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PubMed2002

The Biological Macromolecule Crystallization Database: crystallization procedures and strategies.

The Biological Macromolecule Crystallization Database (BMCD) archives crystallization data from published reports for all forms of biological macromolecules that have produced crystals suitable for X-ray diffraction studies. The information includes the crystallization conditions, crystal data, comments about the crystallization procedure and information on the biological macromolecule or biological macromolecule complex. Crystallization procedures, including fast screens and more general procedures, can be developed effectively using this web-based resource (http://wwwbmcd.nist.gov:8080/bmcd/bmcd.html).

Crystallization↗

PubMedDate not supplied

CIBEX: center for information biology gene expression database.

We describe the current status of the gene expression database CIBEX (Center for Information Biology gene EXpression database, http://cibex.nig.ac.jp), with a data retrieval system in compliance with MIAME, a standard that the MGED Society has developed for comparing and data produced in microarray experiments at different laboratories worldwide. CIBEX serves as a public repository for a wide range of high-throughput experimental data in gene expression research, including microarray-based experiments measuring mRNA, serial analysis of gene expression (SAGE tags), and mass spectrometry proteomic data.

Computational Biology↗

PubMed2000

Environmental biotechnology informatics.

Environmental biotechnology informatics is in its infancy and is growing fast. Computer and information science can assist environmental biotechnology by developing biological databases and building mathematical models of biological systems. Funding and training limitations in this field may, however, hinder its future growth.

Biodegradation, Environmental↗

PubMed2003

Challenges in data management for functional genomics.

Biological databases face challenges in four main areas: (1). integration, interoperation and federation; (2). ontologies and definitions of semantics; (3). community annotation; and (4). integration of data analysis tools with databases. Each of these areas provides interesting targets for research and development.

Computational Biology↗

PubMed2003

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.

Animals↗

PubMed2005

Evaluation of BioCreAtIvE assessment of task 2.

BACKGROUND: Molecular Biology accumulated substantial amounts of data concerning functions of genes and proteins. Information relating to functional descriptions is generally extracted manually from textual data and stored in biological databases to build up annotations for large collections of gene products. Those annotation databases are crucial for the interpretation of large scale analysis approaches using bioinformatics or experimental techniques. Due to the growing accumulation of functional descriptions in biomedical literature the need for text mining tools to facilitate the extraction of such annotations is urgent. In order to make text mining tools useable in real world scenarios, for instance to assist database curators during annotation of protein function, comparisons and evaluations of different approaches on full text articles are needed. RESULTS: The Critical Assessment for Information Extraction in Biology (BioCreAtIvE) contest consists of a community wide competition aiming to evaluate different strategies for text mining tools, as applied to biomedical literature. We report on task two which addressed the automatic extraction and assignment of Gene Ontology (GO) annotations of human proteins, using full text articles. The predictions of task 2 are based on triplets of protein--GO term--article passage. The annotation-relevant text passages were returned by the participants and evaluated by expert curators of the GO annotation (GOA) team at the European Institute of Bioinformatics (EBI). Each participant could submit up to three results for each sub-task comprising task 2. In total more than 15,000 individual results were provided by the participants. The curators evaluated in addition to the annotation itself, whether the protein and the GO term were correctly predicted and traceable through the submitted text fragment. CONCLUSION: Concepts provided by GO are currently the most extended set of terms used for annotating gene products, thus they were explored to assess how effectively text mining tools are able to extract those annotations automatically. Although the obtained results are promising, they are still far from reaching the required performance demanded by real world applications. Among the principal difficulties encountered to address the proposed task, were the complex nature of the GO terms and protein names (the large range of variants which are used to express proteins and especially GO terms in free text), and the lack of a standard training set. A range of very different strategies were used to tackle this task. The dataset generated in line with the BioCreative challenge is publicly available and will allow new possibilities for training information extraction methods in the domain of molecular biology.

Computational Biology↗

PubMed2000

Biological sequence compression algorithms.

Today, more and more DNA sequences are becoming available. The information about DNA sequences are stored in molecular biology databases. The size and importance of these databases will be bigger and bigger in the future, therefore this information must be stored or communicated efficiently. Furthermore, sequence compression can be used to define similarities between biological sequences. The standard compression algorithms such as gzip or compress cannot compress DNA sequences, but only expand them in size. On the other hand, CTW (Context Tree Weighting Method) can compress DNA sequences less than two bits per symbol. These algorithms do not use special structures of biological sequences. Two characteristic structures of DNA sequences are known. One is called palindromes or reverse complements and the other structure is approximate repeats. Several specific algorithms for DNA sequences that use these structures can compress them less than two bits per symbol. In this paper, we improve the CTW so that characteristic structures of DNA sequences are available. Before encoding the next symbol, the algorithm searches an approximate repeat and palindrome using hash and dynamic programming. If there is a palindrome or an approximate repeat with enough length then our algorithm represents it with length and distance. By using this preprocessing, a new program achieves a little higher compression ratio than that of existing DNA-oriented compression algorithms. We also describe new compression algorithm for protein sequences.

Algorithms↗

PubMed2006

Design and implementation of a library-based information service in molecular biology and genetics at the University of Pittsburgh.

SETTING: In summer 2002, the Health Sciences Library System (HSLS) at the University of Pittsburgh initiated an information service in molecular biology and genetics to assist researchers with identifying and utilizing bioinformatics tools. PROGRAM COMPONENTS: This novel information service comprises hands-on training workshops and consultation on the use of bioinformatics tools. The HSLS also provides an electronic portal and networked access to public and commercial molecular biology databases and software packages. EVALUATION MECHANISMS: Researcher feedback gathered during the first three years of workshops and individual consultation indicate that the information service is meeting user needs. NEXT STEPS/FUTURE DIRECTIONS: The service's workshop offerings will expand to include emerging bioinformatics topics. A frequently asked questions database is also being developed to reuse advice on complex bioinformatics questions.

Computational Biology↗

PubMed1998

TAMBIS--Transparent Access to Multiple Bioinformatics Information Sources.

The TAMBIS project aims to provide transparent access to disparate biological databases and analysis tools, enabling users to utilize a wide range of resources with the minimum of effort. A prototype system has been developed that includes a knowledge base of biological terminology (the biological Concept Model), a model of the underlying data sources (the Source Model) and a 'knowledge-driven' user interface. Biological concepts are captured in the knowledge base using a description logic called GRAIL. The Concept Model provides the user with the concepts necessary to construct a wide range of multiple-source queries, and the user interface provides a flexible means of constructing and manipulating those queries. The Source Model provides a description of the underlying sources and mappings between terms used in the sources and terms in the biological Concept Model. The Concept Model and Source Model provide a level of indirection that shields the user from source details, providing a high level of source transparency. Source independent, declarative queries formed from terms in the Concept Model are transformed into a set of source dependent, executable procedures. Query formulation, translation and execution is demonstrated using a working example.

Artificial Intelligence↗

PubMed2005

Expansion of the BioCyc collection of pathway/genome databases to 160 genomes.

The BioCyc database collection is a set of 160 pathway/genome databases (PGDBs) for most eukaryotic and prokaryotic species whose genomes have been completely sequenced to date. Each PGDB in the BioCyc collection describes the genome and predicted metabolic network of a single organism, inferred from the MetaCyc database, which is a reference source on metabolic pathways from multiple organisms. In addition, each bacterial PGDB includes predicted operons for the corresponding species. The BioCyc collection provides a unique resource for computational systems biology, namely global and comparative analyses of genomes and metabolic networks, and a supplement to the BioCyc resource of curated PGDBs. The Omics viewer available through the BioCyc website allows scientists to visualize combinations of gene expression, proteomics and metabolomics data on the metabolic maps of these organisms. This paper discusses the computational methodology by which the BioCyc collection has been expanded, and presents an aggregate analysis of the collection that includes the range of number of pathways present in these organisms, and the most frequently observed pathways. We seek scientists to adopt and curate individual PGDBs within the BioCyc collection. Only by harnessing the expertise of many scientists we can hope to produce biological databases, which accurately reflect the depth and breadth of knowledge that the biomedical research community is producing.

Animals↗

PubMed2000

An infrastructure for comparative genomics to functionally characterize genes and proteins.

Current genome projects are resulting in a flood of sequence data. The interpretation of these sequences is lagging, and optimized data analysis strategies need to be developed. Much can be learned from comparing different genomes, as genomes of distant organisms may still encode proteins with high sequence similarity. The order of genes (co linearity) in genomes may also be conserved to some extend. We have employed both these observations to create a multi-functional, computational analysis system (genomeSCOUT) which allows for rapid identification and functional characterization of genes and proteins through genome comparison. With a number of independent algorithms, information about different levels of protein homology (concerning e.g. paralogs, orthologs and clusters of orthologous groups, COGs) and gene order is collected and stored in several value added databases. These databases are then used for interactive comparison of genomes and subsequent analysis. The application is based on the well established data integration system SRS. This ensures (1) fast handling of large genomic data sets, (2) straightforward access to a multitude of biological databases, (3) unique linking functions between these databases, (4) highly efficient collection of information on genes and proteins, and 5. fully integrated and user friendly graphical representations of search results. This application can be used for projects as diverse as the correct annotation of genomes, the optimization of (micro) organisms for industrial production, or the identification of drug targets.

Computational Biology↗

PubMedDate not supplied

The Biological Macromolecule Crystallization Database and NASA Protein Crystal Growth Archive.

The NIST/NASA/CARB Biological Macromolecule Crystallization Database (BMCD), NIST Standard Reference Database 21, contains crystal data and crystallization conditions for biological macromolecules. The database entries include data abstracted from published crystallographic reports. Each entry consists of information describing the biological macromolecule crystallized and crystal data and the crystallization conditions for each crystal form. The BMCD serves as the NASA Protein Crystal Growth Archive in that it contains protocols and results of crystallization experiments undertaken in microgravity (space). These database entries report the results, whether successful or not, from NASA-sponsored protein crystal growth experiments in microgravity and from microgravity crystallization studies sponsored by other international organizations. The BMCD was designed as a tool to assist x-ray crystallographers in the development of protocols to crystallize biological macromolecules, those that have previously been crystallized, and those that have not been crystallized.

Crystallization↗

PubMed1999

An analysis of the Protein Data Bank in search of temporal and global trends.

MOTIVATION: Biological databases, with their rapidly expanding contents, are indispensable tools in the quest to understand more about biological function. However, a serious user of a database that comprises a large collection of data, collected over a long period, will likely be struck by the inconsistency in reporting individual items of data. This paper takes a critical look at the Protein Data Bank (PDB) to explore the seriousness of the problem in one particular data set and to explore the implications to those actively engaged in comparative analysis of these data. RESULTS: Averaged over the complete corpus, the stereochemical quality of atomic models has, in the past few years, moved towards ideal values. At the same time, there are inconsistencies in how data are reported. Water content is not reported consistently and the percent of data collected when reporting the high-resolution shell varies, detracting from the value of resolution as a yardstick for assessing the quality of a structure. A more detailed analysis of these inconsistencies is hampered by the lack of machine-readable experimental data. To the user of macromolecular structure data, this suggests that structural details beyond the standard quality measures of resolution and R value should be considered when using coordinate sets for further derivation or in inferring biological function. To the curators of the PDB, this suggests the need to capture more of the experimental data associated with the experiment in a way that permits straightforward parsing.

Computational Biology↗

PubMed2006

An object-oriented programming system for the integration of internet-based bioinformatics resources.

The Internet consists of a vast inhomogeneous reservoir of data. Developing software that can integrate a wide variety of different data sources is a major challenge that must be addressed for the realisation of the full potential of the Internet as a scientific research tool. This article presents a semi-automated object-oriented programming system for integrating web-based resources. We demonstrate that the current Internet standards (HTML, CGI [common gateway interface], Java, etc.) can be exploited to develop a data retrieval system that scans existing web interfaces and then uses a set of rules to generate new Java code that can automatically retrieve data from the Web. The validity of the software has been demonstrated by testing it on several biological databases. We also examine the current limitations of the Internet and discuss the need for the development of universal standards for web-based data.

Computational Biology↗

PubMed2005

Distributed modules for text annotation and IE applied to the biomedical domain.

Biological databases contain facts from scientific literature that have been curated by hand to ensure high quality. Curation is time-consuming and can be supported by information extraction methods. We present a server software infrastructure which allows to easily plug in modules to identify biologically interesting pieces of text to be then presented in a web interface to the curator. There are modules which identify UniProt, UMLS and GO terminology, gene and protein names, mutations and protein-protein interactions. UniProt, UMLS and GO concepts are automatically linked to the original source. The module for mutations is based on syntax patterns and the one for protein-protein interactions relies on chunk parsing. All modules work as separate servers possibly distributed on different machines and can be combined into processing pipelines as necessary. Communication is based on XML annotated text streams, each server processing the XML elements it is designed for, and possibly adding more information in the form of XML annotation. The server and the underlying software are available to the public.

Abstracting and Indexing↗

PubMed2000

Expression databases--resources for pharmacogenomic R&D.

This review aims to outline the primary biological databases that are being generated to understand fundamental biology, identify new drug targets, and to look at compound profiling in a new light. We will give a brief overview of four of the main areas being studied in molecular biology: genomics, pharmacogenomics, pharmacogenetics and proteomics. Looking initially at each data set and some of its potential applications, we will go on to describe some of the potentially enormous advantages gained by fully integrating these data sets.

Animals↗

PubMed1995

Development, databases and the Internet.

There is now a rapidly expanding population of interlinked developmental biology databases on the World Wide Web that can be readily accessed from a desk-top PC using programs such as Netscape or Mosaic. These databases cover popular organisms (Arabidopsis, Caenorhabditis, Drosophila, zebrafish, mouse, etc.) and include gene and protein sequences, lists of mutants, information on resources and techniques, and teaching aids. More complex are databases relating domains of gene expression to embryonic anatomy and these range from existing text-based systems for specific organs such as kidney, to a massive project under development, that will cover gene expression during the whole of mouse embryogenesis. In this brief article, we review selected examples of databases currently available, look forward to what will be available soon, and explain how to gain access to the World Wide Web.

Animals↗

PubMed2005

Biomolecular interaction network database.

This software review looks at the utility of the Biomolecular Interaction Network Database (BIND) as a web database. BIND offers methods common to related biology databases and specialisations for its protein interaction data. Searching and browsing this database is easy and well integrated with the underlying data and the needs of scientists. Interaction networks are visualised with software that offers many useful options. The innovative ontoglyphs are used throughout to provide visual cues to protein functions, localisation and other aspects one needs to know for this data set. One can expect to get useful results that may be well integrated with one's research needs.

Binding Sites↗