Sagace: A web-based search engine for biomedical databases in Japan

Morita, Mizuki; Igarashi, Yoshinobu; Ito, Maori; Chen, Yi An; Nagao, Chioko; Sakaguchi, Yoshiyuki; Sakate, Ryuichi; Masui, Tohru; Mizuguchi, Kenji

doi:10.1186/1756-0500-5-604

Cited by 7 publications

(2 citation statements)

References 6 publications

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“…A Microdata crawler was created to extract these structured data. We modified "Sagace" 96 , a web-based search engine for biomedical data and resources in Japan, developed at the NIBIOHN in collaboration with NBDC. We confirmed that marked-up data showed up as rich snippets in search results.…”

Section: Schemaorg and Rdfa For Biological Databasesmentioning

confidence: 99%

BioHackathon series in 2013 and 2014: improvements of semantic interoperability in life science data and services

et al. 2019

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Publishing databases in the Resource Description Framework (RDF) model is becoming widely accepted to maximize the syntactic and semantic interoperability of open data in life sciences. Here we report advancements made in the 6th and 7th annual BioHackathons which were held in Tokyo and Miyagi respectively. This review consists of two major sections covering: 1) improvement and utilization of RDF data in various domains of the life sciences and 2) meta-data about these RDF data, the resources that store them, and the service quality of SPARQL Protocol and RDF Query Language (SPARQL) endpoints. The first section describes how we developed RDF data, ontologies and tools in genomics, proteomics, metabolomics, glycomics and by literature text mining. The second section describes how we defined descriptions of datasets, the provenance of data, and quality assessment of services and service discovery. By enhancing the harmonization of these two layers of machine-readable data and knowledge, we improve the way community wide resources are developed and published. Moreover, we outline best practices for the future, and prepare ourselves for an exciting and unanticipatable variety of real world applications in coming years.

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Section: Schemaorg and Rdfa For Biological Databasesmentioning

confidence: 99%

BioHackathon series in 2013 and 2014: improvements of semantic interoperability in life science data and services

et al. 2019

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“…The national cyber infrastructure of the United States has progressively improved to support the integration of various big data sources, particularly for biomedical research [46]. There also has been an effort to integrate biomedical data sources in Japan [47]. There is evidence of integrating big data sources in studies related to mental health [48].…”

Section: Implications For Vaccine Researchmentioning

confidence: 99%

Big Data Usage Patterns in the Health Care Domain: A Use Case Driven Approach Applied to the Assessment of Vaccination Benefits and Risks

Liyanage¹,

Lusignan²,

Liaw³

et al. 2014

Yearb Med Inform

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SummaryBackground: Generally benefits and risks of vaccines can be determined from studies carried out as part of regulatory compliance, followed by surveillance of routine data; however there are some rarer and more long term events that require new methods. Big data generated by increasingly affordable personalised computing, and from pervasive computing devices is rapidly growing and low cost, high volume, cloud computing makes the processing of these data inexpensive. Objective: To describe how big data and related analytical methods might be applied to assess the benefits and risks of vaccines. Method: We reviewed the literature on the use of big data to improve health, applied to generic vaccine use cases, that illustrate benefits and risks of vaccination. We defined a use case as the interaction between a user and an information system to achieve a goal. We used flu vaccination and pre-school childhood immunisation as exemplars. Results: We reviewed three big data use cases relevant to assessing vaccine benefits and risks: (i) Big data processing using crowdsourcing, distributed big data processing, and predictive analytics, (ii) Data integration from heterogeneous big data sources, e.g. the increasing range of devices in the "internet of things", and (iii) Real-time monitoring for the direct monitoring of epidemics as well as vaccine effects via social media and other data sources. Conclusions: Big data raises new ethical dilemmas, though its analysis methods can bring complementary real-time capabilities for monitoring epidemics and assessing vaccine benefit-risk balance.

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Plant Genome DataBase Japan (PGDBj)

Nakaya

Ichihara

Asamizu

et al. 2016

Methods in Molecular Biology

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A portal website that integrates a variety of information related to genomes of model and crop plants from databases (DBs) and the literature was generated. This website, named the Plant Genome DataBase Japan (PGDBj, http://pgdbj. jp/en/ ), is comprised of three component DBs and a cross-search engine which provides a seamless search over their contents. One of the three component DBs is the Ortholog DB, which provides gene cluster information based on the amino acid sequence similarity. Over 1,000,000 amino acid sequences of 40 Viridiplantae species were collected from the public DNA DBs, and plant genome DBs such as TAIR and RAP-DB were subjected to reciprocal BLAST searches for clustering. Another component DB is the Plant Resource DB for genomic- and bio-resources. This DB also integrates the SABRE DB, which provides cDNA and genome sequence resources maintained in the RIKEN BioResource Center and National BioResource Projects Japan. The third component DB of PGDBj is the DNA Marker DB, which manually or automatically collects curated information on DNA markers, quantitative trait loci (QTL), and related genetic linkage maps, from the literature and external DBs. By combining these component DBs and a cross-search engine, PGDBj serves as a useful platform to study genetic systems for both fundamental and applied researches for a wide range of plant species.

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Sagace: A web-based search engine for biomedical databases in Japan

Cited by 7 publications

References 6 publications

BioHackathon series in 2013 and 2014: improvements of semantic interoperability in life science data and services

BioHackathon series in 2013 and 2014: improvements of semantic interoperability in life science data and services

Big Data Usage Patterns in the Health Care Domain: A Use Case Driven Approach Applied to the Assessment of Vaccination Benefits and Risks

Plant Genome DataBase Japan (PGDBj)

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