利用SWISS-PROT网获取生物信息学资源

生物信息学是是采用数学、统计学和计算机方法对生物学数据信息进行采集、存储、传播、分析、归类、解释的科学[1] 。Ｉｎｔｅｒｎｅｔ网络是信息传输、检索、获取、交流的重要手段。当前 ,在Ｉｎｔｅｒｎｅｔ网上可以查询到大量的生物信息学数据库 ,其中ＳＷＩＳＳ ＰＲＯＴ蛋白质序列数据库是网上生物信息学最核心的 3个数据库之一。通过该数据库 ,可以较完整地获得生物大分子的序列信息。同时 ,研究者也可以将测定的序列信息通过该数据库予以认定、发表、交流。本文主要探讨ＳＷＩＳＳ ＰＲＯＴ蛋白质序列数据库的特点、检索方法及利用Ｉ…     

利用SWISS-PROT网上获取生物信息学资源

生物信息学是是采用数学、统计学和计算机方法对生物学数据信息进行采集、存储、传播、分析、归类、解释的科学[1].Internet网络是信息传输、检索、获取、交流的重要手段.当前,在Internet网上可以查询到大量的生物信息学数据库,其中SWISS-PROT蛋白质序列数据库是网上生物信息学最核心的3个数据库之一.通过该数据库,可以较完整地获得生物大分子的序列信息.同时,研究者也可以将测定的序列信息通过该数据库予以认定、发表、交流.本文主要探讨SWISS-PROT蛋白质序列数据库的特点、检索方法及利用Internet获取蛋白质序列信息.     

基于Internet网生物信息资源特定基因同源新基因克隆策略

随着人类基因组计划的基本完成,各类生物信息学数据库和软件层出不穷,利用Internet网上生物信息资源克隆新基因的策略也得到新的发展。作者在简单介绍网上生物信息资源以及新基因克隆策略的同时,着重对基于EST数据库和基因组数据库特定基因的同源新基因克隆策略进行了详细阐述。     

生物信息学的研究现状及其发展问题的探讨

结合生物信息学产生的历史条件,对生物信息学的定义进行了介绍;归纳总结了现代生物信息表述、采集、储存、传递、检索的表现形式-生物学数据库的分类与分布;着重介绍了生物信息学的主要研究内容和基本的分析方法,阐明了生物信息的分析和解读模式;强调了生物信息学与其他相关学科的相关性,提出了生物信息学发展的一些亟待解决的问题及其相应的解决方案。     

农林院校生物信息学专业数据库技术课程教学改革刍议

生物信息学是一门交叉学科,对于现代生物学研究具有重要的意义。数据库技术是生物信息学的基础之一。本文对农林院校的生物信息学专业的数据库技术课程的教学现状做了一些介绍,对目前生物信息专业数据库教学存在的问题进行了分析。结合教学的实践,有针对性的提出了一些教学改革的具体措施。     

生物信息处理中心的建立

本文提出了一套生物信息处理中心的建立方案,具有实用、建设成本低廉、构建方便、全面共享和可扩展性强等特点。生物信息处理中心以数据库相似性搜索、数据库资源检索和生物序列分析为主线,建立了软硬件环境和应用程序及数据库,能够满足绝大多数科研人员的生物信息学分析需求。     

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。     

生物信息学在孤儿G蛋白偶联受体配基筛选中的应用

生物信息学的飞速发展为孤儿G蛋白偶联受体(orphan G protein—coupled receptors,oGPCRs)配基的筛选提供了重要的信息资源。利用生物信息学数据库和工具对oGPCRs的核酸和蛋白质序列进行运算、分析、注释和预测,获得足够的生物信息,辅助实验研究,以尽可能快速、准确地筛选出oGPCRs的特异性配基。本介绍有关生物信息学在oGPCRs配基筛选研究中的应用。     

我国生物信息产业的现状及问题分析

针对我国生物信息产业的现状及存在的问题进行分析,介绍了生物信息学以及生物芯片研究的现状和新技术、生物信息产业的发展,并对生物信息产业的知识产权保护问题进行了分析和讨论。对于今后如何发展我国生物信息产业以及如何采取策略和措施提供参考。     

网络上的生物信息资源

生物信息学是生命科学中最活跃的领域之一。目前,生物信息资源的利用已实现了高度的网络化。算法和软件的进步、数据库的一体化、服务器－客户模式的建立使之成为生物、医药、农业等学科强有力的工具。     

Facilities that make the PDB data collection more powerful

We describe a series of databases and tools that directly or indirectly support biomedical research on macromolecules, with focus on their applicability in protein structure bioinformatics research. DSSP, that determines secondary structures of proteins, has been updated to work well with extremely large structures in multiple formats. The PDBREPORT database that lists anomalies in protein structures has been remade to remove many small problems. These reports are now available as PDF‐formatted files with a computer‐readable summary. The VASE software has been added to analyze and visualize HSSP multiple sequence alignments for protein structures. The Lists collection of databases has been extended with a series of databases, most noticeably with a database that gives each protein structure a grade for usefulness in protein structure bioinformatics projects. The PDB‐REDO collection of reanalyzed and re‐refined protein structures that were solved by X‐ray crystallography has been improved by dealing better with sugar residues and with hydrogen bonds, and adding many missing surface loops. All academic software underlying these protein structure bioinformatics applications and databases are now publicly accessible, either directly from the authors or from the GitHub software repository.     

国内外生物信息学数据库服务新进展

生物信息学是生命科学中最活跃的领域之一. 各类生物信息学数据库在近年不断出现,其规模呈爆炸趋势增长,同时数据结构日趋复杂. 目前生物信息学数据库服务已实现了高度的计算机和网络化. 算法和软件的进步、数据库的一体化、服务器-客户模式的建立使之成为生物、医药、农业等学科的强有力工具. 在国内北京大学物理化学研究所于1996年建立了第一家生物信息学网络服务器. 现已为国内外科学家提供了7万余次服务,在国际上具有一定影响.     

EBI databases and services

The EMBL Outstation-European Bioinformatics Institute (EBI) is a center for research and services in bioinformatics. It serves researchers in molecular biology, genetics, medicine, and agriculture from academia, and the agricultural, biotechnology, chemical, and pharmaceutical industries. The Institute manages and makes available databases of biological data including nucleic acid, protein sequences, and macromolecular structures. It provides to this community bioinformatics services relevant to molecular biology free of charge over the Internet. Some of these databases and services are described in this review. For more information, visit the EBI Web server at http://www.ebi.ac.uk/.     

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.     

The Path to Enlightenment： Making Sense of Genomic and Proteomic Information

Whereas genomics describes the study of genome, mainly represented by its gene expression on the DNA or RNA level, the term proteomics denotes the study of the proteome, which is the protein complement encoded by the genome. In recent years, the number of proteomic experiments increased tremendously. While all fields of proteomics have made major technological advances, the biggest step was seen in bioinformatics. Biological information management relies on sequence and structure databases and powerful software tools to translate experimental results into meaningful biological hypotheses and answers. In this resource article, I provide a collection of databases and software available on the Internet that are useful to interpret genomic and proteomic data. The article is a toolbox for researchers who have genomic or proteomic datasets and need to put their findings into a biological context.     

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。     

Farm animal genome databases

The requirements for bioinformatics resources to support genome research in farm animals is reviewed.The resources developed to meet these needs are described. Resource databases and associated tools have been developed to handle experimental data. Several of these systems serve the needs of multinational collaborations. Genome databases have been established to provide contemporary summaries of the status of genome maps in a range of farm and domestic animals along with experimental details and citations. New resources and tools will be required to address the informatics needs of emerging technologies such as microarrays. However, continued investment is also required to maintain the currency and utility of the current systems, especially the genome databases.     

In silico tools for signal transduction research

Signal transduction is a fundamental process that takes place in all living organisms and understanding how this event occurs at the cellular level is of vital importance to virtually all fields of biomedicine. There are several major steps involved in deciphering the signalling pathways: (a) Which molecules are involved in signalling? (b) Who talks to whom?, ie making sense of the molecular interactions in a context-dependent way. (c) Where are the signalling events taking place?, eg when a resting cell becomes activated. The challenge lies in reconstructing signalling modules and networks evoked in a particular response to a single input as well as correlating the signalling response to different cellular inputs. There is also the need for interpretation of cross-talk between signalling modules in response to single and multiple inputs. To follow up these questions there are many good databases that provide an information system on regulatory networks. This review aims to find some of the bioinformatics tools and websites available to conduct signal transduction research and to discuss the representation of databases available for the processes of signalling. The databases considered here can provide a well-structured overview on the subject and a basis for advanced bioinformatics analysis to interpret the function of genomic sequences or to analyse signalling networks within a cell. However, the knowledge of most signalling pathways is incomplete and for this reason the existing databases will provide insight, but very rarely a more complete picture.     

一个园艺植物基因组序列和注释的在线批量实时提取平台

目前, 大量园艺植物基因组测序已经完成或接近尾声, 它们的基因组序列和注释数据极大地促进了功能基因组学研究。为给科研人员提供批量下载特定的基因组区段序列和注释平台, 笔者开发了一个称为OBRRP的生物信息学工具。OBRRP具有提取葡萄(Vitis vinifera)、桃(Prunus persica)、草莓(Fragaria vesca)、黄瓜(Cucumis sativus)、西瓜(Citrullus lanatus)、番茄(Solanum lycopersicum)、甜橙(Citrus sinensis)、苹果(Malus x domestica)、猕猴桃(Actinidia chinensis)、马铃薯(Solanum tuberosum)、香蕉(Musa acuminata)和拟南芥(Arabidopsis thaliana) 12种植物基因组序列及注释数据的功能; 同时, 也具有扩展到其它Gbrowser浏览器架构的数据库功能。测试结果表明, OBRRP是一个快捷简便的在线、批量和实时提取工具, 其登录地址为http://bioinfo.jit.edu.cn/OBRRP/。