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PubMed2000

Ontology-based knowledge representation for bioinformatics.

Much of biology works by applying prior knowledge ('what is known') to an unknown entity, rather than the application of a set of axioms that will elicit knowledge. In addition, the complex biological data stored in bioinformatics databases often require the addition of knowledge to specify and constrain the values held in that database. One way of capturing knowledge within bioinformatics applications and databases is the use of ontologies. An ontology is the concrete form of a conceptualisation of a community's knowledge of a domain. This paper aims to introduce the reader to the use of ontologies within bioinformatics. A description of the type of knowledge held in an ontology will be given.The paper will be illustrated throughout with examples taken from bioinformatics and molecular biology, and a survey of current biological ontologies will be presented. From this it will be seen that the use to which the ontology is put largely determines the content of the ontology. Finally, the paper will describe the process of building an ontology, introducing the reader to the techniques and methods currently in use and the open research questions in ontology development.

Artificial Intelligence↗
PubMed2003

KISS for STRAP: user extensions for a protein alignment editor.

SUMMARY: The Structural Alignment Program STRAP is a comfortable comprehensive editor and analyzing tool for protein alignments. A wide range of functions related to protein sequences and protein structures are accessible with an intuitive graphical interface. Recent features include mapping of mutations and polymorphisms onto structures and production of high quality figures for publication. Here we address the general problem of multi-purpose program packages to keep up with the rapid development of bioinformatical methods and the demand for specific program functions. STRAP was remade implementing a novel design which aims at Keeping Interfaces in STRAP Simple (KISS). KISS renders STRAP extendable to bio-scientists as well as to bio-informaticians. Scientists with basic computer skills are capable of implementing statistical methods or embedding existing bioinformatical tools in STRAP themselves. For bio-informaticians STRAP may serve as an environment for rapid prototyping and testing of complex algorithms such as automatic alignment algorithms or phylogenetic methods. Further, STRAP can be applied as an interactive web applet to present data related to a particular protein family and as a teaching tool. REQUIREMENTS: JAVA-1.4 or higher. AVAILABILITY: http://www.charite.de/bioinf/strap/

Computer Graphics↗
PubMed2026

ReGAIN: a bioinformatics platform for assessing probabilistic co-occurrence between resistance genes in bacterial pathogens.

MOTIVATION: Multidrug-resistant bacterial pathogens continue to rise globally, yet scalable methods are needed to infer how resistance determinants co-occur across pathogen populations and to quantify conditional dependencies underlying co-occurrence and shared genetic context. RESULTS: We present ReGAIN (Resistance Gene Association and Inference Network), an open-source platform that applies Bayesian network structure learning to infer probabilistic, conditional dependency relationships among antibiotic resistance, heavy metal tolerance, stress response, and virulence determinants in bacteria. In contrast to pairwise co-occurrence analyses, ReGAIN reports conditional probabilities, relative risks, and absolute risk differences with confidence intervals to prioritize candidate relationships for downstream prioritization. Applied across ESKAPEE pathogens, ReGAIN recapitulated established resistance gene relationships and identified additional candidate patterns consistent with co-selection and shared genetic context. Together, these results support scalable, reproducible population-wide analysis of resistance networks for surveillance, comparative genomics and epidemiology. AVAILABILITY: ReGAIN analyses are performed using Python v3.11.5 and R v4.4.1 and is available as open-source software through Bioconda at {https://anaconda.org/bioconda/regain-cli}. Source code and documentation can be found at {https://github.com/ERBringHorvath/regain_CLI}. All genomes used in this publication were downloaded from the National Center for Biotechnology Information database. Large supplementary tables and results data from the ESKAPEE pathogen example network analyses can be downloaded from https://figshare.com/articles/dataset/ReGAIN_command_line_software_and_supplemental_figures_/28959431.

Computational Biology↗
PubMed2003

The apoptosis database.

The apoptosis database is a public resource for researchers and students interested in the molecular biology of apoptosis. The resource provides functional annotation, literature references, diagrams/images, and alternative nomenclatures on a set of proteins having 'apoptotic domains'. These are the distinctive domains that are often, if not exclusively, found in proteins involved in apoptosis. The initial choice of proteins to be included is defined by apoptosis experts and bioinformatics tools. Users can browse through the web accessible lists of domains, proteins containing these domains and their associated homologs. The database can also be searched by sequence homology using basic local alignment search tool, text word matches of the annotation, and identifiers for specific records. The resource is available at http://www.apoptosis-db.org and is updated on a regular basis.

Animals↗
PubMed2002

CHOMPER: a bioinformatic tool for rapid validation of tandem mass spectrometry search results associated with high-throughput proteomic strategies.

Current efforts aimed at developing high-throughput proteomics focus on increasing the speed of protein identification. Although improvements in sample separation, enrichment, automated handling, mass spectrometric analysis, as well as data reduction and database interrogation strategies have done much to increase the quality, quantity and efficiency of data collection, significant bottlenecks still exist. Various separation techniques have been coupled with tandem mass spectrometric (MS/MS) approaches to allow a quicker analysis of complex mixtures of proteins, especially where a high number of unambiguous protein identifications are the exception, rather than the rule. MS/MS is required to provide structural / amino acid sequence information on a peptide and thus allow protein identity to be inferred from individual peptides. Currently these spectra need to be manually validated because: (a) the potential of false positive matches i.e., protein not in database, and (b) observed fragmentation trends may not be incorporated into current MS/MS search algorithms. This validation represents a significant bottleneck associated with high-throughput proteomic strategies. We have developed CHOMPER, a software program which reduces the time required to both visualize and confirm MS/MS search results and generate post-analysis reports and protein summary tables. CHOMPER extracts the identification information from SEQUEST MS/MS search result files, reproduces both the peptide and protein identification summaries, provides a more interactive visualization of the MS/MS spectra and facilitates the direct submission of manually validated identifications to a database.

Algorithms↗
PubMed2003

Analysis of gene expression profiles: an application of memetic algorithms to the minimum sum-of-squares clustering problem.

Microarrays have become a key technology in experimental molecular biology since they allow monitoring of gene expression for more than 10,000 genes in parallel producing huge amounts of data. In the exploration of transcriptional regulatory networks, an important task is to cluster gene expression data to identify groups of genes with similar patterns and hence similar function. In this paper, memetic algorithms (MAs)-evolutionary algorithms incorporating local search-are proposed for minimum sum-of-squares clustering (MSSC). In a fitness landscape analysis, it is shown that the MSSC problem has correlation structure exploitable by MAs. The proposed MAs are shown to be superior to multi-start k-means as well as five other clustering algorithms from the bioinformatics literature including hierarchical algorithms and self-organizing maps. Although the fitness values of the different clustering solutions lie close together, it is shown that the solutions differ significantly from each other in terms of cluster memberships which is extremely important for the biological interpretation of the clustering results.

Algorithms↗
PubMed2004

EST-PAGE--managing and analyzing EST data.

UNLABELLED: EST-PAGE provides a bioinformatics solution for expressed sequence tags (EST) data entry, database management, GenBank submission, process control and data retrieval from a unified web interface that can be easily customized and adapted by groups working on diverse EST sequencing projects. AVAILABILITY: The system and source code are available upon request from the authors. SUPPLEMENTARY INFORMATION: http://EST-PAGE.binf.gmu.edu

Database Management Systems↗
PubMed2001

Recent advances in computational genomics.

In the post-genomic era, the new discipline of functional genomics is now facing the challenge of associating a function (as well as estimating its relevance to industrial applications) to about 100,000 microbial, plant or animal genes of known sequence but unknown function. Besides the design of databases, computational methods are increasingly becoming intimately linked with the various experimental approaches. Consequently, bioinformatics is rapidly evolving into independent fields addressing the specific problems of interpreting i) genomic sequences, ii) protein sequences and 3D-structures, as well as iii) transcriptome and macromolecular interaction data. It is thus increasingly difficult for the biologist to choose the computational approaches that perform best in these various areas. This paper attempts to review the most useful developments of the last 2 years.

Computational Biology↗
PubMed2003

Talisman--rapid application development for the grid.

In order to make use of the emerging grid and network services offered by various institutes and mandated by many current research projects, some kind of user accessible client is required. In contrast with attempts to build generic workbenches, Talisman is designed to allow a bioinformatics expert to rapidly build custom applications, immediately visible using standard web technology, for users who wish to concentrate on the biology of their problem rather than the informatics aspects. As a component of the MyGrid project, it is intended to allow access to arbitrary resources, including but not limited to relational, object and flat file data sources, analysis programs and grid based storage, tracking and distributed annotation systems.

Computational Biology↗
PubMedDate not supplied

EMDep: a web-based system for the deposition and validation of high-resolution electron microscopy macromolecular structural information.

This paper describes the design and implementation of a Web-based deposition system, EMDep, for macro-molecular volumes determined by electron microscopy and deposited at the European Bioinformatics Institute (EBI) for inclusion in the Electron Microscopy Data Base (EMDB). EMDep is a flexible and portable system (http://www.ebi.ac.uk/msd-srv/emdep/) that allows for the acceptance and validation of data, by an interactive depositor-driven operation. The system takes full advantage of the knowledge and expertise of the experimenters, rather than relying on the database curators, for the complete and accurate description of the structural experiment and its results.

Algorithms↗
PubMed2003

cDNA2Genome: a tool for mapping and annotating cDNAs.

BACKGROUND: In the last years several high-throughput cDNA sequencing projects have been funded worldwide with the aim of identifying and characterizing the structure of complete novel human transcripts. However some of these cDNAs are error prone due to frameshifts and stop codon errors caused by low sequence quality, or to cloning of truncated inserts, among other reasons. Therefore, accurate CDS prediction from these sequences first require the identification of potentially problematic cDNAs in order to speed up the posterior annotation process. RESULTS: cDNA2Genome is an application for the automatic high-throughput mapping and characterization of cDNAs. It utilizes current annotation data and the most up to date databases, especially in the case of ESTs and mRNAs in conjunction with a vast number of approaches to gene prediction in order to perform a comprehensive assessment of the cDNA exon-intron structure. The final result of cDNA2Genome is an XML file containing all relevant information obtained in the process. This XML output can easily be used for further analysis such us program pipelines, or the integration of results into databases. The web interface to cDNA2Genome also presents this data in HTML, where the annotation is additionally shown in a graphical form. cDNA2Genome has been implemented under the W3H task framework which allows the combination of bioinformatics tools in tailor-made analysis task flows as well as the sequential or parallel computation of many sequences for large-scale analysis. CONCLUSIONS: cDNA2Genome represents a new versatile and easily extensible approach to the automated mapping and annotation of human cDNAs. The underlying approach allows sequential or parallel computation of sequences for high-throughput analysis of cDNAs.

Chromosome Mapping↗
PubMed1997

Database of p53 gene somatic mutations in human tumors and cell lines: updated compilation and future prospects.

In recent years, there has been an exponential increase in the number of p53 mutations identified in human cancers. The p53 mutation database consists of a list of point mutations in thep53 gene of human tumors and cell lines, compiled from the published literature and made available through electronic media. The database is now maintained at the International Agency for Research on Cancer (IARC) and is updated twice a year. The current version contains records on 5091 published mutations and is expected to surpass the 6000 mark in the January 1997 release. The database is available in various formats through the European Bioinformatics Institute (EBI) ftp server at: ftp://ftp.ebi.ac.uk/pub/databases/p53/ or by request from IARC (p53database@iarc.fr) and will be searchable through the SRS system in the near future. This report provides a description of the criteria for inclusion of data and of the current formats, a summary of the relevance ofp53 mutation analysis to clinical and biological questions, and a brief discussion of the prospects for future developments.

Databases, Factual↗
PubMed1998

GeneExpress: a computer system for description, analysis, and recognition of regulatory sequences in eukaryotic genome.

GeneExpress system has been designed to integrate description, analysis, and recognition of eukaryotic regulatory sequences. The system includes 5 basic units: (1) GeneNet contains an object-oriented database for accumulation of data on gene networks and signal transduction pathways and a Java-based viewer that allows an exploration and visualization of the GeneNet information; (2) Transcription Regulation combines the database on transcription regulatory regions of eukaryotic genes (TRRD) and TRRD Viewer; (3) Transcription Factor Binding Site Recognition contains a compilation of transcription factor binding sites (TFBSC) and programs for their analysis and recognition; (4) mRNA Translation is designed for analysis of structural and contextual features of mRNA 5'UTRs and prediction of their translation efficiency; and (5) ACTIVITY is the module for analysis and site activity prediction of a given nucleotide sequence. Integration of the databases in the GeneExpress is based on the Sequence Retrieval System (SRS) created in the European Bioinformatics Institute.

Artificial Intelligence↗
PubMed2001

FOUNTAIN: a JAVA open-source package to assist large sequencing projects.

BACKGROUND: Better automation, lower cost per reaction and a heightened interest in comparative genomics has led to a dramatic increase in DNA sequencing activities. Although the large sequencing projects of specialized centers are supported by in-house bioinformatics groups, many smaller laboratories face difficulties managing the appropriate processing and storage of their sequencing output. The challenges include documentation of clones, templates and sequencing reactions, and the storage, annotation and analysis of the large number of generated sequences. RESULTS: We describe here a new program, named FOUNTAIN, for the management of large sequencing projects http://genetics.hpi.uni-hamburg.de/FOUNTAIN.html. FOUNTAIN uses the JAVA computer language and data storage in a relational database. Starting with a collection of sequencing objects (clones), the program generates and stores information related to the different stages of the sequencing project using a web browser interface for user input. The generated sequences are subsequently imported and annotated based on BLAST searches against the public databases. In addition, simple algorithms to cluster sequences and determine putative polymorphic positions are implemented. CONCLUSIONS: A simple, but flexible and scalable software package is presented to facilitate data generation and storage for large sequencing projects. Open source and largely platform and database independent, we wish FOUNTAIN to be improved and extended in a community effort.

Algorithms↗
PubMed2001

Bioinformatics issues for automating the annotation of genomic sequences.

The rapid explosion in the amount of biological data being generated worldwide is surpassing efforts to manage analysis of the data. As part of an ongoing project to automate and manage bioinformatics analysis, the authors have designed and implemented a simple automated annotation system, which is described in this paper. The system is applied to existing GenBank/DDBJ/EMBL entries and compared with existing annotations to illustrate not only potential errors but also that they are generally not up-to-date, as a result of new versions of analysis tools and updates of genomic repositories. We highlight the important Bioinformatics issues of storage and management of information to ensure data and results are kept up-to-date in light of new information becoming available. Surprisingly, from just four database entries, a significant number of new features were found. We describe the results as well as identify important issues that need to be addressed in order to automate the re-analysis/re-annotation of genomic sequences within a reasonable timeframe.

Computational Biology↗
PubMed2003

Statistical bioinformatic methods in microbial genome analysis.

It is probable that, increasingly, genome investigations are going to be based on statistical formalization. This review summarizes the state of art and potentiality of using statistics in microbial genome analysis. First, I focus on recent advances in functional genomics, such as finding genes and operons, identifying gene conversion events, detecting DNA replication origins and analysing regulatory sites. Then I describe how to use phylogenetic methods in genome analysis and methods for genome-wide scanning for positively selected amino acids. I conclude with speculations on the future course of genome statistical modeling.

Computational Biology↗
PubMed2003

An integrated genetic data environment (GDE)-based LINUX interface for analysis of HIV-1 and other microbial sequences.

MOTIVATION: Sequence databases encode a wealth of information needed to develop improved vaccination and treatment strategies for the control of HIV and other important pathogens. To facilitate effective utilization of these datasets, we developed a user-friendly GDE-based LINUX interface that reduces input/output file formatting. DESIGN AND RESULTS: GDE was adapted to the Linux operating system, bioinformatics tools were integrated with microbe-specific databases, and up-to-date GDE menus were developed for several clinically important viral, bacterial and parasitic genomes. Each microbial interface was designed for local access and contains Genbank, BLAST-formatted and phylogenetic databases. AVAILABILITY: GDE-Linux is available for research purposes by direct application to the corresponding author. Application-specific menus and support files can be downloaded from (http://www.bioafrica.net).

Database Management Systems↗
PubMed2003

Wrapping up BLAST and other applications for use on Unix clusters.

UNLABELLED: We have developed two programs that speed up common bioinformatic applications by spreading them across a UNIX cluster.(1) BLAST.pm, a new module for the 'MOLLUSC' package. (2) WRAPID, a simple tool for parallelizing large numbers of small instances of programs such as BLAST, FASTA and CLUSTALW. AVAILABILITY: The packages were developed in Perl on a 20-node Linux cluster and are provided together with a configuration script and documentation. They can be freely downloaded from http://wolfe.gen.tcd.ie/wrapper.

Computer Communication Networks↗