Variety Of Formats Research Articles

NCBI Bookshelf: books and documents in life sciences and health care

Bookshelf (http://www.ncbi.nlm.nih.gov/books/) is a full-text electronic literature resource of books and documents in life sciences and health care at the National Center for Biotechnology Information (NCBI). Created in 1999 with a single book as an encyclopedic reference for resources such as PubMed and GenBank, it has grown to its current size of >1300 titles. Unlike other NCBI databases, such as GenBank and Gene, which have a strict data structure, books come in all forms; they are diverse in publication types, formats, sizes and authoring models. The Bookshelf data format is XML tagged in the NCBI Book DTD (Document Type Definition), modeled after the National Library of Medicine journal article DTDs. The book DTD has been used for systematically tagging the diverse data formats of books, a move that has set the foundation for the growth of this resource. Books at NCBI followed the route of journal articles in the PubMed Central project, using the PubMed Central architectural framework, workflows and processes. Through integration with other NCBI molecular databases, books at NCBI can be used to provide reference information for biological data and facilitate its discovery. This article describes Bookshelf at NCBI: its growth, data handling and retrieval and integration with molecular databases.

Classification of Vertebral Column using Naïve Bayes Technique

Medical database contain data in various formats like ECG,EEG,X-rays, textual data etc., This data is not located on the same system, it may be distributed amongst various computers depending on data source. This makes medical data retrieval more complex process. So there is need for data mining tools in medical information processing systems to be effective and user friendly. This paper focuses on finding the machine learning methods which can be applied to extract the data useful for medical data analysis and also to patients to search for any relevant information about diseases or analogies. General Terms classification algorithms, Bayesian techniques.

Mapping of Elementary Educational Infrastructure in India: A State and District Level Analysis

Education plays an important role in a country’s development process. Indian education system comprises the elementary, secondary and tertiary levels. Over two decades India registered a significant growth in the educational infrastructure at tertiary level of education but elementary and secondary levels of education are struggling with low accessibility of infrastructure and resources. This is affecting the quality of education particularly at elementary level of education which is responsible for growth in secondary and tertiary education. The assessment of infrastructure across the country is very difficult due to regional inequalities and economic diversities. This paper is an attempt to map accessibility of infrastructure at elementary level of education at district and state level in India. For mapping and analysis, advance computation techniques like GIS and contour mapping techniques are used. A novel technique and algorithm was developed to represent the data in various formats in the qualitative way; to the knowledge of the authors this novel representation of data is hitherto unreported in the open literature. Analysis confirms that there are regional inequalities in the accessibility of required infrastructure and in some states the situation is pathetic despite various government initiatives. Keywords - Elementary education, GIS, Mapping, Contours

Perceiving and interpreting smart home datasets with $$\mathcal{PI}$$

Pervasive healthcare systems facilitate various aspects of research including sensor technology, software technology, artificial intelligence and human-computer interaction. Researchers can often benefit from access to real-world data sets against which to evaluate new approaches and algorithms. Whilst more than a dozen data sets are currently publicly available, their use of heterogeneous mark-up impedes widespread and easy use. We describe \(\mathcal{PI}\)—the Perceiver and semantic Interpreter—which offers a workbench API for the querying, re-structuring and re-purposing of a range of diverse data formats currently in use. The use of a single API reduces cognitive overload, improves access, and supports integration of generic and domain-specific information within a common framework.

Construction of a robust, large-scale, collaborative database for raw data in computational chemistry: The Collaborative Chemistry Database Tool (CCDBT)

A robust metadata database called the Collaborative Chemistry Database Tool (CCDBT) for massive amounts of computational chemistry raw data has been designed and implemented. It performs data synchronization and simultaneously extracts the metadata. Computational chemistry data in various formats from different computing sources, software packages, and users can be parsed into uniform metadata for storage in a MySQL database. Parsing is performed by a parsing pyramid, including parsers written for different levels of data types and sets created by the parser loader after loading parser engines and configurations.

BeadArray Expression Analysis Using Bioconductor

Illumina whole-genome expression BeadArrays are a popular choice in gene profiling studies. Aside from the vendor-provided software tools for analyzing BeadArray expression data (GenomeStudio/BeadStudio), there exists a comprehensive set of open-source analysis tools in the Bioconductor project, many of which have been tailored to exploit the unique properties of this platform. In this article, we explore a number of these software packages and demonstrate how to perform a complete analysis of BeadArray data in various formats. The key steps of importing data, performing quality assessments, preprocessing, and annotation in the common setting of assessing differential expression in designed experiments will be covered.

디지털 콘텐츠 제작 기반의 통합 출력 및 배포 도구를 위한 웹 응용프로그램

The web trend has been flowed from portal site to user created contents site, recently. Therefore, many companies have suggested web program of producing contents for user`s convenience. However, web applications that are operated in various web browsers and heterogeneous devices have many problems regarding distribution and management so far. Because of diverse one-source data formats. In this paper, we present an integrative displaying and distributing tool (IDD-Tool) for editing, distributing and managing multimedia contents and environment so that users can work. It is inspected that the tool is widely used in the fields of education, publication, corporations and etc. because a user can participates in contents producing easily in personal customized workplace with IDD-Tool and contents made by IDD-Tool are distributed.

Semantic Model based on Three-layered Metadata for Oil-gas Data Integration

Data integration is an old problem that reemerged as an active research topic recently, due to the increased requirements for exchange of data in various formats in our increasingly interconnected but inevitably heterogeneous world. On the basis of existing technologies, metadata is proposed to realize heterogeneous data integration. Firstly, three-layered metadata model is introduced, including data source metadata, business metadata and topic metadata. Based on this, four-layered data integration service framework based on metadata has been put forward, and it respectively includes application layer, access layer, data integration layer and data source layer from top to down. The application layer supports C/S and B/S applications by the client SDK, the access layer provides uniform data access interfaces for different users by RESTful Web Services. The data integration layer shields the heterogeneity among all data sources, and provides the transparent access support for users. Finally, multiple sources and heterogeneous information resource access platform is implemented with c#. Metadata can provide a clear standard for scattered and heterogeneous data so as to achieve integration and sharing of data, which makes the users access all sources by uniform data access interface transparently. Meanwhile, metadata can not only keep the data consistency, but also provide better expansibility.

CADLIVE Converter for constructing a biochemical network map

In systems biotechnology biochemical network maps are the essential bases for analyzing their topological features and for simulating their dynamic behaviors. Most of network data are available at public databases, relating to gene expression, protein–protein interaction, and metabolic pathways. On the other hand, since those databases use a variety of data formats, computational tools always require the conversion of such database formats into their available format. In this work, we developed a GUI-based WWW browser program, which converts different databases (KEGG, RegulonDB, DIP, etc.) into the format available to our CADLIVE system, integrates a variety of network data into a fully functional pathway map, and visualizes the integrated map. This program is named the CADLIVE Converter. We demonstrated the feasibility and availability of it by performing metabolic pathway analysis and dynamic modeling. The visualization of the network map lead to an intuitive understanding of topological architecture of complex networks.

COSMIC: the catalogue of somatic mutations in cancer

The Catalogue Of Somatic Mutations In Cancer (COSMIC) [1] is one of the largest repositories of information on somatic mutations in human cancer. The project has been running for more than ten years as part of the Cancer Genome Project (CGP) at the Wellcome Trust Sanger Institute in the UK. The data in COSMIC are curated from a variety of sources, primarily the scientific literature and large international consortia. The project includes information from the CGP, along with data from other consortia such as the International Cancer Genome Consortium and The Cancer Genome Atlas. In addition, COSMIC is regularly updated with the genes highlighted in the Cancer Gene Census, which curates the scientific literature for known cancer genes [2]. With the advent of whole exome and genome sequencing technology, the amount of data in COSMIC is increasing rapidly. The recent COSMIC release (version 53; 18 May 2011) contains 608,042 tumor and cell line samples, annotating 176,856 mutations across 19,439 genes, with 352 full exomes, 43 whole genome rearrangement screens and 4 full genomes now available. The data are updated regularly, with new releases scheduled every two months. COSMIC provides a large number of graphical and tabular views for interpreting and mining the large quantity of information, as well as the facility to export the relevant data in various formats. The website can be navigated in many ways to examine mutation patterns on the basis of genes, samples and phenotypes, which are the main entry points to COSMIC. COSMIC also provides various options to browse the data in a genomic context. Integration with the Ensembl genome browser allows the visualization of full genome annotations, together with COSMIC data, on the GRCh37 genome coordinates. COSMIC also contains its own genome browser, which facilitates data analysis by combining genome-wide gene structures and sequences with rearrangement breakpoints, copy number variations and all somatic substitutions, deletions, insertions and complex gene mutations. The main COSMIC website [1] encompasses all of the available data. However, within COSMIC, the Cancer Cell Line Project [3] is a specialized component, which provides details of the genotyping of almost 800 commonly used cancer cell lines, through the set of known cancer genes. Its focus is to identify driver mutations, or those likely to be implicated in the oncogenesis of each tumor. This information forms the basis for integrating COSMIC with the Genomics of Drug Sensitivity in Cancer project [4], which is a joint effort with the Massachusetts General Hospital [5] to screen this panel of cancer cell lines against potential anticancer therapeutic compounds to investigate correlations between somatic mutations and drug sensitivity. Data on somatic mutations in cancer are being produced at a rapidly increasing rate, and the combined analysis of large distributed datasets is becoming ever more difficult. However, COSMIC curates and standardizes this information in a single database, providing user-friendly browsing tools and analytical functions, thus ensuring its role as a key resource in human cancer genetics.

Conformational dynamics data bank: a database for conformational dynamics of proteins and supramolecular protein assemblies.

The conformational dynamics data bank (CDDB, http://www.cdyn.org) is a database that aims to provide comprehensive results on the conformational dynamics of high molecular weight proteins and protein assemblies. Analysis is performed using a recently introduced coarse-grained computational approach that is applied to the majority of structures present in the electron microscopy data bank (EMDB). Results include equilibrium thermal fluctuations and elastic strain energy distributions that identify rigid versus flexible protein domains generally, as well as those associated with specific functional transitions, and correlations in molecular motions that identify molecular regions that are highly coupled dynamically, with implications for allosteric mechanisms. A practical web-based search interface enables users to easily collect conformational dynamics data in various formats. The data bank is maintained and updated automatically to include conformational dynamics results for new structural entries as they become available in the EMDB. The CDDB complements static structural information to facilitate the investigation and interpretation of the biological function of proteins and protein assemblies essential to cell function.

PEAS V1.0: a package for elementary analysis of SNP data

We have developed a software package named PEAS to facilitate analyses of large data sets of single nucleotide polymorphisms (SNPs) for population genetics and molecular phylogenetics studies. PEAS reads SNP data in various formats as input and is versatile in data formatting; using PEAS, it is easy to create input files for many popular packages, such as STRUCTURE, frappe, Arlequin, Haploview, LDhat, PLINK, EIGENSOFT, PHASE, fastPHASE, MEGA and PHYLIP. In addition, PEAS fills up several analysis gaps in currently available computer programs in population genetics and molecular phylogenetics. Notably, (i) It calculates genetic distance matrices with bootstrapping for both individuals and populations from genome-wide high-density SNP data, and the output can be streamlined to MEGA and PHYLIP programs for further processing; (ii) It calculates genetic distances from STRUCTURE output and generates MEGA file to reconstruct component trees; (iii) It provides tools to conduct haplotype sharing analysis for phylogenetic studies based on high-density SNP data. To our knowledge, these analyses are not available in any other computer program. PEAS for Windows is freely available for academic users from http://www.picb.ac.cn/~xushua/index.files/Download_PEAS.htm.

Web service based hydrologic data distribution system

Hydrological modeling has been undergoing an exciting phase of transformation driven by rapid advances in remote sensing technology and computing power. In particular, NASA’s Earth Observation System (EOS) suite of satellite platforms and sensors has made available a variety of biophysical measurements that have the potential to immensely advance the science and application of hydrology. These sensors use a variety of remote sensing technologies to make measurements of hydrological variables at several scales of spatial and temporal resolution. These rich datasets are available in a variety of data formats with different data access techniques, data quality issues and temporal and spatial extents that may be intimidating to the end user. As more and more watersheds become gauged and satellite instruments get deployed, it becomes important to make data availability and usage as streamlined as possible for potential users. We propose a Web Services based data distribution system to deliver remote sensing data to the hydrologic community. The use of Web Services for data delivery will permit hydrologists to directly integrate data sources into their hydrological models with minimal effort.

Relational and XML Data Exchange

Data exchange is the problem of finding an instance of a target schema, given an instance of a source schema and a specification of the relationship between the source and the target. Such a target instance should correctly represent information from the source instance under the constraints imposed by the target schema, and it should allow one to evaluate queries on the target instance in a way that is semantically consistent with the source data. Data exchange is an old problem that re-emerged as an active research topic recently, due to the increased need for exchange of data in various formats, often in e-business applications. In this lecture, we give an overview of the basic concepts of data exchange in both relational and XML contexts. We give examples of data exchange problems, and we introduce the main tasks that need to addressed. We then discuss relational data exchange, concentrating on issues such as relational schema mappings, materializing target instances (including canonical solutions and cores), query answering, and query rewriting. After that, we discuss metadata management, i.e., handling schema mappings themselves. We pay particular attention to operations on schema mappings, such as composition and inverse. Finally, we describe both data exchange and metadata management in the context of XML. We use mappings based on transforming tree patterns, and we show that they lead to a host of new problems that did not arise in the relational case, but they need to be addressed for XML. These include consistency issues for mappings and schemas, as well as imposing tighter restrictions on mappings and queries to achieve tractable query answering in data exchange. Table of Contents: Overview / Relational Mappings and Data Exchange / Metadata Management / XML Mappings and Data Exchange

CyanoBase: the cyanobacteria genome database update 2010

CyanoBase (http://genome.kazusa.or.jp/cyanobase) is the genome database for cyanobacteria, which are model organisms for photosynthesis. The database houses cyanobacteria species information, complete genome sequences, genome-scale experiment data, gene information, gene annotations and mutant information. In this version, we updated these datasets and improved the navigation and the visual display of the data views. In addition, a web service API now enables users to retrieve the data in various formats with other tools, seamlessly.

From data to text in the Neonatal Intensive Care Unit: Using NLG technology for decision support and information management

Contemporary Neonatal Intensive Care Units collect vast amounts of patient data in various formats, making efficient processing of information by medical professionals difficult. Moreover, different stakeholders in the neonatal scenario, which include parents as well as staff occupying different roles, have different information requirements. This paper describes recent and ongoing work on building systems that automatically generate textual summaries of neonatal data. Our evaluation results show that the technology is viable and comparable in its effectiveness for decision support to existing presentation modalities. We discuss the lessons learned so far, as well as the major challenges involved in extending current technology to deal with a broader range of data types, and to improve the textual output in the form of more coherent summaries.

Incremental pattern discovery on streams, graphs and tensors

Incremental pattern discovery targets streaming applications where the data continuously arrive incrementally. The questions are how to find patterns (main trends) incrementally; or how to efficiently update the old patterns when new data arrive; or how to utilize the patterns to solve other problems such as anomaly detection? We first investigate a powerful data model, tensor stream (TS), where there is one tensor per timestamp. To capture diverse data formats, we have a zero-order TS for a single time-series (e.g., the stock price over time), a first-order TS for multiple time-series (sensor measurement streams), a second-order TS for matrices (graphs), and a high-order TS for multi-arrays (Internet communication network, source-destination-port). Second, we develop different online algorithms on TS: 1) the centralized and distributed SPIRIT [7] for mining a 1st-order TS, as well as its extensions for local correlation function and privacy preservation; 2) the compact matrix decomposition (CMD) [5] and GraphScope [4] for a 2nd-order TS; 3) the dynamic tensor analysis (DTA) [2], streaming tensor analysis (STA) and window-based tensor analysis (WTA) for a high-order TS. All the techniques are extensively evaluated for real applications such as network forensics, cluster monitoring.

CC+: a relational database of coiled-coil structures

We introduce the CC+ Database, a detailed, searchable repository of coiled-coil assignments, which is freely available at http://coiledcoils.chm.bris.ac.uk/ccplus. Coiled coils were identified using the program SOCKET, which locates coiled coils based on knobs-into-holes packing of side chains between α-helices. A method for determining the overall sequence identity of coiled-coil sequences was introduced to reduce statistical bias inherent in coiled-coil data sets. There are two points of entry into the CC+ Database: the ‘Periodic Table of Coiled-coil Structures’, which presents a graphical path through coiled-coil space based on manually validated data, and the ‘Dynamic Interface’, which allows queries of the database at different levels of complexity and detail. The latter entry level, which is the focus of this article, enables the efficient and rapid compilation of subsets of coiled-coil structures. These can be created and interrogated with increasingly sophisticated pull-down, keyword and sequence-based searches to return detailed structural and sequence information. Also provided are means for outputting the retrieved coiled-coil data in various formats, including PyMOL and RasMol scripts, and Position-Specific Scoring Matrices (or amino-acid profiles), which may be used, for example, in protein-structure prediction.

496: FOX-DB: A fetal ontology X-reference database for fetal medicine

Terminology and coding systems vary widely in fetal medicine. This lack of uniformity hampers effective communication & comparison of results between different units, specialties and countries. We aimed to develop a lexicon of terminology and definitions (a biomedical ontology) that could be used by all MFM’s in Canada. This would be maintained through a web server allowing clinicians to obtain standardized, transferable, accurate results for clinical and research purposes. FOX-DB was developed in Visual Studio.Net 2005 to cross-reference some of the most respected and widely used international coding systems: 1) ICD-10, 2) London Database, 3) American Cardiac Association, 4) OMIM, 5) British Pediatric Association COD, 6) Orpha.Net. Other appropriate systems can be included in the future. A mutidisciplinary group used FOX-DB to develop and evaluate a unified ontology by x-referencing terminologies and codes across various coding systems. Variables were compared at several levels: i) clinical systems, ii) sub-components, iii) antenatal findings, iv) postnatal diagnoses, v) frequency of occurence. Preliminary analyses show marked differences and overlap in terminology and coding between systems. We created a unified ontology in XML format of several thousand entries. These data can be converted into a variety of formats for different computer systems & epidemiological databases. Entries were divided into findings and diagnoses, each being associated with various ontological properties and x-referenced with various coding systems. We are developing an online web server to facilitate maintenance, distribution and analysis in a variety of data formats. Standardized terminology is essential for effective clinical and research communication between specialties, databases, units & countries. It would allow data sharing between institutions and would improve record accuracy. We suggest that FOX-DB may have widespread application and appeal for many clinicians internationally.

Imaging Infrastructure Issues for Automated Imaging

Increased sophistication in laboratory automation has increased the importance of computer technology, and has had an impact on the information technology infrastructure of organizations as a whole. Scientific imaging architecture is the subject of this technical note, because of the diversity of the technology, variety of data formats, and the volume of data it represents. The infrastructure elements affected by automated imaging are acquisition computers, image analysis workstations, data storage, and network. This note describes infrastructure issues that may arise and suggest solutions.