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PubMed2003

Public services from the European Bioinformatics Institute.

The European Bioinformatics Institute (EBI) provides numerous free-of-charge, publicly available bioinformatics services that can be divided into the following categories: ftp downloads; data submissions processing and biological database production; access to query; analysis and retrieval systems and tools; user support; training and education and industry support through EBI's SME program. These services are all available at the website. It is imperative that EBI's data as well as the tools to analyse it efficiently are made available in a free and unambiguous way to the scientific community. An important part of the EBI's mission is to make this happen in a fast, reliable and efficient manner. This paper serves as a brief introduction to each of these services.

Computational Biology↗
PubMed2005

A hybrid genetic-neural system for predicting protein secondary structure.

BACKGROUND: Due to the strict relation between protein function and structure, the prediction of protein 3D-structure has become one of the most important tasks in bioinformatics and proteomics. In fact, notwithstanding the increase of experimental data on protein structures available in public databases, the gap between known sequences and known tertiary structures is constantly increasing. The need for automatic methods has brought the development of several prediction and modelling tools, but a general methodology able to solve the problem has not yet been devised, and most methodologies concentrate on the simplified task of predicting secondary structure. RESULTS: In this paper we concentrate on the problem of predicting secondary structures by adopting a technology based on multiple experts. The system performs an overall processing based on two main steps: first, a "sequence-to-structure" prediction is enforced by resorting to a population of hybrid (genetic-neural) experts, and then a "structure-to-structure" prediction is performed by resorting to an artificial neural network. Experiments, performed on sequences taken from well-known protein databases, allowed to reach an accuracy of about 76%, which is comparable to those obtained by state-of-the-art predictors. CONCLUSION: The adoption of a hybrid technique, which encompasses genetic and neural technologies, has demonstrated to be a promising approach in the task of protein secondary structure prediction.

Algorithms↗
PubMed2004

Protein kinases of the human malaria parasite Plasmodium falciparum: the kinome of a divergent eukaryote.

BACKGROUND: Malaria, caused by the parasitic protist Plasmodium falciparum, represents a major public health problem in the developing world. The P. falciparum genome has been sequenced, which provides new opportunities for the identification of novel drug targets. Eukaryotic protein kinases (ePKs) form a large family of enzymes with crucial roles in most cellular processes; hence malarial ePKS represent potential drug targets. We report an exhaustive analysis of the P. falciparum genomic database (PlasmoDB) aimed at identifying and classifying all ePKs in this organism. RESULTS: Using a variety of bioinformatics tools, we identified 65 malarial ePK sequences and constructed a phylogenetic tree to position these sequences relative to the seven established ePK groups. Predominant features of the tree were: (i) that several malarial sequences did not cluster within any of the known ePK groups; (ii) that the CMGC group, whose members are usually involved in the control of cell proliferation, had the highest number of malarial ePKs; and (iii) that no malarial ePK clustered with the tyrosine kinase (TyrK) or STE groups, pointing to the absence of three-component MAPK modules in the parasite. A novel family of 20 ePK-related sequences was identified and called FIKK, on the basis of a conserved amino acid motif. The FIKK family seems restricted to Apicomplexa, with 20 members in P. falciparum and just one member in some other Apicomplexan species. CONCLUSION: The considerable phylogenetic distance between Apicomplexa and other Eukaryotes is reflected by profound divergences between the kinome of malaria parasites and that of yeast or mammalian cells.

Animals↗
PubMed2005

A human-curated annotation of the Candida albicans genome.

Recent sequencing and assembly of the genome for the fungal pathogen Candida albicans used simple automated procedures for the identification of putative genes. We have reviewed the entire assembly, both by hand and with additional bioinformatic resources, to accurately map and describe 6,354 genes and to identify 246 genes whose original database entries contained sequencing errors (or possibly mutations) that affect their reading frame. Comparison with other fungal genomes permitted the identification of numerous fungus-specific genes that might be targeted for antifungal therapy. We also observed that, compared to other fungi, the protein-coding sequences in the C. albicans genome are especially rich in short sequence repeats. Finally, our improved annotation permitted a detailed analysis of several multigene families, and comparative genomic studies showed that C. albicans has a far greater catabolic range, encoding respiratory Complex 1, several novel oxidoreductases and ketone body degrading enzymes, malonyl-CoA and enoyl-CoA carriers, several novel amino acid degrading enzymes, a variety of secreted catabolic lipases and proteases, and numerous transporters to assimilate the resulting nutrients. The results of these efforts will ensure that the Candida research community has uniform and comprehensive genomic information for medical research as well as for future diagnostic and therapeutic applications.

Journal Article↗
PubMed2003

Extending SEE for large-scale phenotyping of mouse open-field behavior.

SEE (Software for the Exploration of Exploration) is a visualization and analysis tool designed for the study of open-field behavior in rodents. In this paper, I present new extensions of SEE that were designed to facilitate its use for mouse behavioral phenotyping and, especially, for the problems of discrimination of genotypes and the replication of results across laboratories and experimental conditions. These extensions were specifically designed to promote a new approach in behavioral phenotyping, reminiscent of the approach that has been successfully employed in bioinformatics during recent years. The path coordinates of all animals from many experiments are stored in a database. SEE can be used to query, visualize, and analyze any desirable subsection of this database and to design new measures (endpoints) with increasingly better discriminative power and replicability. The use of the new extensions is demonstrated here in the analysis of results from several experiments and laboratories, with an emphasis on this approach.

Animals↗
PubMed2005

Application of restriction fragment differential display-polymerase chain reaction in study on differential expression profiles of human diseases.

OBJECTIVE: To establish the restriction fragment differential display-polymerase chain reaction (RFDD-PCR) as an efficient technique for constructing and studying the gene expression profile of human tissues. METHODS: The tissues of mamma adenocarcinoma (T), cancerometastasis lymph node (L) and normal mammary (N) from one mammary infiltrating ductal carcinoma case were collected, and the gene expression profile of each kind of tissue was constructed using RFDD-PCR technique at equal pace according to the operating manual of Qbio-gene Company. Then all fragments of the three gene expression profiles were separated and displayed by electrophoresis. With the use of gene database at the website http://www.Qbio-gene.com/display, the authors identified the names of the probable fragments by bioinformatics analysis. Through comparison of the three profiles, the numbers and types of most differentially expressed gene fragments were displayed. RESULTS: The expression profiles of the three kinds of tissue have been constructed covering 1716 fragments of mammary adenocarcinoma, 1769 of cancerometastasis lymph nodes and 1922 of normal mammary tissue. Among these 5407 fragments, 39.39% were exactly the same. While 33.9% sequences of T and L showed differences in abundance or presence, 40.9% of T and N and 39.6% fragments of L and N were observed differentially expressed. These differentially expressed gene fragments were found to relate with metastasis, differentiation, inflammation and so on. CONCLUSION: RFDD-PCR is an efficient technique for research in human diseases genomics as a mass screening for complete gene expression profile with high-flux. Through comparison among three or more profiles, the screening for candidate genes of a certain disease can be accomplished, and there is probably a chance to identify novel gene or expressed sequence tag.

Adenocarcinoma↗
PubMed2005

PSORTdb: a protein subcellular localization database for bacteria.

Information about bacterial subcellular localization (SCL) is important for protein function prediction and identification of suitable drug/vaccine/diagnostic targets. PSORTdb (http://db.psort.org/) is a web-accessible database of SCL for bacteria that contains both information determined through laboratory experimentation and computational predictions. The dataset of experimentally verified information (approximately 2000 proteins) was manually curated by us and represents the largest dataset of its kind. Earlier versions have been used for training SCL predictors, and its incorporation now into this new PSORTdb resource, with its associated additional annotation information and dataset version control, should aid researchers in future development of improved SCL predictors. The second component of this database contains computational analyses of proteins deduced from the most recent NCBI dataset of completely sequenced genomes. Analyses are currently calculated using PSORTb, the most precise automated SCL predictor for bacterial proteins. Both datasets can be accessed through the web using a very flexible text search engine, a data browser, or using BLAST, and the entire database or search results may be downloaded in various formats. Features such as GO ontologies and multiple accession numbers are incorporated to facilitate integration with other bioinformatics resources. PSORTdb is freely available under GNU General Public License.

Bacterial Proteins↗
PubMed2000

Website review: interPro (the integrated resource of protein domains and functional sites).

The family and motif databases, PROSITE, PRINTS, Pfam and ProDom, have been integrated into a powerful resource for protein secondary annotation. As of June 2000, InterPro had processed 384 572 proteins in SWISS-PROT and TrEMBL. Because the contributing databases have different clustering principles and scoring sensitivities, the combined assignments compliment each other for grouping protein families and delineating domains. The graphic displays of all matches above the scoring thresholds enables judgements to be made on the concordances or differences between the assignments. The website links can be used to analyse novel sequences and for queries across the proteomes of 32 organisms, including the partial human set, by domain and/or protein family. An analysis of selected HtrA/DegQ proteases demonstrates the utility of this website for detailed comparative genomics. Further information on the project can be found at the European Bioinformatics Institute at http://www.ebi.ac.uk/interpro/

Amino Acid Motifs↗
PubMed2006

Gene Aging Nexus: a web database and data mining platform for microarray data on aging.

The recent development of microarray technology provided unprecedented opportunities to understand the genetic basis of aging. So far, many microarray studies have addressed aging-related expression patterns in multiple organisms and under different conditions. The number of relevant studies continues to increase rapidly. However, efficient exploitation of these vast data is frustrated by the lack of an integrated data mining platform or other unifying bioinformatic resource to enable convenient cross-laboratory searches of array signals. To facilitate the integrative analysis of microarray data on aging, we developed a web database and analysis platform 'Gene Aging Nexus' (GAN) that is freely accessible to the research community to query/analyze/visualize cross-platform and cross-species microarray data on aging. By providing the possibility of integrative microarray analysis, GAN should be useful in building the systems-biology understanding of aging. GAN is accessible at http://gan.usc.edu.

Aging↗
PubMed2004

FLOSYS--a web-accessible workflow system for protocol-driven biomolecular sequence analysis.

FLOSYS is an interactive web-accessible bioinformatics workflow system designed to assist biologists in multi-step data analyses. FLOSYS allows the user to create complex analysis pathways (protocols) graphically, similar to drawing a flowchart: icons representing particular bioinformatics tools are dragged and dropped onto a canvas and lines connecting those icons are drawn to specify the relationships between the tools. In addition, FLOSYS permits to select input-data, execute the protocol and store the results in a personal workspace. The three-tier architecture of FLOSYS has been implemented in Java and uses a relational database system together with new technologies for distributed and web computing such as CORBA, RMI, JSP and JDBC. The prototype of FLOSYS, which is part of the bioinformatics workbench AnaBench, is accessible on-line at http://malawimonas.bcm.umontreal.ca: 8091/anabench. The entire package is available on request to academic groups who wish to have a customized local analysis environment for research or teaching.

Computational Biology↗
PubMed2006

VIPERdb: a relational database for structural virology.

VIPERdb (http://viperdb.scripps.edu) is a database for icosahedral virus capsid structures. Our aim is to provide a comprehensive resource specific to the needs of the structural virology community, with an emphasis on the description and comparison of derived data from structural and energetic analyses of capsids. A relational database implementation based on a schema for macromolecular structure makes the data highly accessible to the user, allowing detailed queries at the atomic level. Together with curation practices that maintain data uniformity, this will facilitate structural bioinformatics studies of virus capsids. User friendly search, visualization and educational tools on the website allow both structural and derived data to be examined easily and extensively. Links to relevant literature, sequence and taxonomy databases are provided for each entry.

Capsid↗
PubMed2005

Who tangos with GOA?-Use of Gene Ontology Annotation (GOA) for biological interpretation of '-omics' data and for validation of automatic annotation tools.

The number of large-scale experimental datasets generated from high-throughput technologies has grown rapidly. Biological knowledge resources such as the Gene Ontology Annotation (GOA) database, which provides high-quality functional annotation to proteins within the UniProt Knowledgebase, can play an important role in the analysis of such data. The integration of GOA with analytical tools has proved to aid the clustering, annotation and biological interpretation of such large expression datasets. GOA is also useful in the development and validation of automated annotation tools, in particular text-mining systems. The increasing interest in GOA highlights the great potential of this freely available resource to assist both the biological research and bioinformatics communities.

Animals↗
PubMed2006

Functional genomics of hepatocellular carcinoma.

The majority of DNA-microarray based gene expression profiling studies on human hepatocellular carcinoma (HCC) has focused on identifying genes associated with clinicopathological features of HCC patients. Although notable success has been achieved, this approach still faces significant challenges due to the heterogeneous nature of HCC (and other cancers) as well as the many confounding factors embedded in gene expression profile data. However, these limitations are being overcome by improved bioinformatics and sophisticated analyses. Also, application of cross comparison of multiple gene expression data sets from human tumors and animal models are facilitating the identification of critical regulatory modules in the expression profiles. The success of this new experimental approach, comparative functional genomics, suggests that integration of independent data sets will enhance our ability to identify key regulatory elements in tumor development. Furthermore, integrating gene expression profiles with data from DNA sequence information in promoters, array-based CGH, and expression of non-coding genes (i.e., microRNAs) will further increase the reliability and significance of the biological and clinical inferences drawn from the data. The pace of current progress in the cancer profiling field, combined with the advances in high-throughput technologies in genomics and proteomics, as well as in bioinformatics, promises to yield unprecedented biological insights from the integrative (or systems) analysis of the combined cancer genomics database. The predicted beneficial impact of this "new integrative biology" on diagnosis, treatment and prevention of liver cancer and indeed cancer in general is enormous.

Animals↗
PubMedDate not supplied

Using functional domain composition to predict enzyme family classes.

According to their main EC (Enzyme Commission) numbers, enzymes are classified into the following 6 main classes: oxidoreductases, transferases, hydrolases, lyases, isomerases, and ligases. A new method has been developed to predict the enzymatic attribute of proteins by introducing the functional domain composition to formulate a given protein sequence. The advantage by doing so is that both the sequence-order-related features and the function-related features are naturally incorporated in the predictor. As a demonstration, the jackknife cross-validation test was performed on a dataset that consists of proteins with only less than 20% sequence identity to each other in order to get rid of any homologous bias. The overall success rate thus obtained was 85% in identifying the enzyme family classes (including the identification of nonenzyme protein sequences as well). The success rate is significantly higher than those obtained by the other methods on such a stringent dataset. This indicates that using the functional domain composition to represent protein samples for statistical prediction is indeed very promising, and will become a powerful tool in bioinformatics and proteomics.

Algorithms↗
PubMed1999

Genomics, mutations and the Internet: the naming and use of parts.

Mutations are the source of genetic variation and diversity; by their effect, some are neutral, others are pathogenic. In contemporary genetics, mutations appear at the interface between genomics (structural and functional) and genetics (heredity), where they serve gene discovery and mapping (genomics) and generate challenges to modify their phenotypic effects (medical genetics). Assuming the human genome harbours 80,000 transcribed genes each possessing at least 100 different (germline) alleles in a typical population, how then to record and recover data on at least 8 million human alleles? Bioinformatics is the essential resource to create the corresponding accessible digital libraries (genomic and locus-specific mutation databases) for this purpose, a goal to which The HUGO Mutation Database Initiative (Science 279: 10-11, 1998) aspires. Guidelines now exist for naming alleles (Hum Mutat 11: 1-3, 1998). The principles behind the practice are illustrated by PAHdb (http:/(/)www.mcgill.ca/ pahdb), a prototype locus-specific mutation database (NAR 26: 220-225, 1998), and by prototype genomic mutation databases (HGMD (NAR 26: 285-287, 1998), http:/(/)www.uwcm.ac.uk/uwcm/mg/hgmd0.h tml; the EBI mutation database, http:/(/)www2.ebi.ac.uk/mutations/; and OMIM, http:/(/)www.ncbi.nlm. nih.gov/Omim.html).

Databases, Factual↗
PubMed1998

Identification of genes expressed in human CD34(+) hematopoietic stem/progenitor cells by expressed sequence tags and efficient full-length cDNA cloning.

Hematopoietic stem/progenitor cells (HSPCs) possess the potentials of self-renewal, proliferation, and differentiation toward different lineages of blood cells. These cells not only play a primordial role in hematopoietic development but also have important clinical application. Characterization of the gene expression profile in CD34(+) HSPCs may lead to a better understanding of the regulation of normal and pathological hematopoiesis. In the present work, genes expressed in human umbilical cord blood CD34(+) cells were catalogued by partially sequencing a large amount of cDNA clones [or expressed sequence tags (ESTs)] and analyzing these sequences with the tools of bioinformatics. Among 9,866 ESTs thus obtained, 4,697 (47.6%) showed identity to known genes in the GenBank database, 2, 603 (26.4%) matched to the ESTs previously deposited in a public domain database, 1,415 (14.3%) were previously undescribed ESTs, and the remaining 1,151 (11.7%) were mitochondrial DNA, ribosomal RNA, or repetitive (Alu or L1) sequences. Integration of ESTs of known genes generated a profile including 855 genes that could be divided into different categories according to their functions. Some (8.2%) of the genes in this profile were considered related to early hematopoiesis. The possible function of ESTs corresponding to so far unknown genes were approached by means of homology and functional motif searches. Moreover, attempts were made to generate libraries enriched for full-length cDNAs, to better explore the genes in HSPCs. Nearly 60% of the cDNA clones of mRNA under 2 kb in our libraries had 5' ends upstream of the first ATG codon of the ORF. With this satisfactory result, we have developed an efficient working system that allowed fast sequencing of 32 full-length cDNAs, 16 of them being mapped to the chromosomes with radiation hybrid panels. This work may lay a basis for the further research on the molecular network of hematopoietic regulation.

ATPases Associated with Diverse Cellular Activitie↗
PubMed2001

On the parallelisation of bioinformatics applications.

This paper surveys the computational strategies followed to parallelise the most used software in the bioinformatics arena. The studied algorithms are computationally expensive and their computational patterns range from regular, such as database-searching applications, to very irregularly structured patterns (phylogenetic trees). Fine- and coarse-grained parallel strategies are discussed for these very diverse sets of applications. This overview outlines computational issues related to parallelism, physical machine models, parallel programming approaches and scheduling strategies for a broad range of computer architectures. In particular, it deals with shared, distributed and shared/distributed memory architectures.

Algorithms↗