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PubMedDate not supplied

Informatics in radiology (infoRAD): Vendor-neutral case input into a server-based digital teaching file system.

Although digital teaching files are important to radiology education, there are no current satisfactory solutions for export of Digital Imaging and Communications in Medicine (DICOM) images from picture archiving and communication systems (PACS) in desktop publishing format. A vendor-neutral digital teaching file, the Radiology Interesting Case Server (RadICS), offers an efficient tool for harvesting interesting cases from PACS without requiring modifications of the PACS configurations. Radiologists push imaging studies from PACS to RadICS via the standard DICOM Send process, and the RadICS server automatically converts the DICOM images into the Joint Photographic Experts Group format, a common desktop publishing format. They can then select key images and create an interesting case series at the PACS workstation. RadICS was tested successfully against multiple unmodified commercial PACS. Using RadICS, radiologists are able to harvest and author interesting cases at the point of clinical interpretation with minimal disruption in clinical work flow.

Computer-Assisted Instruction↗

PubMed2004

A common open representation of mass spectrometry data and its application to proteomics research.

A broad range of mass spectrometers are used in mass spectrometry (MS)-based proteomics research. Each type of instrument possesses a unique design, data system and performance specifications, resulting in strengths and weaknesses for different types of experiments. Unfortunately, the native binary data formats produced by each type of mass spectrometer also differ and are usually proprietary. The diverse, nontransparent nature of the data structure complicates the integration of new instruments into preexisting infrastructure, impedes the analysis, exchange, comparison and publication of results from different experiments and laboratories, and prevents the bioinformatics community from accessing data sets required for software development. Here, we introduce the 'mzXML' format, an open, generic XML (extensible markup language) representation of MS data. We have also developed an accompanying suite of supporting programs. We expect that this format will facilitate data management, interpretation and dissemination in proteomics research.

Database Management Systems↗

PubMed2006

HiRes--a tool for comprehensive assessment and interpretation of metabolomic data.

UNLABELLED: The increasing role of metabolomics in system biology is driving the development of tools for comprehensive analysis of high-resolution NMR spectral datasets. This task is quite challenging since unlike the datasets resulting from other 'omics', a substantial preprocessing of the data is needed to allow successful identification of spectral patterns associated with relevant biological variability. HiRes is a unique stand-alone software tool that combines standard NMR spectral processing functionalities with techniques for multi-spectral dataset analysis, such as principal component analysis and non-negative matrix factorization. In addition, HiRes contains extensive abilities for data cleansing, such as baseline correction, solvent peak suppression, removal of frequency shifts owing to experimental conditions as well as auxiliary information management. Integration of these components together with multivariate analytical procedures makes HiRes very capable of addressing the challenges for assessment and interpretation of large metabolomic datasets, greatly simplifying this otherwise lengthy and difficult process and assuring optimal information retrieval. AVAILABILITY: HiRes is freely available for research purposes at http://hatch.cpmc.columbia.edu/highresmrs.html

Algorithms↗

PubMed2003

Exploring semantic groups through visual approaches.

Objectives. We investigate several visual approaches for exploring semantic groups, a grouping of semantic types from the Unified Medical Language System (UMLS) semantic network. We are particularly interested in the semantic coherence of the groups, and we use the semantic relationships as important indicators of that coherence. Methods. First, we create a radial representation of the number of relationships among the groups, generating a profile for each semantic group. Second, we show that, in our partition, the relationships are organized around a limited number of pivot groups and that partitions created at random do not exhibit this property. Finally, we use correspondence analysis to visualize groupings resulting from the association between semantic types and the relationships. Results. The three approaches provide different views on the semantic groups and help detect potential inconsistencies. They make outliers immediately apparent, and, thus, serve as a tool for auditing and validating both the semantic network and the semantic groups.

Abstracting and Indexing↗

PubMed2004

Textmining in support of knowledge discovery for vaccine development.

Complete genome data of infectious microorganisms permit systematic computational sequence-based predictions and experimental testing of candidate vaccine epitopes. Both, predictions and the interpretation of experiments rely on existing information in the literature which is mostly manually extracted and curated. The growing amount of data and literature information has created a major bottleneck for the interpretation of results and maintenance of curated databases. The lack of suitable free-text information extraction, processing, and reporting tools prompted us to develop a knowledge discovery support system that enhances the understanding of immune response and vaccine development. The current prototype system, Gene expression/epitpopes/protein interaction (GEpi), focuses on molecular functions of HIV-infected T-cells and HIV epitope information, using textmining, and interrelation of biomolecular data from domain-specific databases with MEDLINE abstract-inferred information. Results showed that extraction and processing of molecular interaction, disease associations, and gene ontology-derived functional information generate intuitive knowledge reports that aid the interpretation of host-pathogen interaction. In contrast, epitope (word and sequence) information in MEDLINE abstracts is surprisingly sparse and often lacks necessary context information, such as HLA-restriction. Since the majority of epitope information is found in tables, figures, and legends of full-text articles, its extraction may not require sophisticated natural language processing techniques. Support of vaccine development through textmining requires therefore the timely development of domain-specific extraction rules for full-text articles, and a knowledge model for epitope-related information.

Animals↗

PubMed2005

Predicting post-synaptic activity in proteins with data mining.

The bioinformatics problem being addressed in this paper is to predict whether or not a protein has post-synaptic activity. This problem is of great intrinsic interest because proteins with post-synaptic activities are connected with functioning of the nervous system. Indeed, many proteins having post-synaptic activity have been functionally characterized by biochemical, immunological and proteomic exercises. They represent a wide variety of proteins with functions in extracellular signal reception and propagation through intracellular apparatuses, cell adhesion molecules and scaffolding proteins that link them in a web. The challenge is to automatically discover features of the primary sequences of proteins that typically occur in proteins with post-synaptic activity but rarely (or never) occur in proteins without post-synaptic activity, and vice-versa. In this context, we used data mining to automatically discover classification rules that predict whether or not a protein has post-synaptic activity. The discovered rules were analysed with respect to their predictive accuracy (generalization ability) and with respect to their interestingness to biologists (in the sense of representing novel, unexpected knowledge).

Database Management Systems↗

PubMed2004

Discovery of functional genes for systemic acquired resistance in Arabidopsis thaliana through integrated data mining.

Various data mining techniques combined with sequence motif information in the promoter region of genes were applied to discover functional genes that are involved in the defense mechanism of systemic acquired resistance (SAR) in Arabidopsis thaliana. A series of K-Means clustering with difference-in-shape as distance measure was initially applied. A stability measure was used to validate this clustering process. A decision tree algorithm with the discover-and-mask technique was used to identify a group of most informative genes. Appearance and abundance of various transcription factor binding sites in the promoter region of the genes were studied. Through the combination of these techniques, we were able to identify 24 candidate genes involved in the SAR defense mechanism. The candidate genes fell into 2 highly resolved categories, each category showing significantly unique profiles of regulatory elements in their promoter regions. This study demonstrates the strength of such integration methods and suggests a broader application of this approach.

Algorithms↗

PubMed2006

GOPET: a tool for automated predictions of Gene Ontology terms.

BACKGROUND: Vast progress in sequencing projects has called for annotation on a large scale. A Number of methods have been developed to address this challenging task. These methods, however, either apply to specific subsets, or their predictions are not formalised, or they do not provide precise confidence values for their predictions. DESCRIPTION: We recently established a learning system for automated annotation, trained with a broad variety of different organisms to predict the standardised annotation terms from Gene Ontology (GO). Now, this method has been made available to the public via our web-service GOPET (Gene Ontology term Prediction and Evaluation Tool). It supplies annotation for sequences of any organism. For each predicted term an appropriate confidence value is provided. The basic method had been developed for predicting molecular function GO-terms. It is now expanded to predict biological process terms. This web service is available via http://genius.embnet.dkfz-heidelberg.de/menu/biounit/open-husar CONCLUSION: Our web service gives experimental researchers as well as the bioinformatics community a valuable sequence annotation device. Additionally, GOPET also provides less significant annotation data which may serve as an extended discovery platform for the user.

Artificial Intelligence↗

PubMed2005

IPD--the Immuno Polymorphism Database.

The Immuno Polymorphism Database (IPD) (http://www.ebi.ac.uk/ipd/) is a set of specialist databases related to the study of polymorphic genes in the immune system. IPD currently consists of four databases: IPD-KIR, contains the allelic sequences of Killer-cell Immunoglobulin-like Receptors; IPD-MHC, a database of sequences of the Major Histocompatibility Complex of different species; IPD-HPA, alloantigens expressed only on platelets; and IPD-ESTAB, which provides access to the European Searchable Tumour Cell-Line Database, a cell bank of immunologically characterized melanoma cell lines. The IPD project works with specialist groups or nomenclature committees who provide and curate individual sections before they are submitted to IPD for online publication. The IPD project stores all the data in a set of related databases. Those sections with similar data, such as IPD-KIR and IPD-MHC share the same database structure. The sharing of a common database structure makes it easier to implement common tools for data submission and retrieval. The data are currently available online from the website and ftp directory; files will also be made available in different formats to download from the website and ftp server. The data will also be included in SRS, BLAST and FASTA search engines at the European Bioinformatics Institute.

Animals↗

PubMed2005

MiGenes: a searchable interspecies database of mitochondrial proteins curated using gene ontology annotation.

MOTIVATION: There has been an explosion of interest in the role of mitochondria in programmed cell death and other fundamental pathological processes underlying the development of human diseases. Nevertheless, the inventory of mitochondrial proteins encoded in the nuclear genome remains incomplete, providing an impediment to mitochondrial research at the interface with systems biology. We created the MiGenes database to further define the scope of the mitochondrial proteome in humans and model organisms including mice, rats, flies and worms as well as budding and fission yeasts. MiGenes is intended to stimulate mitochondrial research using model organisms. SUMMARY: MiGenes is a large-scale relational database that is automatically updated to keep pace with advances in mitochondrial proteomics and is curated to assure that the designation of proteins as mitochondrial reflects gene ontology (GO) annotations supported by high-quality evidence codes. A set of postulates is proposed to help define which proteins are authentic components of mitochondria. MiGenes incorporates >1160 new GO annotations to human, mouse and rat protein records, 370 of which represent the first GO annotation reflecting a mitochondrial localization. MiGenes employs a flexible search interface that permits batchwise accession number searches to support high-throughput proteomic studies. A web interface is provided to permit members of the mitochondrial research community to suggest modifications in protein annotations or mitochondrial status.

Animals↗

PubMed2004

BioLingua: a programmable knowledge environment for biologists.

UNLABELLED: BioLingua is an interactive, web-based programming environment that enables biologists to analyze biological systems by combining knowledge and data through direct end-user programming. BioLingua embeds a mature symbolic programming language in a frame-based knowledge environment, integrating genomic and pathway knowledge about a class of similar organisms. The BioLingua language provides interfaces to numerous state-of-the-art bioinformatic tools, making these available as an integrated package through the novel use of web-based programmability and an integrated Wiki-based community code and data store. The pilot instantiation of BioLingua, which has been developed in collaboration with several cyanobacteriologists, integrates knowledge about a subset of cyanobacteria with the Gene Ontology, KEGG and BioCyc knowledge bases. We introduce the BioLingua concept, architecture and language, and give several examples of its use in complex analyses. AVAILABILITY: Extensive documentation is available online at http://nostoc.stanford.edu/Docs/index.html CONTACT: JShrager@Stanford.edu

Artificial Intelligence↗

PubMed2005

Bioinformatic insights from metagenomics through visualization.

Cutting-edge biological and bioinformatics research seeks a systems perspective through the analysis of multiple types of high-throughput and other experimental data for the same sample. Systems-level analysis requires the integration and fusion of such data, typically through advanced statistics and mathematics. Visualization is a complementary computational approach that supports integration and analysis of complex data or its derivatives. We present a bioinformatics visualization prototype, Juxter, which depicts categorical information derived from or assigned to these diverse data for the purpose of comparing patterns across categorizations. The visualization allows users to easily discern correlated and anomalous patterns in the data. These patterns, which might not be detected automatically by algorithms, may reveal valuable information leading to insight and discovery. We describe the visualization and interaction capabilities and demonstrate its utility in a new field, metagenomics, which combines molecular biology and genetics to identify and characterize genetic material from multi-species microbial samples.

Algorithms↗

PubMedDate not supplied

Data input module for Birth Defects Systems Manager.

The need for a computational bioinformatics infrastructure to manage the vast digital information from functional genomics and proteomics motivated us to develop Birth Defects Systems Manager (BDSM) as an open resource to facilitate analysis and discovery in developmental biology and developmental toxicity. This report describes the design, development and implementation of the data loading module of BDSM, referred to as LoadBDSM. It includes a shared data directory resource that can be granted various levels of security for different research groups or investigators to manage experimental datasets individually or in groups. LoadBDSM allows the upload of data and experiment details using controlled semantics for developmental exposure (toxicant, dosing scenario, intervention), biological sample (species, tissue, stage) and disease outcome (time, risk, phenotype). It adheres to existing controlled vocabulary plus rules of inference (ontologies) for experiment, data and metadata annotations. LoadBDSM extends the capabilities of BDSM to support the emergence of "embryo-formatics" defined here as the data, information and knowledge from genomic sciences applied to, or derived from, an embryological context. This includes, but is not limited to, delineating pathways and biological regulatory networks for specific chemicals or classes of developmental toxicants, developing novel biomarkers indicative of exposure and/or predictive of adverse effects, and integrating modern computing and information technology with data from molecular biology.

Abnormalities, Drug-Induced↗

PubMed2005

Recording of time-varying back-pain data: a wireless solution.

Chronic back pain is a debilitating experience for a considerable proportion of the adult population, with a significant impact on countries' economies and health systems. While there has been increasing anecdotal evidence to support the fact that for certain categories of patients (such as wheelchair users), the back pain experienced is dynamically varying with time, there is a relative scarcity of data to support and document this observation, with consequential impact upon such patients' treatment and care. Part of the reason behind this state of affairs is the relative difficulty in gathering pain measurements at precisely defined moments in time. In this paper, we describe a wireless-enabled solution that collects both questionnaire and diagrammatic, visual-based data, via a pain drawing, which overcomes such limitations, enabling seamless data collection and its upload to a hospital server using existing wireless fidelity technology. Results show that it is generally perceived to be an easy-to-use and convenient solution to the challenges of anywhere/anytime data collection.

Back Pain↗

PubMed2005

BioContrasts: extracting and exploiting protein-protein contrastive relations from biomedical literature.

MOTIVATION: Contrasts are useful conceptual vehicles for learning processes and exploratory research of the unknown. For example, contrastive information between proteins can reveal what similarities, divergences and relations there are of the two proteins, leading to invaluable insights for better understanding about the proteins. Such contrastive information are found to be reported in the biomedical literature. However, there have been no reported attempts in current biomedical text mining work that systematically extract and present such useful contrastive information from the literature for exploitation. RESULTS: Our BioContrasts system extracts protein-protein contrastive information from MEDLINE abstracts and presents the information to biologists in a web-application for exploitation. Contrastive information are identified in the text abstracts with contrastive negation patterns such as 'A but not B'. A total of 799 169 pairs of contrastive expressions were successfully extracted from 2.5 million MEDLINE abstracts. Using grounding of contrastive protein names to Swiss-Prot entries, we were able to produce 41 471 pieces of contrasts between Swiss-Prot protein entries. These contrastive pieces of information are then presented via a user-friendly interactive web portal that can be exploited for applications such as the refinement of biological pathways. AVAILABILITY: BioContrasts can be accessed at http://biocontrasts.i2r.a-star.edu.sg. It is also mirrored at http://biocontrasts.biopathway.org. SUPPLEMENTARY INFORMATION: Supplementary materials are available at Bioinformatics online.

Artificial Intelligence↗

PubMed2002

Rat Genome Database (RGD): mapping disease onto the genome.

The Rat Genome Database (RGD, http://rgd.mcw.edu) is an NIH-funded project whose stated mission is 'to collect, consolidate and integrate data generated from ongoing rat genetic and genomic research efforts and make these data widely available to the scientific community'. In a collaboration between the Bioinformatics Research Center at the Medical College of Wisconsin, the Jackson Laboratory and the National Center for Biotechnology Information, RGD has been created to meet these stated aims. The rat is uniquely suited to its role as a model of human disease and the primary focus of RGD is to aid researchers in their study of the rat and in applying their results to studies in a wider context. In support of this we have integrated a large amount of rat genetic and genomic resources in RGD and these are constantly being expanded through ongoing literature and bulk dataset curation. RGD version 2.0, released in June 2001, includes curated data on rat genes, quantitative trait loci (QTL), microsatellite markers and rat strains used in genetic and genomic research. VCMap, a dynamic sequence-based homology tool was introduced, and allows researchers of rat, mouse and human to view mapped genes and sequences and their locations in the other two organisms, an essential tool for comparative genomics. In addition, RGD provides tools for gene prediction, radiation hybrid mapping, polymorphic marker selection and more. Future developments will include the introduction of disease-based curation expanding the curated information to cover popular disease systems studied in the rat. This will be integrated with the emerging rat genomic sequence and annotation pipelines to provide a high-quality disease-centric resource, applicable to human and mouse via comparative tools such as VCMap. RGD has a defined community outreach focus with a Visiting Scientist program and the Rat Community Forum, a web-based forum for rat researchers and others interested in using the rat as an experimental model. Thus, RGD is not only a valuable resource for those working with the rat but also for researchers in other model organisms wishing to harness the existing genetic and physiological data available in the rat to complement their own work.

Animals↗

PubMed2002

Design and development of an Internet registry for congenital heart defects.

BACKGROUND: Congenital Heart Defects (CHD) are conditions that encompass more than 50 diagnoses and are due to developmental abnormalities early in fetal life. The King Faisal Specialist Hospital and Research Centre in the Kingdom of Saudi Arabia treats approximately 100 new cases per month. We recently developed a new CHD Registry that captures, stores and processes our data via the Internet. METHODS: The Registry was developed using Hypertext Markup Language (HTML), Microsoft Active Server Pages and Microsoft Structured Query Language (SQL). RESULTS: Details of CHD cases are captured in a World Wide Web (WWW) Registry, permitting any browser-enabled PC or Mac to participate fully in all registry functions, including data-entry, viewing, editing, searching, reporting, validating, charting, and exporting data subsets to statistics packages. It includes "administrative" features and an active security system. The paper forms have been designed to reflect the "look and feel" of the Web pages. Automatic validation procedures are also included. CONCLUSIONS: Our Registry has been in operation for 3 years. It serves 10 PCs and contains more than 3,000 registered cases of CHD. It is the first CHD Registry to be fully functional on the Internet. It is also the first dedicated CHD registry, and the first to routinely report on the full spectrum of CHD diagnoses. The WWW offers several logistical advantages to disease registries, especially those that represent large regions. It also offers the possibility of sharing resources between registries, facilitating the aggregation and analysis of disease data on a world-wide scale. This is useful for rare diseases such as CHD (see http://rc.kfshrc.edu.sa/chdr/demo/).

Adolescent↗

PubMed2002

PGAAS: a prokaryotic genome assembly assistant system.

MOTIVATION: In order to accelerate the finishing phase of genome assembly, especially for the whole genome shotgun approach of prokaryotic species, we have developed a software package designated prokaryotic genome assembly assistant system (PGAAS). The approach upon which PGAAS is based is to confirm the order of contigs and fill gaps between contigs through peptide links obtained by searching each contig end with BLASTX against protein databases. RESULTS: We used the contig dataset of the cyanobacterium Synechococcus sp. strain PCC7002 (PCC7002), which was sequenced with six-fold coverage and assembled using the Phrap package. The subject database is the protein database of the cyanobacterium, Synechocystis sp. strain PCC6803 (PCC6803). We found more than 100 non-redundant peptide segments which can link at least 2 contigs. We tested one pair of linked contigs by sequencing and obtained satisfactory result. PGAAS provides a graphic user interface to show the bridge peptides and pier contigs. We integrated Primer3 into our package to design PCR primers at the adjacent ends of the pier contigs. AVAILABILITY: We tested PGAAS on a Linux (Redhat 6.2) PC machine. It is developed with free software (MySQL, PHP and Apache). The whole package is distributed freely and can be downloaded as UNIX compress file: ftp://ftp.cbi.pku.edu.cn/pub/software/unix/pgaas1.0.tar.gz. The package is being continually updated.

Algorithms↗