例及其优缺点。     

机器学习在动物行为分析中的应用研究进展

动物行为分析是研究动物高级神经中枢功能的一项重要技术手段,动物的行为及其规律综合反映了其心理和生理状况,在实验动物学领域得到了广泛研究。近年来,行为采集手段的发展让大量行为数据得以产生,机器学习的出现大大提升了动物行为数据的处理效率。其中,监督学习可以实现对动物行为的自动识别和分类,而无监督学习则有利于发现人眼所观测不到的新行为或异常行为,探索行为结构。本文对机器学习方法在动物行为分析中的应用进行了阐述,为后期的研究工作和方向提供参考。     

基于社会网络分析法的生态工业园典型案例研究

以丹麦卡伦堡和广西贵港生态工业园为例,应用社会网络分析法分析典型生态工业园的组织结构和网络结构。用簇系数、平均最短距离、传递性以及核心-边缘结构来衡量其稳定性,分析其不同结构特征。卡伦堡生态工业园的簇系数为0.715,远高于贵港生态工业园的0.246,说明其聚合性较好;从最短距离长度来看,卡伦堡和贵港分别为2.110和2.236,复杂性弱;从传递性来看,两者传递性皆低于25%,节点之间联系性不够强;从核心-边缘结构来看,卡伦堡各节点之间的异质性(0.057)高于贵港(0.005),可见贵港参与主体的中心性较为均衡,而卡伦堡差异性较大。两者都以一个产业或者企业集团为网络核心;网络内其他节点联系不够紧密,长链条联结较少;网络复杂性弱。     

景观中心度及其在生态网络规划与管理中的应用

构建连续性生态网络已成为生物多样性保护、生态环境安全管理、游憩和历史文化资源保护的重要景观规划策略,其规划与管理已受到广泛关注.关键景观组分的识别是生态网络规划与管理的重点和难点,为解决这一问题,本文借鉴图论网络分析理论提出了景观中心度的概念及度量方法,并探讨了景观中心度在生态网络规划与管理中的应用内容和框架.景观中心度方法虽然可为景观规划与管理中关键景观要素的确定和连续生态网络的构建提供新途径,但仍需从指标的生态意义、实验数据的分析和简单通用的分析软件等方面对该方法进行验证和完善.     

泛函连接网络计算软件及其在生物多样性研究中的应用

针对农田生物多样性分析的需要,研制出泛函连接网络（FLANN）计算软件。该软件由7个Java类和1个HTML文件组成,是一种Internet在线计算工具,可运行于多种操作系统和Web浏览器上,并在各种类型的PC及工作站上使用,可读取多种类型的数据库文件。对水稻田昆虫生物多样性的两组取样调查数据Zmar18和Zapr15,用生物多样性工具软件LUMP和非监督分类－离差平方和聚类法进行统计归纳及分类,分别划分为21个和20个功能群,各包含60个样本。以FLANN计算软件对昆虫生物多样性进行了模式分类分析。结果表明,泛函连接网络的模式分类及预测与实际测查结果吻合良好。泛函连接网络Internet在线计算软件的应用可促进生物多样性数据采集和分析的规范化,有利于数据和信息共享,也为形成高度的生物多样性智能分析系统提供了一种工具。     

区域可持续发展能力评价及其在山东五莲的应用

在分析、评价当前关于区域可持续发展评价研究成果的基础上,从可持续发展的内涵和对可持续发展评价的基本要求出发,尝试利用区域复合生态系统场力分析理论,构造了用于区域可持续发展评价的综合评价指数-可持续发展度,并给出了其具体计算式,最后以山东省五莲县为例,对区域可持续发展能力的变化及其原因进行了分析。     

代谢组学及其在微藻研究中的应用

代谢组学以完整的生物体为研究对象,运用合适的分析测试手段检测靶向或非靶向代谢物,结合统计模型进行分析解释。随着微藻研究的深入,微藻与代谢组学结合探究分子作用机理的研究日益增多。本文总结代谢组学的发展概况、研究流程及常用分析技术特点和代谢组学在微藻领域的研究进展,展望代谢组学在微藻研究的应用前景与发展趋势,并提出实际应用中所面临的困难与挑战。     

代谢物组学及其在微生物研究中的应用

代谢物组学(metabolomics)是继基因组学(genomics)、蛋白质组学(proteomics)后发展起来的一门新学科。对代谢物组学的含义,研究方法及流程,特别是其在微生物中的应用进行了介绍,包括使用代谢物组学中的NMR技术研究微生物在降解环境污染物中的作用;使用代谢物组学技术研究微生物代谢通量,从而在分析代谢通量的基础上通过代谢工程改变代谢通量,提高目的产物的得率;确定所获得基因库中沉默基因的功能;运用代谢物组学分析方法阐明生物体系对于环境变化的响应,从而协助我们确定最佳的取样时间及最佳分析组织,设计实验。随后简要对代谢物组学发展动态进行了展望。     

Friends with benefits: Social support and its relevance for farm animal welfare

Despite growing interest in promoting positive welfare, rather than just alleviating poor welfare, potential measures of good welfare, and means to provide it, have remained elusive. In humans social support improves stress-coping abilities, health, and promotes positive psychological welfare. Therefore, social support may be a key approach to promote positive physical and psychological welfare in farm animals. However, the roles of positive social behaviors and social support have been overlooked in comparison to negative social behaviors such as agonistic interactions. The benefits of social partners on an animal's stress coping abilities and welfare are yet poorly understood.The purpose of this paper is to review the protective or buffering effects of social support against stressful challenges and its potential implications for farm animal welfare. The biology of social support is first presented with its behavior, endocrine, autonomic and immune components. The major factors modulating the social support process are then synthesized. Research and implications for animal welfare in different farm species are discussed. Lastly, this review identifies research areas that especially deserve further attention in our effort to understand and implement social support in farm animal welfare.Social support could constitute one of the foundations for welfare researchers to leap from the absence of negative welfare to the provision of positive welfare and emotional experiences.     

关联分析及其在真菌遗传学研究中的应用

近年来,基于连锁不平衡的关联分析被逐渐应用于解析真菌数量性状的遗传基础。本文在介绍关联分析方法的基础上,综述了关联分析在真菌遗传学中的研究进展,并对其未来的应用前景进行了展望。     

Multilevel modeling analysis of dyadic network data with an application to Ye'kwana food sharing

Behavioral ecologists have recently begun using multilevel modeling for the analysis of social behavior. We present a multilevel modeling formulation of the Social Relations Model that is well suited for the analysis of dyadic network data. This model, which we adapt for count data and small datasets, can be fitted using standard multilevel modeling software packages. We illustrate this model with an analysis of meal sharing among Ye'kwana horticulturalists in Venezuela. In this setting, meal sharing among households is predicted by an association index, which reflects the amount of time that members of the households are interacting. This result replicates recent findings that interhousehold food sharing is especially prevalent among households that interact and cooperate in multiple ways. We discuss opportunities for human behavioral ecologists to expand their focus to the multiple currencies and cooperative behaviors that characterize interpersonal relationships in preindustrial societies. We discuss possible extensions to this statistical modeling approach and applications to research by human behavioral ecologists and primatologists. Am J Phys Anthropol 157:507–512, 2015. © 2015 Wiley Periodicals, Inc.     

关联分析及其在植物遗传学研究中的应用

植物的很多重要经济性状均属于复杂性状。基于连锁分析的QTL作图是研究复杂性状的有效手段, 但其尚存在一定的局限性。随着现代生物学的发展, 一种基于连锁不平衡的新剖分复杂性状方法--关联分析法, 开始应用于植物遗传学研究。与QTL作图法相比, 应用关联分析法具有不需要构建特殊的群体, 可同时对多个等位基因进行分析, 定位QTL精度可达到单基因水平等优势。该文介绍了关联分析方法学的基础和特性, 简述了其在植物遗传学研究中的进展情况, 并对其未来发展和在植物遗传学研究中的应用进行了展望。     

一种基于代谢网络分析最小化基因组的方法及其在大肠杆菌中的应用

最小生命体的合成是合成生物学研究的重要方向。最小化基因组的同时而又不对细胞生长产生影响是代谢工程研究的一个重要目标。文中提出了一种从基因组尺度代谢网络模型出发,通过零通量反应删除及对非必需基因组合删除计算获得基因组最小化代谢网络模型的方法,利用该方法简化了大肠杆菌经典代谢网络模型iAF1260,由起始的1 260个基因简化得到了312个基因,而最优生物质生成速率保持不变。基因组最小化代谢网络模型预测了在细胞正常生长的前提下包含最少基因的代谢途径,为大肠杆菌获得最小基因组的湿实验设计提供了重要参考。     

Amino acid network and its scoring application in protein-protein docking

Protein-protein complex, composed of hydrophobic and hydrophilic residues, can be divided into hydrophobic and hydrophilic amino acid network structures respectively. In this paper, we are interested in analyzing these two different types of networks and find that these networks are of small-world properties. Due to the characteristic complementarity of the complex interfaces, protein-protein docking can be viewed as a particular network rewiring. These networks of correct docked complex conformations have much more increase of the degree values and decay of the clustering coefficients than those of the incorrect ones. Therefore, two scoring terms based on the network parameters are proposed, in which the geometric complementarity, hydrophobic-hydrophobic and polar-polar interactions are taken into account. Compared with a two-term energy function, a simple scoring function HPNet which includes the two network-based scoring terms shows advantages in two aspects, not relying on energy considerations and better discrimination. Furthermore, combing the network-based scoring terms with some other energy terms, a new multi-term scoring function HPNet-combine can also make some improvements to the scoring function of RosettaDock.     

Social network size in humans

This paper examines social network size in contemporary Western society based on the exchange of Christmas cards. Maximum network size averaged 153.5 individuals, with a mean network size of 124.9 for those individuals explicitly contacted; these values are remarkably close to the group size of 150 predicted for humans on the basis of the size of their neocortex. Age, household type, and the relationship to the individual influence network structure, although the proportion of kin remained relatively constant at around 21%. Frequency of contact between network members was primarily determined by two classes of variable: passive factors (distance, work colleague, overseas) and active factors (emotional closeness, genetic relatedness). Controlling for the influence of passive factors on contact rates allowed the hierarchical structure of human social groups to be delimited. These findings suggest that there may be cognitive constraints on network size. This project was funded by a grant from Hewlett Packard Research Laboratories (Bristol) and the Economic and Social Research Council (ESRC). The support of the ESRC is gratefully acknowledged. This work was part of the programme of the ESRC Research Centre for Economic Learning and Social Evolution (ELSE). Russell Hill (B.Sc., M.Phil, Ph.D.) is an Addison Wheeler Research Fellow at the University of Durham. His main research interests are in the evolution of mammalian social systems. Robin Dunbar (B.A., Ph.D.) is a professor of evolutionary psychology at the University of Liverpool. His research interests span mammalian behavioral ecology, including humans, cognitive mechanisms, and Darwinian psychology.     

Stoichiometric analysis of animal cell growth and its application in medium design

Animal cell cultivation in vitro has been studied for more than 40 years. However, the culture medium composition has not been designed on the basis of the stoichiometric nutritional demands for animal cell growth. In this article, a model was developed to study the stoichiometric demands for nutrients (including glucose, 20 amino acids, and 10 vitamins)for the synthesis of cell mass and product. The coefficients for these nutrients in the stoichiometric equation governing animal cell growth were determined based on cell composition. In addition, a detailed analysis of the nutrients' roles in the synthesis of cell mass and product was also performed. Applications of the stoichiometric analysis in animal cell cultivation, such as culture medium design, supplemental medium formulation, and feeding strategy will also be discussed. The stoichiometric analysis can be potentially employed to analyze results from animal cell cultures, to improve the performance of culture processes, and to design new process rationally. It can also help to provide a better understanding of animal cell metabolism. Simplifications on the cellular energy metabolism were made in order to simplify the model and to provide the preliminary bases to test the process performance. However, this could introduce inaccuracies for the model and results in errors in the calculations of glucose and glutamine concentrations when employed in medium design. (c) 1994 John Wiley & Sons, Inc.