A Molecular Biology Database Digest

Computational Biology or Bioinformatics has been defined as the application of mathematical and Computer Science methods to solving problems in Molecular Biology that require large scale data, computation, and analysis [18]. As expected, Molecular Biology databases play an essential role in Computational Biology research and development. This paper introduces into current Molecular Biology databases, stressing data modeling, data acquisition, data retrieval, and the integration of Molecular Biology data from different sources. This paper is primarily intended for an audience of computer scientists with a limited background in Biology

Querying the public databases for sequences using complex keywords contained in the feature lines

BACKGROUND: High throughput technologies often require the retrieval of large data sets of sequences. Retrieval of EMBL or GenBank entries using keywords is easy using tools such as ACNUC, Entrez or SRS, but has some limitations, in particular when querying with complex keywords. RESULTS: We show that Entrez has severe limitations with respect to retrieving subsequences. SRS works well with simple keywords but not with keywords composed of several terms, and has problems with complex queries. ACNUC works well, but does not allow precise queries in the Feature qualifiers. We developed specific Perl scripts to precisely retrieve subsequences as defined by complex descriptors in the Features qualifiers of the EMBL entries. We improved parts of the bioPerl library to allow parsing of large data files, and we embedded these scripts in a user friendly interface (OS independent) for easy use. CONCLUSION: Although not as fast as the public tools that use prebuilt indexes, parsing the complete entries using a script is often necessary in order to retrieve the exact data searched for. Embedding in a user friendly interface allows biologists to use the scripts, which can easily be modified, if necessary, by bioinformaticians for unforeseen needs

SeqHound: biological sequence and structure database as a platform for bioinformatics research

BACKGROUND: SeqHound has been developed as an integrated biological sequence, taxonomy, annotation and 3-D structure database system. It provides a high-performance server platform for bioinformatics research in a locally-hosted environment. RESULTS: SeqHound is based on the National Center for Biotechnology Information data model and programming tools. It offers daily updated contents of all Entrez sequence databases in addition to 3-D structural data and information about sequence redundancies, sequence neighbours, taxonomy, complete genomes, functional annotation including Gene Ontology terms and literature links to PubMed. SeqHound is accessible via a web server through a Perl, C or C++ remote API or an optimized local API. It provides functionality necessary to retrieve specialized subsets of sequences, structures and structural domains. Sequences may be retrieved in FASTA, GenBank, ASN.1 and XML formats. Structures are available in ASN.1, XML and PDB formats. Emphasis has been placed on complete genomes, taxonomy, domain and functional annotation as well as 3-D structural functionality in the API, while fielded text indexing functionality remains under development. SeqHound also offers a streamlined WWW interface for simple web-user queries. CONCLUSIONS: The system has proven useful in several published bioinformatics projects such as the BIND database and offers a cost-effective infrastructure for research. SeqHound will continue to develop and be provided as a service of the Blueprint Initiative at the Samuel Lunenfeld Research Institute. The source code and examples are available under the terms of the GNU public license at the Sourceforge site http://sourceforge.net/projects/slritools/ in the SLRI Toolkit

Evidence for RNA recombination between distinct isolates of Pepino mosaic virus.

Genetic recombination plays an important role in the evolution of virus genomes. In this study we analyzed publicly available genomic sequences of Pepino mosaic virus (PepMV) for recombination events using several bioinformatics tools. The genome-wide analyses not only confirm the presence of previously found recombination events in PepMV but also provide the first evidence for double recombinant origin of the US2 isolate

Web-based Named Entity Recognition and Data Integration to Accelerate Molecular Biology Research

Finding information about a biological entity is a step tightly bound to molecular biology research. Despite ongoing efforts, this task is both tedious and time consuming, and tends to become Sisyphean as the number of entities increases. Our aim is to assist researchers by providing them with summary information about biological entities while they are browsing the web, as well as with simplified programmatic access to biological data. To materialise this aim we employ emerging web technologies offering novel web-browsing experiences and new ways of software communication Reflect is a tool that couples biological named entity recognition with informative summaries, and can be applied to any web page, during web browsing. Invoked either via its browser extensions or via its web page, Reflect highlights gene, protein and chemical molecule names in a web page, and, dynamically, attaches to them summary information. The latter provides an overview of what is known about the entity, such as a description, the domain composition, the 3D structure and links to more detailed resources. The annotation process occurs via easy-to-use interfaces. The fast performance allows for Reflect to be an interactive companion for scientific readers/researchers, while they are surfing the internet. OnTheFly is a web-based application that not only extends Reflect functionality to Microsoft Word, Microsoft Excel, PDF and plain text format files, but also supports the extraction of networks of known and predicted interactions about the entities recognised in a document. A combination of Reflect and OnTheFly offers a data annotation solution for documents used by life science researchers throughout their work. EasySRS is a set of remote methods that expose the functionality of the Sequence Retrieval System (SRS), a data integration platform used in providing access to life science information including genetic, protein, expression and pathway data. EasySRS supports simultaneous queries to all of the integrated resources. Accessed from a single point, via the web, and based on a simple, common query format, EasySRS facilitates the task of biological data collection and annotation. EasySRS has been employed to enrich the entries of a Plant Defence Mechanism database. UniprotProfiler is a prototype application that employs EasySRS to generate graphs of knowledge based on database record cross-references. These graphs are converted into 3D diagrams of interconnected data. The 3D diagram generation occurs via Systems Biology visualisation tools that employ intuitive graphs to replace long result lists and facilitate hypothesis generation and knowledge discovery

Retrieval and interpretation of textual geolocalized information based on semantic geolocalized relations

This paper describes a method for geolocalized information retrieval from natural language text and its interpretation by assigning them geographic coordinates. A proof-of-concept implementation is discussed, along with geolocalized dictionary stored in PostGIS/PostgreSQL spatial relational database. Discussed research focuses on strongly inflectional Polish language, hence additional complexity had to be taken into account. Presented method has been evaluated with the use of diverse metrics

BNDB – The Biochemical Network Database

<p>Abstract</p> <p>Background</p> <p>Technological advances in high-throughput techniques and efficient data acquisition methods have resulted in a massive amount of life science data. The data is stored in numerous databases that have been established over the last decades and are essential resources for scientists nowadays. However, the diversity of the databases and the underlying data models make it difficult to combine this information for solving complex problems in systems biology. Currently, researchers typically have to browse several, often highly focused, databases to obtain the required information. Hence, there is a pressing need for more efficient systems for integrating, analyzing, and interpreting these data. The standardization and virtual consolidation of the databases is a major challenge resulting in a unified access to a variety of data sources.</p> <p>Description</p> <p>We present the Biochemical Network Database (BNDB), a powerful relational database platform, allowing a complete semantic integration of an extensive collection of external databases. BNDB is built upon a comprehensive and extensible object model called BioCore, which is powerful enough to model most known biochemical processes and at the same time easily extensible to be adapted to new biological concepts. Besides a web interface for the search and curation of the data, a Java-based viewer (BiNA) provides a powerful platform-independent visualization and navigation of the data. BiNA uses sophisticated graph layout algorithms for an interactive visualization and navigation of BNDB.</p> <p>Conclusion</p> <p>BNDB allows a simple, unified access to a variety of external data sources. Its tight integration with the biochemical network library BN++ offers the possibility for import, integration, analysis, and visualization of the data. BNDB is freely accessible at <url>http://www.bndb.org</url>.</p

GENDB : a second generation genome annotation system

Meyer F. GENDB : a second generation genome annotation system. Bielefeld (Germany): Bielefeld University; 2001.The advent of new high throughput technologies opens the road towards a new era of genome analysis. Data from high throughput sequencers, chip based RNA expression analysis and proteome analysis systems create the need for software systems to support new kinds of analysis and data. At the same time the focus of molecular research shifted from the analysis of single genes to the analysis of whole genomes, multiple high throughput sources of data are routinely used. Yet there is a shortage of software systems that help store, integrate and analyse the wealth of information now available. We describe the development of a new genome annotation system (GENDB) based on a relational database system and object oriented technology that helps with the analysis of this data. GENDB significantly reduces the storage and compute overhead of existing systems, while offering more flexibility. The ability to integrate new kinds of data and new methods of analysis is one of the primary design targets for GENDB. The GENDB system has been succesfully used in a number of genome projects

Arena3D: visualization of biological networks in 3D

<p>Abstract</p> <p>Background</p> <p>Complexity is a key problem when visualizing biological networks; as the number of entities increases, most graphical views become incomprehensible. Our goal is to enable many thousands of entities to be visualized meaningfully and with high performance.</p> <p>Results</p> <p>We present a new visualization tool, Arena3D, which introduces a new concept of staggered layers in 3D space. Related data – such as proteins, chemicals, or pathways – can be grouped onto separate layers and arranged via layout algorithms, such as Fruchterman-Reingold, distance geometry, and a novel hierarchical layout. Data on a layer can be clustered via k-means, affinity propagation, Markov clustering, neighbor joining, tree clustering, or UPGMA ('unweighted pair-group method with arithmetic mean'). A simple input format defines the name and URL for each node, and defines connections or similarity scores between pairs of nodes. The use of Arena3D is illustrated with datasets related to Huntington's disease.</p> <p>Conclusion</p> <p>Arena3D is a user friendly visualization tool that is able to visualize biological or any other network in 3D space. It is free for academic use and runs on any platform. It can be downloaded or lunched directly from <url>http://arena3d.org</url>. Java3D library and Java 1.5 need to be pre-installed for the software to run.</p