PubMed Health⌕ Search

SEARCH · PubMed Health

Results for “Biological databases”

Explore indexed PubMed citations for clinical trials, systematic reviews and public health research. Read source abstracts and follow each citation to its original PubMed record.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 541 records · Page 30Linked to original sources
PubMed2005

Assigning new GO annotations to protein data bank sequences by combining structure and sequence homology.

Accompanying the discovery of an increasing number of proteins, there is the need to provide functional annotation that is both highly accurate and consistent. The Gene Ontology (GO) provides consistent annotation in a computer readable and usable form; hence, GO annotation (GOA) has been assigned to a large number of protein sequences based on direct experimental evidence and through inference determined by sequence homology. Here we show that this annotation can be extended and corrected for cases where protein structures are available. Specifically, using the Combinatorial Extension (CE) algorithm for structure comparison, we extend the protein annotation currently provided by GOA at the European Bioinformatics Institute (EBI) to further describe the contents of the Protein Data Bank (PDB). Specific cases of biologically interesting annotations derived by this method are given. Given that the relationship between sequence, structure, and function is complicated, we explore the impact of this relationship on assigning GOA. The effect of superfolds (folds with many functions) is considered and, by comparison to the Structural Classification of Proteins (SCOP), the individual effects of family, superfamily, and fold.

Algorithms↗
PubMed2006

Identification of functional modules in a PPI network by clique percolation clustering.

Large-scale experiments and data integration have provided the opportunity to systematically analyze and comprehensively understand the topology of biological networks and biochemical processes in cells. Modular architecture which encompasses groups of genes/proteins involved in elementary biological functional units is a basic form of the organization of interacting proteins. Here we apply a graph clustering algorithm based on clique percolation clustering to detect overlapping network modules of a protein-protein interaction (PPI) network. Our analysis of the yeast Sacchromyces cerevisiae suggests that most of the detected modules correspond to one or more experimentally functional modules and half of these annotated modules match well with experimentally determined protein complexes. Our method of analysis can of course be applied to protein-protein interaction data for any species and even other biological networks.

Algorithms↗
PubMed2006

Essential genes on metabolic maps.

Within the past five years genome-scale gene essentiality data sets have been published for ten diverse bacterial species. These data are a rich source of information about cellular networks that we are only beginning to explore. The analysis of these data, very heterogeneous in nature, is a challenging task. Even the definition of 'essential genes' in various genome-scale studies varies from genes 'absolutely required for survival' to those 'strongly contributing to fitness' and robust competitive growth. A comparative analysis of gene essentiality across multiple organisms based on projection of experimentally observed essential genes to functional roles in a collection of metabolic pathways and subsystems is emerging as a powerful tool of systems biology.

Computational Biology↗
PubMed2006

Enrichment of OBO ontologies.

This paper describes a frame-based integration of the three GO subontologies, the Chemical Entities of Biological Interest ontology, and the Cell Type Ontology in which relationships are modeled in a way that better captures the semantics between biological concepts represented by the terms, rather than between the terms themselves, than previous frame-based efforts. We also describe a methodology for creating suggested enriching assertions by identifying patterns in GO terms, mapping these patterns to new, specific relationships, and matching term substrings to concepts. Using this methodology, a predicted assertion was made for 62% of GO terms that matched one of 31 patterns, and 97% of these predicted assertions were assessed to be valid, resulting in an initial set of over 4000 assertions. Furthermore, this methodology programmatically integrates assertions into an ontology such that each assertion is fully consistent with respect to higher (i.e., more general) relevant class and slot levels.

Computational Biology↗
PubMed2003

Motif-based construction of a functional map for mammalian olfactory receptors.

We applied an automatic and unsupervised system to a nearly complete database of mammalian odor receptor genes. The generated motifs and gene classification were subjected to extensive and systematic downstream analysis to obtain biological insights. Two major results from this analysis were: (1) a map of sequence motifs that may correlate with function and (2) the corresponding receptor classes in which members of each class are likely to share specific functions. We have discovered motifs that have been implicated in structural integrity and posttranslational modification, as well as motifs very likely to be directly involved in ligand binding. We further propose a combinatorial molecular hypothesis, based on unique combinations of the observed motifs, that provides a foundation for understanding the generation of a large number of ligand binding sites.

Amino Acid Motifs↗
PubMed2004

Global network analysis of phenotypic effects: protein networks and toxicity modulation in Saccharomyces cerevisiae.

Using genome-wide information to understand holistically how cells function is a major challenge of the postgenomic era. Recent efforts to understand molecular pathway operation from a global perspective have lacked experimental data on phenotypic context, so insights concerning biologically relevant network characteristics of key genes or proteins have remained largely speculative. Here, we present a global network investigation of the genotype/phenotype data set we developed for the recovery of the yeast Saccharomyces cerevisiae from exposure to DNA-damaging agents, enabling explicit study of how protein-protein interaction network characteristics may be associated with phenotypic functional effects. We show that toxicity-modulating proteins have similar topological properties as essential proteins, suggesting that cells initiate highly coordinated responses to damage similar to those needed for vital cellular functions. We also identify toxicologically important protein complexes, pathways, and modules. These results have potential implications for understanding toxicity-modulating processes relevant to a number of human diseases, including cancer and aging.

Cluster Analysis↗
PubMed2006

Review: on the analysis and interpretation of correlations in metabolomic data.

A remarkable inherent feature of cellular metabolism is that the concentrations of a small but significant number of metabolites are strongly correlated when measurements of biological replicates are performed. This review seeks to summarize the recent efforts to elucidate the origin of these observed correlations and points out several aspects concerning their interpretation. It is argued that correlations between metabolites differ profoundly from their transcriptomic and proteomic counterparts, and a straightforward interpretation in terms of the underlying biochemical pathways will unavoidably fail. It is demonstrated that the comparative correlations analysis offers a way to exploit the observed correlations to obtain additional information about the physiological state of the system.

Animals↗
PubMed2001

ARED: human AU-rich element-containing mRNA database reveals an unexpectedly diverse functional repertoire of encoded proteins.

The adenylate uridylate-rich elements (AREs) mediate the rapid turnover of mRNAs encoding proteins that regulate cellular growth and body response to exogenous agents such as microbes, inflammatory and environmental stimuli. However, the full repertoire of ARE-containing mRNAs is unknown. Here, we explore the distribution of AREs in human mRNA sequences. Computational derivation of a 13-bp ARE pattern was performed using multiple expectation maximization for motif elicitations (MEME) and consensus analyses. This pattern was statistically validated for the specificity towards the 3'-untranslated region and not coding region. The computationally derived ARE pattern is the basis of a database which contains non-redundant full-length ARE-mRNAs. The ARE-mRNA database (ARED; http://rc.kfshrc.edu.sa/ared) reveals that ARE-mRNAs encode a wide repertoire of functionally diverse proteins that belong to different biological processes and are important in several disease states. Cluster analysis was performed using the ARE sequences to demonstrate potential relationships between the type and number of ARE motifs, and the functional characteristics of the proteins.

Adenosine↗
PubMed2004

ASD: the Alternative Splicing Database.

Alternative splicing is widespread in mammalian gene expression, and variant splice patterns are often specific to different stages of development, particular tissues or a disease state. There is a need to systematically collect data on alternatively spliced exons, introns and splice isoforms, and to annotate this data. The Alternative Splicing Database consortium has been addressing this need, and is committed to maintaining and developing a value-added database of alternative splice events, and of experimentally verified regulatory mechanisms that mediate splice variants. In this paper we present two of the products from this project: namely, a database of computationally delineated alternative splice events as seen in alignments of EST/cDNA sequences with genome sequences, and a database of alternatively spliced exons collected from literature. The reported splice events are from nine different organisms and are annotated for various biological features including expression states and cross-species conservation. The data are presented on our ASD web pages (http://www.ebi.ac.uk/asd).

Alternative Splicing↗
PubMed2006

Apoptosis Gene Information System--AGIS.

Genes implicated in apoptosis have great relevance to biology, medicine and oncology. Here, we describe a unique resource, Apoptosis Gene Information System (AGIS) that provides data for over 2400 genes involved directly or indirectly, in apoptotic pathways of more than 350 different organisms. The organization of this information system is based on the principle of one-gene, one record. AGIS will be updated on a six monthly basis as new information becomes available. AGIS can be accessed at: http://www.cellfate.org/AGIS/.

Amino Acid Sequence↗
PubMed2004

GOChase: correcting errors from Gene Ontology-based annotations for gene products.

SUMMARY: The Gene Ontology (GO) is a controlled biological vocabulary that provides three structured networks of terms to describe biological processes, cellular components and molecular functions. Many databases of gene products are annotated using the GO vocabularies. We found that some GO-updating operations are not easily traceable by the current biological databases and GO browsers. Consequently, numerous annotation errors arise and are propagated throughout biological databases and GO-based high-level analyses. GOChase is a set of web-based utilities to detect and correct the errors in GO-based annotations.

Database Management Systems↗
PubMed2006

Addressing the problems with life-science databases for traditional uses and systems biology.

A prerequisite to systems biology is the integration of heterogeneous experimental data, which are stored in numerous life-science databases. However, a wide range of obstacles that relate to access, handling and integration impede the efficient use of the contents of these databases. Addressing these issues will not only be essential for progress in systems biology, it will also be crucial for sustaining the more traditional uses of life-science databases.

Animals↗
PubMedDate not supplied

A bioinformatics perspective on proteomics: data storage, analysis, and integration.

The field of proteomics is advancing rapidly as a result of powerful new technologies and proteomics experiments yield a vast and increasing amount of information. Data regarding protein occurrence, abundance, identity, sequence, structure, properties, and interactions need to be stored. Currently, a common standard has not yet been established and open access to results is needed for further development of robust analysis algorithms. Databases for proteomics will evolve from pure storage into knowledge resources, providing a repository for information (meta-data) which is mainly not stored in simple flat files. This review will shed light on recent steps towards the generation of a common standard in proteomics data storage and integration, but is not meant to be a comprehensive overview of all available databases and tools in the proteomics community.

Computational Biology↗
PubMed2004

Symbolic inference of xenobiotic metabolism.

We present a new symbolic computational approach to elucidate the biochemical networks of living systems de novo and we apply it to an important biomedical problem: xenobiotic metabolism. A crucial issue in analyzing and modeling a living organism is understanding its biochemical network beyond what is already known. Our objective is to use the available metabolic information in a representational framework that enables the inference of novel biochemical knowledge and whose results can be validated experimentally. We describe a symbolic computational approach consisting of two parts. First, biotransformation rules are inferred from the molecular graphs of compounds in enzyme-catalyzed reactions. Second, these rules are recursively applied to different compounds to generate novel metabolic networks, containing new biotransformations and new metabolites. Using data for 456 generic reactions and 825 generic compounds from KEGG we were able to extract 110 biotransformation rules, which generalize a subset of known biocatalytic functions. We tested our approach by applying these rules to ethanol, a common substance of abuse and to furfuryl alcohol, a xenobiotic organic solvent, which is absent in metabolic databases. In both cases our predictions on the fate of ethanol and furfuryl alcohol are consistent with the literature on the metabolism of these compounds.

Algorithms↗
PubMed2004

The International Protein Index: an integrated database for proteomics experiments.

Despite the complete determination of the genome sequence of several higher eukaryotes, their proteomes remain relatively poorly defined. Information about proteins identified by different experimental and computational methods is stored in different databases, meaning that no single resource offers full coverage of known and predicted proteins. IPI (the International Protein Index) has been developed to address these issues and offers complete nonredundant data sets representing the human, mouse and rat proteomes, built from the Swiss-Prot, TrEMBL, Ensembl and RefSeq databases.

Animals↗