Overview of the LiMB database.

The rapidly increasing number of databases relevant to molecular biology has given rise to a need for a coordinated effort to identify, characterize, and link them. The LiMB database, which contains information about molecular biology and related databases, is a step in that direction. It serves molecular biologists seeking data sets containing information relevant to their research, and is also intended to anticipate the needs of database designers and managers building software links for related data sets. We present an abbreviated version of the database here; the full database is available free of charge as described below.     

SciDBMaker: new software for computer-aided design of specialized biological databases

Background  

The exponential growth of research in molecular biology has brought concomitant proliferation of databases for stocking its findings. A variety of protein sequence databases exist. While all of these strive for completeness, the range of user interests is often beyond their scope. Large databases covering a broad range of domains tend to offer less detailed information than smaller, more specialized resources, often creating a need to combine data from many sources in order to obtain a complete picture. Scientific researchers are continually developing new specific databases to enhance their understanding of biological processes.     

Evolution and applications of plant pathway resources and databases

Plants are important sources of food and plant products are essential for modern human life. Plants are increasingly gaining importance as drug and fuel resources, bioremediation tools and as tools for recombinant technology. Considering these applications, database infrastructure for plant model systems deserves much more attention. Study of plant biological pathways, the interconnection between these pathways and plant systems biology on the whole has in general lagged behind human systems biology. In this article we review plant pathway databases and the resources that are currently available. We lay out trends and challenges in the ongoing efforts to integrate plant pathway databases and the applications of database integration. We also discuss how progress in non-plant communities can serve as an example for the improvement of the plant pathway database landscape and thereby allow quantitative modeling of plant biosystems. We propose Good Database Practice as a possible model for collaboration and to ease future integration efforts.     

Re-thinking organisms: The impact of databases on model organism biology

Community databases have become crucial to the collection, ordering and retrieval of data gathered on model organisms, as well as to the ways in which these data are interpreted and used across a range of research contexts. This paper analyses the impact of community databases on research practices in model organism biology by focusing on the history and current use of four community databases: FlyBase, Mouse Genome Informatics, WormBase and The Arabidopsis Information Resource. We discuss the standards used by the curators of these databases for what counts as reliable evidence, acceptable terminology, appropriate experimental set-ups and adequate materials (e.g., specimens). On the one hand, these choices are informed by the collaborative research ethos characterising most model organism communities. On the other hand, the deployment of these standards in databases reinforces this ethos and gives it concrete and precise instantiations by shaping the skills, practices, values and background knowledge required of the database users. We conclude that the increasing reliance on community databases as vehicles to circulate data is having a major impact on how researchers conduct and communicate their research, which affects how they understand the biology of model organisms and its relation to the biology of other species.     

RNAcentral: A vision for an international database of RNA sequences

During the last decade there has been a great increase in the number of noncoding RNA genes identified, including new classes such as microRNAs and piRNAs. There is also a large growth in the amount of experimental characterization of these RNA components. Despite this growth in information, it is still difficult for researchers to access RNA data, because key data resources for noncoding RNAs have not yet been created. The most pressing omission is the lack of a comprehensive RNA sequence database, much like UniProt, which provides a comprehensive set of protein knowledge. In this article we propose the creation of a new open public resource that we term RNAcentral, which will contain a comprehensive collection of RNA sequences and fill an important gap in the provision of biomedical databases. We envision RNA researchers from all over the world joining a federated RNAcentral network, contributing specialized knowledge and databases. RNAcentral would centralize key data that are currently held across a variety of databases, allowing researchers instant access to a single, unified resource. This resource would facilitate the next generation of RNA research and help drive further discoveries, including those that improve food production and human and animal health. We encourage additional RNA database resources and research groups to join this effort. We aim to obtain international network funding to further this endeavor.     

Virgil database for rich links (1999 update).

With so many databases available for research in the Human Genome Project, it is crucial to efficiently relate information from different resources. For that purpose, we maintain Virgil, a database of rich links for data browsing, data analysis and database interconnection. Virgil current version contains more than 40 000 rich links from five major databases: SWISS-PROT, GenBank, PDB, GDB and OMIM. Materials described in this paper are available from http://www.infobiogen.fr/services/virgil/     

Cancer and the web

The applications of functional genomics, proteomics and informatics to cancer research have yielded a tremendous amount of information, which is growing all the time. Much of this information is available publicly on the Internet and ranges from general information about different cancers from a patient or clinical viewpoint, through to databases suitable for cancer researchers of all backgrounds, to very specific sites dedicated to individual genes or molecules. A simple search for 'cancer' from a typical Web browser search engine yields more than half a million hits; an even more specific search for 'leukaemia' (>40 000 hits) or 'p53' (>5700 hits) yields far too many hits to allow one to identify particular sites of interest. This review aims to provide a brief guide to some of the resources and databases that can be used as springboards to home in rapidly on information relevant to many fields of cancer research. As such, this article will not focus on a single website but hopes to illustrate some of the ways that postgenomic biology is revolutionizing cancer research. It will cover genomics and proteomics approaches that have been applied to studying global expression patterns in cancers, in addition to providing links ranging from general information about cancer to specific cancer gene mutation databases.     

Public access for teaching genomics,proteomics, and bioinformatics

When the human genome project was conceived, its leaders wanted all researchers to have equal access to the data and associated research tools. Their vision of equal access provides an unprecedented teaching opportunity. Teachers and students have free access to the same databases that researchers are using. Furthermore, the recent movement to deliver scientific publications freely has presented a second source of current information for teaching. I have developed a genomics course that incorporates many of the public-domain databases, research tools, and peer-reviewed journals. These online resources provide students with exciting entree into the new fields of genomics, proteomics, and bioinformatics. In this essay, I outline how these fields are especially well suited for inclusion in the undergraduate curriculum. Assessment data indicate that my students were able to utilize online information to achieve the educational goals of the course and that the experience positively influenced their perceptions of how they might contribute to biology.     

Conceptual biology,hypothesis discovery,and text mining: Swanson's legacy

Innovative biomedical librarians and information specialists who want to expand their roles as expert searchers need to know about profound changes in biology and parallel trends in text mining. In recent years, conceptual biology has emerged as a complement to empirical biology. This is partly in response to the availability of massive digital resources such as the network of databases for molecular biologists at the National Center for Biotechnology Information. Developments in text mining and hypothesis discovery systems based on the early work of Swanson, a mathematician and information scientist, are coincident with the emergence of conceptual biology. Very little has been written to introduce biomedical digital librarians to these new trends. In this paper, background for data and text mining, as well as for knowledge discovery in databases (KDD) and in text (KDT) is presented, then a brief review of Swanson's ideas, followed by a discussion of recent approaches to hypothesis discovery and testing. 'Testing' in the context of text mining involves partially automated methods for finding evidence in the literature to support hypothetical relationships. Concluding remarks follow regarding (a) the limits of current strategies for evaluation of hypothesis discovery systems and (b) the role of literature-based discovery in concert with empirical research. Report of an informatics-driven literature review for biomarkers of systemic lupus erythematosus is mentioned. Swanson's vision of the hidden value in the literature of science and, by extension, in biomedical digital databases, is still remarkably generative for information scientists, biologists, and physicians.     

Data warehousing in molecular biology

In the business and healthcare sectors data warehousing has provided effective solutions for information usage and knowledge discovery from databases. However, data warehousing applications in the biological research and development (R&D) sector are lagging far behind. The fuzziness and complexity of biological data represent a major challenge in data warehousing for molecular biology. By combining experiences in other domains with our findings from building a model database, we have defined the requirements for data warehousing in molecular biology.     

基因转录调控相关数据库集成系统及其应用

通过互联网访问的有关基因转录调控的数据库集成系统及其应用 ,包括调控区 (3’和 5’调控区、内显子和外显子调控区等 )、调控单元 (启动子 ,增强子 ,沉默子等 )和转录因子结合位点相关数据库及其数据库系统的性质、组成和功能。也介绍了这些数据库和系统的查询和搜索方法以及相关开发的程序工具。这些生物信息学资源对于从事生物信息学、分子生物学、遗传工程、基因功能、生物技术、代谢工程、药物设计、病理学和药理学研究的机构及人员在教学研究方面具一定的参考价值和帮助。     

A dedicated database program for cataloging recombinant clones and other laboratory products of molecular biology technology

A novel computer database program dedicated to storing, cataloging, and accessing information about recombinant clones and libraries has been developed for the IBM (or compatible) personal computer. This program, named CLONES, also stores information about bacterial strains and plasmid and bacteriophage vectors used in molecular biology. The advantages of this method are improved organization of data, fast and easy assimilation of new data, automatic association of new data with existing data, and rapid retrieval of desired records using search criteria specified by the user. Individual records are indexed in the database using B-trees, which automatically index new entries and expedite later access. The use of multiple windows, pull-down menus, scrolling pick-lists, and field-input techniques make the program intuitive to understand and easy to use. Daughter databases can be created to include all records of a particular type, or only those records matching user-specified search criteria. Separate databases can also be merged into a larger database. This computer program provides an easy-to-use and accurate means to organize, maintain, access, and share information about recombinant clones and other laboratory products of molecular biology technology.     

Books for free? How can this be?— A PubMed resource you may be overlooking

The NCBI (National Center for Biotechnology Information) at the National Institutes of Health collects a wide range of molecular biological data, and develops tools and databases to analyse and disseminate this information. Many life scientists are familiar with the website maintained by the NCBI (http://www.ncbi.nlm.nih.gov), because they use it to search GenBank for homologues of their genes of interest or to search the PubMed database for scientific literature of interest. There is also a database called the Bookshelf that includes searchable popular life science textbooks, medical and research reference books and NCBI reference materials. The Bookshelf can be useful for researchers and educators to find basic biological information. This article includes a representative list of the resources currently available on the Bookshelf, as well as instructions on how to access the information in these resources.     

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.