Swami一新一代生物学平台

生物信息学的发展产生了越来越多的数据库和生物学软件,研究人员在应用这些生物学工具处理实验数据时需要大量的时间解决数据格式转换和管理等问题。本文介绍了一种交互式的基于网络的新一代生物信息学分析平台一Swam,它综合了主要的生物信息学数据库和软件,可以加速数据处理并帮助用户管理数据。因此它将推动生物信息学向更深层次发展。     

Swami—新一代生物学平台

生物信息学的发展产生了越来越多的数据库和生物学软件,研究人员在应用这些生物学工具处理实验数据时需要大量的时间解决数据格式转换和管理等问题。本文介绍了一种交互式的基于网络的新一代生物信息学分析平台—Swami,它综合了主要的生物信息学数据库和软件,可以加速数据处理并帮助用户管理数据。因此它将推动生物信息学向更深层次发展。     

获取生物物种名录信息的R程序包SP2000

物种名录为衡量区域和全球生物多样性提供了数据基础。随着互联网的兴起与发展, 人们将地球上已知的动物、植物、微生物等类群的物种名录信息存储到公共数据平台中, 并对物种名录进行快速及时地更新, 这极大地促进了分类学、保护生物学和宏观生态学等学科的发展, 成为政府或国际组织开展物种保育现状评估、红色名录编撰和生物多样性保护的重要依据。物种2000中国节点(http://www.sp2000.org.cn)和Catalogue of Life网站(http://www.catalogueoflife.org)分别是中国和全球最大的生物物种名录数据平台, 截至2020年6月4日, 其收录的物种数分别为122,280种和1,829,672种。然而这些数据平台仅提供物种查询、检索、下载等基本功能, 难以满足使用者准确、快速地批量获取所需生物物种名录数据信息的需求, 制约了这些大数据平台在生物多样性研究和保护中的作用。因此, 我们选取R语言开发了程序包SP2000, 旨在帮助用户批量获取中国或全球生物物种名录信息。该程序包具有跨Windows、MacOS、Linux等多个系统运行、操作便捷、代码开源等特点。为了方便用户使用, 本文详细介绍了SP2000的基本原理、特点及使用指南, 包括程序包的下载、安装、运行和参数设置等。     

数量生态学软件研发及应用

数量生态学是生物数学的重要组成部分,其数学基础是统计分析．由于数量生态学问题本身的复杂性以及研究中需要大量的数据处理,因此,大部分数量运算都要依赖于计算机完成．国际通用数学软件Matlab是一个具有强大数值计算能力、图形处理能力的交互式计算机代数系统,其强大的函数库和独特的内建程序设计语言为科学计算及程序设计提供了友好平台．本研究选择国际通用计算机代数系统Matlab作为程序设计平台,应用Matlab下强大的图形用户界面GUI软件包研发了植被数量生态学分析软件Quatitatlve Ecology中英文版,内容包括生物多样性,种间关联等简单的计算方法以及排序、分类、格局分析,生物一环境关系分析等复杂的分析方法．当进入应用状态时,只需要在相应的框中输入基本数据或者调用文本数据文件或Excel文件,即会得到具体的计算公式,计算结果,图形以及相应的分析或结论．特别是强大的帮助系统涵盖了所有数量分析方法并辅以应用实例供使用者参考．这将为数量生态学的发展注入新的活力．     

北京市高等植物种质资源信息查询系统的构建与特点

生物多样性信息学是生物多样性研究的重要内容,信息平台是生物多样性保护、生态教育和普及有效模式.目前,北京开展了大量的生物多样性资源的调查,但还缺少针对该区域系统而全面的物种资源信息化平台.针对北京地区生物多样性保护和生态教育的需要,基于2007～2009年开展的北京市高等植物种质资源全面系统的调查以及以往的研究数据,以物种多样性编目的数据库为框架,以计算机网络技术为支撑,构建北京市种质资源信息查询网络平台.该平台实现了高等植物种质资源信息的共享,用户可以准确查询到149科,61属,256种及变种的详细文字信息和图片信息,包括植物物种的分类、生态学特征、分布特点、濒危与保护状况、利用与人为干扰等.该平台的研建不仅为北京市植物物种资源的保护规划、外来物种的管理、资源利用等提供了重要信息支持,对科学研究和生态教育等也具有重要意义.     

共显性分子标记基因型数据转换为二元型数据的处理软件及其在研究种质资源遗传多样性中的意义

遗传多样性研究是植物种质资源有效利用和保护的重要基础.遗传多样性研究所采用的分子标记工具主要有显性和共显性两种,两种不同类型的分子标记将产生不同的数据类型.显性分子标记产生二元型数据,共显性分子标记产生基因型数据.数据形式不同给遗传多样性的分析和研究带来多方面的困难,不同类型数据之间的互相比较也需要将基因型数据进行二元型转换.本研究基于Excel平台,设计开发了将基因型数据转换成二元型数据的处理软件.该软件按照基因型数据向二元型数据转换的原理,可以将庞大的分子标记基因型数据矩阵,迅速、高效、准确地转换成二元型(0、1)数据矩阵.利用显性分子标记ISSR和共显性分子标记SSR对野生大豆居群遗传多样性的案例分析表明,将共显性分子标记的基因型数据转换为二元型数据,有利于种质资源遗传多样性研究中不同分子标记获取的遗传多样性结果之间的比较和综合分析.     

生物多样性信息资源.Ⅰ.物种分布、编目、系统发育与生活史性状

物种分布、编目、系统发育与生活史性状等是生物多样性研究的数据基础,在物种起源与进化、生物多样性保护等研究中发挥着重要作用。近年来,大量数据共享平台的建设极大地促进了生物多样性信息学的蓬勃发展,但这些海量的、高异构性的数据资源也使得研究人员无从下手。如何高效选择和有效利用这些资源,成为生态学家和保护生物学家面临的一大挑战。针对现有的生物多样性数据零散分布的现状,本文将这些数据从物种分布、编目、系统发育与生活史性状4个方面进行整理,分别选取一些代表性的数据库如:全球生物多样性信息网络(GBIF)、世界植物种名录(The Plant List)、Open Tree of Life、植物性状数据库(TRY),对其数据类型、采集方式、范围、获取方式等进行描述,并对相关研究成果进行简要介绍。在各部分中,针对我国生物多样性数字平台的构建等方面的工作与成果,我们也进行了简要描述。通过这些数据资源的整理,希望为研究人员了解和使用这些数据库提供桥梁和纽带,能够进一步促进国内研究人员对这些数据库的有效利用,并通过科研人员与公众等的参与,促进数据共享平台的构建与完善,进一步推动生物多样性的研究和保护领域的发展。     

中国生物多样性保护优先区域生物多样性调查和评估方法

我国高度重视生物多样性保护,而开展本底调查是生物多样性保护的基础。但以往研究对苔藓、生物多样性相关传统知识等关注不够,而且调查大部分集中在生物多样性丰富区域。随着我国社会经济的快速发展,全国土地利用格局和生态环境发生了巨大变化,已有的部分调查成果数据与实际情况不符,难以满足我国生物多样性保护管理需求,因此亟待组织开展全国生物多样性调查与评估工作。在整理历史和现有生物多样性调查技术的基础上,推荐采用网格法开展全国生物多样性调查,按照10 km×10 km分辨率,将全国划分为97109个调查网格;制定了陆生高等植物、植被、陆生哺乳动物、鸟类、两栖类和爬行类、昆虫、大型真菌、内陆鱼类、内陆浮游生物、内陆大型底栖无脊椎动物、内陆周丛藻类以及生物多样性相关传统知识12个类群县域生物多样性调查评估技术规定;建立了全国统一、动态更新、信息共享的生物多样性数据库和信息化管理平台。从调查内容规范、评估指标体系和技术要求等方面探讨了陆域生态系统与物种调查、重点河流水生生物调查、重点物种调查、生物多样性相关传统知识调查技术方法,并构建生物多样性综合评估指标体系,规范了生物多样性保护优先区域生物多样性调查和评估。技术方法在横断山南、武陵山、太行山、西双版纳等生物多样性保护优先区域得到应用,同时北京、江苏、浙江和湖北等省份和祁连山、武夷山等区域也采用该技术体系开展调查,网格法得到逐步推广,并获得大量的生物多样性基础数据,为我国生物多样性保护和可持续利用、生物多样性公约履约等提供了基础数据。     

基于高通量RNA测序数据分析的弹性云平台

高通量RNA测序（RNA-seq）技术为研究人员提供了海量数据,如何对这些数据进行快速有效的分析,并为后续转录组、基因表达等研究提供支持,是生物信息学领域的热点方向。本文讨论了当前RNA-seq数据分析的发展水平和常用软件、算法,并设计了一系列数据处理模块和分析流程。同时,为了给用户提供更好的使用环境,我们设计了基于弹性资源管理系统的生物云平台BioCloud。该平台集成了丰富的软件,采用高灵活度、高扩展性的体系架构,在给用户提供低成本、高性能计算服务的同时,还提供个性化的流程定制服务。     

生物多样性国际研究态势分析

生物多样性研究是综合性和高度交叉性的跨学科研究领域,是1997年底Science周刊上预测的1998年及近期的6个重大科学热点之一。检索1986—2008年间SCIE文献数据库中关于生物多样性的研究论文(article,proceedings paper和review),利用Thomson Data Analyzer(TDA)分析工具和Aureka分析平台进行数据挖掘。分析表明,该研究涉及多个学科领域,近年来在生态学领域的论文数量增加最多,而生物多样性保护、进化生物学、生物化学与分子生物学方面的论文增长速度较快。生物多样性研究越来越重视全球变化和人类社会对生物多样性的影响,DNA技术和基因工程等先进技术在生物多样性研究和保护中的作用也更加突出。     

Automics: an integrated platform for NMR-based metabonomics spectral processing and data analysis

Background  

Spectral processing and post-experimental data analysis are the major tasks in NMR-based metabonomics studies. While there are commercial and free licensed software tools available to assist these tasks, researchers usually have to use multiple software packages for their studies because software packages generally focus on specific tasks. It would be beneficial to have a highly integrated platform, in which these tasks can be completed within one package. Moreover, with open source architecture, newly proposed algorithms or methods for spectral processing and data analysis can be implemented much more easily and accessed freely by the public.     

生物工程专业“试验设计与数据处理”教学中常用软件的探讨

试验设计与数据处理在生物工程专业方向有着重要的应用,但是在本科教学中开设该课程的高校较少。本文结合生物工程中的常见案例,对该课程教学过程中常用的软件包括Excel、正交试验设计助手、Data processing system(DPS)和Design expert在单因素、多因素、正交、均匀、P-B(Plackett-Burman)和响应面等数据处理方法进行了探讨。通过比较分析各种软件和数据处理方法之间特点,增加该课程教学的实践性和应用性,从而提高教学质量。     

Benchmarking currently available SELDI‐TOF MS preprocessing techniques

SELDI protein profiling experiments can be used as a first step in studying the pathogenesis of various diseases such as cancer. There are a plethora of software packages available for doing the preprocessing of SELDI data, each with many options and written from different signal processing perspectives, offering many researchers choices they may not have the background or desire to make. Moreover, several studies have shown that mistakes in the preprocessing of the data can bias the biological interpretation of the study. For this reason, we conduct a large scale evaluation of available signal processing techniques to establish which are most effective. We use data generated from a standard, published simulation engine so that “truth” is known. We select the top algorithms by considering two logical performance metrics, and give our recommendations for research directions that are likely to be most promising. There is considerable opportunity for future contributions improving the signal processing of SELDI spectra.     

What is in the black box? – A perspective on software in cryoelectron microscopy

This article bemoans the demise of truly modular open-source image processing systems, such as SPIDER, in recent years’ development of tools for three-dimensional reconstruction in cryo-electron microscopy. Instead, today’s users have to rely on the functionality of software systems that have little or no transparency. As a consequence, users of such packages no longer gain a conceptual understanding and intuitive grasp of the analytical routes leading from the stream of input data to the final density map. Possible remedies of this situation with free software are discussed.     

Network Meta-Analysis Using R: A Review of Currently Available Automated Packages

Network meta-analysis (NMA) – a statistical technique that allows comparison of multiple treatments in the same meta-analysis simultaneously – has become increasingly popular in the medical literature in recent years. The statistical methodology underpinning this technique and software tools for implementing the methods are evolving. Both commercial and freely available statistical software packages have been developed to facilitate the statistical computations using NMA with varying degrees of functionality and ease of use. This paper aims to introduce the reader to three R packages, namely, gemtc, pcnetmeta, and netmeta, which are freely available software tools implemented in R. Each automates the process of performing NMA so that users can perform the analysis with minimal computational effort. We present, compare and contrast the availability and functionality of different important features of NMA in these three packages so that clinical investigators and researchers can determine which R packages to implement depending on their analysis needs. Four summary tables detailing (i) data input and network plotting, (ii) modeling options, (iii) assumption checking and diagnostic testing, and (iv) inference and reporting tools, are provided, along with an analysis of a previously published dataset to illustrate the outputs available from each package. We demonstrate that each of the three packages provides a useful set of tools, and combined provide users with nearly all functionality that might be desired when conducting a NMA.     

Measuring Software Timing Errors in the Presentation of Visual Stimuli in Cognitive Neuroscience Experiments

Because of the features provided by an abundance of specialized experimental software packages, personal computers have become prominent and powerful tools in cognitive research. Most of these programs have mechanisms to control the precision and accuracy with which visual stimuli are presented as well as the response times. However, external factors, often related to the technology used to display the visual information, can have a noticeable impact on the actual performance and may be easily overlooked by researchers. The aim of this study is to measure the precision and accuracy of the timing mechanisms of some of the most popular software packages used in a typical laboratory scenario in order to assess whether presentation times configured by researchers do not differ from measured times more than what is expected due to the hardware limitations. Despite the apparent precision and accuracy of the results, important issues related to timing setups in the presentation of visual stimuli were found, and they should be taken into account by researchers in their experiments.     

MapDraw，在Excel中绘制遗传连锁图的宏

MAPMAKER是现今广泛使用的遗传连锁数据分析软件,然而其广泛使用的DOS版本却不具有连锁图绘制功能,给连锁作图工作带来了相当大的麻烦。为了解决这一问题,我们以大家广泛使用的数据处理软件Microsoft Excel为平台,编写了一个Excel宏——MapDraw来在轻松的操作中实现遗传连锁图的绘制。 Abstract:MAPMAKER is one of the most widely used computer software package for constructing genetic linkage maps.However,the PC version,MAPMAKER 3.0 for PC,could not draw the genetic linkage maps that its Macintosh version,MAPMAKER 3.0 for Macintosh,was able to do.Especially in recent years,Macintosh computer is much less popular than PC.Most of the geneticists use PC to analyze their genetic linkage data.So a new computer software to draw the same genetic linkage maps on PC as the MAPMAKER for Macintosh to do on Macintosh has been crying for.Microsoft Excel,one component of Microsoft Office package,is one of the most popular software in laboratory data processing.Microsoft Visual Basic for Applications (VBA) is one of the most powerful functions of Microsoft Excel.Using this program language,we can take creative control of Excel,including genetic linkage map construction,automatic data processing and more.In this paper,a Microsoft Excel macro called MapDraw is constructed to draw genetic linkage maps on PC computer based on given genetic linkage data.Use this software,you can freely construct beautiful genetic linkage map in Excel and freely edit and copy it to Word or other application.This software is just an Excel format file.You can freely copy it from ftp://211.69.140.177 or ftp://brassica.hzau.edu.cn and the source code can be found in Excel′s Visual Basic Editor.     

An integrated framework for discovery and genotyping of genomic variants from high-throughput sequencing experiments

Recent advances in high-throughput sequencing (HTS) technologies and computing capacity have produced unprecedented amounts of genomic data that have unraveled the genetics of phenotypic variability in several species. However, operating and integrating current software tools for data analysis still require important investments in highly skilled personnel. Developing accurate, efficient and user-friendly software packages for HTS data analysis will lead to a more rapid discovery of genomic elements relevant to medical, agricultural and industrial applications. We therefore developed Next-Generation Sequencing Eclipse Plug-in (NGSEP), a new software tool for integrated, efficient and user-friendly detection of single nucleotide variants (SNVs), indels and copy number variants (CNVs). NGSEP includes modules for read alignment, sorting, merging, functional annotation of variants, filtering and quality statistics. Analysis of sequencing experiments in yeast, rice and human samples shows that NGSEP has superior accuracy and efficiency, compared with currently available packages for variants detection. We also show that only a comprehensive and accurate identification of repeat regions and CNVs allows researchers to properly separate SNVs from differences between copies of repeat elements. We expect that NGSEP will become a strong support tool to empower the analysis of sequencing data in a wide range of research projects on different species.