Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

DDBJ in preparation for overview of research activities behind data submissions.

ABSTRACT: In the past year, DDBJ (http://www.ddbj.nig.ac.jp) collected and released 1,956,826 entries or 1,741,313,111 bases. The released data include approximately 90,000 ESTs and cDNAs of Macaca fascicularis, and 280 million bases of mouse GSS. In addition to the data collection, we have indexed the submitted data to the International Nucleotide Sequence Database Collaboration (INSDC, http://www.insdc.org) to classify the entries into research projects behind data submissions. They are expected to be useful to the data submitters and users for enhancing the data submission, retrieval and systematic data analyses at INSDC. The results of indexing also allow one to grasp research projects in life sciences that promoted and produced the DNA sequences submitted to INSDC.

SUBMITTER: Okubo K

PROVIDER: S-EPMC1347473 | biostudies-literature | 2006 Jan

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Publications

DDBJ in preparation for overview of research activities behind data submissions.

Okubo Kousaku K Sugawara Hideaki H Gojobori Takashi T Tateno Yoshio Y

Nucleic acids research 20060101 Database issue

In the past year, DDBJ (http://www.ddbj.nig.ac.jp) collected and released 1,956,826 entries or 1,741,313,111 bases. The released data include approximately 90,000 ESTs and cDNAs of Macaca fascicularis, and 280 million bases of mouse GSS. In addition to the data collection, we have indexed the submitted data to the International Nucleotide Sequence Database Collaboration (INSDC, http://www.insdc.org) to classify the entries into research projects behind data submissions. They are expected to be u ...[more]

PMID: 16381940

Similar Datasets

ArrayExpress update--simplifying data submissions.

Project description:The ArrayExpress Archive of Functional Genomics Data (http://www.ebi.ac.uk/arrayexpress) is an international functional genomics database at the European Bioinformatics Institute (EMBL-EBI) recommended by most journals as a repository for data supporting peer-reviewed publications. It contains data from over 7000 public sequencing and 42,000 array-based studies comprising over 1.5 million assays in total. The proportion of sequencing-based submissions has grown significantly over the last few years and has doubled in the last 18 months, whilst the rate of microarray submissions is growing slightly. All data in ArrayExpress are available in the MAGE-TAB format, which allows robust linking to data analysis and visualization tools and standardized analysis. The main development over the last two years has been the release of a new data submission tool Annotare, which has reduced the average submission time almost 3-fold. In the near future, Annotare will become the only submission route into ArrayExpress, alongside MAGE-TAB format-based pipelines. ArrayExpress is a stable and highly accessed resource. Our future tasks include automation of data flows and further integration with other EMBL-EBI resources for the representation of multi-omics data.

| S-EPMC4383899 | biostudies-literature

Data integration in biological research: an overview.

Project description:Data sharing, integration and annotation are essential to ensure the reproducibility of the analysis and interpretation of the experimental findings. Often these activities are perceived as a role that bioinformaticians and computer scientists have to take with no or little input from the experimental biologist. On the contrary, biological researchers, being the producers and often the end users of such data, have a big role in enabling biological data integration. The quality and usefulness of data integration depend on the existence and adoption of standards, shared formats, and mechanisms that are suitable for biological researchers to submit and annotate the data, so it can be easily searchable, conveniently linked and consequently used for further biological analysis and discovery. Here, we provide background on what is data integration from a computational science point of view, how it has been applied to biological research, which key aspects contributed to its success and future directions.

| S-EPMC4557916 | biostudies-literature

DNA Data Bank of Japan (DDBJ) update report 2021.

Project description:The Bioinformation and DDBJ (DNA Data Bank of Japan) Center (DDBJ Center; https://www.ddbj.nig.ac.jp) operates archival databases that collect nucleotide sequences, study and sample information, and distribute them without access restriction to progress life science research as a member of the International Nucleotide Sequence Database Collaboration (INSDC), in collaboration with the National Center for Biotechnology Information (NCBI) and the European Bioinformatics Institute. Besides the INSDC databases, the DDBJ Center also provides the Genomic Expression Archive for functional genomics data and the Japanese Genotype-phenotype Archive for human data requiring controlled access. Additionally, the DDBJ Center started a new public repository, MetaboBank, for experimental raw data and metadata from metabolomics research in October 2020. In response to the COVID-19 pandemic, the DDBJ Center openly shares SARS-CoV-2 genome sequences in collaboration with Shizuoka Prefecture and Keio University. The operation of DDBJ is based on the National Institute of Genetics (NIG) supercomputer, which is open for large-scale sequence data analysis for life science researchers. This paper reports recent updates on the archival databases and the services of DDBJ.

| S-EPMC8689959 | biostudies-literature

An overview of longitudinal data analysis methods for neurological research.

Project description:The purpose of this article is to provide a concise, broad and readily accessible overview of longitudinal data analysis methods, aimed to be a practical guide for clinical investigators in neurology. In general, we advise that older, traditional methods, including (1) simple regression of the dependent variable on a time measure, (2) analyzing a single summary subject level number that indexes changes for each subject and (3) a general linear model approach with a fixed-subject effect, should be reserved for quick, simple or preliminary analyses. We advocate the general use of mixed-random and fixed-effect regression models for analyses of most longitudinal clinical studies. Under restrictive situations or to provide validation, we recommend: (1) repeated-measure analysis of covariance (ANCOVA), (2) ANCOVA for two time points, (3) generalized estimating equations and (4) latent growth curve/structural equation models.

| S-EPMC3243635 | biostudies-literature

DDBJ dealing with mass data produced by the second generation sequencer.

Project description:DNA Data Bank of Japan (DDBJ) (http://www.ddbj.nig.ac.jp) collected and released 2 368 110 entries or 1 415 106 598 bases in the period from July 2007 to June 2008. The releases in this period include genome scale data of Bombyx mori, Oryzas latipes, Drosophila and Lotus japonicus. In addition, from this year we collected and released trace archive data in collaboration with National Center for Biotechnology Information (NCBI). The first release contains those of O. latipes and bacterial meta genomes in human gut. To cope with the current progress of sequencing technology, we also accepted and released more than 100 million of short reads of parasitic protozoa and their hosts that were produced by using a Solexa sequencer.

| S-EPMC2686496 | biostudies-literature

DDBJ progress report.

Project description:The DNA Data Bank of Japan (DDBJ, http://www.ddbj.nig.ac.jp) provides a nucleotide sequence archive database and accompanying database tools for sequence submission, entry retrieval and annotation analysis. The DDBJ collected and released 3,637,446 entries/2,272,231,889 bases between July 2009 and June 2010. A highlight of the released data was archive datasets from next-generation sequencing reads of Japanese rice cultivar, Koshihikari submitted by the National Institute of Agrobiological Sciences. In this period, we started a new archive for quantitative genomics data, the DDBJ Omics aRchive (DOR). The DOR stores quantitative data both from the microarray and high-throughput new sequencing platforms. Moreover, we improved the content of the DDBJ patent sequence, released a new submission tool of the DDBJ Sequence Read Archive (DRA) which archives massive raw sequencing reads, and enhanced a cloud computing-based analytical system from sequencing reads, the DDBJ Read Annotation Pipeline. In this article, we describe these new functions of the DDBJ databases and support tools.

| S-EPMC3013661 | biostudies-literature

The DDBJ Japanese Genotype-phenotype Archive for genetic and phenotypic human data.

Project description:The DNA Data Bank of Japan Center (DDBJ Center; http://www.ddbj.nig.ac.jp) maintains and provides public archival, retrieval and analytical services for biological information. Since October 2013, DDBJ Center has operated the Japanese Genotype-phenotype Archive (JGA) in collaboration with our partner institute, the National Bioscience Database Center (NBDC) of the Japan Science and Technology Agency. DDBJ Center provides the JGA database system which securely stores genotype and phenotype data collected from individuals whose consent agreements authorize data release only for specific research use. NBDC has established guidelines and policies for sharing human-derived data and reviews data submission and usage requests from researchers. In addition to the JGA project, DDBJ Center develops Semantic Web technologies for data integration and sharing in collaboration with the Database Center for Life Science. This paper describes the overview of the JGA project, updates to the DDBJ databases, and services for data retrieval, analysis and integration.

| S-EPMC4383935 | biostudies-literature

DNA data bank of Japan (DDBJ) in collaboration with mass sequencing teams.

Project description:We at DDBJ (http://www.ddbj.nig.ac.jp) process and publicise the massive amounts of data submitted mainly by Japanese genome projects and sequencing teams. It is emphasised that the collaboration between data producing teams and the data bank is crucial in carrying out these processes smoothly. The amount of data submitted in 1999 is so large that it alone exceeds the total amount submitted in the preceding 10 years. To cope with this situation, we have developed tools not only for processing such massive amounts of data but also for efficiently retrieving data on demand.

| S-EPMC102400 | biostudies-literature

A data driven methodology for social science research with left-behind children as a case study.

Project description:For decades, traditional correlation analysis and regression models have been used in social science research. However, the development of machine learning algorithms makes it possible to apply machine learning techniques for social science research and social issues, which may outperform standard regression methods in some cases. Under the circumstances, this article proposes a methodological workflow for data analysis by machine learning techniques that have the possibility to be widely applied in social issues. Specifically, the workflow tries to uncover the natural mechanisms behind the social issues through a data-driven perspective from feature selection to model building. The advantage of data-driven techniques in feature selection is that the workflow can be built without so much restriction of related knowledge and theory in social science. The advantage of using machine learning techniques in modelling is to uncover non-linear and complex relationships behind social issues. The main purpose of our methodological workflow is to find important fields relevant to the target and provide appropriate predictions. However, to explain the result still needs theory and knowledge from social science. In this paper, we trained a methodological workflow with left-behind children as the social issue case, and all steps and full results are included.

| S-EPMC7678991 | biostudies-literature

DDBJ launches a new archive database with analytical tools for next-generation sequence data.

Project description:The DNA Data Bank of Japan (DDBJ) (http://www.ddbj.nig.ac.jp) has collected and released 1,701,110 entries/1,116,138,614 bases between July 2008 and June 2009. A few highlighted data releases from DDBJ were the complete genome sequence of an endosymbiont within protist cells in the termite gut and Cap Analysis Gene Expression tags for human and mouse deposited from the Functional Annotation of the Mammalian cDNA consortium. In this period, we started a novel user announcement service using Really Simple Syndication (RSS) to deliver a list of data released from DDBJ on a daily basis. Comprehensive visualization of a DDBJ release data was attempted by using a word cloud program. Moreover, a new archive for sequencing data from next-generation sequencers, the 'DDBJ Read Archive' (DRA), was launched. Concurrently, for read data registered in DRA, a semi-automatic annotation tool called the 'DDBJ Read Annotation Pipeline' was released as a preliminary step. The pipeline consists of two parts: basic analysis for reference genome mapping and de novo assembly and high-level analysis of structural and functional annotations. These new services will aid users' research and provide easier access to DDBJ databases.

| S-EPMC2808917 | biostudies-literature

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data