Analysis and comparison of metabolic pathway databases

Enormous amounts of data result from genome sequencing projects and new experimental methods. Within this tremendous amount of genomic data 30-40 per cent of the genes being identified in an organism remain unknown in terms of their biological function. As a consequence of this lack of information the overall schema of all the biological functions occurring in a specific organism cannot be properly represented. To understand the functional properties of the genomic data more experimental data must be collected. A pathway database is an effort to handle the current knowledge of biochemical pathways and in addition can be used for interpretation of sequence data. Some of the existing pathway databases can be interpreted as detailed functional annotations of genomes because they are tightly integrated with genomic information. However, experimental data are often lacking in these databases. This paper summarises a list of pathway databases and some of their corresponding biological databases, and also focuses on information about the content and the structure of these databases, the organisation of the data and the reliability of stored information from a biological point of view. Moreover, information about the representation of the pathway data and tools to work with the data are given. Advantages and disadvantages of the analysed databases are pointed out, and an overview to biological scientists on how to use these pathway databases is given.     

The homeodomain resource: a prototype database for a large protein family

The Homeodomain Resource is an annotated collection of non-redundant protein sequences, three-dimensional structures and genomic information for the homeodomain protein family. Release 2.0 contains 765 full-length homeodomain-containing sequences, 29 experimentally derived structures and 116 homeobox loci implicated in human genetic disorders. Entries are fully hyperlinked to facilitate easy retrieval of the original records from source databases. A simple search engine with a graphical user interface is provided to query the component databases and assemble customized data sets. A new feature for this release is the addition of more automated methods for database searching, maintenance and implementation of efficient data management. The Homeodomain Resource is freely available through the WWW at http://genome.nhgri.nih.gov/homeodomain     

Novel gene and gene model detection using a whole genome open reading frame analysis in proteomics

Background  

Defining the location of genes and the precise nature of gene products remains a fundamental challenge in genome annotation. Interrogating tandem mass spectrometry data using genomic sequence provides an unbiased method to identify novel translation products. A six-frame translation of the entire human genome was used as the query database to search for novel blood proteins in the data from the Human Proteome Organization Plasma Proteome Project. Because this target database is orders of magnitude larger than the databases traditionally employed in tandem mass spectra analysis, careful attention to significance testing is required. Confidence of identification is assessed using our previously described Poisson statistic, which estimates the significance of multi-peptide identifications incorporating the length of the matching sequence, number of spectra searched and size of the target sequence database.     

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.     

A bioinformatics workflow for variant peptide detection in shotgun proteomics

Shotgun proteomics data analysis usually relies on database search. However, commonly used protein sequence databases do not contain information on protein variants and thus prevent variant peptides and proteins from been identified. Including known coding variations into protein sequence databases could help alleviate this problem. Based on our recently published human Cancer Proteome Variation Database, we have created a protein sequence database that comprehensively annotates thousands of cancer-related coding variants collected in the Cancer Proteome Variation Database as well as noncancer-specific ones from the Single Nucleotide Polymorphism Database (dbSNP). Using this database, we then developed a data analysis workflow for variant peptide identification in shotgun proteomics. The high risk of false positive variant identifications was addressed by a modified false discovery rate estimation method. Analysis of colorectal cancer cell lines SW480, RKO, and HCT-116 revealed a total of 81 peptides that contain either noncancer-specific or cancer-related variations. Twenty-three out of 26 variants randomly selected from the 81 were confirmed by genomic sequencing. We further applied the workflow on data sets from three individual colorectal tumor specimens. A total of 204 distinct variant peptides were detected, and five carried known cancer-related mutations. Each individual showed a specific pattern of cancer-related mutations, suggesting potential use of this type of information for personalized medicine. Compatibility of the workflow has been tested with four popular database search engines including Sequest, Mascot, X!Tandem, and MyriMatch. In summary, we have developed a workflow that effectively uses existing genomic data to enable variant peptide detection in proteomics.     

Fantastic databases and where to find them: Web applications for researchers in a rush

Public databases are essential to the development of multi-omics resources. The amount of data created by biological technologies needs a systematic and organized form of storage, that can quickly be accessed, and managed. This is the objective of a biological database. Here, we present an overview of human databases with web applications. The databases and tools allow the search of biological sequences, genes and genomes, gene expression patterns, epigenetic variation, protein-protein interactions, variant frequency, regulatory elements, and comparative analysis between human and model organisms. Our goal is to provide an opportunity for exploring large datasets and analyzing the data for users with little or no programming skills. Public user-friendly web-based databases facilitate data mining and the search for information applicable to healthcare professionals. Besides, biological databases are essential to improve biomedical search sensitivity and efficiency and merge multiple datasets needed to share data and build global initiatives for the diagnosis, prognosis, and discovery of new treatments for genetic diseases. To show the databases at work, we present a a case study using ACE2 as example of a gene to be investigated. The analysis and the complete list of databases is available in the following website <https://kur1sutaru.github.io/fantastic_databases_and_where_to_find_them/>.     

FunRich: An open access standalone functional enrichment and interaction network analysis tool

As high‐throughput techniques including proteomics become more accessible to individual laboratories, there is an urgent need for a user‐friendly bioinformatics analysis system. Here, we describe FunRich, an open access, standalone functional enrichment and network analysis tool. FunRich is designed to be used by biologists with minimal or no support from computational and database experts. Using FunRich, users can perform functional enrichment analysis on background databases that are integrated from heterogeneous genomic and proteomic resources (>1.5 million annotations). Besides default human specific FunRich database, users can download data from the UniProt database, which currently supports 20 different taxonomies against which enrichment analysis can be performed. Moreover, the users can build their own custom databases and perform the enrichment analysis irrespective of organism. In addition to proteomics datasets, the custom database allows for the tool to be used for genomics, lipidomics and metabolomics datasets. Thus, FunRich allows for complete database customization and thereby permits for the tool to be exploited as a skeleton for enrichment analysis irrespective of the data type or organism used. FunRich ( http://www.funrich.org ) is user‐friendly and provides graphical representation (Venn, pie charts, bar graphs, column, heatmap and doughnuts) of the data with customizable font, scale and color (publication quality).     

Development of bioinformatics resources for display and analysis of copy number and other structural variants in the human genome

The discovery of an abundance of copy number variants (CNVs; gains and losses of DNA sequences >1 kb) and other structural variants in the human genome is influencing the way research and diagnostic analyses are being designed and interpreted. As such, comprehensive databases with the most relevant information will be critical to fully understand the results and have impact in a diverse range of disciplines ranging from molecular biology to clinical genetics. Here, we describe the development of bioinformatics resources to facilitate these studies. The Database of Genomic Variants (http://projects.tcag.ca/variation/) is a comprehensive catalogue of structural variation in the human genome. The database currently contains 1,267 regions reported to contain copy number variation or inversions in apparently healthy human cases. We describe the current contents of the database and how it can serve as a resource for interpretation of array comparative genomic hybridization (array CGH) and other DNA copy imbalance data. We also present the structure of the database, which was built using a new data modeling methodology termed Cross-Referenced Tables (XRT). This is a generic and easy-to-use platform, which is strong in handling textual data and complex relationships. Web-based presentation tools have been built allowing publication of XRT data to the web immediately along with rapid sharing of files with other databases and genome browsers. We also describe a novel tool named eFISH (electronic fluorescence in situ hybridization) (http://projects.tcag.ca/efish/), a BLAST-based program that was developed to facilitate the choice of appropriate clones for FISH and CGH experiments, as well as interpretation of results in which genomic DNA probes are used in hybridization-based experiments.     

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.     

RiDs db: Repeats in diseases database

The non-coding fraction of the human genome, which is approximately 98%, is mainly constituted by repeats. Transpositions, expansions and deletions of these repeat elements contribute to a number of diseases. None of the available databases consolidates information on both tandem and interspersed repeats with the flexibility of FASTA based homology search with reference to disease genes. Repeats in diseases database (RiDs db) is a web accessible relational database, which aids analysis of repeats associated with Mendelian disorders. It is a repository of disease genes, which can be searched by FASTA program or by limitedor free- text keywords. Unlike other databases, RiDs db contains the sequences of these genes with access to corresponding information on both interspersed and tandem repeats contained within them, on a unified platform. Comparative analysis of novel or patient sequences with the reference sequences in RiDs db using FASTA search will indicate change in structure of repeats, if any, with a particular disorder. This database also provides links to orthologs in model organisms such as zebrafish, mouse and Drosophila. AVAILABILITY: The database is available for free at http://115.111.90.196/ridsdb/index.php.     

BioMolQuest: integrated database-based retrieval of protein structural and functional information

MOTIVATION: Information about a particular protein or protein family is usually distributed among multiple databases and often in more than one entry in each database. Retrieval and organization of this information can be a laborious task. This task is complicated even further by the existence of alternative terms for the same concept. RESULTS: The PDB, SWISS-PROT, ENZYME, and CATH databases have been imported into a combined relational database, BIOMOLQUEST: A powerful search engine has been built using this database as a back end. The search engine achieves significant improvements in query performance by automatically utilizing cross-references between the legacy databases. The results of the queries are presented in an organized, hierarchical way.     

A new database on polymorphic retroelements in human genome (PRED)

Comparison of primate genomes sequences has confirmed the evidence that substantial part of intra- and interspecies differences is provided by retroelements. Human genome contains thousands of polymorphic retroelement copies considered to be perspective molecular genetic markers of new generation. However utilization of polymorphic retroelements as molecular genetic markers is limited due to lack of systematic data on their number, genomic context and distribution among human populations. We have created first bilingual (Russian/English) internet-resource devoted to known polymorphic retroelements discovered in human genome by our group as well as by other researchers worldwide. The database contains information about each retroelement copy location, position relative to known and predicted genes, frequency of alleles in human populations and others. Our internet portal allows to perform a search in database using multiple search conditions and available on http://labcfg.ibch.ru/home.html. The database provides an opportunity to investigate distribution of polymorphic retroelements in human genome and to design new genetic markers for various population and medical studies.     

A bioinformatics approach to investigating developmental pathways in the kidney and other tissues.

Over the past few years, large amounts of data linking gene-expression (GE) patterns and other genetic data with the development of the mouse kidney have been published, and the next task will be to integrate these data with the molecular networks responsible for the emergence of the kidney phenotype. This paper discusses how a start to this task can be made by using the kidney database and its associated search tools, and shows how the data generated by such an approach can be used as a guide to future experimentation. Many of the events taking place as the kidney develops do, of course, also take place in other tissues and organisms and it will soon be possible to incorporate relevant information from these systems into analyses of kidney data as well as the new information from microarray technology. The key to success here will be the ability to access over the internet data from the textual and graphical databases for the mouse and other organisms now being established. In order to do this, informatic tools will be needed that will allow a user working with one database to query another. This paper also considers both the types of tools that will be necessary and the databases on which they will operate.     

Protein identification in DNA databases by peptide mass fingerprinting.

Proteins can be identified using a set of peptide fragment weights produced by a specific digestion to search a protein database in which sequences have been replaced by fragment weights calculated for various cleavage methods. We present a method using multidimensional searches that greatly increases the confidence level for identification, allowing DNA sequence databases to be examined. This method provides a link between 2-dimensional gel electrophoresis protein databases and genome sequencing projects. Moreover, the increased confidence level allows unknown proteins to be matched to expressed sequence tags, potentially eliminating the need to obtain sequence information for cloning. Database searching from a mass profile is offered as a free service by an automatic server at the ETH, Zürich. For information, send an electronic message to the address cbrg/inf.ethz.ch with the line: help mass search, or help all.     

JXP4BIGI: a generalized, Java XML-based approach for biological information gathering and integration

MOTIVATION: In the post-genomic era, biologists interested in systems biology often need to import data from public databases and construct their own system-specific or subject-oriented databases to support their complex analysis and knowledge discovery. To facilitate the analysis and data processing, customized and centralized databases are often created by extracting and integrating heterogeneous data retrieved from public databases. A generalized methodology for accessing, extracting, transforming and integrating the heterogeneous data is needed. RESULTS: This paper presents a new data integration approach named JXP4BIGI (Java XML Page for Biological Information Gathering and Integration). The approach provides a system-independent framework, which generalizes and streamlines the steps of accessing, extracting, transforming and integrating the data retrieved from heterogeneous data sources to build a customized data warehouse. It allows the data integrator of a biological database to define the desired bio-entities in XML templates (or Java XML pages), and use embedded extended SQL statements to extract structured, semi-structured and unstructured data from public databases. By running the templates in the JXP4BIGI framework and using a number of generalized wrappers, the required data from public databases can be efficiently extracted and integrated to construct the bio-entities in the XML format without having to hard-code the extraction logics for different data sources. The constructed XML bio-entities can then be imported into either a relational database system or a native XML database system to build a biological data warehouse. AVAILABILITY: JXP4BIGI has been integrated and tested in conjunction with the IKBAR system (http://www.ikbar.org/) in two integration efforts to collect and integrate data for about 200 human genes related to cell death from HUGO, Ensembl, and SWISS-PROT (Bairoch and Apweiler, 2000), and about 700 Drosophila genes from FlyBase (FlyBase Consortium, 2002). The integrated data has been used in comparative genomic analysis of x-ray induced cell death. Also, as explained later, JXP4BIGI is a middleware and framework to be integrated with biological database applications, and cannot run as a stand-alone software for end users. For demonstration purposes, a demonstration version is accessible at (http://www.ikbar.org/jxp4bigi/demo.html).     

MitBASE : a comprehensive and integrated mitochondrial DNA database. The present status

MitBASE is an integrated and comprehensive database of mitochondrial DNA data which collects, under a single interface, databases for Plant, Vertebrate, Invertebrate, Human, Protist and Fungal mtDNA and a Pilot database on nuclear genes involved in mitochondrial biogenesis in Saccharomyces cerevisiae. MitBASE reports all available information from different organisms and from intraspecies variants and mutants. Data have been drawn from the primary databases and from the literature; value adding information has been structured, e.g., editing information on protist mtDNA genomes, pathological information for human mtDNA variants, etc. The different databases, some of which are structured using commercial packages (Microsoft Access, File Maker Pro) while others use a flat-file format, have been integrated under ORACLE. Ad hoc retrieval systems have been devised for some of the above listed databases keeping into account their peculiarities. The database is resident at the EBI and is available at the following site: http://www3.ebi.ac.uk/Research/Mitbase/mitbas e.pl. The impact of this project is intended for both basic and applied research. The study of mitochondrial genetic diseases and mitochondrial DNA intraspecies diversity are key topics in several biotechnological fields. The database has been funded within the EU Biotechnology programme.