Paper2sequences: retrieval of sequences listed in a publication

Our web-based tool simplifies the often laborious procedure of retrieving a set of biosequences in a publication or webpage. As a front-end to the Bioperl toolkit, it accepts as an input a list of identifiers. They are specified in an ASCII table (copy-pasted from the publication's PDF or HTML page) and give rise to queries in multiple databases for the protein/nucleic acid data specified. Currently, GenBank, PIR (Protein Information Resource) and Swiss-Prot are supported. For any sequence accession code listed, the database can be specified and, if retrieval fails, automatic lookup for the same code in other databases can be requested. Sequence length information (if specified) and heuristic rules are used to drive the lookup if multiple protein coding sequences (CDS) are part of a single accession. Warnings are issued in cases of ambiguities and inconsistencies. An advanced option enables the user to format the output in whatever format they wish.     

ANAP: an integrated knowledge base for Arabidopsis protein interaction network analysis

Protein interactions are fundamental to the molecular processes occurring within an organism and can be utilized in network biology to help organize, simplify, and understand biological complexity. Currently, there are more than 10 publicly available Arabidopsis (Arabidopsis thaliana) protein interaction databases. However, there are limitations with these databases, including different types of interaction evidence, a lack of defined standards for protein identifiers, differing levels of information, and, critically, a lack of integration between them. In this paper, we present an interactive bioinformatics Web tool, ANAP (Arabidopsis Network Analysis Pipeline), which serves to effectively integrate the different data sets and maximize access to available data. ANAP has been developed for Arabidopsis protein interaction integration and network-based study to facilitate functional protein network analysis. ANAP integrates 11 Arabidopsis protein interaction databases, comprising 201,699 unique protein interaction pairs, 15,208 identifiers (including 11,931 The Arabidopsis Information Resource Arabidopsis Genome Initiative codes), 89 interaction detection methods, 73 species that interact with Arabidopsis, and 6,161 references. ANAP can be used as a knowledge base for constructing protein interaction networks based on user input and supports both direct and indirect interaction analysis. It has an intuitive graphical interface allowing easy network visualization and provides extensive detailed evidence for each interaction. In addition, ANAP displays the gene and protein annotation in the generated interactive network with links to The Arabidopsis Information Resource, the AtGenExpress Visualization Tool, the Arabidopsis 1,001 Genomes GBrowse, the Protein Knowledgebase, the Kyoto Encyclopedia of Genes and Genomes, and the Ensembl Genome Browser to significantly aid functional network analysis. The tool is available open access at http://gmdd.shgmo.org/Computational-Biology/ANAP.     

The EBI SRS server-new features

MOTIVATION: Here we report on recent developments at the EBI SRS server (http://srs.ebi.ac.uk). SRS has become an integration system for both data retrieval and sequence analysis applications. The EBI SRS server is a primary gateway to major databases in the field of molecular biology produced and supported at EBI as well as European public access point to the MEDLINE database provided by US National Library of Medicine (NLM). It is a reference server for latest developments in data and application integration. The new additions include: concept of virtual databases, integration of XML databases like the Integrated Resource of Protein Domains and Functional Sites (InterPro), Gene Ontology (GO), MEDLINE, Metabolic pathways, etc., user friendly data representation in 'Nice views', SRSQuickSearch bookmarklets. AVAILABILITY: SRS6 is a licensed product of LION Bioscience AG freely available for academics. The EBI SRS server (http://srs.ebi.ac.uk) is a free central resource for molecular biology data as well as a reference server for the latest developments in data integration.     

Protein kinase resource: an integrated environment for phosphorylation research

The protein kinase superfamily is an important group of enzymes controlling cellular signaling cascades. The increasing amount of available experimental data provides a foundation for deeper understanding of details of signaling systems and the underlying cellular processes. Here, we describe the Protein Kinase Resource, an integrated online service that provides access to information relevant to cell signaling and enables kinase researchers to visualize and analyze the data directly in an online environment. The data set is synchronized with Uniprot and Protein Data Bank (PDB) databases and is regularly updated and verified. Additional annotation includes interactive display of domain composition, cross-references between orthologs and functional mapping to OMIM records. The Protein Kinase Resource provides an integrated view of the protein kinase superfamily by linking data with their visual representation. Thus, human kinases can be mapped onto the human kinome tree via an interactive display. Sequence and structure data can be easily displayed using applications developed for the PKR and integrated with the website and the underlying database. Advanced search mechanisms, such as multiparameter lookup, sequence pattern, and blast search, enable fast access to the desired information, while statistics tools provide the ability to analyze the relationships among the kinases under study. The integration of data presentation and visualization implemented in the Protein Kinase Resource can be adapted by other online providers of scientific data and should become an effective way to access available experimental information.     

The EBI SRS server--recent developments

MOTIVATION: The current data explosion is intractable without advanced data management systems. The numerous data sets become really useful when they are interconnected under a uniform interface--representing the domain knowledge. The SRS has become an integration system for both data retrieval and applications for data analysis. It provides capabilities to search multiple databases by shared attributes and to query across databases fast and efficiently. RESULTS: Here we present recent developments at the EBI SRS server (http://srs.ebi.ac.uk). The EBI SRS server contains today more than 130 biological databases and integrates more than 10 applications. It is a central resource for molecular biology data as well as a reference server for the latest developments in data integration. One of the latest additions to the EBI SRS server is the InterPro database-Integrated Resource of Protein Domains and Functional Sites. Distributed in XML format it became a turning point in low level XML-SRS integration. We present InterProScan as an example of data analysis applications, describe some advanced features of SRS6, and introduce the SRSQuickSearch JavaScript interfaces to SRS.     

The need for a shared database infrastructure: combining X-ray crystallography and electron microscopy

Advances in structural biology are opening greater opportunities for understanding biological structures from the cellular to the atomic level. Particularly promising are the links that can be established between the information provided by electron microscopy and the atomic structures derived from X-ray crystallography and nuclear magnetic resonance spectroscopy. Combining such different kinds of structural data can result in novel biological information on the interaction of biomolecules in large supramolecular assemblies. As a consequence, the need to develop new databases in the field of structural biology that allow for an integrated access to data from all the experimental techniques is becoming critical. Pilot studies performed in recent years have already established a solid background as far as the basic information that an integrated macromolecular structure database should contain, as well as the basic principles for integration. These efforts started in the context of the BioImage project, and resulted in a first complete database prototype that provided a versatile platform for the linking of atomic models or X-ray diffraction data with electron microscopy information. Analysis of the requirements needed to combine data at different levels of resolution have resulted in sets of specifications that make possible the integration of all these different types in the context of a web environment. The case of a structural study linking electron microscopy and X-ray data, which is already contained within the BioImage data base and in the Protein Data Bank, is used here to illustrate the current approach, while a general discussion highlights the urgent need for integrated databases. Received: 26 January 2000 / Revised version: 15 May 2000 / Accepted: 15 May 2000     

Het-PDB Navi.: a database for protein-small molecule interactions

The genomes of more than 100 species have been sequenced, and the biological functions of encoded proteins are now actively being researched. Protein function is based on interactions between proteins and other molecules. One approach to assuming protein function based on genomic sequence is to predict interactions between an encoded protein and other molecules. As a data source for such predictions, knowledge regarding known protein-small molecule interactions needs to be compiled. We have, therefore, surveyed interactions between proteins and other molecules in Protein Data Bank (PDB), the protein three-dimensional (3D) structure database. Among 20,685 entries in PDB (April, 2003), 4,189 types of small molecules were found to interact with proteins. Biologically relevant small molecules most often found in PDB were metal ions, such as calcium, zinc, and magnesium. Sugars and nucleotides were the next most common. These molecules are known to act as cofactors for enzymes and/or stabilizers of proteins. In each case of interactions between a protein and small molecule, we found preferred amino acid residues at the interaction sites. These preferences can be the basis for predicting protein function from genomic sequence and protein 3D structures. The data pertaining to these small molecules were collected in a database named Het-PDB Navi., which is freely available at http://daisy.nagahama-i-bio.ac.jp/golab/hetpdbnavi.html and linked to the official PDB home page.     

Mayday--a microarray data analysis workbench

Mayday is a workbench for visualization, analysis and storage of microarray data. It features a graphical user interface and supports the development and integration of existing and new analysis methods. Besides the infrastructural core functionality, Mayday offers a variety of plug-ins, such as various interactive viewers, a connection to the R statistical environment, a connection to SQL-based databases and different data mining methods, including WEKA-library based methods for classification and various clustering methods. In addition, so-called meta information objects are provided for annotation of the microarray data allowing integration of data from different sources, which is a feature that, for instance, is employed in the enhanced heatmap visualization. Supplementary information: The software and more detailed information including screenshots and a user guide as well as test data can be found on the Mayday home page http://www.zbit.uni-tuebingen.de/pas/mayday. The core is published under the GPL (GNU Public License) and the associated plug-ins under the LGPL (Lesser GNU Public License).     

Incremental generation of summarized clustering hierarchy for protein family analysis

MOTIVATION: Protein sequence clustering has been widely exploited to facilitate in-depth analysis of protein functions and families. For some applications of protein sequence clustering, it is highly desirable that a hierarchical structure, also referred to as dendrogram, which shows how proteins are clustered at various levels, is generated. However, as the sizes of contemporary protein databases continue to grow at rapid rates, it is of great interest to develop some summarization mechanisms so that the users can browse the dendrogram and/or search for the desired information more effectively. RESULTS: In this paper, the design of a novel incremental clustering algorithm aimed at generating summarized dendrograms for analysis of protein databases is described. The proposed incremental clustering algorithm employs a statistics-based model to summarize the distributions of the similarity scores among the proteins in the database and to control formation of clusters. Experimental results reveal that, due to the summarization mechanism incorporated, the proposed incremental clustering algorithm offers the users highly concise dendrograms for analysis of protein clusters with biological significance. Another distinction of the proposed algorithm is its incremental nature. As the sizes of the contemporary protein databases continue to grow at fast rates, due to the concern of efficiency, it is desirable that cluster analysis of a protein database can be carried out incrementally, when the protein database is updated. Experimental results with the Swiss-Prot protein database reveal that the time complexity for carrying out incremental clustering with k new proteins added into the database containing n proteins is O(n2betalogn), where beta congruent with 0.865, provided that k < n. AVAILABILITY: The Linux executable is available on the following supplementary page.     

The ARKdb: genome databases for farmed and other animals

The ARKdb genome databases provide comprehensive public repositories for genome mapping data from farmed species and other animals (http://www.thearkdb.org) providing a resource similar in function to that offered by GDB or MGD for human or mouse genome mapping data, respectively. Because we have attempted to build a generic mapping database, the system has wide utility, particularly for those species for which development of a specific resource would be prohibitive. The ARKdb genome database model has been implemented for 10 species to date. These are pig, chicken, sheep, cattle, horse, deer, tilapia, cat, turkey and salmon. Access to the ARKdb databases is effected via the World Wide Web using the ARKdb browser and Anubis map viewer. The information stored includes details of loci, maps, experimental methods and the source references. Links to other information sources such as PubMed and EMBL/GenBank are provided. Responsibility for data entry and curation is shared amongst scientists active in genome research in the species of interest. Mirror sites in the United States are maintained in addition to the central genome server at Roslin.     

海洋生物多样性信息资源

海洋生物多样性甚高, 但却饱受人为的破坏及干扰。目前全球最大的含点位数据的在线开放性数据库是海洋生物地理信息系统(OBIS), 共约12万种3,700万笔资料; 另一个较大的数据库世界海洋生物物种登录(WoRMS)已收集全球22万种海洋生物之物种分类信息。除此之外, 以海洋生物为主的单一类群的数据库只有鱼库(FishBase)、藻库(AlgaeBase)及世界六放珊瑚(Hexacorallians of the World)3个。跨类群及跨陆海域的全球性物种数据库则甚多, 如网络生命大百科(EOL)、全球生物物种名录(CoL)、整合分类信息系统(ITIS)、维基物种(Wikispecies)、ETI生物信息(ETI Bioinformatics)、生命条形码(BOL)、基因库(GenBank)、生物多样性历史文献图书馆(BHL)、海洋生物库(SeaLifeBase); 海洋物种鉴定入口网(Marine Species Identification Portal)、FAO渔业及水产养殖概要(FAO Fisheries and Aquaculture Fact Sheets)等可查询以分类或物种解说为主的数据库。全球生物多样性信息网络(GBIF)、发现生命(Discover Life)、水生物图库(AquaMaps)等则是以生态分布数据为主, 且可作地理分布图并提供下载功能, 甚至于可以改变水温、盐度等环境因子的参数值, 利用既定的模式作参数改变后之物种分布预测。谷歌地球(Google Earth)及国家地理(National Geographic)网站中的海洋子网页, 以及珊瑚礁库(ReefBase)等官方机构或非政府组织之网站, 则大多以海洋保育的教育倡导为主, 所提供的信息及素材可谓包罗万象, 令人目不暇给。更令用户感到方便的是上述许多网站或数据库彼此间均已可交互链接及查询。另外, 属于搜索引擎的谷歌图片(Google Images)与谷歌学术(Google Scholar)透过海洋生物数据库所提供的直接链接, 在充实物种生态图片与学术论文上亦发挥极大帮助, 让用户获得丰富多样的信息。为了保育之目的, 生物多样性数据库除了整合与公开分享外, 还应鼓励并推荐大家来使用。本文乃举Rainer Froese在巴黎演讲之内容为例, 介绍如何使用海洋生物多样性之数据来预测气候变迁对鱼类分布的影响。最后就中国大陆与台湾目前海洋生物多样性数据库的现况、两岸的合作及如何与国际接轨作介绍。     

The EMBL Nucleotide Sequence Database: major new developments

The EMBL Nucleotide Sequence Database (http://www.ebi.ac.uk/embl/) incorporates, organizes and distributes nucleotide sequences from all available public sources. The database is located and maintained at the European Bioinformatics Institute (EBI) near Cambridge, UK. In an international collaboration with DDBJ (Japan) and GenBank (USA), data are exchanged amongst the collaborating databases on a daily basis to achieve optimal synchronization. Webin is the preferred web-based submission system for individual submitters, while automatic procedures allow incorporation of sequence data from large-scale genome sequencing centres and from the European Patent Office (EPO). Database releases are produced quarterly. Network services allow free access to the most up-to-date data collection via FTP, Email and World Wide Web interfaces. EBI's Sequence Retrieval System (SRS) integrates and links the main nucleotide and protein databases plus many other specialized molecular biology databases. For sequence similarity searching, a variety of tools (e.g. Fasta, BLAST) are available which allow external users to compare their own sequences against the latest data in the EMBL Nucleotide Sequence Database and SWISS-PROT. All resources can be accessed via the EBI home page at http://www.ebi.ac.uk.     

Naming CRISPR alleles: endonuclease-mediated mutation nomenclature across species

The widespread use of CRISPR/Cas and other targeted endonuclease technologies in many species has led to an explosion in the generation of new mutations and alleles. The ability to generate many different mutations from the same target sequence either by homology-directed repair with a donor sequence or non-homologous end joining-induced insertions and deletions necessitates a means for representing these mutations in literature and databases. Standardized nomenclature can be used to generate unambiguous, concise, and specific symbols to represent mutations and alleles. The research communities of a variety of species using CRISPR/Cas and other endonuclease-mediated mutation technologies have developed different approaches to naming and identifying such alleles and mutations. While some organism-specific research communities have developed allele nomenclature that incorporates the method of generation within the official allele or mutant symbol, others use metadata tags that include method of generation or mutagen. Organism-specific research community databases together with organism-specific nomenclature committees are leading the way in providing standardized nomenclature and metadata to facilitate the integration of data from alleles and mutations generated using CRISPR/Cas and other targeted endonucleases.

     

PRASA: An integrated web server that analyzes protein interaction types

This work presents the Protein Association Analyzer (PRASA) (http://zoro.ee.ncku.edu.tw/prasa/) that predicts protein interactions as well as interaction types. Protein interactions are essential to most biological functions. The existence of diverse interaction types, such as physically contacted or functionally related interactions, makes protein interactions complex. Different interaction types are distinct and should not be confused. However, most existing tools focus on a specific interaction type or mix different interaction types. This work collected 7234058 associations with experimentally verified interaction types from five databases and compiled individual probabilistic models for different interaction types. The PRASA result page shows predicted associations and their related references by interaction type. Experimental results demonstrate the performance difference when distinguishing between different interaction types. The PRASA provides a centralized and organized platform for easy browsing, downloading and comparing of interaction types, which helps reveal insights into the complex roles that proteins play in organisms.     

Plant genome resources at the national center for biotechnology information

The National Center for Biotechnology Information (NCBI) integrates data from more than 20 biological databases through a flexible search and retrieval system called Entrez. A core Entrez database, Entrez Nucleotide, includes GenBank and is tightly linked to the NCBI Taxonomy database, the Entrez Protein database, and the scientific literature in PubMed. A suite of more specialized databases for genomes, genes, gene families, gene expression, gene variation, and protein domains dovetails with the core databases to make Entrez a powerful system for genomic research. Linked to the full range of Entrez databases is the NCBI Map Viewer, which displays aligned genetic, physical, and sequence maps for eukaryotic genomes including those of many plants. A specialized plant query page allow maps from all plant genomes covered by the Map Viewer to be searched in tandem to produce a display of aligned maps from several species. PlantBLAST searches against the sequences shown in the Map Viewer allow BLAST alignments to be viewed within a genomic context. In addition, precomputed sequence similarities, such as those for proteins offered by BLAST Link, enable fluid navigation from unannotated to annotated sequences, quickening the pace of discovery. NCBI Web pages for plants, such as Plant Genome Central, complete the system by providing centralized access to NCBI's genomic resources as well as links to organism-specific Web pages beyond NCBI.     

A database application for pre-processing, storage and comparison of mass spectra derived from patients and controls

Background  

Statistical comparison of peptide profiles in biomarker discovery requires fast, user-friendly software for high throughput data analysis. Important features are flexibility in changing input variables and statistical analysis of peptides that are differentially expressed between patient and control groups. In addition, integration the mass spectrometry data with the results of other experiments, such as microarray analysis, and information from other databases requires a central storage of the profile matrix, where protein id's can be added to peptide masses of interest.     

Protein sequence databases

A variety of protein sequence databases exist, ranging from simple sequence repositories, which store data with little or no manual intervention in the creation of the records, to expertly curated universal databases that cover all species and in which the original sequence data are enhanced by the manual addition of further information in each sequence record. As the focus of researchers moves from the genome to the proteins encoded by it, these databases will play an even more important role as central comprehensive resources of protein information. Several the leading protein sequence databases are discussed here, with special emphasis on the databases now provided by the Universal Protein Knowledgebase (UniProt) consortium.     

Regeneration of the visual system in gastropods (Mollusca)

Abstract. The topic of tissue and organ regeneration has been of interest to life scientists ever since the phenomenon was noticed. The reason for this is obvious: if one can learn what drives and controls regeneration, i.e., how lost or damaged structures can be replaced, one not only has a better chance to understand an animal's embryogenesis and evolutionary relationship with other taxa, but one would also be in a better position to treat organ loss or tissue damage in humans. In this context, the possible restitution of individual sensory neurons or nerve projections has been of special interest to us. We identified central visual projections in several gastropod species and found that: (1) projections are very extensive across the brain and (2) they have connections with other systems and organs (including, most likely, non-ocular skin photoreceptors) that may be involved in the integration of signals from different sensors. Investigations of afferent and efferent visual elements at a morphological level should help reveal the neuronal basis of a gastropod's behavioral reactions.     

The SWISS-MODEL workspace: a web-based environment for protein structure homology modelling

MOTIVATION: Homology models of proteins are of great interest for planning and analysing biological experiments when no experimental three-dimensional structures are available. Building homology models requires specialized programs and up-to-date sequence and structural databases. Integrating all required tools, programs and databases into a single web-based workspace facilitates access to homology modelling from a computer with web connection without the need of downloading and installing large program packages and databases. RESULTS: SWISS-MODEL workspace is a web-based integrated service dedicated to protein structure homology modelling. It assists and guides the user in building protein homology models at different levels of complexity. A personal working environment is provided for each user where several modelling projects can be carried out in parallel. Protein sequence and structure databases necessary for modelling are accessible from the workspace and are updated in regular intervals. Tools for template selection, model building and structure quality evaluation can be invoked from within the workspace. Workflow and usage of the workspace are illustrated by modelling human Cyclin A1 and human Transmembrane Protease 3. AVAILABILITY: The SWISS-MODEL workspace can be accessed freely at http://swissmodel.expasy.org/workspace/