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。     

生物信息学在昆虫学研究中的应用

随着深度测序和基因芯片技术的不断发展,基因组、转录组、表达谱数据大量积累。目前,至少有10多个昆虫的基因组已被测序,30多个昆虫的转录组数据被报道。显然,传统的生物统计学方法无法处理如此海量的生物数据。量变引发质变,生物数据的大量积累催生了一门新兴学科,生物信息学。生物信息学融合了统计学、信息科学和生物学等各学科的理论和研究内容,在医学、基础生物学、农业科学以及昆虫学等方面获得了广泛的应用。生物信息学的目标是存储数据、管理数据和数据挖掘。因此,建立维护生物学数据库、设计开发基于模式识别、机器学习、数据挖掘等方法的生物软件,以及运用上述工具进行深度的数据挖掘,是生物信息学的重要研究内容。本文首先简要介绍了生物信息学的历史、研究现状及其在昆虫学科中的应用,然后综述了昆虫基因组学和转录组学的研究进展,最后对生物信息学在昆虫学研究中的应用前景进行了展望。     

科学出版社生命科学编辑部新书推介

生物信息学方法指南 S.米塞诺,S.A.克拉维茨 著 欧阳红生 等译 2005年3月出版 7-03-014465-1／Q 1498 定价：58．00 计算机在管理生物学日益增长的海量数据方面起到了不可估量的作用,并推进了现代生物学的快速发展。本书详细介绍了一些重要生物学软件和数据库的使用,同时提供了一些实用的技巧和最新研究进展。全书分为五部分,包括序列分析软件包、分子生物学软件、网络信息资源、计算机和分子生物学的关系、生物信息学教学与最新文献跟踪。     

科学出版社生命科学编辑部新书推介

生物信息学方法指南 S.米塞诺,S.A.克拉维茨著欧阳红生等译 2005年3月出版7-03-014465-1／Q.1498定价:58.00 计算机在管理生物学日益增长的海量数据方面起到了不可估量的作用,并推进了现代生物学的快速发展。本书详细 介绍了一些重要生物学软件和数据库的使用,同时提供了一些实用的技巧和最新研究进展。全书分为五部分,包括序列分 析软件包、分子生物学软件、网络信息资源、计算机和分子生物学的关系、生物信息学教学与最新文献跟踪。内容全面,实用 性较强,可帮助生物信息学人员对该学科有更深入地了解。本书可作为大专院校、科研机构的分子生物学、生物信息学等 相关专业的研究生、科研和教学人员的参考书。     

科学出版社生命科学编辑部新书推介

生物信息学方法指南S.米塞诺,S.A.克拉维茨著欧阳红生等译2005年3月出版7-03-014465-1/Q.1498定价:58.00计算机在管理生物学日益增长的海量数据方面起到了不可估量的作用,并推进了现代生物学的快速发展.本书详细介绍了一些重要生物学软件和数据库的使用,同时提供了一些实用的技巧和最新研究进展.全书分为五部分,包括序列分析软件包、分子生物学软件、网络信息资源、计算机和分子生物学的关系、生物信息学教学与最新文献跟踪.内容全面,实用性较强,可帮助生物信息学人员对该学科有更深入地了解.本书可作为大专院校、科研机构的分子生物学、…     

生物数据库建立与应用的研究

生物信息学是一门在生命科学的研究中计算机科学与生物学及应用数学等多学科相互交叉而形成的综合性学科。主要介绍了生物信息学数据库的分类和生物信息学数据库的特点及其应用,同时对生物信息学数据库的未来发展作了进一步的展望。     

肿瘤生物信息学数据库

恶性肿瘤已经成为严重危害人类健康的主要疾病之一。近年来,高通量检测技术迅速发展,成为肿瘤研究的重要手段之一,使得与肿瘤相关的组学数据迅速积累。这些数据对于研究肿瘤的发生发展机制具有重要意义。对海量生物学数据的管理和挖掘已经成为癌症研究的基础与重要方向。主要介绍人类肿瘤研究中经常用到的生物信息学数据库,包括综合性数据库、基因组、转录组、蛋白组、表观遗传组数据库等。在总结国内外肿瘤数据库发展现状的基础上,讨论了目前数据库开发存在的问题,旨为现有的研究提供帮助。     

医学生物信息学在心血管研究领域的应用--数据与知识

随着生物技术的进步,特别是以基因组、蛋白质组为标志的导致高通量实验数据产生的工作的开展,大量的实验数据在各个领域堆积拥塞,与领域内的知识的累计出现了极为不平衡的发展,因此,对这些数据的处理成为了学科发展的迫切需求。为了避免这些数据成为垃圾,数据库、统计学、信号处理、数据挖掘、知识管理、人工智能等多种技术被运用到医学生物学领域,使得医学生物信息学不再是医学、生物学和信息学、计算机科学的单纯交叉,而独立成为一门专业的学科,重点也由原来单纯的研究计算机信息技术在医学生物信息学中的延展和运用,转变到研究、发现、开发、创新适合医学生物学自身特点的新思想和新方法上来。本文对近年来心血管领域内医学生物信息发展和运用的情况进行了回顾和分析,并对该领域可能的发展方向做出判断。     

生物信息学软件研究的可视化分析

以Web of Science数据库为数据来源,利用Cite Space和UCINET软件对发表在Nucleic Acids Research期刊上有关生物信息学软件研究的文献做了可视化分析,揭示了该领域的研究力量、作者团队与高被引作者、知识基础、期刊分布、研究热点与前沿,为生物信息学软件的研究和发展提供必要的参考依据。     

生物信息数据库与序列分析

随着生物信息学与生物技术的不断发展,生物信息数据库中数据呈指数增长,理解其中所包含的生物学知识,揭示生物内在规律将成为今后自然科学研究中的重要课题。对近几年来国外常用生物信息数据库的使用作了简介,同时也较为详细地描述了如何进行序列分析。     

Workflow management systems for gene sequence analysis and evolutionary studies – A Review

Post ‘omic’ era has resulted in the development of many primary, secondary and derived databases. Many analytical and visualization bioinformatics tools have been developed to manage and analyze the data available through large sequencing projects. Availability of heterogeneous databases and tools make it difficult for researchers to access information from varied sources and run different bioinformatics tools to get desired analysis done. Building integrated bioinformatics platforms is one of the most challenging tasks that bioinformatics community is facing. Integration of various databases, tools and algorithm is a challenging problem to deal with. This article describes the bioinformatics analysis workflow management systems that are developed in the area of gene sequence analysis and phylogeny. This article will be useful for biotechnologists, molecular biologists, computer scientists and statisticians engaged in computational biology and bioinformatics research.     

BioWAP, mobile Internet service for bioinformatics

We have developed a new Internet service, which provides mobile access to bioinformatics databases and software tools. The BioWAP service facilitates access to basic bioinformatics databases and analysis tools from everywhere without a PC or a laptop computer. Both open source bioinformatics program suites and Internet services, which are not designed for mobile Internet access, were utilized in the BioWAP service. AVAILABILITY: The BioWAP service starting page can be browsed with any WAP terminal from http://bioinf.uta.fi/wml/welcome.wml.     

基于质谱的选择反应监测技术相关策略和方法的研究进展

随着蛋白质组学研究的不断深入,基于质谱的选择反应监测技术(SRM)已经成为以发现生物标志物为代表的定向蛋白质组学研究的重要手段.SRM技术根据假设信息,特异性地获取符合假设条件的质谱信号,去除不符合条件的离子信号干扰,从而得到特定蛋白质的定量信息.SRM技术具有更高的灵敏度和精确性、更大的动态范围等优势.该技术可分为实验设计、数据获取和数据分析三个步骤.在这几个步骤中,最重要的是利用生物信息学手段总结当前实验数据的结果,并用机器学习方法和总结的经验规则进行SRM实验的母离子和子离子对的预测.针对数据质控和定量的生物信息学方法研究在提高SRM数据可靠性方面具有重要作用.此外,为方便SRM的研究,本文还收集、汇总了SRM技术相关的软件、工具和数据库资源.随着质谱仪器的不断发展,新的SRM实验策略以及分析方法、计算工具也应运而生.结合更优化的实验策略、方法,采用更精准的生物信息学算法和工具,SRM在未来蛋白质组学的发展中将发挥更加重要的作用.     

Bioinformatics toolbox for narrowing rodent quantitative trait loci

Quantitative trait locus (QTL) analysis is a powerful method for localizing disease genes, but identifying the causal gene remains difficult. Rodent models of disease facilitate QTL gene identification, and causal genes underlying rodent QTL are often associated with the corresponding human diseases. Recently developed bioinformatics methods, including comparative genomics, combined cross analysis, interval-specific and genome-wide haplotype analysis, followed by sequence and expression analysis, each facilitated by public databases, provide new tools for narrowing rodent QTLs. Here we discuss each tool, illustrate its application and generate a bioinformatics strategy for narrowing QTLs. Combining these bioinformatics tools with classical experimental methods should accelerate QTL gene identification.     

Microarray analysis using bioinformatics analysis audit trails (BAATs)

Bioinformatics analysis plays an integrative role in genomics and functional genomics. The ability to conduct quality managed, hypothesis-driven bioinformatics analysis with the plethora of data available is mandatory. Biological interpretation of this data is dependent on versions of databases, programs and the parameters used. Thus, tracking and auditing the analyses process is important. This paper outlines what we term Bioinformatics Analysis Audit Trails (BAATs) and describes YABI, a bioinformatics environment that implements BAATs. YABI can incorporate most bioinformatics tools within the same environment, making it a valuable resource.     

The quest to deduce protein function from sequence: the role of pattern databases

In the wake of the numerous now-fruitful genome projects, we have witnessed a 'tsunami' of sequence data and with it the birth of the field of bioinformatics. Bioinformatics involves the application of information technology to the management and analysis of biological data. For many of us, this means that databases and their search tools have become an essential part of the research environment. However, the rate of sequence generation and the haphazard proliferation of databases have made it difficult to keep pace with developments, even for the cognoscenti. Moreover, increasing amounts of sequence information do not necessarily equate with an increase in knowledge, and in the panic to automate the route from raw data to biological insight, we may be generating and propagating innumerable errors in our precious databases. In the genome era upon us, researchers want rapid, easy-to-use, reliable tools for functional characterisation of newly determined sequences. For the pharmaceutical industry in particular, the Pandora's box of bioinformatics harbours an information-rich nugget, ripe with potential drug targets and possible new avenues for the development of therapeutic agents. This review outlines the current status of the major pattern databases now used routinely in the analysis of protein sequences. The review is divided into three main sections. In the first, commonly used terms are defined and the methods behind the databases are briefly described; in the second, the structure and content of the principal pattern databases are discussed; and in the final part, several alignment databases, which are frequently confused with pattern databases, are mentioned. For the new-comer, the array of resources, the range of methods behind them and the different tools required to search them can be confusing. The review therefore also briefly mentions a current international endeavour to integrate the diverse databases, which effort should facilitate sequence analysis in the future. This is particularly important for target-discovery programmes, where the challenge is to rationalise the enormous numbers of potential targets generated by sequence database searches. This problem may be addressed, at least in part, by reducing search outputs to the more focused and manageable subsets suggested by searches of integrated groups of family-specific pattern databases.     

MetaBasis

We have developed an integrated web-based relational database information system, which offers an extensive search functionality of validated entries containing available bioinformatics computing resources. This system, called MetaBasis, aims to provide the bioinformatics community, and especially newcomers to the field, with easy access to reliable bioinformatics databases and tools. MetaBasis is focused on non-commercial and open-source software tools. AVAILABILITY: http://metabasis.bioacademy.gr/     

Bioinformatics Basics: Applications in Biological Science and Medicine. * Edited by Lukas K. Buehler and Hooman H. Rashidi

Bioinformatics has blossomed in the past decades with the introductionof biological experiments that rapidly produce massive amountsof data (such as the multiple genome projects, the large-scaleanalysis of gene expression, the large-scale analysis of protein–proteininteractions and the large-scale analysis of genome-wide genotype-phenotypeassociations). The resulting bioinformatics tools mainly liein two groups. They may be databases     

Relax with CouchDB--into the non-relational DBMS era of bioinformatics

With the proliferation of high-throughput technologies, genome-level data analysis has become common in molecular biology. Bioinformaticians are developing extensive resources to annotate and mine biological features from high-throughput data. The underlying database management systems for most bioinformatics software are based on a relational model. Modern non-relational databases offer an alternative that has flexibility, scalability, and a non-rigid design schema. Moreover, with an accelerated development pace, non-relational databases like CouchDB can be ideal tools to construct bioinformatics utilities. We describe CouchDB by presenting three new bioinformatics resources: (a) geneSmash, which collates data from bioinformatics resources and provides automated gene-centric annotations, (b) drugBase, a database of drug-target interactions with a web interface powered by geneSmash, and (c) HapMap-CN, which provides a web interface to query copy number variations from three SNP-chip HapMap datasets. In addition to the web sites, all three systems can be accessed programmatically via web services.     

细菌sRNA数据库

细菌sRNA是一类长度在50～500 nt的调控小RNA（small regulatory RNA）,主要通过与靶标mRNA或靶标蛋白质结合发挥多种生物学功能。目前,随着生物信息学与高通量测序的应用,发现了越来越多的细菌sRNA,开发了多个相关数据库。为了sRNA工作者系统了解与应用这些数据,本文拟对包含细菌sRNA的综合数据库和细菌sRNA专业数据库作一概述,并对sRNA数据库的未来发展进行展望。