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Sequence determinants in human polyadenylation site selection.

BACKGROUND: Differential polyadenylation is a widespread mechanism in higher eukaryotes producing mRNAs with different 3' ends in different contexts. This involves several alternative polyadenylation sites in the 3' UTR, each with its specific strength. Here, we analyze the vicinity of human polyadenylation signals in search of patterns that would help discriminate strong and weak polyadenylation sites, or true sites from randomly occurring signals. RESULTS: We used human genomic sequences to retrieve the region downstream of polyadenylation signals, usually absent from cDNA or mRNA databases. Analyzing 4956 EST-validated polyadenylation sites and their -300/+300 nt flanking regions, we clearly visualized the upstream (USE) and downstream (DSE) sequence elements, both characterized by U-rich (not GU-rich) segments. The presence of a USE and a DSE is the main feature distinguishing true polyadenylation sites from randomly occurring A(A/U)UAAA hexamers. While USEs are indifferently associated with strong and weak poly(A) sites, DSEs are more conspicuous near strong poly(A) sites. We then used the region encompassing the hexamer and DSE as a training set for poly(A) site identification by the ERPIN program and achieved a prediction specificity of 69 to 85% for a sensitivity of 56%. CONCLUSION: The availability of complete genomes and large EST sequence databases now permit large-scale observation of polyadenylation sites. Both U-rich sequences flanking both sides of poly(A) signals contribute to the definition of "true" sites. However, the downstream U-rich sequences may also play an enhancing role. Based on this information, poly(A) site prediction accuracy was moderately but consistently improved compared to the best previously available algorithm.

3' Flanking Region↗

Libraries of strategies and ontology-driven subject area models as "corner stones" in Grid development.

Series of experiments of Grid-based calculations by Monte-Carlo simulation of molecular conformations have shown that there are classes of problems that could be "gridified" in short time with reasonable efforts. That could awake serious interest in the Grid from the biophysics and biochemistry community. Experiments with scientific problems that include both intensive computations and intensive data interchange have shown that libraries of strategies could provide an effective tool to adapt Grid-node infrastructure to problem structure. Libraries of strategies on different levels of Grid hierarchy--from local clusters to regional segments--could provide an effective usage of Grid resources. Ontologies provide a universal tool to link distributed databases. Besides, ontologies also allow for the formal construction of models of subject areas. These models are the tools to formalize information requests and to construct intellectual queries to information space. There should be a multi-level hierarchy of ontologies and a critical mass of low-level ontologies must be reached in order to build a knowledge space for a subject area.

Algorithms↗

The Genomic Threading Database: a comprehensive resource for structural annotations of the genomes from key organisms.

Currently, the Genomic Threading Database (GTD) contains structural assignments for the proteins encoded within the genomes of nine eukaryotes and 101 prokaryotes. Structural annotations are carried out using a modified version of GenTHREADER, a reliable fold recognition method. The Gen THREADER annotation jobs are distributed across multiple clusters of processors using grid technology and the predictions are deposited in a relational database accessible via a web interface at http://bioinf.cs.ucl.ac.uk/GTD. Using this system, up to 84% of proteins encoded within a genome can be confidently assigned to known folds with 72% of the residues aligned. On average in the GTD, 64% of proteins encoded within a genome are confidently assigned to known folds and 58% of the residues are aligned to structures.

Animals↗

KDE Bioscience: platform for bioinformatics analysis workflows.

Bioinformatics is a dynamic research area in which a large number of algorithms and programs have been developed rapidly and independently without much consideration so far of the need for standardization. The lack of such common standards combined with unfriendly interfaces make it difficult for biologists to learn how to use these tools and to translate the data formats from one to another. Consequently, the construction of an integrative bioinformatics platform to facilitate biologists' research is an urgent and challenging task. KDE Bioscience is a java-based software platform that collects a variety of bioinformatics tools and provides a workflow mechanism to integrate them. Nucleotide and protein sequences from local flat files, web sites, and relational databases can be entered, annotated, and aligned. Several home-made or 3rd-party viewers are built-in to provide visualization of annotations or alignments. KDE Bioscience can also be deployed in client-server mode where simultaneous execution of the same workflow is supported for multiple users. Moreover, workflows can be published as web pages that can be executed from a web browser. The power of KDE Bioscience comes from the integrated algorithms and data sources. With its generic workflow mechanism other novel calculations and simulations can be integrated to augment the current sequence analysis functions. Because of this flexible and extensible architecture, KDE Bioscience makes an ideal integrated informatics environment for future bioinformatics or systems biology research.

Biological Science Disciplines↗

Phylogenetic analysis of the formin homology 2 domain.

Formin proteins are key regulators of eukaryotic actin filament assembly and elongation, and many species possess multiple formin isoforms. A nomenclature system based on fundamental features would be desirable, to aid the rapid identification and characterization of novel formins. In this article, we attempt to systematize the formin family by performing phylogenetic analyses of the formin homology 2 (FH2) domain, an independently folding region common to all formins, which alone can influence actin dynamics. Through database searches, we identify 101 FH2 domains from 26 eukaryotic species, including 15 in mice. Sequence alignments reveal a highly conserved yeast-specific insert in the "knob loop" region of the FH2 domain, with unknown functional consequences. Phylogenetic analysis using minimum evolution (ME), maximum parsimony (MP), and maximum likelihood (ML) algorithms strongly supports the existence of seven metazoan groups. Yeast FH2 domains segregate from all other eukaryotes, including metazoans, other fungi, plants, and protists. Sequence comparisons of non-FH2 regions support relationships between three metazoan groups (Dia, DAAM, and FRL) and examine previously identified coiled-coil and Diaphanous auto-regulatory domain sequences. This analysis allows for a formin nomenclature system based on sequence relationships, as well as suggesting strategies for the determination of biochemical and cellular activities of these proteins.

Adaptor Proteins, Signal Transducing↗

Mapping PDB chains to UniProtKB entries.

MOTIVATION: UniProtKB/SwissProt is the main resource for detailed annotations of protein sequences. This database provides a jumping-off point to many other resources through the links it provides. Among others, these include other primary databases, secondary databases, the Gene Ontology and OMIM. While a large number of links are provided to Protein Data Bank (PDB) files, obtaining a regularly updated mapping between UniProtKB entries and PDB entries at the chain or residue level is not straightforward. In particular, there is no regularly updated resource which allows a UniProtKB/SwissProt entry to be identified for a given residue of a PDB file. RESULTS: We have created a completely automatically maintained database which maps PDB residues to residues in UniProtKB/SwissProt and UniProtKB/trEMBL entries. The protocol uses links from PDB to UniProtKB, from UniProtKB to PDB and a brute-force sequence scan to resolve PDB chains for which no annotated link is available. Finally the sequences from PDB and UniProtKB are aligned to obtain a residue-level mapping. AVAILABILITY: The resource may be queried interactively or downloaded from http://www.bioinf.org.uk/pdbsws/.

Amino Acid Sequence↗

HemoPDB: Hematopoiesis Promoter Database, an information resource of transcriptional regulation in blood cell development.

Hematopoiesis describes the process of the normal formation and development of blood cells, involving both proliferation and differentiation from stem cells. Abnormalities in this developmental program yield blood cell diseases, such as leukemia. Although, in recent years, extensive molecular research in normal hematopoietic development has characterized transcription factors and their binding sites in the target gene promoters, the information generated is highly fragmented. In order to integrate this important regulatory information with the corresponding genomic sequences, we have developed a new database called Hematopoiesis Promoter Database (HemoPDB). HemoPDB is a comprehensive resource focused on transcriptional regulation during hematopoietic development and associated aberrances that result in malignancy. HemoPDB (version 1.0) contains 246 promoter sequences and 604 experimentally known cis-regulatory elements of 187 different transcription factors, with links to published references. Orthologous promoters from different species are linked with each other and displayed in the same database record, accompanied by a visual image of the promoters and corresponding annotations of cis-regulatory elements. HemoPDB may be searched for the promoter of a specific gene, transcription factors and target genes, and genes that are expressed in a certain cell type or lineage, through a user-friendly web interface at http://bioinformatics.med.ohio-state.edu/HemoPDB. Links to the documentation and other technical details are provided on this website.

Animals↗

The Ensembl Web site: mechanics of a genome browser.

The Ensembl Web site (http://www.ensembl.org/) is the principal user interface to the data of the Ensembl project, and currently serves >500,000 pages (approximately 2.5 million hits) per week, providing access to >80 GB (gigabyte) of data to users in more than 80 countries. Built atop an open-source platform comprising Apache/mod_perl and the MySQL relational database management system, it is modular, extensible, and freely available. It is being actively reused and extended in several different projects, and has been downloaded and installed in companies and academic institutions worldwide. Here, we describe some of the technical features of the site, with particular reference to its dynamic configuration that enables it to handle disparate data from multiple species.

Animals↗

A database of bacterial lipoproteins (DOLOP) with functional assignments to predicted lipoproteins.

Lipid modification of the N-terminal Cys residue (N-acyl-S-diacylglyceryl-Cys) has been found to be an essential, ubiquitous, and unique bacterial posttranslational modification. Such a modification allows anchoring of even highly hydrophilic proteins to the membrane which carry out a variety of functions important for bacteria, including pathogenesis. Hence, being able to identify such proteins is of great value. To this end, we have created a comprehensive database of bacterial lipoproteins, called DOLOP, which contains information and links to molecular details for about 278 distinct lipoproteins and predicted lipoproteins from 234 completely sequenced bacterial genomes. The website also features a tool that applies a predictive algorithm to identify the presence or absence of the lipoprotein signal sequence in a user-given sequence. The experimentally verified lipoproteins have been classified into different functional classes and more importantly functional domain assignments using hidden Markov models from the SUPERFAMILY database that have been provided for the predicted lipoproteins. Other features include the following: primary sequence analysis, signal sequence analysis, and search facility and information exchange facility to allow researchers to exchange results on newly characterized lipoproteins. The website, along with additional information on the biosynthetic pathway, statistics on predicted lipoproteins, and related figures, is available at http://www.mrc-lmb.cam.ac.uk/genomes/dolop/.

Bacterial Proteins↗

Public sphere and the sustainability of the bioinformatics promise.

The literature about genomics and bioinformatics achievements in high-impact journals such as Nature and Science has raised disproportionate expectations amongst the general public about fast and revolutionary drugs and breakthroughs in biomedicine. However, the yield obtained by database mining activities has been modest, as reported in the February 2001 issues of these journals featuring the completion of human genome draft sequences by the Human Genome Project Consortium and the company Celera. I have compared changes in rethoric employed by molecular biologists in 2001 and in April 2003, when the final sequence was announced. The comparison suggests that researchers are concerned about the sustainability of society's investment in this field, though not explicitly.

Bibliometrics↗

OQAFMA Querying agent for the Foundational Model of Anatomy: a prototype for providing flexible and efficient access to large semantic networks.

The development of large semantic networks, such as the UMLS, which are intended to support a variety of applications, requires a flexible and efficient query interface for the extraction of information. Using one of the source vocabularies of UMLS as a test bed, we have developed such a prototype query interface. We first identify common classes of queries needed by applications that access these semantic networks. Next, we survey StruQL, an existing query language that we adopted, which supports all of these classes of queries. We then describe the OQAFMA Querying Agent for the Foundational Model of Anatomy (OQAFMA), which provides an efficient implementation of a subset of StruQL by pre-computing a variety of indices. We describe how OQAFMA leverages database optimization by converting StruQL queries to SQL. We evaluate the flexibility and efficiency of our implementation using English queries written by anatomists. This evaluation verifies that OQAFMA provides flexible, efficient access to one such large semantic network, the Foundational Model of Anatomy, and suggests that OQAFMA could be an efficient query interface to other large biomedical knowledge bases, such as the Unified Medical Language System.

Abstracting and Indexing↗

Computer prediction of allergen proteins from sequence-derived protein structural and physicochemical properties.

BACKGROUND: Computational methods have been developed for predicting allergen proteins from sequence segments that show identity, homology, or motif match to a known allergen. These methods achieve good prediction accuracies, but are less effective for novel proteins with no similarity to any known allergen. METHODS: This work tests the feasibility of using a statistical learning method, support vector machines, as such a method. The prediction system is trained and tested by using 1005 allergen proteins from the Allergome database and 22,469 non-allergen proteins from 7871 Pfam families. RESULTS: Testing results by an independent set of 229 allergen and 6717 non-allergen proteins from 7871 Pfam families show that 93.0% and 99.9% of these are correctly predicted, which are comparable to the best results of other methods. Of the 18 novel allergen proteins non-homologous to any other proteins in the Swissprot database, 88.9% is correctly predicted. A further screening of 168,128 proteins in the Swissprot database finds that 2.9% of the proteins are predicted as allergen proteins, which is consistent with the estimated numbers from motif-based methods. CONCLUSIONS: Our study suggests that SVM is a potentially useful method for predicting allergen proteins and it has certain capability for predicting novel allergen proteins. Our software can be accessed at .

Allergens↗

Construction of a non-redundant human SH2 domain database.

Domain database is essential for domain property research. Eliminating redundant information in database query is very important for database quality. Here we report the manual construction of a non-redundant human SH2 domain database. There are 119 human SH2 domains in 110 SH2-containing proteins. Human SH2s were aligned with ClustalX, and a homologous tree was generated. In this tree, proteins with similar known function were classified into the same group. Some proteins in the same group have been reported to have similar binding motifs experimentally. The tree might provide clues about possible functions of hypothetical proteins for further experimental verification.

Amino Acid Sequence↗

Science's signal transduction knowledge environment: the connections maps database.

Knowledge environment (KE) describes the collection of electronic networking tools that have been and continue to be developed by AAAS and Stanford University libraries. Knowledge environments use practical, production-quality tools to systematize the consensus knowledge within a scientific domain and facilitate users' access to that knowledge. Science's Signal Transduction Knowledge Environment (STKE) is the first in this new concept in electronic publishing that combines the traditional, albeit electronic, publishing of articles, such as reviews, perspectives, and protocols, with tools for organizing and collating information in the cross-disciplinary field of signal transduction. One of the major tools developed for the STKE is the Connections Map database and the software (called CMADES [Connections Maps Authority Data Entry Software]) created to facilitate data entry by Pathway Authorities. The Connections Maps are a graphical representation of a database of information about the molecules involved in cellular signaling cascades. CMADES automates many of the functions involved in adding data into the Connections Maps database, such as references and descriptors, as well as allowing the Authorities to indicate the relationships between the components in the pathway through the use of a graphing tool. CMADES and the Connections Maps represent evolving tools that assist the Authorities in systemizing information regarding a particular system at the organism- and cell-specific level and the canonical level, as well as provide the STKE user with organized and expert-supplied information about signal transduction pathways.

Biology↗

Extending the accuracy limits of prediction for side-chain conformations.

Current techniques for the prediction of side-chain conformations on a fixed backbone have an accuracy limit of about 1.0-1.5 A rmsd for core residues. We have carried out a detailed and systematic analysis of the factors that influence the prediction of side-chain conformation and, on this basis, have succeeded in extending the limits of side-chain prediction for core residues to about 0.7 A rmsd from native, and 94 % and 89 % of chi(1) and chi(1+2 ) dihedral angles correctly predicted to within 20 degrees of native, respectively. These results are obtained using a force-field that accounts for only van der Waals interactions and torsional potentials. Prediction accuracy is strongly dependent on the rotamer library used. That is, a complete and detailed rotamer library is essential. The greatest accuracy was obtained with an extensive rotamer library, containing over 7560 members, in which bond lengths and bond angles were taken from the database rather than simply assuming idealized values. Perhaps the most surprising finding is that the combinatorial problem normally associated with the prediction of the side-chain conformation does not appear to be important. This conclusion is based on the fact that the prediction of the conformation of a single side-chain with all others fixed in their native conformations is only slightly more accurate than the simultaneous prediction of all side-chain dihedral angles.

Computational Biology↗

Analysis of the molecular evolutionary history of the ascorbate peroxidase gene family: inferences from the rice genome.

Ascorbate peroxidase (APx) is a class I peroxidase that catalyzes the conversion of H(2)O(2) to H(2)O and O(2) using ascorbate as the specific electron donor. This enzyme has a key function in scavenging reactive oxygen species (ROS) and the protection against toxic effects of ROS in higher plants, algae, and Euglena. Here we report the identification of an APx multigene family in rice and propose a molecular evolutionary relationship between the diverse APx isoforms. In rice, the APx gene family has eight members, which encode two cytosolic, two putative peroxisomal, and four chloroplastic isoforms, respectively. Phylogenetic analyses were conducted using all APx protein sequences available in the NCBI databases. The results indicate that the different APx isoforms arose by a complex evolutionary process involving several gene duplications. The structural organization of APx genes also reflects this process and provides evidence for a close relationship among proteins located in the same subcellular compartment. A molecular evolutionary pathway, in which cytosolic and peroxisomal isoforms diverged early from chloroplastic ones, is proposed.

Amino Acid Sequence↗

Assignment of folds for proteins of unknown function in three microbial genomes.

Analysis of DNA sequences of several microbial genomes has revealed that a large fraction of predicted coding regions has no known protein function. Information about the three-dimensional folds of these proteins may provide insight into their possible functions. To predict the folds for protein sequences with little or no homology to proteins of known function, we used computational neural networks trained on the database of proteins with known three-dimensional structures. Global descriptions of protein sequences based on physical and structural properties of the constituent amino acids were used as inputs for neural networks. Of the 131, 498, and 868 protein sequences of unknown function from Mycoplasma genitalium, Haemophilus influenzae, and Methanococcus jannaschii (Fleischmann et al. 1995), we have made high-confidence fold assignments for 4, 10, and 19 sequences, respectively.

Amino Acid Sequence↗

Virtual resource development in the glycosciences.

The development of Internet-based virtual resources is a relatively new area of scientific and technical activity that is currently undergoing rapid expansion. Major factors fuelling recent growth include the emergence of multimedia capabilities through the rapid evolution of the World Wide Web, the reduction in cost of high quality personal computers and graphics workstations and the provision of mass-marketed provider services. Prior to 1995 the presence of Internet resources in the glycosciences was virtually non-existent. Existing scientific knowledge was primarily made available on the Net through the provision of databases from gopher and ftp sites. A particular example in the glycosciences is the Carbbank database of biological carbohydrate sequences. We will describe here our efforts in 1994-95 in establishing The Glycoscience Network (TGN, http:@ bellatrix.pcl.ox.ac.uk/TGN/). These activities included the establishment of a newsgroup, mailing lists, Web resources and the running of the First Electronic Glycoscience Conference (EGC-1, http:@bellatrix.pcl.ox.ac.uk/egc/). EGC-1 included many novel initiatives in the glycosciences including electronic posters and papers, a Virtual Conference Centre, a Web-based hyperglossary, Virtual Trade and Employment Centres, refereed electronic publishing, and the creation of a Virtual Reality Gallery. We would like to look towards the near future and discuss several initiatives in virtual resource creation that we believe will have significant scientific impact on the glycosciences including the development of bioinformatics-based servers, sophisticated interactive databases, and videoconferencing. Furthermore, we cherish the belief that these resources will foster international scientific collaboration and progress of an extent never previously possible. Finally, we indulge in speculation and make some suggestions on the form and long-term impact of Glycoscience Virtual Resources. We predict that their development may completely reconstruct the scientific environment that we work in as scientists and we reflect on the probable benefits and pitfalls to be encountered.

Carbohydrates↗