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A simple spreadsheet-based, MIAME-supportive format for microarray data: MAGE-TAB.

BACKGROUND: Sharing of microarray data within the research community has been greatly facilitated by the development of the disclosure and communication standards MIAME and MAGE-ML by the MGED Society. However, the complexity of the MAGE-ML format has made its use impractical for laboratories lacking dedicated bioinformatics support. RESULTS: We propose a simple tab-delimited, spreadsheet-based format, MAGE-TAB, which will become a part of the MAGE microarray data standard and can be used for annotating and communicating microarray data in a MIAME compliant fashion. CONCLUSION: MAGE-TAB will enable laboratories without bioinformatics experience or support to manage, exchange and submit well-annotated microarray data in a standard format using a spreadsheet. The MAGE-TAB format is self-contained, and does not require an understanding of MAGE-ML or XML.

Computational Biology↗

DWARF--a data warehouse system for analyzing protein families.

BACKGROUND: The emerging field of integrative bioinformatics provides the tools to organize and systematically analyze vast amounts of highly diverse biological data and thus allows to gain a novel understanding of complex biological systems. The data warehouse DWARF applies integrative bioinformatics approaches to the analysis of large protein families. DESCRIPTION: The data warehouse system DWARF integrates data on sequence, structure, and functional annotation for protein fold families. The underlying relational data model consists of three major sections representing entities related to the protein (biochemical function, source organism, classification to homologous families and superfamilies), the protein sequence (position-specific annotation, mutant information), and the protein structure (secondary structure information, superimposed tertiary structure). Tools for extracting, transforming and loading data from public available resources (ExPDB, GenBank, DSSP) are provided to populate the database. The data can be accessed by an interface for searching and browsing, and by analysis tools that operate on annotation, sequence, or structure. We applied DWARF to the family of alpha/beta-hydrolases to host the Lipase Engineering database. Release 2.3 contains 6138 sequences and 167 experimentally determined protein structures, which are assigned to 37 superfamilies 103 homologous families. CONCLUSION: DWARF has been designed for constructing databases of large structurally related protein families and for evaluating their sequence-structure-function relationships by a systematic analysis of sequence, structure and functional annotation. It has been applied to predict biochemical properties from sequence, and serves as a valuable tool for protein engineering.

Amino Acid Sequence↗

Integrating protein structures and precomputed genealogies in the Magnum database: examples with cellular retinoid binding proteins.

BACKGROUND: When accurate models for the divergent evolution of protein sequences are integrated with complementary biological information, such as folded protein structures, analyses of the combined data often lead to new hypotheses about molecular physiology. This represents an excellent example of how bioinformatics can be used to guide experimental research. However, progress in this direction has been slowed by the lack of a publicly available resource suitable for general use. RESULTS: The precomputed Magnum database offers a solution to this problem for ca. 1,800 full-length protein families with at least one crystal structure. The Magnum deliverables include 1) multiple sequence alignments, 2) mapping of alignment sites to crystal structure sites, 3) phylogenetic trees, 4) inferred ancestral sequences at internal tree nodes, and 5) amino acid replacements along tree branches. Comprehensive evaluations revealed that the automated procedures used to construct Magnum produced accurate models of how proteins divergently evolve, or genealogies, and correctly integrated these with the structural data. To demonstrate Magnum's capabilities, we asked for amino acid replacements requiring three nucleotide substitutions, located at internal protein structure sites, and occurring on short phylogenetic tree branches. In the cellular retinoid binding protein family a site that potentially modulates ligand binding affinity was discovered. Recruitment of cellular retinol binding protein to function as a lens crystallin in the diurnal gecko afforded another opportunity to showcase the predictive value of a browsable database containing branch replacement patterns integrated with protein structures. CONCLUSION: We integrated two areas of protein science, evolution and structure, on a large scale and created a precomputed database, known as Magnum, which is the first freely available resource of its kind. Magnum provides evolutionary and structural bioinformatics resources that are useful for identifying experimentally testable hypotheses about the molecular basis of protein behaviors and functions, as illustrated with the examples from the cellular retinoid binding proteins.

Amino Acid Sequence↗

Maximum common subgraph: some upper bound and lower bound results.

BACKGROUND: Structure matching plays an important part in understanding the functional role of biological structures. Bioinformatics assists in this effort by reformulating this process into a problem of finding a maximum common subgraph between graphical representations of these structures. Among the many different variants of the maximum common subgraph problem, the maximum common induced subgraph of two graphs is of special interest. RESULTS: Based on current research in the area of parameterized computation, we derive a new lower bound for the exact algorithms of the maximum common induced subgraph of two graphs which is the best currently known. Then we investigate the upper bound and design techniques for approaching this problem, specifically, reducing it to one of finding a maximum clique in the product graph of the two given graphs. Considering the upper bound result, the derived lower bound result is asymptotically tight. CONCLUSION: Parameterized computation is a viable approach with great potential for investigating many applications within bioinformatics, such as the maximum common subgraph problem studied in this paper. With an improved hardness result and the proposed approaches in this paper, future research can be focused on further exploration of efficient approaches for different variants of this problem within the constraints imposed by real applications.

Algorithms↗

Identification of "pathologs" (disease-related genes) from the RIKEN mouse cDNA dataset using human curation plus FACTS, a new biological information extraction system.

BACKGROUND: A major goal in the post-genomic era is to identify and characterise disease susceptibility genes and to apply this knowledge to disease prevention and treatment. Rodents and humans have remarkably similar genomes and share closely related biochemical, physiological and pathological pathways. In this work we utilised the latest information on the mouse transcriptome as revealed by the RIKEN FANTOM2 project to identify novel human disease-related candidate genes. We define a new term "patholog" to mean a homolog of a human disease-related gene encoding a product (transcript, anti-sense or protein) potentially relevant to disease. Rather than just focus on Mendelian inheritance, we applied the analysis to all potential pathologs regardless of their inheritance pattern. RESULTS: Bioinformatic analysis and human curation of 60,770 RIKEN full-length mouse cDNA clones produced 2,578 sequences that showed similarity (70-85% identity) to known human-disease genes. Using a newly developed biological information extraction and annotation tool (FACTS) in parallel with human expert analysis of 17,051 MEDLINE scientific abstracts we identified 182 novel potential pathologs. Of these, 36 were identified by computational tools only, 49 by human expert analysis only and 97 by both methods. These pathologs were related to neoplastic (53%), hereditary (24%), immunological (5%), cardio-vascular (4%), or other (14%), disorders. CONCLUSIONS: Large scale genome projects continue to produce a vast amount of data with potential application to the study of human disease. For this potential to be realised we need intelligent strategies for data categorisation and the ability to link sequence data with relevant literature. This paper demonstrates the power of combining human expert annotation with FACTS, a newly developed bioinformatics tool, to identify novel pathologs from within large-scale mouse transcript datasets.

Animals↗

Comparative analysis of the kinomes of three pathogenic trypanosomatids: Leishmania major, Trypanosoma brucei and Trypanosoma cruzi.

BACKGROUND: The trypanosomatids Leishmania major, Trypanosoma brucei and Trypanosoma cruzi cause some of the most debilitating diseases of humankind: cutaneous leishmaniasis, African sleeping sickness, and Chagas disease. These protozoa possess complex life cycles that involve development in mammalian and insect hosts, and a tightly coordinated cell cycle ensures propagation of the highly polarized cells. However, the ways in which the parasites respond to their environment and coordinate intracellular processes are poorly understood. As a part of an effort to understand parasite signaling functions, we report the results of a genome-wide analysis of protein kinases (PKs) of these three trypanosomatids. RESULTS: Bioinformatic searches of the trypanosomatid genomes for eukaryotic PKs (ePKs) and atypical PKs (aPKs) revealed a total of 176 PKs in T. brucei, 190 in T. cruzi and 199 in L. major, most of which are orthologous across the three species. This is approximately 30% of the number in the human host and double that of the malaria parasite, Plasmodium falciparum. The representation of various groups of ePKs differs significantly as compared to humans: trypanosomatids lack receptor-linked tyrosine and tyrosine kinase-like kinases, although they do possess dual-specificity kinases. A relative expansion of the CMGC, STE and NEK groups has occurred. A large number of unique ePKs show no strong affinity to any known group. The trypanosomatids possess few ePKs with predicted transmembrane domains, suggesting that receptor ePKs are rare. Accessory Pfam domains, which are frequently present in human ePKs, are uncommon in trypanosomatid ePKs. CONCLUSION: Trypanosomatids possess a large set of PKs, comprising approximately 2% of each genome, suggesting a key role for phosphorylation in parasite biology. Whilst it was possible to place most of the trypanosomatid ePKs into the seven established groups using bioinformatic analyses, it has not been possible to ascribe function based solely on sequence similarity. Hence the connection of stimuli to protein phosphorylation networks remains enigmatic. The presence of numerous PKs with significant sequence similarity to known drug targets, as well as a large number of unusual kinases that might represent novel targets, strongly argue for functional analysis of these molecules.

Animals↗

Characterization of SR3 reveals abundance of non-LTR retrotransposons of the RTE clade in the genome of the human blood fluke, Schistosoma mansoni.

BACKGROUND: It is becoming apparent that perhaps as much as half of the genome of the human blood fluke Schistosoma mansoni is constituted of mobile genetic element-related sequences. Non-long terminal repeat (LTR) retrotransposons, related to the LINE elements of mammals, comprise much of this repetitive component of the schistosome genome. Of more than 12 recognized clades of non-LTR retrotransposons, only members of the CR1, RTE, and R2 clades have been reported from the schistosome genome. RESULTS: Inspection of the nucleotide sequence of bacterial artificial chromosome number 49_J_14 from chromosome 1 of the genome of Schistosoma mansoni (GenBank AC093105) revealed the likely presence of several RTE-like retrotransposons. Among these, a new non-LTR retrotransposon designated SR3 was identified and is characterized here. Analysis of gene structure and phylogenetic analysis of both the reverse transcriptase and endonuclease domains of the mobile element indicated that SR3 represented a new family of RTE-like non-LTR retrotransposons. Remarkably, two full-length copies of SR3-like elements were present in BAC 49-J-14, and one of 3,211 bp in length appeared to be intact, indicating SR3 to be an active non-LTR retrotransposon. Both were flanked by target site duplications of 10-12 bp. Southern hybridization and bioinformatics analyses indicated the presence of numerous copies (probably >1,000) of SR3 interspersed throughout the genome of S. mansoni. Bioinformatics analyses also revealed SR3 to be transcribed in both larval and adult developmental stages of S. mansoni and to be also present in the genomes of the other major schistosome parasites of humans, Schistosoma haematobium and S. japonicum. CONCLUSION: Numerous copies of SR3, a novel non-LTR retrotransposon of the RTE clade are present in the genome of S. mansoni. Non-LTR retrotransposons of the RTE clade including SR3 appear to have been remarkably successful in colonizing, and proliferation within the schistosome genome.

Animals↗

In silico and microarray-based genomic approaches to identifying potential vaccine candidates against Leptospira interrogans.

BACKGROUND: Currently available vaccines against leptospirosis are of low efficacy, have an unacceptable side-effect profile, do not induce long-term protection, and provide no cross-protection against the different serovars of pathogenic leptospira. The current major focus in leptospirosis research is to discover conserved protective antigens that may elicit longer-term protection against a broad range of Leptospira. There is a need to screen vaccine candidate genes in the genome of Leptospira interrogans. RESULTS: Bioinformatics, comparative genomic hybridization (CGH) analysis and transcriptional analysis were used to identify vaccine candidates in the genome of L. interrogans serovar Lai strain #56601. Of a total of 4727 open reading frames (ORFs), 616 genes were predicted to encode surface-exposed proteins by P-CLASSIFIER combined with signal peptide prediction, alpha-helix transmembrane topology prediction, integral beta-barrel outer membrane protein and lipoprotein prediction, as well as by retaining the genes shared by the two sequenced L. interrogans genomes and by subtracting genes with human homologues. A DNA microarray of L. interrogans strain #56601 was constructed for CGH analysis and transcriptome analysis in vitro. Three hundred and seven differential genes were identified in ten pathogenic serovars by CGH; 1427 genes had high transcriptional levels (Cy3 signal > or = 342 and Cy5 signal > or = 363.5, respectively). There were 565 genes in the intersection between the set encoding surface-exposed proteins and the set of 307 differential genes. The number of genes in the intersection between this set of 565 and the set of 1427 highly transcriptionally active genes was 226. These 226 genes were thus identified as putative vaccine candidates. The proteins encoded by these genes are not only potentially surface-exposed in the bacterium, but also conserved in two sequenced L. interrogans. Moreover, these genes are conserved among ten epidemic serovars in China and have high transcriptional levels in vitro. CONCLUSION: Of the 4727 ORFs in the genome of L. interrogans, 226 genes were identified as vaccine candidates by bioinformatics, CGH and transcriptional analysis on the basis of the theory of reverse vaccinology. The proteins encoded by these genes might be useful as vaccine candidates as well as for diagnosis of leptospirosis.

Bacterial Outer Membrane Proteins↗

In silico identification and comparative analysis of differentially expressed genes in human and mouse tissues.

BACKGROUND: Screening for differentially expressed genes on the genomic scale and comparative analysis of the expression profiles of orthologous genes between species to study gene function and regulation are becoming increasingly feasible. Expressed sequence tags (ESTs) are an excellent source of data for such studies using bioinformatic approaches because of the rich libraries and tremendous amount of data now available in the public domain. However, any large-scale EST-based bioinformatics analysis must deal with the heterogeneous, and often ambiguous, tissue and organ terms used to describe EST libraries. RESULTS: To deal with the issue of tissue source, in this work, we carefully screened and organized more than 8 million human and mouse ESTs into 157 human and 108 mouse tissue/organ categories, to which we applied an established statistic test using different thresholds of the p value to identify genes differentially expressed in different tissues. Further analysis of the tissue distribution and level of expression of human and mouse orthologous genes showed that tissue-specific orthologs tended to have more similar expression patterns than those lacking significant tissue specificity. On the other hand, a number of orthologs were found to have significant disparity in their expression profiles, hinting at novel functions, divergent regulation, or new ortholog relationships. CONCLUSION: Comprehensive statistics on the tissue-specific expression of human and mouse genes were obtained in this very large-scale, EST-based analysis. These statistical results have been organized into a database, freely accessible at our website http://gln.ibms.sinica.edu.tw/product/HMDEG/EST/index.php, for easy searching of human and mouse tissue-specific genes and for investigating gene expression profiles in the context of comparative genomics. Comparative analysis showed that, although highly tissue-specific genes tend to exhibit similar expression profiles in human and mouse, there are significant exceptions, indicating that orthologous genes, while sharing basic genomic properties, could result in distinct phenotypes.

Animals↗

Identification of potential CepR regulated genes using a cep box motif-based search of the Burkholderia cenocepacia genome.

BACKGROUND: The Burkholderia cenocepacia CepIR quorum sensing system has been shown to positively and negatively regulate genes involved in siderophore production, protease expression, motility, biofilm formation and virulence. In this study, two approaches were used to identify genes regulated by the CepIR quorum sensing system. Transposon mutagenesis was used to create lacZ promoter fusions in a cepI mutant that were screened for differential expression in the presence of N-acylhomoserine lactones. A bioinformatics approach was used to screen the B. cenocepacia J2315 genome for CepR binding site motifs. RESULTS: Four positively regulated and two negatively regulated genes were identified by transposon mutagenesis including genes potentially involved in iron transport and virulence. The promoter regions of selected CepR regulated genes and site directed mutagenesis of the cepI promoter were used to predict a consensus cep box sequence for CepR binding. The first-generation consensus sequence for the cep box was used to identify putative cep boxes in the genome sequence. Eight potential CepR regulated genes were chosen and the expression of their promoters analyzed. Six of the eight were shown to be regulated by CepR. A second generation motif was created from the promoters of these six genes in combination with the promoters of cepI, zmpA, and two of the CepR regulated genes identified by transposon mutagenesis. A search of the B. cenocepacia J2315 genome with the new motif identified 55 cep boxes in 65 promoter regions that may be regulated by CepR. CONCLUSION: Using transposon mutagenesis and bioinformatics expression of twelve new genes have been determined to be regulated by the CepIR quorum sensing system. A cep box consensus sequence has been developed based on the predicted cep boxes of ten CepR regulated genes. This consensus cep box has led to the identification of over 50 new genes potentially regulated by the CepIR quorum sensing system.

4-Butyrolactone↗

Computational framework for the prediction of transcription factor binding sites by multiple data integration.

Control of gene expression is essential to the establishment and maintenance of all cell types, and its dysregulation is involved in pathogenesis of several diseases. Accurate computational predictions of transcription factor regulation may thus help in understanding complex diseases, including mental disorders in which dysregulation of neural gene expression is thought to play a key role. However, biological mechanisms underlying the regulation of gene expression are not completely understood, and predictions via bioinformatics tools are typically poorly specific. We developed a bioinformatics workflow for the prediction of transcription factor binding sites from several independent datasets. We show the advantages of integrating information based on evolutionary conservation and gene expression, when tackling the problem of binding site prediction. Consistent results were obtained on a large simulated dataset consisting of 13050 in silico promoter sequences, on a set of 161 human gene promoters for which binding sites are known, and on a smaller set of promoters of Myc target genes. Our computational framework for binding site prediction can integrate multiple sources of data, and its performance was tested on different datasets. Our results show that integrating information from multiple data sources, such as genomic sequence of genes' promoters, conservation over multiple species, and gene expression data, indeed improves the accuracy of computational predictions.

Animals↗

Comparison of transcripts in Phalaenopsis bellina and Phalaenopsis equestris (Orchidaceae) flowers to deduce monoterpene biosynthesis pathway.

BACKGROUND: Floral scent is one of the important strategies for ensuring fertilization and for determining seed or fruit set. Research on plant scents has hampered mainly by the invisibility of this character, its dynamic nature, and complex mixtures of components that are present in very small quantities. Most progress in scent research, as in other areas of plant biology, has come from the use of molecular and biochemical techniques. Although volatile components have been identified in several orchid species, the biosynthetic pathways of orchid flower fragrance are far from understood. We investigated how flower fragrance was generated in certain Phalaenopsis orchids by determining the chemical components of the floral scent, identifying floral expressed-sequence-tags (ESTs), and deducing the pathways of floral scent biosynthesis in Phalaneopsis bellina by bioinformatics analysis. RESULTS: The main chemical components in the P. bellina flower were shown by gas chromatography-mass spectrometry to be monoterpenoids, benzenoids and phenylpropanoids. The set of floral scent producing enzymes in the biosynthetic pathway from glyceraldehyde-3-phosphate (G3P) to geraniol and linalool were recognized through data mining of the P. bellina floral EST database (dbEST). Transcripts preferentially expressed in P. bellina were distinguished by comparing the scent floral dbEST to that of a scentless species, P. equestris, and included those encoding lipoxygenase, epimerase, diacylglycerol kinase and geranyl diphosphate synthase. In addition, EST filtering results showed that transcripts encoding signal transduction and Myb transcription factors and methyltransferase, in addition to those for scent biosynthesis, were detected by in silico hybridization of the P. bellina unigene database against those of the scentless species, rice and Arabidopsis. Altogether, we pinpointed 66% of the biosynthetic steps from G3P to geraniol, linalool and their derivatives. CONCLUSION: This systems biology program combined chemical analysis, genomics and bioinformatics to elucidate the scent biosynthesis pathway and identify the relevant genes. It integrates the forward and reverse genetic approaches to knowledge discovery by which researchers can study non-model plants.

Acyclic Monoterpenes↗

A homology model of restriction endonuclease SfiI in complex with DNA.

BACKGROUND: Restriction enzymes (REases) are commercial reagents commonly used in recombinant DNA technologies. They are attractive models for studying protein-DNA interactions and valuable targets for protein engineering. They are, however, extremely divergent: the amino acid sequence of a typical REase usually shows no detectable similarities to any other proteins, with rare exceptions of other REases that recognize identical or very similar sequences. From structural analyses and bioinformatics studies it has been learned that some REases belong to at least four unrelated and structurally distinct superfamilies of nucleases, PD-DxK, PLD, HNH, and GIY-YIG. Hence, they are extremely hard targets for structure prediction and homology-based inference of sequence-function relationships and the great majority of REases remain structurally and evolutionarily unclassified. RESULTS: SfiI is a REase which recognizes the interrupted palindromic sequence 5'GGCCNNNN--NGGCC3' and generates 3 nt long 3' overhangs upon cleavage. SfiI is an archetypal Type IIF enzyme, which functions as a tetramer and cleaves two copies of the recognition site in a concerted manner. Its sequence shows no similarity to other proteins and nothing is known about the localization of its active site or residues important for oligomerization. Using the threading approach for protein fold-recognition, we identified a remote relationship between SfiI and BglI, a dimeric Type IIP restriction enzyme from the PD-DxK superfamily of nucleases, which recognizes the 5'GCCNNNN--NGGC3' sequence and whose structure in complex with the substrate DNA is available. We constructed a homology model of SfiI in complex with its target sequence and used it to predict residues important for dimerization, tetramerization, DNA binding and catalysis. CONCLUSIONS: The bioinformatics analysis suggest that SfiI, a Type IIF enzyme, is more closely related to BglI, an "orthodox" Type IIP restriction enzyme, than to any other REase, including other Type IIF REases with known structures, such as NgoMIV. NgoMIV and BglI belong to two different, very remotely related branches of the PD-DxK superfamily: the alpha-class (EcoRI-like), and the beta-class (EcoRV-like), respectively. Thus, our analysis provides evidence that the ability to tetramerize and cut the two DNA sequences in a concerted manner was developed independently at least two times in the evolution of the PD-DxK superfamily of REases. The model of SfiI will also serve as a convenient platform for further experimental analyses.

Amino Acid Sequence↗

Construction and use of Plasmodium falciparum phage display libraries to identify host parasite interactions.

BACKGROUND: The development of Plasmodium falciparum within human erythrocytes induces a wide array of changes in the ultrastructure, function and antigenic properties of the host cell. Numerous proteins encoded by the parasite have been shown to interact with the erythrocyte membrane. The identification of new interactions between human erythrocyte and P. falciparum proteins has formed a key area of malaria research. To circumvent the difficulties provided by conventional protein techniques, a novel application of the phage display technology was utilised. METHODS: P. falciparum phage display libraries were created and biopanned against purified erythrocyte membrane proteins. The identification of interacting and in-frame amino acid sequences was achieved by sequencing parasite cDNA inserts and performing bioinformatic analyses in the PlasmoDB database. RESULTS: Following four rounds of biopanning, sequencing and bioinformatic investigations, seven P. falciparum proteins with significant binding specificity toward human erythrocyte spectrin and protein 4.1 were identified. The specificity of these P. falciparum proteins were demonstrated by the marked enrichment of the respective in-frame binding sequences from a fourth round phage display library. CONCLUSION: The construction and biopanning of P. falciparum phage display expression libraries provide a novel approach for the identification of new interactions between the parasite and the erythrocyte membrane.

Journal Article↗

Identification of conserved regulatory elements by comparative genome analysis.

BACKGROUND: For genes that have been successfully delineated within the human genome sequence, most regulatory sequences remain to be elucidated. The annotation and interpretation process requires additional data resources and significant improvements in computational methods for the detection of regulatory regions. One approach of growing popularity is based on the preferential conservation of functional sequences over the course of evolution by selective pressure, termed 'phylogenetic footprinting'. Mutations are more likely to be disruptive if they appear in functional sites, resulting in a measurable difference in evolution rates between functional and non-functional genomic segments. RESULTS: We have devised a flexible suite of methods for the identification and visualization of conserved transcription-factor-binding sites. The system reports those putative transcription-factor-binding sites that are both situated in conserved regions and located as pairs of sites in equivalent positions in alignments between two orthologous sequences. An underlying collection of metazoan transcription-factor-binding profiles was assembled to facilitate the study. This approach results in a significant improvement in the detection of transcription-factor-binding sites because of an increased signal-to-noise ratio, as demonstrated with two sets of promoter sequences. The method is implemented as a graphical web application, ConSite, which is at the disposal of the scientific community at http://www.phylofoot.org/. CONCLUSIONS: Phylogenetic footprinting dramatically improves the predictive selectivity of bioinformatic approaches to the analysis of promoter sequences. ConSite delivers unparalleled performance using a novel database of high-quality binding models for metazoan transcription factors. With a dynamic interface, this bioinformatics tool provides broad access to promoter analysis with phylogenetic footprinting.

Algorithms↗

Update on genome completion and annotations: Protein Information Resource.

The Protein Information Resource (PIR) recently joined the European Bioinformatics Institute (EBI) and Swiss Institute of Bioinformatics (SIB) to establish UniProt--the Universal Protein Resource--which now unifies the PIR, Swiss-Prot and TrEMBL databases. The PIRSF (SuperFamily) classification system is central to the PIR/UniProt functional annotation of proteins, providing classifications of whole proteins into a network structure to reflect their evolutionary relationships. Data integration and associative studies of protein family, function and structure are supported by the iProClass database, which offers value-added descriptions of all UniProt proteins with highly informative links to more than 50 other databases. The PIR system allows consistent, rich and accurate protein annotation for all investigators.

Animals↗

EST-PAC a web package for EST annotation and protein sequence prediction.

With the decreasing cost of DNA sequencing technology and the vast diversity of biological resources, researchers increasingly face the basic challenge of annotating a larger number of expressed sequences tags (EST) from a variety of species. This typically consists of a series of repetitive tasks, which should be automated and easy to use. The results of these annotation tasks need to be stored and organized in a consistent way. All these operations should be self-installing, platform independent, easy to customize and amenable to using distributed bioinformatics resources available on the Internet. In order to address these issues, we present EST-PAC a web oriented multi-platform software package for expressed sequences tag (EST) annotation. EST-PAC provides a solution for the administration of EST and protein sequence annotations accessible through a web interface. Three aspects of EST annotation are automated: 1) searching local or remote biological databases for sequence similarities using Blast services, 2) predicting protein coding sequence from EST data and, 3) annotating predicted protein sequences with functional domain predictions. In practice, EST-PAC integrates the BLASTALL suite, EST-Scan2 and HMMER in a relational database system accessible through a simple web interface. EST-PAC also takes advantage of the relational database to allow consistent storage, powerful queries of results and, management of the annotation process. The system allows users to customize annotation strategies and provides an open-source data-management environment for research and education in bioinformatics.

Journal Article↗

From microarrays to genome duplications.

A report on the fifth annual conference of the Society for Bioinformatics in the Nordic Countries (SOCBIN), 'Bioinformatics 2003', Helsinki, Finland, 22-24 May 2003.

Animals↗