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At least 703 records · Page 39Linked to original sources
PubMed1991

Genome mapping databases: data acquisition, storage and access.

The introduction of the genome database to the human gene mapping community in September 1990 heralded the advent of a new generation of databases to serve the needs of the human genome initiative over the coming years. The databases will act as a fulcrum around which the activities of the human genome initiative can be coordinated at an international level.

Animals↗
PubMed2003

The impact of future trends in electronic data collection on musculoskeletal research and evidence-based orthopaedic care.

Electronic medical documentation systems offer the greatest potential source of data to enable the evolution to evidence-based musculoskeletal care. To this end, it is important that providers of musculoskeletal care embrace structured medical records systems that record medical information in fields thereby making data easily accessible for the purpose of later analysis. Gathering data in a structured format can be labor intensive but significant time and cost savings are realized by reduced dictation and transcription and the automated output of requisitions and correspondence. Physicians will only use structured electronic records if the system reduces overhead while at the same time minimizing their work load. Since getting information into the system is the greatest impediment to successful implementation of a structured record, the use of Web forms for previsit patient data entry and touch screen handheld computers with wireless connectivity for provider data entry will play an important role in facilitating their adoption. Ultimately, industry-standard, field-naming nomenclature for specific historical features, examination findings, and therapeutic interventions will make data in all documentation systems comparable regardless of vendor. When that day comes, every new patient assessed will be a candidate for a prospective study.

Data Collection↗
PubMed2026

Analysis of deep-resequencing data of 984 soybean accessions reveals structural variations underlying agronomic traits.

Genomic structural variants (SVs) are major sources of genetic variation and have profound impacts on phenotypic traits. However, their functional effects remain largely unexplored in soybean. Here, we resequence 940 soybean accessions. Together with 44 publicly available datasets, we identify 602,281 SVs. Using a graph-based genome, we detect an additional 58,760 presence/absence variations (PAVs) that broadly affect gene expression. Population genomic analyses reveal that SVs serve as a core driving force for soybean domestication and improvement. Integrating SVs with QTLs for oil and protein content, and performing GWAS on 27 traits, we identify key functional SVs. These include transposable element insertions altering seed coat color, multiple insertions within a cytochrome P450 gene modifying flower and hypocotyl color, and a GmMATE1 deletion enhancing seed size. Together, our study establishes a comprehensive SV map of soybean, offering a valuable resource for dissecting the genetic basis of complex traits to accelerate molecular breeding.

Glycine max↗
PubMed2004

NASCArrays: a repository for microarray data generated by NASC's transcriptomics service.

NASC operates an Affymetrix 'GeneChip' (microarray) service for the Arabidopsis thaliana community. All data produced by the service are publicly available through our microarray data base 'NASCArrays' published at http://affymetrix. arabidopsis.info. The data are accessible through text searching and a series of data mining tools. All data are annotated with sample preparation details, and the original Affymetrix data are available for download. The database aims to be MIAME supportive and provide a coordinated resource for re searchers interested in the transcriptome of Arabidopsis. Using this database, data produced will be shared with other databases worldwide.

Arabidopsis↗
PubMed2002

The Bioperl toolkit: Perl modules for the life sciences.

The Bioperl project is an international open-source collaboration of biologists, bioinformaticians, and computer scientists that has evolved over the past 7 yr into the most comprehensive library of Perl modules available for managing and manipulating life-science information. Bioperl provides an easy-to-use, stable, and consistent programming interface for bioinformatics application programmers. The Bioperl modules have been successfully and repeatedly used to reduce otherwise complex tasks to only a few lines of code. The Bioperl object model has been proven to be flexible enough to support enterprise-level applications such as EnsEMBL, while maintaining an easy learning curve for novice Perl programmers. Bioperl is capable of executing analyses and processing results from programs such as BLAST, ClustalW, or the EMBOSS suite. Interoperation with modules written in Python and Java is supported through the evolving BioCORBA bridge. Bioperl provides access to data stores such as GenBank and SwissProt via a flexible series of sequence input/output modules, and to the emerging common sequence data storage format of the Open Bioinformatics Database Access project. This study describes the overall architecture of the toolkit, the problem domains that it addresses, and gives specific examples of how the toolkit can be used to solve common life-sciences problems. We conclude with a discussion of how the open-source nature of the project has contributed to the development effort.

Algorithms↗
PubMed2005

The maize genetics and genomics database. The community resource for access to diverse maize data.

The Maize Genetics and Genomics Database (MaizeGDB) serves the maize (Zea mays) research community by making a wealth of genetics and genomics data available through an intuitive Web-based interface. The goals of the MaizeGDB project are 3-fold: to provide a central repository for public maize information; to present the data through the MaizeGDB Web site in a way that recapitulates biological relationships; and to provide an array of computational tools that address biological questions in an easy-to-use manner at the site. In addition to these primary tasks, MaizeGDB team members also serve the community of maize geneticists by lending technical support for community activities, including the annual Maize Genetics Conference and various workshops, teaching researchers to use both the MaizeGDB Web site and Community Curation Tools, and engaging in collaboration with individual research groups to make their unique data types available through MaizeGDB.

Base Sequence↗