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At least 1,063 records · Page 59Linked to original sources
PubMed1998

Pfam: multiple sequence alignments and HMM-profiles of protein domains.

Pfam contains multiple alignments and hidden Markov model based profiles (HMM-profiles) of complete protein domains. The definition of domain boundaries, family members and alignment is done semi-automatically based on expert knowledge, sequence similarity, other protein family databases and the ability of HMM-profiles to correctly identify and align the members. Release 2.0 of Pfam contains 527 manually verified families which are available for browsing and on-line searching via the World Wide Web in the UK at http://www.sanger.ac.uk/Pfam/ and in the US at http://genome.wustl. edu/Pfam/ Pfam 2.0 matches one or more domains in 50% of Swissprot-34 sequences, and 25% of a large sample of predicted proteins from the Caenorhabditis elegans genome.

Amino Acid Sequence↗
PubMed1998

AtDB, the Arabidopsis thaliana database, and graphical-web-display of progress by the Arabidopsis Genome Initiative.

AtDB, the Arabidopsis thaliana Database, has a primary role to provide public access to the collected genomic information for A. thaliana via the World Wide Web (URL: http://genome-www.stanford. edu/ ). AtDB presents interactive physical and genetics maps that are hyperlinked with detailed information about the clones and markers placed on these maps. A large literature collection on Arabidopsis , contact information on researchers worldwide, laboratory method manuals and other information useful to plant molecular biologists are also provided. This paper discusses the database-driven clickable displays that provide easy navigation within a variety of genomic maps, including those summarizing progress of the international Arabidopsis genomic sequencing effort, AGI (the Arabidopsis Genome Initiative). The interface uses client-side hyperlinked GIF-images that direct the user to detailed database-information. A new BLAST service is also described. This gives users access to the thousands of Arabidopsis BAC clone end-sequences and includes hyperlinked images summarizing the search results. The linking of genetic and physically mapped regions and their sequence into information for loci within that region is an ongoing goal for this project.

Arabidopsis↗
PubMed2001

The Stanford Microarray Database.

The Stanford Microarray Database (SMD) stores raw and normalized data from microarray experiments, and provides web interfaces for researchers to retrieve, analyze and visualize their data. The two immediate goals for SMD are to serve as a storage site for microarray data from ongoing research at Stanford University, and to facilitate the public dissemination of that data once published, or released by the researcher. Of paramount importance is the connection of microarray data with the biological data that pertains to the DNA deposited on the microarray (genes, clones etc.). SMD makes use of many public resources to connect expression information to the relevant biology, including SGD [Ball,C.A., Dolinski,K., Dwight,S.S., Harris,M.A., Issel-Tarver,L., Kasarskis,A., Scafe,C.R., Sherlock,G., Binkley,G., Jin,H. et al. (2000) Nucleic Acids Res., 28, 77-80], YPD and WormPD [Costanzo,M.C., Hogan,J.D., Cusick,M.E., Davis,B.P., Fancher,A.M., Hodges,P.E., Kondu,P., Lengieza,C., Lew-Smith,J.E., Lingner,C. et al. (2000) Nucleic Acids Res., 28, 73-76], Unigene [Wheeler,D.L., Chappey,C., Lash,A.E., Leipe,D.D., Madden,T.L., Schuler,G.D., Tatusova,T.A. and Rapp,B.A. (2000) Nucleic Acids Res., 28, 10-14], dbEST [Boguski,M.S., Lowe,T.M. and Tolstoshev,C.M. (1993) Nature Genet., 4, 332-333] and SWISS-PROT [Bairoch,A. and Apweiler,R. (2000) Nucleic Acids Res., 28, 45-48] and can be accessed at http://genome-www.stanford.edu/microarray.

Animals↗
PubMed2003

ToxoDB: accessing the Toxoplasma gondii genome.

ToxoDB (http://ToxoDB.org) provides a genome resource for the protozoan parasite Toxoplasma gondii. Several sequencing projects devoted to T. gondii have been completed or are in progress: an EST project (http://genome.wustl.edu/est/index.php?toxoplasma=1), a BAC clone end-sequencing project (http://www.sanger.ac.uk/Projects/T_gondii/) and an 8X random shotgun genomic sequencing project (http://www.tigr.org/tdb/e2k1/tga1/). ToxoDB was designed to provide a central point of access for all available T. gondii data, and a variety of data mining tools useful for the analysis of unfinished, un-annotated draft sequence during the early phases of the genome project. In later stages, as more and different types of data become available (microarray, proteomic, SNP, QTL, etc.) the database will provide an integrated data analysis platform facilitating user-defined queries across the different data types.

Animals↗
PubMedDate not supplied

Use of MindMapper software for research domain mapping.

The application of concept mapping software to facilitate the first steps of the research review process is discussed in relation to other software programs currently used for research synthesis. MindMapper software was used to develop a strategy for organizing the results of a comprehensive literature search into discrete categories with relationships among concepts graphically displayed to reveal the structure of the research domain. A Mind Map was developed for the scholarly literature on Web-based consumer health information. A second Mind Map examined the subconcept of barriers to consumer use of the Internet for health information. MindMapper has many features that facilitate description of the breadth and depth of literature in a domain of inquiry. It also facilitates identification of the number and nature of studies underpinning mapped relationships among concepts, thus laying the groundwork for systematic research reviews and meta-analyses.

Computer Graphics↗
PubMedDate not supplied

Three-dimensional shape-structure comparison method for protein classification.

In this paper, a 3D shape-based approach is presented for the efficient search, retrieval, and classification of protein molecules. The method relies primarily on the geometric 3D structure of the proteins, which is produced from the corresponding PDB files and secondarily on their primary and secondary structure. After proper positioning of the 3D structures, in terms of translation and scaling, the Spherical Trace Transform is applied to them so as to produce geometry-based descriptor vectors, which are completely rotation invariant and perfectly describe their 3D shape. Additionally, characteristic attributes of the primary and secondary structure of the protein molecules are extracted, forming attribute-based descriptor vectors. The descriptor vectors are weighted and an integrated descriptor vector is produced. Three classification methods are tested. A part of the FSSP/DALI database, which provides a structural classification of the proteins, is used as the ground truth in order to evaluate the classification accuracy of the proposed method. The experimental results show that the proposed method achieves more than 99 percent classification accuracy while remaining much simpler and faster than the DALI method.

Algorithms↗
PubMedDate not supplied

A visualization system for space-time and multivariate patterns (VIS-STAMP).

The research reported here integrates computational, visual, and cartographic methods to develop a geovisual analytic approach for exploring and understanding spatio-temporal and multivariate patterns. The developed methodology and tools can help analysts investigate complex patterns across multivariate, spatial, and temporal dimensions via clustering, sorting, and visualization. Specifically, the approach involves a self-organizing map, a parallel coordinate plot, several forms of reorderable matrices (including several ordering methods), a geographic small multiple display, and a 2-dimensional cartographic color design method. The coupling among these methods leverages their independent strengths and facilitates a visual exploration of patterns that are difficult to discover otherwise. The visualization system we developed supports overview of complex patterns and, through a variety of interactions, enables users to focus on specific patterns and examine detailed views. We demonstrate the system with an application to the IEEE InfoVis 2005 Contest data set, which contains time-varying, geographically referenced, and multivariate data for technology companies in the US.

Algorithms↗
PubMedDate not supplied

Informatics: essential infrastructure for quality assessment and improvement in nursing.

In recent decades there have been major advances in the creation and implementation of information technologies and in the development of measures of health care quality. The premise of this article is that informatics provides essential infrastructure for quality assessment and improvement in nursing. In this context, the term quality assessment and improvement comprises both short-term processes such as continuous quality improvement (CQI) and long-term outcomes management. This premise is supported by 1) presentation of a historical perspective on quality assessment and improvement; 2) delineation of the types of data required for quality assessment and improvement; and 3) description of the current and potential uses of information technology in the acquisition, storage, transformation, and presentation of quality data, information, and knowledge.

Computer Communication Networks↗
PubMedDate not supplied

Care planning as a strategy to manage variation in practice: from care plan to integrated person-based record.

This article begins with a summary of the trend toward a person-based health record, and the need to integrate data from a variety of sources to achieve this. A project is described that demonstrated problems with the structure of nursing care plans. These problems affected the ability to integrate care plan data into a clinical database capable of analysis to link control of process with clinical outcome. A second project is described that focused on the development of data sets holding higher-level descriptions suitable for the maintenance of a person-based record, but at a summarized level and with no clinical detail. Finally, a prototype care planning system is described that, while maintaining the data required by the Nursing Process, was more flexibly structured to support analysis and hierarchical levels of description.

Community Health Nursing↗
PubMed2004

A relational database application in support of integrated neuroscience research.

The development of relational databases has significantly improved the performance of storage, search, and retrieval functions and has made it possible for applications that perform real-time data acquisition and analysis to interact with these types of databases. The purpose of this research was to develop a user interface for interaction between a data acquisition and analysis application and a relational database using the Oracle9i system. The overall system was designed to have an indexing capability that threads into the data acquisition and analysis programs. Tables were designed and relations within the database for indexing the files and information contained within the files were established. The system provides retrieval capabilities over a broad range of media, including analog, event, and video data types. The system's ability to interact with a data capturing program at the time of the experiment to create both multimedia files as well as the meta-data entries in the relational database avoids manual entries in the database and ensures data integrity and completeness for further interaction with the data by analysis applications.

Database Management Systems↗
PubMed2005

Decision tree based information integration for automated protein classification.

We propose a novel technique for automatically generating the SCOP classification of a protein structure with high accuracy. We achieve accurate classification by combining the decisions of multiple methods using the consensus of a committee (or an ensemble) classifier. Our technique, based on decision trees, is rooted in machine learning which shows that by judicially employing component classifiers, an ensemble classifier can be constructed to outperform its components. We use two sequence- and three structure-comparison tools as component classifiers. Given a protein structure and using the joint hypothesis, we first determine if the protein belongs to an existing category (family, superfamily, fold) in the SCOP hierarchy. For the proteins that are predicted as members of the existing categories, we compute their family-, superfamily-, and fold-level classifications using the consensus classifier. We show that we can significantly improve the classification accuracy compared to the individual component classifiers. In particular, we achieve error rates that are 3-12 times less than the individual classifiers' error rates at the family level, 1.5-4.5 times less at the superfamily level, and 1.1-2.4 times less at the fold level.

Algorithms↗
PubMed2000

Data mining: data analysis on a grand scale?

Modern data mining has evolved largely as a result of efforts by computer scientists to address the needs of 'data owners' in extracting useful information from massive observational data sets. Because of this historical context, data mining to date has largely focused on computational and algorithmic issues rather than the more traditional statistical aspects of data analysis. This paper provides a brief review of the origins of data mining as well as discussing some of the primary themes in current research in data mining, including scalable algorithms for massive data sets, discovering novel patterns in data, and analysis of text, web, and related multimedia data sets.

Algorithms↗
PubMed2005

Automated methods of predicting the function of biological sequences using GO and BLAST.

BACKGROUND: With the exponential increase in genomic sequence data there is a need to develop automated approaches to deducing the biological functions of novel sequences with high accuracy. Our aim is to demonstrate how accuracy benchmarking can be used in a decision-making process evaluating competing designs of biological function predictors. We utilise the Gene Ontology, GO, a directed acyclic graph of functional terms, to annotate sequences with functional information describing their biological context. Initially we examine the effect on accuracy scores of increasing the allowed distance between predicted and a test set of curator assigned terms. Next we evaluate several annotator methods using accuracy benchmarking. Given an unannotated sequence we use the Basic Local Alignment Search Tool, BLAST, to find similar sequences that have already been assigned GO terms by curators. A number of methods were developed that utilise terms associated with the best five matching sequences. These methods were compared against a benchmark method of simply using terms associated with the best BLAST-matched sequence (best BLAST approach). RESULTS: The precision and recall of estimates increases rapidly as the amount of distance permitted between a predicted term and a correct term assignment increases. Accuracy benchmarking allows a comparison of annotation methods. A covering graph approach performs poorly, except where the term assignment rate is high. A term distance concordance approach has a similar accuracy to the best BLAST approach, demonstrating lower precision but higher recall. However, a discriminant function method has higher precision and recall than the best BLAST approach and other methods shown here. CONCLUSION: Allowing term predictions to be counted correct if closely related to a correct term decreases the reliability of the accuracy score. As such we recommend using accuracy measures that require exact matching of predicted terms with curator assigned terms. Furthermore, we conclude that competing designs of BLAST-based GO term annotators can be effectively compared using an accuracy benchmarking approach. The most accurate annotation method was developed using data mining techniques. As such we recommend that designers of term annotators utilise accuracy benchmarking and data mining to ensure newly developed annotators are of high quality.

Benchmarking↗
PubMed2005

Comparative mapping of sequence-based and structure-based protein domains.

BACKGROUND: Protein domains have long been an ill-defined concept in biology. They are generally described as autonomous folding units with evolutionary and functional independence. Both structure-based and sequence-based domain definitions have been widely used. But whether these types of models alone can capture all essential features of domains is still an open question. METHODS: Here we provide insight on domain definitions through comparative mapping of two domain classification databases, one sequence-based (Pfam) and the other structure-based (SCOP). A mapping score is defined to indicate the significance of the mapping, and the properties of the mapping matrices are studied. RESULTS: The mapping results show a general agreement between the two databases, as well as many interesting areas of disagreement. In the cases of disagreement, the functional and evolutionary characteristics of the domains are examined to determine which domain definition is biologically more informative.

Algorithms↗