MOLE: a data management application based on a protein production data model

MOLE (mining, organizing, and logging experiments) has been developed to meet the growing data management and target tracking needs of molecular biologists and protein crystallographers. The prototype reported here will become a Laboratory Information Management System (LIMS) to help protein scientists manage the large amounts of laboratory data being generated due to the acceleration in proteome research and will furthermore facilitate collaborations between groups based at different sites. To achieve this, MOLE is based on the data model for protein production devised at the European Bioinformatics Institute (Pajon A, et al., Proteins in press).     

TURBOVEG,a comprehensive data base management system for vegetation data

Abstract. The computer software package TURBOVEG (for Microsoft® Windows®) was developed in The Netherlands for the processing of phytosociological data. This package comprises an easy‐to‐use data base management system. The data bank to be managed can be divided into several data bases which may consist of up to 100 000 relevés each. The program provides methods for input, import, selection, and export of relevés. In 1994, TURBOVEG was accepted as the standard computer package for the European Vegetation Survey. Currently it has been installed in more than 25 countries throughout Europe and overseas.     

Automating data manipulation for genetic analysis using a data base management system

Inefficient coding and manipulation of pedigree data have often hindered the progress of genetic studies. In this paper we present the methodology for interfacing a data base management system (DBMS) called MEGADATS with a linkage analysis program called LIPED. Two families that segregate a dominant trait and one test marker were used in a simulated exercise to demonstrate how a DBMS can be used to automate tedious clerical steps and improve the efficiency of a genetic analysis. The merits of this approach to data management are discussed. We conclude that a standardized format for genetic analysis programs would greatly facilitate data analysis.     

HGVbase: a human sequence variation database emphasizing data quality and a broad spectrum of data sources

HGVbase (Human Genome Variation database; http://hgvbase.cgb.ki.se, formerly known as HGBASE) is an academic effort to provide a high quality and non-redundant database of available genomic variation data of all types, mostly comprising single nucleotide polymorphisms (SNPs). Records include neutral polymorphisms as well as disease-related mutations. Online search tools facilitate data interrogation by sequence similarity and keyword queries, and searching by genome coordinates is now being implemented. Downloads are freely available in XML, Fasta, SRS, SQL and tagged-text file formats. Each entry is presented in the context of its surrounding sequence and many records are related to neighboring human genes and affected features therein. Population allele frequencies are included wherever available. Thorough semi-automated data checking ensures internal consistency and addresses common errors in the source information. To keep pace with recent growth in the field, we have developed tools for fully automated annotation. All variants have been uniquely mapped to the draft genome sequence and are referenced to positions in EMBL/GenBank files. Data utility is enhanced by provision of genotyping assays and functional predictions. Recent data structure extensions allow the capture of haplotype and genotype information, and a new initiative (along with BiSC and HUGO-MDI) aims to create a central repository for the broad collection of clinical mutations and associated disease phenotypes of interest.     

Further advances in the development of a data interchange standard for proteomics data

The Protein Standards Initiative (PSI) aims to define community standards for data representation in proteomics and to facilitate data comparison, exchange and verification. Significant progress was made in advancing the design and implementation of a draft standard for exchanging experimental data from proteomics experiments involving mass spectrometry at the 51st Annual Conference of the American Society for Mass Spectrometry. In collaboration with the American Society for Tests and Measurements, the PSI propose to publish this first draft at the forthcoming HUPO 2nd World Congress in Montreal, 8-11 October 2003.     

Weights for data related by a tree

How can one characterize a set of data collected from different biological species, or indeed any set of data related by an evolutionary tree? The structure imposed by the tree implies that the data are not independent, and for most applications this should be taken into account. We describe strategies for weighting the data that circumvent some of the problems of dependency.     

Monitoring accumulating data in a clinical trial

A clinical trial is monitored for efficacy or safety; the variable of interest is death or a similarly serious event. The probability that one therapy has a greater mortality rate than the other is calculated ad libitum during the trial. Adjustments are made for differing patients' prognoses and for survival times.     

Image data in need of a home

Recognized public community databases for image data deposition have been lacking so far. New databases are emerging that provide a promising infrastructure for hosting and distributing high content imaging datasets.     

CyDAS: a cytogenetic data analysis system

For statistical analyses in cancer cytogenetics, the genomic changes encoded by the karyotype must be translated into numerical codes. We developed a program, which extracts chromosomal gains and losses as well as breakpoints from the karyotype. The changes are compiled in tables according to the chromosome bands involved and/or depicted in projection to the respective chromosome ideogram. The data are ready to be integrated into further statistical analyses. The program may be run as desktop or Internet application.     

Booly: a new data integration platform

Background  

Data integration is an escalating problem in bioinformatics. We have developed a web tool and warehousing system, Booly, that features a simple yet flexible data model coupled with the ability to perform powerful comparative analysis, including the use of Boolean logic to merge datasets together, and an integrated aliasing system to decipher differing names of the same gene or protein. Furthermore, Booly features a collaborative sharing system and a public repository so that users can retrieve new datasets while contributors can easily disseminate new content.     

GenoMap,a circular genome data viewer

A Tcl/Tk-based application called GenoMap is described, a viewer for genome-wide map of microarray expression data within a circular bacterial genome. An interactive interface facilitates easy identification of the expressed region. This software is also used for drawing genome-wide quantitative data.     

BIOS a database for marine biological data

BIOS is a computerised database system for holding species distributiondata. Emphasis has been placed on the flexibility in which storedinformation can be accessed. Multiple retrieval pathways permitsimple enquiries to be answered or complicated interrogationsequences for statistical treatment of data. The structuralorganisation of the database is explained and details of itscontents are listed. Examples of applications in the fieldsof zoogeography and ecology are given together with illustrations.     

Mediante: a web-based microarray data manager

Mediante is a MIAME-compliant microarray data manager that links together annotations and experimental data. Developed as a J2EE three-tier application, Mediante integrates a management system for production of long oligonucleotide microarrays, an experimental data repository suitable for home made or commercial microarrays, and a user interface dedicated to the management of microarrays projects. Several tools allow quality control of hybridizations and submission of validated data to public repositories. AVAILABILITY: http://www.microarray.fr. SUPPLEMENTARY INFORMATION: http://www.microarray.fr/SP/lebrigand2007/     

Non-linear PCA: a missing data approach

MOTIVATION: Visualizing and analysing the potential non-linear structure of a dataset is becoming an important task in molecular biology. This is even more challenging when the data have missing values. RESULTS: Here, we propose an inverse model that performs non-linear principal component analysis (NLPCA) from incomplete datasets. Missing values are ignored while optimizing the model, but can be estimated afterwards. Results are shown for both artificial and experimental datasets. In contrast to linear methods, non-linear methods were able to give better missing value estimations for non-linear structured data.Application: We applied this technique to a time course of metabolite data from a cold stress experiment on the model plant Arabidopsis thaliana, and could approximate the mapping function from any time point to the metabolite responses. Thus, the inverse NLPCA provides greatly improved information for better understanding the complex response to cold stress. CONTACT: scholz@mpimp-golm.mpg.de.