Pedro: a configurable data entry tool for XML

Pedro is a Java application that dynamically generates data entry forms for data models expressed in XML Schema, producing XML data files that validate against this schema. The software uses an intuitive tree-based navigation system, can supply context-sensitive help to users and features a sophisticated interface for populating data fields with terms from controlled vocabularies. The software also has the ability to import records from tab delimited text files and features various validation routines. AVAILABILITY: The application, source code, example models from several domains and tutorials can be downloaded from http://pedro.man.ac.uk/.     

Tools for loading MEDLINE into a local relational database

Background  

Researchers who use MEDLINE for text mining, information extraction, or natural language processing may benefit from having a copy of MEDLINE that they can manage locally. The National Library of Medicine (NLM) distributes MEDLINE in eXtensible Markup Language (XML)-formatted text files, but it is difficult to query MEDLINE in that format. We have developed software tools to parse the MEDLINE data files and load their contents into a relational database. Although the task is conceptually straightforward, the size and scope of MEDLINE make the task nontrivial. Given the increasing importance of text analysis in biology and medicine, we believe a local installation of MEDLINE will provide helpful computing infrastructure for researchers.     

Straightforward and complete deposition of NMR data to the PDBe

We present a suite of software for the complete and easy deposition of NMR data to the PDB and BMRB. This suite uses the CCPN framework and introduces a freely downloadable, graphical desktop application called CcpNmr Entry Completion Interface (ECI) for the secure editing of experimental information and associated datasets through the lifetime of an NMR project. CCPN projects can be created within the CcpNmr Analysis software or by importing existing NMR data files using the CcpNmr FormatConverter. After further data entry and checking with the ECI, the project can then be rapidly deposited to the PDBe using AutoDep, or exported as a complete deposition NMR-STAR file. In full CCPN projects created with ECI, it is straightforward to select chemical shift lists, restraint data sets, structural ensembles and all relevant associated experimental collection details, which all are or will become mandatory when depositing to the PDB. Instructions and download information for the ECI are available from the PDBe web site at http://www.ebi.ac.uk/pdbe/nmr/deposition/eci.html.     

PDBML: the representation of archival macromolecular structure data in XML

Summary: The Protein Data Bank (PDB) has recently released versionsof the PDB Exchange dictionary and the PDB archival data filesin XML format collectively named PDBML. The automated generationof these XML files is driven by the data dictionary infrastructurein use at the PDB. The correspondences between the PDB dictionaryand the XML schema metadata are described as well as the XMLrepresentations of PDB dictionaries and data files. Availability: The current software translated XML schema fileis located at http://deposit.pdb.org/pdbML/pdbx-v1.000.xsd,and on the PDB mmCIF resource page at http://deposit.pdb.org/mmcif/.PDBML files are stored on the PDB beta ftp site at ftp://beta.rcsb.org/pub/pdb/uniformity/data/XML Contact: jwest{at}rcsb.rutgers.edu     

BioMagResBank databases DOCR and FRED containing converted and filtered sets of experimental NMR restraints and coordinates from over 500 protein PDB structures

We present two new databases of NMR-derived distance and dihedral angle restraints: the Database Of Converted Restraints (DOCR) and the Filtered Restraints Database (FRED). These databases currently correspond to 545 proteins with NMR structures deposited in the Protein Databank (PDB). The criteria for inclusion were that these should be unique, monomeric proteins with author-provided experimental NMR data and coordinates available from the PDB capable of being parsed and prepared in a consistent manner. The Wattos program was used to parse the files, and the CcpNmr FormatConverter program was used to prepare them semi-automatically. New modules, including a new implementation of Aqua in the BioMagResBank (BMRB) software Wattos were used to analyze the sets of distance restraints (DRs) for inconsistencies, redundancies, NOE completeness, classification and violations with respect to the original coordinates. Restraints that could not be associated with a known nomenclature were flagged. The coordinates of hydrogen atoms were recalculated from the positions of heavy atoms to allow for a full restraint analysis. The DOCR database contains restraint and coordinate data that is made consistent with each other and with IUPAC conventions. The FRED database is based on the DOCR data but is filtered for use by test calculation protocols and longitudinal analyses and validations. These two databases are available from websites of the BMRB and the Macromolecular Structure Database (MSD) in various formats: NMR-STAR, CCPN XML, and in formats suitable for direct use in the software packages CNS and CYANA.Supplementary material to this paper is available in electronic form at http://dx.doi.org/10.1007/s10858-005-2195-0These authors contributed equally to this work.     

SPINS: a laboratory information management system for organizing and archiving intermediate and final results from NMR protein structure determinations

Recent technological advances and experimental techniques have contributed to an increasing number and size of NMR datasets. In order to scale up productivity, laboratory information management systems for handling these extensive data need to be designed and implemented. The SPINS (Standardized ProteIn Nmr Storage) Laboratory Information Management System (LIMS) addresses these needs by providing an interface for archival of complete protein NMR structure determinations, together with functionality for depositing these data to the public BioMagResBank (BMRB). The software tracks intermediate files during each step of an NMR structure-determination process, including: data collection, data processing, resonance assignments, resonance assignment validation, structure calculation, and structure validation. The underlying SPINS data dictionary allows for the integration of various third party NMR data processing and analysis software, enabling users to launch programs they are accustomed to using for each step of the structure determination process directly out of the SPINS user interface.     

植物激素相关核酸和蛋白质二级数据库的构建与应用

以NCBI维护的一级数据库为数据源建立植物激素相关核酸和蛋白质二级数据库。将该二级数据库设计为基因、蛋白质和文献三部分,编写软件从上述数据源中采集数据,并以XML作为中间格式保存,通过解析提交到二级数据库中并集成部分生物信息学工具软件,初步实现了数据检索、统计分析、基于Web的本地化BLAST同源序列检索、序列的自动拼接以及蛋白质结构和功能位点的分析等功能。该二级数据库的构建为植物激素作用分子机理研究提供了高针对性的植物激素数据源和生物信息学辅助工具。     

Simultaneous modelling of metabolic, genetic and product-interaction networks

The creation of cell models from annotated genome information, as well as additional data from other databases, requires both a format and medium for its distribution. Standards are described for the representation of the data in the form of Document Type Definitions (DTDs) for XML files. Separate DTDs are detailed for genetic, metabolic and gene product-interaction networks, which can be used to hold information on individual subsystems, or which may be combined to create a whole cell DTD. In the execution of this work, a fifth DTD was also created for a metabolite thesaurus, which allows incorporation of metabolite synonyms and generic nomenclature data into the models. A gene-regulation classification scheme was also created, to facilitate incorporation of gene regulatory information in an efficient manner. The work is described with particular reference to the metabolic network of Escherichia coli, which contains 808 individual enzymes. The assignment of confidence levels to these data, through the use of Gene Ontology evidence codes, is highlighted. In silico investigations may now be performed using the mathematical simulation workbench, DBsolve, which incorporates the facility to introduce data directly from XML.     

BioMagResBank database with sets of experimental NMR constraints corresponding to the structures of over 1400 biomolecules deposited in the Protein Data Bank

Experimental constraints associated with NMR structures are available from the Protein Data Bank (PDB) in the form of `Magnetic Resonance' (MR) files. These files contain multiple types of data concatenated without boundary markers and are difficult to use for further research. Reported here are the results of a project initiated to annotate, archive, and disseminate these data to the research community from a searchable resource in a uniform format. The MR files from a set of 1410 NMR structures were analyzed and their original constituent data blocks annotated as to data type using a semi-automated protocol. A new software program called Wattos was then used to parse and archive the data in a relational database. From the total number of MR file blocks annotated as constraints, it proved possible to parse 84% (3337/3975). The constraint lists that were parsed correspond to three data types (2511 distance, 788 dihedral angle, and 38 residual dipolar couplings lists) from the three most popular software packages used in NMR structure determination: XPLOR/CNS (2520 lists), DISCOVER (412 lists), and DYANA/DIANA (405 lists). These constraints were then mapped to a developmental version of the BioMagResBank (BMRB) data model. A total of 31 data types originating from 16 programs have been classified, with the NOE distance constraint being the most commonly observed. The results serve as a model for the development of standards for NMR constraint deposition in computer-readable form. The constraints are updated regularly and are available from the BMRB web site (http://www.bmrb.wisc.edu).     

MASCOT HTML and XML parser: an implementation of a novel object model for protein identification data

Protein identification using MS is an important technique in proteomics as well as a major generator of proteomics data. We have designed the protein identification data object model (PDOM) and developed a parser based on this model to facilitate the analysis and storage of these data. The parser works with HTML or XML files saved or exported from MASCOT MS/MS ions search in peptide summary report or MASCOT PMF search in protein summary report. The program creates PDOM objects, eliminates redundancy in the input file, and has the capability to output any PDOM object to a relational database. This program facilitates additional analysis of MASCOT search results and aids the storage of protein identification information. The implementation is extensible and can serve as a template to develop parsers for other search engines. The parser can be used as a stand-alone application or can be driven by other Java programs. It is currently being used as the front end for a system that loads HTML and XML result files of MASCOT searches into a relational database. The source code is freely available at http://www.ccbm.jhu.edu and the program uses only free and open-source Java libraries.     

Fast and Efficient XML Data Access for Next-Generation Mass Spectrometry

Motivation

In mass spectrometry-based proteomics, XML formats such as mzML and mzXML provide an open and standardized way to store and exchange the raw data (spectra and chromatograms) of mass spectrometric experiments. These file formats are being used by a multitude of open-source and cross-platform tools which allow the proteomics community to access algorithms in a vendor-independent fashion and perform transparent and reproducible data analysis. Recent improvements in mass spectrometry instrumentation have increased the data size produced in a single LC-MS/MS measurement and put substantial strain on open-source tools, particularly those that are not equipped to deal with XML data files that reach dozens of gigabytes in size.

Results

Here we present a fast and versatile parsing library for mass spectrometric XML formats available in C++ and Python, based on the mature OpenMS software framework. Our library implements an API for obtaining spectra and chromatograms under memory constraints using random access or sequential access functions, allowing users to process datasets that are much larger than system memory. For fast access to the raw data structures, small XML files can also be completely loaded into memory. In addition, we have improved the parsing speed of the core mzML module by over 4-fold (compared to OpenMS 1.11), making our library suitable for a wide variety of algorithms that need fast access to dozens of gigabytes of raw mass spectrometric data.

Availability

Our C++ and Python implementations are available for the Linux, Mac, and Windows operating systems. All proposed modifications to the OpenMS code have been merged into the OpenMS mainline codebase and are available to the community at https://github.com/OpenMS/OpenMS.     

jmzTab: A Java interface to the mzTab data standard

mzTab is the most recent standard format developed by the Proteomics Standards Initiative. mzTab is a flexible tab‐delimited file that can capture identification and quantification results coming from MS‐based proteomics and metabolomics approaches. We here present an open‐source Java application programming interface for mzTab called jmzTab. The software allows the efficient processing of mzTab files, providing read and write capabilities, and is designed to be embedded in other software packages. The second key feature of the jmzTab model is that it provides a flexible framework to maintain the logical integrity between the metadata and the table‐based sections in the mzTab files. In this article, as two example implementations, we also describe two stand‐alone tools that can be used to validate mzTab files and to convert PRIDE XML files to mzTab. The library is freely available at http://mztab.googlecode.com .     

New strategy for the representation and the integration of biomolecular knowledge at a cellular scale

The combination of sequencing and post-sequencing experimental approaches produces huge collections of data that are highly heterogeneous both in structure and in semantics. We propose a new strategy for the integration of such data. This strategy uses structured sets of sequences as a unified representation of biological information and defines a probabilistic measure of similarity between the sets. Sets can be composed of sequences that are known to have a biological relationship (e.g. proteins involved in a complex or a pathway) or that share similar values for a particular attribute (e.g. expression profile). We have developed a software, BlastSets, which implements this strategy. It exploits a database where the sets derived from diverse biological information can be deposited using a standard XML format. For a given query set, BlastSets returns target sets found in the database whose similarity to the query is statistically significant. The tool allowed us to automatically identify verified relationships between correlated expression profiles and biological pathways using publicly available data for Saccharomyces cerevisiae. It was also used to retrieve the members of a complex (ribosome) based on the mining of expression profiles. These first results validate the relevance of the strategy and demonstrate the promising potential of BlastSets.     

Representing genetic sequence data for pharmacogenomics: an evolutionary approach using ontological and relational models

MOTIVATION: The information model chosen to store biological data affects the types of queries possible, database performance, and difficulty in updating that information model. Genetic sequence data for pharmacogenetics studies can be complex, and the best information model to use may change over time. As experimental and analytical methods change, and as biological knowledge advances, the data storage requirements and types of queries needed may also change. RESULTS: We developed a model for genetic sequence and polymorphism data, and used XML Schema to specify the elements and attributes required for this model. We implemented this model as an ontology in a frame-based representation and as a relational model in a database system. We collected genetic data from two pharmacogenetics resequencing studies, and formulated queries useful for analysing these data. We compared the ontology and relational models in terms of query complexity, performance, and difficulty in changing the information model. Our results demonstrate benefits of evolving the schema for storing pharmacogenetics data: ontologies perform well in early design stages as the information model changes rapidly and simplify query formulation, while relational models offer improved query speed once the information model and types of queries needed stabilize.     

Relationship between chemical shift value and accessible surface area for all amino acid atoms

Background  

Chemical shifts obtained from NMR experiments are an important tool in determining secondary, even tertiary, protein structure. The main repository for chemical shift data is the BioMagResBank, which provides NMR-STAR files with this type of information. However, it is not trivial to link this information to available coordinate data from the PDB for non-backbone atoms due to atom and chain naming differences, as well as sequence numbering changes.     

jmzML,an open‐source Java API for mzML,the PSI standard for MS data

We here present jmzML, a Java API for the Proteomics Standards Initiative mzML data standard. Based on the Java Architecture for XML Binding and XPath‐based XML indexer random‐access XML parser, jmzML can handle arbitrarily large files in minimal memory, allowing easy and efficient processing of mzML files using the Java programming language. jmzML also automatically resolves internal XML references on‐the‐fly. The library (which includes a viewer) can be downloaded from http://jmzml.googlecode.com .     

植物激素相关核酸和蛋白质二级数据库的构建与应用

以NCBI维护的一级数据库为数据源建立植物激素相关核酸和蛋白质二级数据库。将该二级数据库设计为基因、蛋白质和文献三部分, 编写软件从上述数据源中采集数据, 并以XML作为中间格式保存, 通过解析提交到二级数据库中并集成部分生物信息学工具软件, 初步实现了数据检索、统计分析、基于Web的本地化BLAST同源序列检索、序列的自动拼接以及蛋白质结构和功能位点的分析等功能。该二级数据库的构建为植物激素作用分子机理研究提供了高针对性的植物激素数据源和生物信息学辅助工具。     

OligoFaktory: a visual tool for interactive oligonucleotide design

SUMMARY: The OligoFaktory is a set of tools for the design, on an arbitrary number of target sequences, of high-quality long oligonucleotide for micro-array, of primer pair for PCR, of siRNA and more. The user-centered interface exists in two flavours: a web portal and a standalone software for Mac OS X Tiger. A unified presentation of results provides overviews with distribution charts and relative location bar graphs, as well as detailed features for each oligonucleotide. Input and output files conform to a common XML interchange file format to allow both automatic generation of input data, archiving, and post-processing of results. The design pipeline can use BLAST servers to evaluate specificity of selected oligonucleotides. AVAILABILITY: The web portal http://ueg.ulb.ac.be/oligofaktory/; the software for Macintosh: http://www.oligofaktory.org/     

IDR: the ImmunoDeficiency Resource

The ImmunoDeficiency Resource (IDR), freely available at http://www.uta.fi/imt/bioinfo/idr/, is a comprehensive knowledge base on immunodeficiencies. It is designed for different user groups such as researchers, physicians and nurses as well as patients and their families and the general public. Information on immunodeficiencies is stored as fact files, which are disease- and gene-based information resources. We have developed an inherited disease markup language (IDML) data model, which is designed for storing disease- and gene-specific data in extensible markup language (XML) format. The fact files written by the IDML can be used to present data in different contexts and platforms. All the information in the IDR is validated by expert curators.