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At least 649 records · Page 36Linked to original sources

A multivariate approach for integrating genome-wide expression data and biological knowledge.

MOTIVATION: Several statistical methods that combine analysis of differential gene expression with biological knowledge databases have been proposed for a more rapid interpretation of expression data. However, most such methods are based on a series of univariate statistical tests and do not properly account for the complex structure of gene interactions. RESULTS: We present a simple yet effective multivariate statistical procedure for assessing the correlation between a subspace defined by a group of genes and a binary phenotype. A subspace is deemed significant if the samples corresponding to different phenotypes are well separated in that subspace. The separation is measured using Hotelling's T(2) statistic, which captures the covariance structure of the subspace. When the dimension of the subspace is larger than that of the sample space, we project the original data to a smaller orthonormal subspace. We use this method to search through functional pathway subspaces defined by Reactome, KEGG, BioCarta and Gene Ontology. To demonstrate its performance, we apply this method to the data from two published studies, and visualize the results in the principal component space.

Algorithms↗

Large-scale open bioinformatics data resources.

The data explosion in bioinformatics is relentless. More and more genomes are being sequenced and many new types of datasets are being generated in large-scale projects. Integration and true open access to the data are still difficult issues, although they are gradually being addressed. Notably, certain fields have good standardization and interoperability, while others lag behind. This review summarizes the latest developments in genome and sequences databases, transcriptomics data (ESTs, ORESTES, full-length cDNAs), proteomics data (protein databases, protein structures, family and domain classification) as well as loosely integrated fields, such as microarray experiments, mutation databases and databases of regulatory regions and elements. The review attempts to resist simply summarizing what data are available, and aims to provide a critical look at some of the integration and access issues associated with several of these resources.

Computational Biology↗

Comprehensive analysis of the mouse metabolome based on the transcriptome.

The complete set of cDNAs encoding the enzymes of known metabolic pathways has not previously been available for any mammal. Here, transcripts encoding the metabolic pathways of the mouse (mouse metabolome) were reconstructed by making use of the KEGG metabolic pathway database and gene ontology (GO) assignment to the mouse representative transcript and protein set (RTPS), which contains all available mouse transcript sequences including the FANTOM set of RIKEN mouse cDNA clones. By assigning EC numbers extracted from the molecular function ontology in GO, the known mouse transcriptome was predicted to encode enzymes with 726 unique EC numbers. Of these, 648 EC numbers were newly assigned based on the FANTOM set. The mouse metabolome confirmed by cDNA analysis includes almost all of the enzymes of well known pathways such as the tricarboxylic acid cycle and urea cycle. On the other hand, analysis of enzymes required for the tryptophan metabolism pathway revealed a lack of connectivity, indicating that cDNAs/genes encoding several key enzymes remain to be identified. The information derived from coexpression from the cDNA microarray analysis of enzymes of known function may lead to identification of the missing components of the metabolome, and will add new insights into the connectivity of the mammalian metabolic pathways.

Amino Acids↗

Sequence variation database project at the European Bioinformatics Institute.

The sequence variation project at EBI aims to create a unified resource for browsing and searching sequence differences. Technical advances in reading in new data types and in validating and cross-referencing entries are reported. It is suggested that the hardest problems in unifying mutation databases are related to intellectual property rights. The concept of copylefting is introduced as a potential solution to these.

Computational Biology↗

Dan Shen agents for acute ischaemic stroke.

BACKGROUND: Based mainly on experimental data which indicates improvement to the cerebral microcirculation, Dan Shen, a form of herbal medicine, is widely used in the treatment of acute ischaemic stroke in China. We aimed to assess the evidence from randomised controlled trials of their effects. OBJECTIVES: To review the randomised or quasi-randomised controlled trials of Dan Shen agents for acute ischaemic stroke. The primary objective was to determine whether Dan Shen agents improve functional outcome without causing undue harm in patients with acute ischaemic stroke. Secondary objectives were to assess the effect of Dan Shen agents on impairment and on quality of life. SEARCH STRATEGY: We searched the Cochrane Stroke Group Trials Register (last searched September 2003), the register of the Cochrane Complementary Field (last searched September 2003) and the Chinese Stroke Trials Register (last searched September 2003). In addition we searched the following bibliographic databases: The Cochrane Central Register of Controlled Trials (The Cochrane Library, Issue 4, 2002), MEDLINE (1996 to December 2002), EMBASE (1980 to December 2002), CINAHL (1982 to December 2002), AMED (1985 to December 2002) and China Biological Medicine Database (CBM-disc 1979 to December 2002). We handsearched 10 Chinese journals, searched clinical trials and research databases, scanned reference lists and contacted the pharmaceutical company manufacturing Dan Shen. SELECTION CRITERIA: Randomised controlled trials or quasi-randomised controlled clinical trials comparing Dan Shen agents with placebo or open control (no placebo) in patients with acute ischaemic stroke. DATA COLLECTION AND ANALYSIS: Two reviewers independently selected trials for inclusion, assessed trial quality and extracted the data. MAIN RESULTS: Eight potentially eligible trials were identified, of which three trials (304 patients) were included. Two trials were excluded and three trials are awaiting assessment. Numbers of deaths and dependent patients at the end of follow-up of at least three months were not reported in the three included trials. Only one trial reported adverse events. Three trials measured the outcome "significant improvement in neurological deficit at the end of treatment". Compound Dan Shen agents were associated with a significant increase in the number of patients with the outcome (Peto Odds Ratio (OR) 2.72, 95% Confidence Interval (CI) 1.10 to 6.72). No deaths were reported within the first two weeks of treatment or during the whole follow-up period (21 to 28 days). The trials did not include any assessment of quality of life. REVIEWERS' CONCLUSIONS: There were too few patients and outcome events to draw reliable conclusions from the present data. The methodological qualities of all included studies were poor. Further high-quality randomised controlled trials should be performed.

Acute Disease↗

Rice proteome analysis: a step toward functional analysis of the rice genome.

The technique of proteome analysis using 2-DE has the power to monitor global changes that occur in the protein complement of tissues and subcellular compartments. In this review, we describe construction of the rice proteome database, the cataloging of rice proteins, and the functional characterization of some of the proteins identified. Initially, proteins extracted from various tissues and organelles were separated by 2-DE and an image analyzer was used to construct a display or reference map of the proteins. The rice proteome database currently contains 23 reference maps based on 2-DE of proteins from different rice tissues and subcellular compartments. These reference maps comprise 13 129 rice proteins, and the amino acid sequences of 5092 of these proteins are entered in the database. Major proteins involved in growth or stress responses have been identified by using a proteomics approach and some of these proteins have unique functions. Furthermore, initial work has also begun on analyzing the phosphoproteome and protein-protein interactions in rice. The information obtained from the rice proteome database will aid in the molecular cloning of rice genes and in predicting the function of unknown proteins.

Calreticulin↗

Quantitative analysis of nucleic acid three-dimensional structures.

A new computer program to annotate DNA and RNA three-dimensional structures, MC-Annotate, is introduced. The goals of annotation are to efficiently extract and manipulate structural information, to simplify further structural analyses and searches, and to objectively represent structural knowledge. The input of MC-Annotate is a PDB formatted DNA or RNA three-dimensional structure. The output of MC-Annotate is composed of a structural graph that contains the annotations, and a series of HTML documents, one for each nucleotide conformation and base-base interaction present in the input structure. The atomic coordinates of all nucleotides and the homogeneous transformation matrices of all base-base interactions are stored in the structural graph. Symbolic classifications of nucleotide conformations, using sugar puckering modes and nitrogen base orientations around the glycosyl bond, and base-base interactions, using stacking and hydrogen bonding information, are introduced. Peculiarity factors of nucleotide conformations and base-base interactions are defined to indicate their marginalities with all other examples. The peculiarity factors allow us to identify irregular regions and possible stereochemical errors in 3-D structures without interactive visualization. The annotations attached to each nucleotide conformation include its class, its torsion angles, a distribution of the root-mean-square deviations with examples of the same class, the list of examples of the same class, and its peculiarity value. The annotations attached to each base-base interaction include its class, a distribution of distances with examples of the same class, the list of examples of the same class, and its peculiarity value. The distance between two homogeneous transformation matrices is evaluated using a new metric that distinguishes between the rotation and the translation of a transformation matrix in the context of nitrogen bases. MC-Annotate was used to build databases of nucleotide conformations and base-base interactions. It was applied to the ribosomal RNA fragment that binds to protein L11, which annotations revealed peculiar nucleotide conformations and base-base interactions in the regions where the RNA contacts the protein. The question of whether the current database of RNA three-dimensional structures is complete is addressed.

Base Pairing↗

Domain boundary prediction based on profile domain linker propensity index.

Successful prediction of protein domain boundaries provides valuable information not only for the computational structure prediction of multi-domain proteins but also for the experimental structure determination. In this work, a novel index at the profile level is presented, namely, the profile domain linker propensity index (PDLI), which uses the evolutionary information of profiles for domain linker prediction. The frequency profiles are directly calculated from the multiple sequence alignments outputted by PSI-BLAST and converted into binary profiles with a probability threshold. PDLI is then obtained by the frequencies of binary profiles in domain linkers as compared to those in domains. A smooth and normalized numeric profile is generated for any amino acid sequences from which the domain linkers can be predicted. Testing on the Structural Classification of Proteins (SCOP) database and CASP6 targets shows that PDLI outperforms other indexes at the amino acid level.

Computational Biology↗

Bioinformatics in glycobiology.

In comparison with genes and proteins, attention paid to oligosaccharides that modify proteins is still marginal. Accordingly, bioinformatics is so far poorly involved in glycobiology. Some initiatives have been taken, however, to collect in databases all glycobiology-relevant information or to design specific data mining algorithms to infer predictions or identify oligosaccharide structures. In this review, we make a non-exhaustive survey of the available glycobiology-related bioinformatic resources, focussing mainly on those resources that are available through the World Wide Web. Some well-curated databases are identified, but the development of specialised algorithms appears to be limited.

Algorithms↗

Evidence that public database records for many cancer-associated genes reflect a splice form found in tumors and lack normal splice forms.

Alternative splicing is widespread in the human genome, and it appears that many genes display different splice forms in cancerous tissue than in normal human tissues. However, since cDNAs for many cancer-associated genes were originally cloned from tumor samples, it is important to ask whether this repertoire of cDNAs provides a complete or representative picture of the transcript isoforms found in normal tissues. To answer this, we used bioinformatics and RT-PCR to identify novel splice forms, focusing on in-frame exonskips, for a panel of 50 cancer-associated genes in normal tissue samples. These data show that in nearly two-thirds of the genes, normal tissues expressed previously unknown splice forms, of which 40% were normally a dominant splice form. Surprisingly, the tumor-associated splice forms were twice as likely to be represented in GenBank than their normal tissue-associated splice forms, most likely because 70% of the mRNAs in GenBank for these genes were cloned from tumor samples. As an example, we describe a novel normal splice form of IKBbeta, an important regulator of the NFkappaB pathway. Our data suggest that systematic re-evaluation of cancer genes' splice forms in normal tissue will yield insights into their distinct functions in normal tissues and in cancer. Our database contains 1308 novel normal splice forms, including many known cancer genes.

Alternative Splicing↗

Compound library management.

The increasing size of the collections used for drug-discovery purposes has demanded both hardware and software automation of compound management in order to cope with the increasing demands of HTS. Splitting the collection into a number of copies in different formats is a desirable approach to keep a balance between rapid response to the demands and best storage conditions. Flexibility to different assay configurations can be provided with the appropriate selection of liquid handlers, and the informatic management systems should be accessible to keep track of the samples and link them to a variety of information that can help interpret HTS data. In this respect, QC data on the compounds and quality checks of the equipment used are highly desirable. It is also prudent for a large organization with different research sites to have a unified database and compatible plate format and concentration in order to be able to exchange samples and share screening results. The accomplishment of all the previous requirements is the only way to ensure an efficient and effective compound library management.

Computational Biology↗

Cancer gene discovery using digital differential display.

The Cancer Gene Anatomy Project database of the National Cancer Institute has thousands of expressed sequences, both known and novel, in the form of expressed sequence tags (ESTs). These ESTs, derived from diverse normal and tumor cDNA libraries, offer an attractive starting point for cancer gene discovery. Using a data-mining tool called Digital Differential Display (DDD) from the Cancer Gene Anatomy Project database, ESTs from six different solid tumor types (breast, colon, lung, ovary, pancreas, and prostate) were analyzed for differential expression. An electronic expression profile and chromosomal map position of these hits were generated from the Unigene database. The hits were categorized into major classes of genes including ribosomal proteins, enzymes, cell surface molecules, secretory proteins, adhesion molecules, and immunoglobulins and were found to be differentially expressed in these tumorderived libraries. Genes known to be up-regulated in prostate, breast, and pancreatic carcinomas were discovered by DDD, demonstrating the utility of this technique. Two hundred known genes and 500 novel sequences were discovered to be differentially expressed in these select tumor-derived libraries. Test genes were validated for expression specificity by reverse transcription-PCR, providing a proof of concept for gene discovery by DDD. A comprehensive database of hits can be accessed at http:// www.fau.edu/cmbb/publications/cancergenes. htm. This solid tumor DDD database should facilitate target identification for cancer diagnostics and therapeutics.

Biological Specimen Banks↗

Support vector machines for novel class detection in Bioinformatics.

Novelty detection techniques might be a promising way of dealing with high-dimensional classification problems in Bioinformatics. We present preliminary results of the use of a one-class support vector machine approach to detect novel classes in two Bioinformatics databases. The results are compatible with theory and inspire further investigation.

Artificial Intelligence↗

ASD: a bioinformatics resource on alternative splicing.

Alternative splicing is an important regulatory mechanism of mammalian gene expression. The alternative splicing database (ASD) consortium is systematically collecting and annotating data on alternative splicing. We present the continuation and upgrade of the ASD [T. A. Thanaraj, S. Stamm, F. Clark, J. J. Riethoven, V. Le Texier, J. Muilu (2004) Nucleic Acids Res. 32, D64-D69] that consists of computationally and manually generated data. Its largest parts are AltSplice, a value-added database of computationally delineated alternative splicing events. Its data include alternatively spliced introns/exons, events, isoform splicing patterns and isoform peptide sequences. AltSplice data are generated by examining gene-transcript alignments. The data are annotated for various biological features including splicing signals, expression states, (SNP)-mediated splicing and cross-species conservation. AEdb forms the manually curated component of ASD. It is a literature-based data set containing sequence and properties of alternatively spliced exons, functional enumeration of observed splicing events, characterization of observed splicing regulatory elements, and a collection of experimentally clarified minigene constructs. ASD includes a workbench, which is an analysis tool that enables users to carry out splicing related analysis such as characterization of introns for various splicing signals, identification of splicing regulatory elements on a given RNA sequence, prediction of putative exons and prediction of putative translation start codons. The different ASD modules are integrated and can be accessed through user-friendly interfaces and visualization tools. ASD data has been integrated with Ensembl genome annotation project as a Distributed Annotation System (DAS) resource and can be viewed on Ensembl genome browser. The ASD resource is presented at (http://www.ebi.ac.uk/asd).

Alternative Splicing↗

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

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

Algorithms↗

Web resources for the carbohydrate chemist.

Bioinformatics has played a pivotal role in advancing genetics and protein sciences. The large amount of information generated by genomics, and now proteomics, has been a driving force. By comparison, glycobiology still generates small amounts of data. The need to organize our knowledge about carbohydrates is however growing constantly and has given rise to an increasing number of public databases and freely available tools. This review gives an overview of the carbohydrate-oriented resources currently available on the Internet. Many of the resources are seldom referred to in the literature and difficult to find, in part because of the constant flux of the net itself, but also because many efforts have been lead by a single individual. As the World Wide Web has matured the number of 'permanent' resources, maintained by organizations rather than individuals, has increased. In this paper, we present some of the more useful and accessible public tools and databases. There are also a few commercial initiatives but these have not been reviewed.

Biochemical Phenomena↗

Prospects for glycoinformatics.

High-throughput and automated techniques (mass spectrometry in particular) allow increasingly rapid structural analysis of complex glycans. Information concerning the primary structure (composition, sequence and linkages), three-dimensional structure (including dynamics) and interactions of glycans is now available in sufficient quantity to justify the maintenance of databases and search facilities. Several such resources (both commercial and open access) are now available as web tools. To derive the full value of glycan databases, it will be necessary to develop a universally accepted machine-readable structural representation of glycans.

Animals↗

Enabling the exploration of biochemical pathways.

The Biochemical Pathways Wall Chart (http://www.expasy.org/tools/pathways/ref.1) has been converted into a molecule and reaction database. Major features of this database are that each molecule is represented by lists of all atoms and bonds (as connection tables), and in the reactions the reaction centre, the atoms and bonds directly involved in the bond rearrangement process, are marked. The information in the database has been enriched by a set of diverse 3D structure conformations generated by the programs CORINA and ROTATE. The web-based structure and reaction retrieval system C@ROL provides a wide range of search methods to mine this rich database. The database is accessible at http://www2.chemie.uni-erlangen.de/services/biopath/index.html and http://www.mol-net.de/databases/biopath.html .

Biochemical Phenomena↗