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An optimized protocol for analysis of EST sequences.

The vast body of Expressed Sequence Tag (EST) data in the public databases provide an important resource for comparative and functional genomics studies and an invaluable tool for the annotation of genomic sequences. We have developed a rigorous protocol for reconstructing the sequences of transcribed genes from EST and gene sequence fragments. A key element in developing this protocol has been the evaluation of a number of sequence assembly programs to determine which most faithfully reproduce transcript sequences from EST data. The TIGR Gene Indices constructed using this protocol for human, mouse, rat and a variety of other plant and animal models have demonstrated their utility in a variety of applications and are freely available to the scientific research community.

Algorithms↗

Patome: a database server for biological sequence annotation and analysis in issued patents and published patent applications.

With the advent of automated and high-throughput techniques, the number of patent applications containing biological sequences has been increasing rapidly. However, they have attracted relatively little attention compared to other sequence resources. We have built a database server called Patome, which contains biological sequence data disclosed in patents and published applications, as well as their analysis information. The analysis is divided into two steps. The first is an annotation step in which the disclosed sequences were annotated with RefSeq database. The second is an association step where the sequences were linked to Entrez Gene, OMIM and GO databases, and their results were saved as a gene-patent table. From the analysis, we found that 55% of human genes were associated with patenting. The gene-patent table can be used to identify whether a particular gene or disease is related to patenting. Patome is available at http://www.patome.org/; the information is updated bimonthly.

Amino Acid Sequence↗

The Biomolecular Interaction Network Database and related tools 2005 update.

The Biomolecular Interaction Network Database (BIND) (http://bind.ca) archives biomolecular interaction, reaction, complex and pathway information. Our aim is to curate the details about molecular interactions that arise from published experimental research and to provide this information, as well as tools to enable data analysis, freely to researchers worldwide. BIND data are curated into a comprehensive machine-readable archive of computable information and provides users with methods to discover interactions and molecular mechanisms. BIND has worked to develop new methods for visualization that amplify the underlying annotation of genes and proteins to facilitate the study of molecular interaction networks. BIND has maintained an open database policy since its inception in 1999. Data growth has proceeded at a tremendous rate, approaching over 100 000 records. New services provided include a new BIND Query and Submission interface, a Standard Object Access Protocol service and the Small Molecule Interaction Database (http://smid.blueprint.org) that allows users to determine probable small molecule binding sites of new sequences and examine conserved binding residues.

Animals↗

Pre- and intraoperative processing and integration of various anatomical and functional data in neurosurgery.

A software system is presented, capable of integrating various information sources for neurosurgical procedures. These include anatomical data such as a standard 3D DICOM image stacks, atlas data, as well as functional information (e.g. fmri, MEG, EEG). The system is programmed in C++ using Open GL for visualisation, and was developed in a close cooperation with a neurosurgical department to match existing needs. Preoperatively the data may be combined, registered by a rigid or elastic matching process, enriched by user specified planning information such as annotations or trajectories, and visualised in a standard fashion using different segmentation schemes, interactive rotation, zooming etc. Selected portions of the gathered and generated information may then be exported for neuronavigation input in DICOM or a vendor specific format. Intraoperatively, this information may, on the one hand, be simply used as an integrational part of the routinely used navigational data. On the other hand, the system is also capable of interacting with the navigational system to integrate the actual spatial information of the ongoing procedure into the preoperative data, thus allowing further planning and visualisation beyond the scope of the navigational unit. Furthermore, intraoperatively updated information such as intraoperative MR images or electrophysiological data may be integrated and correlated to the existing information. Ongoing developments comprise redistribution of the relevant data for injection onto the screen of the navigational system or into the optical pathway of the (3D capable) microscope display/ocular. This also includes information about the actual automatically optimized accuracy of the navigation process in relation to the head markers in use.

Humans↗

Prostate cancer expression profiling by cDNA sequencing analysis.

Prostate cancer is a frequently diagnosed solid tumor that is originated mostly from prostate epithelium. One of the key issues in prostate cancer research is to develop molecular markers that can effectively detect and distinguish the progression and malignancy of prostate tumors. Automated, single-pass cDNA sequencing was utilized to rapidly identify expressed genes in a number of cDNA libraries constructed from various normal and tumor prostatic tissues. These included cell lines as well as short-term epithelial culture. A total of 6604 expressed sequence tags (ESTs) were generated and searched against on-line nucleotide and protein databases. A relational database centric software system was constructed to process, store, and analyze EST data rapidly. cDNA contigs were also obtained by assembly of multiple EST sequences. Protein structural signatures were annotated using motif analysis tools including BLOCKS and an in-house-designed neural network. Cross-library comparisons revealed their unique gene expression profiles. Several differentially expressed cDNA clones were identified, and their expression patterns were confirmed by RNA dot blot and RT-PCR analyses.

Cell Line↗

New friendly tools for users of ESTHER, the database of the alpha/beta-hydrolase fold superfamily of proteins.

The structural alpha/beta-hydrolase fold is characterized by a beta-sheet core of five to eight strands connected by alpha-helices to form a alpha/beta/alpha sandwich. The superfamily members, exemplified by the cholinesterases, diverged from a common ancestor into a number of hydrolytic enzymes displaying a wide range of substrate specificities, along with proteins with no recognized hydrolytic activity. In the enzymes, the catalytic triad residues are presented on loops of which one, the nucleophile elbow, is the most conserved feature of the fold. Of the other proteins, which all lack from one to all of the catalytic residues, some may simply be 'inactive' enzymes while others have been shown to be involved in heterologous surface recognition functions. The ESTHER (for esterases, alpha/beta-hydrolase enzymes and relatives) database (http://bioweb.ensam.inra.fr.esther) gathers and annotates all the published pieces of information (gene and protein sequences; biochemical, pharmacological, and structural data) related to the superfamily, and connects them together to provide the bases for studying structure-function relationships within the superfamily. The most recent developments of the database are presented.

Cholinesterases↗

Microarrays as validation strategies in clinical samples: tissue and protein microarrays.

The widespread use of DNA microarrays has led to the discovery of many genes whose expression profile may have significant clinical relevance. The translation of this data to the bedside requires that gene expression be validated as protein expression, and that annotated clinical samples be available for correlative and quantitative studies to assess clinical context and usefulness of putative biomarkers. We review two microarray platforms developed to facilitate the clinical validation of candidate biomarkers: tissue microarrays and reverse-phase protein microarrays. Tissue microarrays are arrays of core biopsies obtained from paraffin-embedded tissues, which can be assayed for histologically-specific protein expression by immunohistochemistry. Reverse-phase protein microarrays consist of arrays of cell lysates or, more recently, plasma or serum samples, which can be assayed for protein quantity and for the presence of post-translational modifications such as phosphorylation. Although these platforms are limited by the availability of validated antibodies, both enable the preservation of precious clinical samples as well as experimental standardization in a high-throughput manner proper to microarray technologies. While tissue microarrays are rapidly becoming a mainstay of translational research, reverse-phase protein microarrays require further technical refinements and validation prior to their widespread adoption by research laboratories.

Animals↗

ClutrFree: cluster tree visualization and interpretation.

UNLABELLED: ClutrFree facilitates the visualization and interpretation of clusters or patterns computed from microarray data through a graphical user interface that displays patterns, membership information of the genes and annotation statistics simultaneously. ClutrFree creates a tree linking the patterns based on similarity, permitting the navigation among patterns identified by different algorithms or by the same algorithm with different parameters, and aids the inferring of conclusions from a microarray experiment. AVAILABILITY: The ClutrFree Java source code and compiled bytecode are available as a package under the GNU General Public License at http://bioinformatics.fccc.edu

Algorithms↗

PROTEIOS: an open source proteomics initiative.

SUMMARY: PROTEIOS is an initiative for the development of a comprehensive open source system for storage, organization, analysis and annotation of proteomics experiments. The PROTEIOS platform is based on commonly acknowledged principles for proteomics data publishing. AVAILABILITY: http://www.proteios.org

Algorithms↗

CARRIE web service: automated transcriptional regulatory network inference and interactive analysis.

We present an intuitive and interactive web service for CARRIE (Computational Ascertainment of Regulatory Relationships Inferred from Expression). CARRIE is a computational method that analyzes microarray and promoter sequence data to infer a transcriptional regulatory network from the response to a specific stimulus. This service displays an interactive graph of the inferred network and provides easy access to the evidence for the involvement of each gene in the network. We provide functionality to include network data in KEGG XML (KGML) format in this graph. Our service also provides Gene Ontology annotation to aid the user in forming hypotheses about the role of each gene in the cellular response. The CARRIE web service is freely available at http://zlab.bu.edu/CARRIE-web.

Binding Sites↗

CRITICA: coding region identification tool invoking comparative analysis.

Gene recognition is essential to understanding existing and future DNA sequence data. CRITICA (Coding Region Identification Tool Invoking Comparative Analysis) is a suite of programs for identifying likely protein-coding sequences in DNA by combining comparative analysis of DNA sequences with more common noncomparative methods. In the comparative component of the analysis, regions of DNA are aligned with related sequences from the DNA databases; if the translation of the aligned sequences has greater amino acid identity than expected for the observed percentage nucleotide identity, this is interpreted as evidence for coding. CRITICA also incorporates noncomparative information derived from the relative frequencies of hexanucleotides in coding frames versus other contexts (i.e., dicodon bias). The dicodon usage information is derived by iterative analysis of the data, such that CRITICA is not dependent on the existence or accuracy of coding sequence annotations in the databases. This independence makes the method particularly well suited for the analysis of novel genomes. CRITICA was tested by analyzing the available Salmonella typhimurium DNA sequences. Its predictions were compared with the DNA sequence annotations and with the predictions of GenMark. CRITICA proved to be more accurate than GenMark, and moreover, many of its predictions that would seem to be errors instead reflect problems in the sequence databases. The source code of CRITICA is freely available by anonymous FTP (rdp.life.uiuc.edu in/pub/critica) and on the World Wide Web (http:/(/)rdpwww.life.uiuc.edu).

Algorithms↗

Plant-based microarray data at the European Bioinformatics Institute. Introducing AtMIAMExpress, a submission tool for Arabidopsis gene expression data to ArrayExpress.

ArrayExpress is a public microarray repository founded on the Minimum Information About a Microarray Experiment (MIAME) principles that stores MIAME-compliant gene expression data. Plant-based data sets represent approximately one-quarter of the experiments in ArrayExpress. The majority are based on Arabidopsis (Arabidopsis thaliana); however, there are other data sets based on Triticum aestivum, Hordeum vulgare, and Populus subsp. AtMIAMExpress is an open-source Web-based software application for the submission of Arabidopsis-based microarray data to ArrayExpress. AtMIAMExpress exports data in MAGE-ML format for upload to any MAGE-ML-compliant application, such as J-Express and ArrayExpress. It was designed as a tool for users with minimal bioinformatics expertise, has comprehensive help and user support, and represents a simple solution to meeting the MIAME guidelines for the Arabidopsis community. Plant data are queryable both in ArrayExpress and in the Data Warehouse databases, which support queries based on gene-centric and sample-centric annotation. The AtMIAMExpress submission tool is available at http://www.ebi.ac.uk/at-miamexpress/. The software is open source and is available from http://sourceforge.net/projects/miamexpress/. For information, contact miamexpress@ebi.ac.uk.

Academies and Institutes↗

Systematic genome-wide approach to positional candidate cloning for identification of novel human disease genes.

BACKGROUND: Recent large-scale genome projects afford a unique opportunity to identify many novel disease genes and thereby better understand the genetic basis of human disease. Functional Annotation of Mouse (FANTOM) 2, the largest mouse transcriptome project yet, provides a wealth of data on novel genes, splice variants and non-coding RNA, and provides a unique opportunity to identify novel human disease genes. AIMS: To demonstrate the power of combining the FANTOM 2 cDNA dataset with a positional candidate approach and bioinformatics analysis to identify genes underlying human genetic disease. RESULTS: By mapping all FANTOM 2 cDNA to the human genome, we were able to identify mouse clones that co-localised on the human genome with mapped but uncloned human disease loci. By this method we identified mouse and corresponding human genes mapping within the loci of 100 different human genetic diseases (mapped interval of <5 cM). Of particular interest was the elucidation through FANTOM 2 novel mouse gene data of candidate human genes for the following: (i) developmental -disorders: neural tube defect, Meckel syndrome, Wolf--Hirschhorn syndrome and keratosis follicularis spinulosa decalvans cum ophiasi; (ii) neurological disorders: benign familial infantile convulsions 3, early-onset cerebellar ataxia with retained tendon reflexes, infantile-onset spinocerebellar ataxia and vacuolar neuro-myopathy and (iii) cancer-related syndromes: tylosis with oesophageal cancer and low-grade B-cell chronic lymphatic leukaemia. CONCLUSIONS: The FANTOM 2 data will dramatically accelerate efforts to identify genes underlying human disease. It will also facilitate the creation of transgenic mouse models to help elucidate the function of potential human disease genes.

Animals↗

UNITE: a database providing web-based methods for the molecular identification of ectomycorrhizal fungi.

Identification of ectomycorrhizal (ECM) fungi is often achieved through comparisons of ribosomal DNA internal transcribed spacer (ITS) sequences with accessioned sequences deposited in public databases. A major problem encountered is that annotation of the sequences in these databases is not always complete or trustworthy. In order to overcome this deficiency, we report on UNITE, an open-access database. UNITE comprises well annotated fungal ITS sequences from well defined herbarium specimens that include full herbarium reference identification data, collector/source and ecological data. At present UNITE contains 758 ITS sequences from 455 species and 67 genera of ECM fungi. UNITE can be searched by taxon name, via sequence similarity using blastn, and via phylogenetic sequence identification using galaxie. Following implementation, galaxie performs a phylogenetic analysis of the query sequence after alignment either to pre-existing generic alignments, or to matches retrieved from a blast search on the UNITE data. It should be noted that the current version of UNITE is dedicated to the reliable identification of ECM fungi. The UNITE database is accessible through the URL http://unite.zbi.ee

DNA, Ribosomal Spacer↗

M-GCAT: interactively and efficiently constructing large-scale multiple genome comparison frameworks in closely related species.

BACKGROUND: Due to recent advances in whole genome shotgun sequencing and assembly technologies, the financial cost of decoding an organism's DNA has been drastically reduced, resulting in a recent explosion of genomic sequencing projects. This increase in related genomic data will allow for in depth studies of evolution in closely related species through multiple whole genome comparisons. RESULTS: To facilitate such comparisons, we present an interactive multiple genome comparison and alignment tool, M-GCAT, that can efficiently construct multiple genome comparison frameworks in closely related species. M-GCAT is able to compare and identify highly conserved regions in up to 20 closely related bacterial species in minutes on a standard computer, and as many as 90 (containing 75 cloned genomes from a set of 15 published enterobacterial genomes) in an hour. M-GCAT also incorporates a novel comparative genomics data visualization interface allowing the user to globally and locally examine and inspect the conserved regions and gene annotations. CONCLUSION: M-GCAT is an interactive comparative genomics tool well suited for quickly generating multiple genome comparisons frameworks and alignments among closely related species. M-GCAT is freely available for download for academic and non-commercial use at: http://alggen.lsi.upc.es/recerca/align/mgcat/intro-mgcat.html.

Algorithms↗

The intelligent data management system for toxicogenomics.

Toxicogenomics is now emerging as one of the most important genomic application because the toxicity test based on gene expression profiles is expected to be more precise and efficient than current histopathological approaches in a pre-clinical phase. One of the challenging issues in toxicogenomics is the construction of intelligent database management system which can deal with heterogeneous and complex data from many different experimental and information sources. TEST(Toxicogenomics for Efficient Safety Test) database is especially focused on the connectivity of heterogeneous data and the intelligent query system which enable users to obtain relevant useful information from the complex data sets. The database deals with four kinds of information; compound, histopathology, gene expression, and annotation information. Currently, TEST database maintains toxicogenomics information for 16 compounds, 45 microarrays, 190 animal experiments, and customized 4.8 K rat clone set. Our presented system is expected to be a good information source for studying of toxicology mechanism in the genome-wide level and can also be applied to the designing toxicity test chip.

Animals↗

The CATH protein family database: a resource for structural and functional annotation of genomes.

Over the last decade, there have been huge increases in the numbers of protein sequences and structures determined. In parallel, many methods have been developed for recognising similarities between these proteins, arising from their common evolutionary background, and for clustering such relatives into protein families. Here we review some of the protein family resources available to the biologist and describe how these can be used to provide structural and functional annotations for newly determined sequences. In particular we describe recent developments to the CATH domain database of protein structural families which have facilitated genome annotation and which have also revealed important caveats that must be considered when transferring functional data between homologous proteins.

Databases, Protein↗

Expression profiling by microarrays in colorectal cancer (Review).

Genome-wide gene profiling studies using microarrays have the potential to improve diagnosis and treatment of human cancers. Microarrays have identified many genes that are deregulated in colorectal cancer compared to normal tissue. Groups of genes that are predictive of tumor stage or presence of metastases, hence putatively associated with cancer progression have also been revealed. Microarray studies have identified genes whose expression are impacted by chemotherapies for colorectal cancer, thus could potentially be used to predict response to treatments. Unique gene expression profiles have also been used to classify metastases of uncertain origin. The wide application of microarrays generates exciting prospects in translational research. However, to date overlaps of candidate gene lists associated with specific clinical/biological phenotypes remain disturbingly poor between studies. Overfitting, bias, reporting of only the best results, and fidelity of probe annotations could present limitations for the interpretation of results shown in microarray publications. Making raw data from these microarray experiments publicly available for analysis by other investigators using different analytical algorithms or for in silico studies may facilitate the most thorough mining of data from these expensive studies. Validations of the results using other more precise techniques and at the biological level represent critical follow-up goals for microarray studies.

Adenoma↗