Bioinformatics software resources

This review looks at internet archives, repositories and lists for obtaining popular and useful biology and bioinformatics software. Resources include collections of free software, services for the collaborative development of new programs, software news media and catalogues of links to bioinformatics software and web tools. Problems with such resources arise from needs for continued curator effort to collect and update these, combined with less than optimal community support, funding and collaboration. Despite some problems, the available software repositories provide needed public access to many tools that are a foundation for analyses in bioscience research efforts.     

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。     

caBIONet--A .NET wrapper to access and process genomic data stored at the National Cancer Institute's Center for Bioinformatics databases

MOTIVATION: The National Cancer Institute's Center for Bioinformatics (NCICB) has developed a Java based data management and information system called caCORE. One component of this software suite is the object oriented API (caBIO) used to access the rich biological datasets collected at the NCI. This API can access the data using native Java classes, SOAP requests or HTTP calls. Non-Java based clients wanting to use this API have to use the SOAP or HTTP interfaces with the data being returned from the NCI servers as an XML data stream. Although the XML can be read and manipulated using DOM or SAX parsers, one loses the convenience and usability of an object oriented programming paradigm. caBIONet is a set of .NET wrapper classes (managers, genes, chromosomes, sequences, etc.) capable of serializing the XML data stream into local .NET objects. The software is able to search NCICB databases and provide local objects representing the data that can be manipulated and used by other .NET programs. The software was written in C# and compiled as a .NET DLL.     

癌症研究的生物信息学资源

随着癌症研究的发展,生物信息学成为癌症研究的一个非常重要的方法和手段,本文从微阵列芯片数据管理和分析软件、微阵列数据仓库、蛋白质功能预测工具和蛋白质结构预测工具等四个方面介绍癌症研究的生物信息学资源信息,以给相关研究提供帮助.     

The European Bioinformatics Institute (EBI) databases.

The European Bioinformatics Institute (EBI) maintains and distributes the EMBL Nucleotide Sequence database, Europe's primary nucleotide sequence data resource. The EBI also maintains and distributes the SWISS-PROT Protein Sequence database, in collaboration with Amos Bairoch of the University of Geneva. Over fifty additional specialist molecular biology databases, as well as software and documentation of interest to molecular biologists are available. The EBI network services include database searching and sequence similarity searching facilities.     

The European Bioinformatics Institute (EBI) databases.

This paper describes the databases and services of the European Bioinformatics Institute (EBI). In collaboration with DDBJ and GenBank/NCBI, the EBI maintains and distributes the EMBL Nucleotide Sequence Database, Europe's primary nucleotide sequence data resource. The EBI also maintains and distributes the SWISS-PROT Protein Sequence Database, in collaboration with Amos Bairoch of the University of Geneva. Over thirty additional specialist molecular biology databases, as well as software and documentation of interest to molecular biologists, are also available. The EBI network services include database searching, entry retrieval, and sequence similarity searching facilities.     

The European Bioinformatics Institute web site: a new view

SUMMARY: The European Bioinformatics Institute (EBI), and outstation of the European Molecular Biology laboratory, has revamped its web site for the second time since 1997 in order to address increased user demand as well as establishing better uniformity and easier accessibility for the ever growing number of users and services it offers to the community. A GRID-like hardware infrastructure has been put in place to provide round the clock services in a redundant and reliable fashion. AVAILABILITY: http://www.ebi.ac.uk/     

Public services from the European Bioinformatics Institute

The European Bioinformatics Institute (EBI) provides numerous free-of-charge, publicly available bioinformatics services that can be divided into the following categories: ftp downloads; data submissions processing and biological database production; access to query; analysis and retrieval systems and tools; user support; training and education and industry support through EBI's SME program. These services are all available at the website. It is imperative that EBI's data as well as the tools to analyse it efficiently are made available in a free and unambiguous way to the scientific community. An important part of the EBI's mission is to make this happen in a fast, reliable and efficient manner. This paper serves as a brief introduction to each of these services.     

WU-Blast2 server at the European Bioinformatics Institute

Since 1995, the WU-BLAST programs (http://blast.wustl.edu) have provided a fast, flexible and reliable method for similarity searching of biological sequence databases. The software is in use at many locales and web sites. The European Bioinformatics Institute's WU-Blast2 (http://www.ebi.ac.uk/blast2/) server has been providing free access to these search services since 1997 and today supports many features that both enhance the usability and expand on the scope of the software.     

Bioinformatics and data mining in proteomics

Proteomic studies involve the identification as well as qualitative and quantitative comparison of proteins expressed under different conditions, and elucidation of their properties and functions, usually in a large-scale, high-throughput format. The high dimensionality of data generated from these studies will require the development of improved bioinformatics tools and data-mining approaches for efficient and accurate data analysis of biological specimens from healthy and diseased individuals. Mining large proteomics data sets provides a better understanding of the complexities between the normal and abnormal cell proteome of various biological systems, including environmental hazards, infectious agents (bioterrorism) and cancers. This review will shed light on recent developments in bioinformatics and data-mining approaches, and their limitations when applied to proteomics data sets, in order to strengthen the interdependence between proteomic technologies and bioinformatics tools.     

Bioinformatics and data mining in proteomics

Proteomic studies involve the identification as well as qualitative and quantitative comparison of proteins expressed under different conditions, and elucidation of their properties and functions, usually in a large-scale, high-throughput format. The high dimensionality of data generated from these studies will require the development of improved bioinformatics tools and data-mining approaches for efficient and accurate data analysis of biological specimens from healthy and diseased individuals. Mining large proteomics data sets provides a better understanding of the complexities between the normal and abnormal cell proteome of various biological systems, including environmental hazards, infectious agents (bioterrorism) and cancers. This review will shed light on recent developments in bioinformatics and data-mining approaches, and their limitations when applied to proteomics data sets, in order to strengthen the interdependence between proteomic technologies and bioinformatics tools.     

The Helmholtz Network for Bioinformatics: an integrative web portal for bioinformatics resources

SUMMARY: The Helmholtz Network for Bioinformatics (HNB) is a joint venture of eleven German bioinformatics research groups that offers convenient access to numerous bioinformatics resources through a single web portal. The 'Guided Solution Finder' which is available through the HNB portal helps users to locate the appropriate resources to answer their queries by employing a detailed, tree-like questionnaire. Furthermore, automated complex tool cascades ('tasks'), involving resources located on different servers, have been implemented, allowing users to perform comprehensive data analyses without the requirement of further manual intervention for data transfer and re-formatting. Currently, automated cascades for the analysis of regulatory DNA segments as well as for the prediction of protein functional properties are provided. AVAILABILITY: The HNB portal is available at http://www.hnbioinfo.de     

Plant-based microarray data at the European Bioinformatics Institute. Introducing AtMIAMExpress, a submission tool for Arabidopsis gene expression data to ArrayExpress

ArrayExpress is a public microarray repository founded on the Minimum Information About a Microarray Experiment (MIAME) principles that stores MIAME-compliant gene expression data. Plant-based data sets represent approximately one-quarter of the experiments in ArrayExpress. The majority are based on Arabidopsis (Arabidopsis thaliana); however, there are other data sets based on Triticum aestivum, Hordeum vulgare, and Populus subsp. AtMIAMExpress is an open-source Web-based software application for the submission of Arabidopsis-based microarray data to ArrayExpress. AtMIAMExpress exports data in MAGE-ML format for upload to any MAGE-ML-compliant application, such as J-Express and ArrayExpress. It was designed as a tool for users with minimal bioinformatics expertise, has comprehensive help and user support, and represents a simple solution to meeting the MIAME guidelines for the Arabidopsis community. Plant data are queryable both in ArrayExpress and in the Data Warehouse databases, which support queries based on gene-centric and sample-centric annotation. The AtMIAMExpress submission tool is available at http://www.ebi.ac.uk/at-miamexpress/. The software is open source and is available from http://sourceforge.net/projects/miamexpress/. For information, contact miamexpress@ebi.ac.uk.     

E-MSD: the European Bioinformatics Institute Macromolecular Structure Database

The E-MSD macromolecular structure relational database (http://www.ebi.ac.uk/msd) is designed to be a single access point for protein and nucleic acid structures and related information. The database is derived from Protein Data Bank (PDB) entries. Relational database technologies are used in a comprehensive cleaning procedure to ensure data uniformity across the whole archive. The search database contains an extensive set of derived properties, goodness-of-fit indicators, and links to other EBI databases including InterPro, GO, and SWISS-PROT, together with links to SCOP, CATH, PFAM and PROSITE. A generic search interface is available, coupled with a fast secondary structure domain search tool.     

Bioinformatics approaches and resources for single nucleotide polymorphism functional analysis

Since the initial sequencing of the human genome, many projects are underway to understand the effects of genetic variation between individuals. Predicting and understanding the downstream effects of genetic variation using computational methods are becoming increasingly important for single nucleotide polymorphism (SNP) selection in genetics studies and understanding the molecular basis of disease. According to the NIH, there are now more than four million validated SNPs in the human genome. The volume of known genetic variations lends itself well to an informatics approach. Bioinformaticians have become very good at functional inference methods derived from functional and structural genomics. This review will present a broad overview of the tools and resources available to collect and understand functional variation from the perspective of structure, expression, evolution and phenotype. Additionally, public resources available for SNP identification and characterisation are summarised.     

Bioinformatics: from genome data to biological knowledge

Recently, molecular biologists have sequenced about a dozen bacterial genomes and the first eukaryotic genome. We can now obtain answers to detailed questions about the complete set of genes of an organism. Bioinformatics methods are increasingly used for attaching biological knowledge to long lists of genes, assigning genes to biological pathways, comparing the gene sets of different species, identifying specificity factors, and describing sets of highly conserved proteins common to all domains of life. Substantial progress has recently been made in the availability of primary and added-value databases, in the development of algorithms and of network information services for genome analysis. The pharmaceutical industry has greatly benefited from the accumulation of sequence data through the identification of targets and candidates for the development of drugs, vaccines, diagnostic markers and therapeutic proteins.