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At least 955 records · Page 53Linked to original sources
PubMed2003

Bioinformatics analysis of experimentally determined protein complexes in the yeast Saccharomyces cerevisiae.

Many important cellular functions are implemented by protein complexes that act as sophisticated molecular machines of varying size and temporal stability. Here we demonstrate quantitatively that protein complexes in the yeast Saccharomyces cerevisiae are comprised of a core in which subunits are highly coexpressed, display the same deletion phenotype (essential or nonessential), and share identical functional classification and cellular localization. This core is surrounded by a functionally mixed group of proteins, which likely represent short-lived or spurious attachments. The results allow us to define the deletion phenotype and cellular task of most known complexes, and to identify with high confidence the biochemical role of hundreds of proteins with yet unassigned functionality.

Computational Biology↗
PubMed2004

Specification of the peroxisome targeting signals type 1 and type 2 of plant peroxisomes by bioinformatics analyses.

To specify the C-terminal peroxisome targeting signal type 1 (PTS1) and the N-terminal PTS2 for higher plants, a maximum number of plant cDNAs and expressed sequence tags that are homologous to PTS1- and PTS2-targeted plant proteins was retrieved from the public databases and the primary structure of their targeting domains was analyzed for conserved properties. According to their high overall frequency in the homologs and their widespread occurence in different orthologous groups, nine major PTS1 tripeptides ([SA][RK][LM]> without AKM> plus SRI> and PRL>) and two major PTS2 nonapeptides (R[LI]x5HL) were defined that are considered good indicators for peroxisomal localization if present in unknown proteins. A lower but significant number of homologs contained 1 of 11 minor PTS1 tripeptides or of 9 minor PTS2 nonapeptides, many of which have not been identified before in plant peroxisomal proteins. The region adjacent to the PTS peptides was characterized by specific conserved properties as well, such as a pronounced incidence of basic and Pro residues and a high positive net charge, which probably play an auxiliary role in peroxisomal targeting. By contrast, several peptides with assumed peroxisomal targeting properties were not found in any of the 550 homologs and hence play--if at all--only a minor role in peroxisomal targeting. Based on the definition of these major and minor PTS and on the recognition of additional conserved properties, the accuracy of predicting peroxisomal proteins can be raised and plant genomes can be screened for novel proteins of peroxisomes more successfully.

Amino Acid Sequence↗
PubMed2005

An expression and bioinformatics analysis of the Arabidopsis serine carboxypeptidase-like gene family.

The Arabidopsis (Arabidopsis thaliana) genome encodes a family of 51 proteins that are homologous to known serine carboxypeptidases. Based on their sequences, these serine carboxypeptidase-like (SCPL) proteins can be divided into several major clades. The first group consists of 21 proteins which, despite the function implied by their annotation, includes two that have been shown to function as acyltransferases in plant secondary metabolism: sinapoylglucose:malate sinapoyltransferase and sinapoylglucose:choline sinapoyltransferase. A second group comprises 25 SCPL proteins whose biochemical functions have not been clearly defined. Genes encoding representatives from both of these clades can be found in many plants, but have not yet been identified in other phyla. In contrast, the remaining SCPL proteins include five members that are similar to serine carboxypeptidases from a variety of organisms, including fungi and animals. Reverse transcription PCR results suggest that some SCPL genes are expressed in a highly tissue-specific fashion, whereas others are transcribed in a wide range of tissue types. Taken together, these data suggest that the Arabidopsis SCPL gene family encodes a diverse group of enzymes whose functions are likely to extend beyond protein degradation and processing to include activities such as the production of secondary metabolites.

Arabidopsis↗
PubMed2001

Rice bioinformatics. analysis of rice sequence data and leveraging the data to other plant species.

Rice (Oryza sativa) is a model species for monocotyledonous plants, especially for members in the grass family. Several attributes such as small genome size, diploid nature, transformability, and establishment of genetic and molecular resources make it a tractable organism for plant biologists. With an estimated genome size of 430 Mb (Arumuganathan and Earle, 1991), it is feasible to obtain the complete genome sequence of rice using current technologies. An international effort has been established and is in the process of sequencing O. sativa spp. japonica var "Nipponbare" using a bacterial artificial chromosome/P1 artificial chromosome shotgun sequencing strategy. Annotation of the rice genome is performed using prediction-based and homology-based searches to identify genes. Annotation tools such as optimized gene prediction programs are being developed for rice to improve the quality of annotation. Resources are also being developed to leverage the rice genome sequence to partial genome projects such as expressed sequence tag projects, thereby maximizing the output from the rice genome project. To provide a low level of annotation for rice genomic sequences, we have aligned all rice bacterial artificial chromosome/P1 artificial chromosome sequences with The Institute of Genomic Research Gene Indices that are a set of nonredundant transcripts that are generated from nine public plant expressed sequence tag projects (rice, wheat, sorghum, maize, barley, Arabidopsis, tomato, potato, and barrel medic). In addition, we have used data from The Institute of Genomic Research Gene Indices and the Arabidopsis and Rice Genome Projects to identify putative orthologues and paralogues among these nine genomes.

Base Sequence↗
PubMed2002

Architecture of a mediator for a bioinformatics database federation.

Developments in our ability to integrate and analyze data held in existing heterogeneous data resources can lead to an increase in our understanding of biological function at all levels. However, supporting ad hoc queries across multiple data resources and correlating data retrieved from these is still difficult. To address this, we are building a mediator based on the functional data model database, P/FDM, which integrates access to heterogeneous distributed biological databases. Our architecture makes use of the existing search capabilities and indexes of the underlying databases, without infringing on their autonomy. Central to our design philosophy is the use of schemas. We have adopted a federated architecture with a five-level schema, arising from the use of the ANSI-SPARC three-level schema to describe both the existing autonomous data resources and the mediator itself. We describe the use of mapping functions and list comprehensions in query splitting, producing execution plans, code generation, and result fusion. We give an example of cross-database querying involving data held locally in P/FDM systems and external data in SRS.

Algorithms↗
PubMed2005

Biometry, biometrics, biostatistics, bioinformatics,..., bio-X.

Recent scientific evolutions force us to rethink our profession's position on the scientific map, in relation to our neighboring professions, the ones with which we traditionally have strong collaborative links as well as the newly emerging fields, but also within our own, diverse professional group. We will show that great inspiration can be drawn from our own history, in fact from the early days of the Society. A recent inspiring example has been set by the late Rob Kempton, who died suddenly just months before he was to become President of the International Biometric Society.

Biometry↗
PubMed2005

Anatomics: the intersection of anatomy and bioinformatics.

Computational resources are now using the tissue names of the major model organisms so that tissue-associated data can be archived in and retrieved from databases on the basis of developing and adult anatomy. For this to be done, the set of tissues in that organism (its anatome) has to be organized in a way that is computer-comprehensible. Indeed, such formalization is a necessary part of what is becoming known as systems biology, in which explanations of high-level biological phenomena are not only sought in terms of lower-level events, but are articulated within a computational framework. Lists of tissue names alone, however, turn out to be inadequate for this formalization because tissue organization is essentially hierarchical and thus cannot easily be put into tables, the natural format of relational databases. The solution now adopted is to organize the anatomy of each organism as a hierarchy of tissue names and linking relationships (e.g. the tibia is PART OF the leg, the tibia IS-A bone) within what are known as ontologies. In these, a unique ID is assigned to each tissue and this can be used within, for example, gene-expression databases to link data to tissue organization, and also used to query other data sources (interoperability), while inferences about the anatomy can be made within the ontology on the basis of the relationships. There are now about 15 such anatomical ontologies, many of which are linked to organism databases; these ontologies are now publicly available at the Open Biological Ontologies website (http://obo.sourceforge.net) from where they can be freely downloaded and viewed using standard tools. This review considers how anatomy is formalized within ontologies, together with the problems that have had to be solved for this to be done. It is suggested that the appropriate term for the analysis, computer formulation and use of the anatome is anatomics.

Adult↗
PubMed2005

Expressed sequence tags from the midgut and an epithelial cell line of Chironomus tentans: annotation, bioinformatic classification of unknown transcripts and analysis of expression levels.

Expressed sequence tags (ESTs) were generated from two Chironomus tentans cDNA libraries, constructed from an embryo epithelial cell line and from larva midgut tissue. 8584 5'-end ESTs were generated and assembled into 3110 tentative unique transcripts, providing the largest contribution of C. tentans sequences to public databases to date. Annotation using Blast gave 1975 (63.5%) transcripts with a significant match in the major gene/protein databases, 1170 with a best match to Anopheles gambiae and 480 to Drosophila melanogaster. 1091 transcripts (35.1%) had no match to any database. Studies of open reading frames suggest that at least 323 of these contain a coding sequence, indicating that a large proportion of the genes in C. tentans belong to previously unknown gene families.

Animals↗