Evidence map›Paper›PMID 39780290›Full record

ArticleJournal of biomedical semantics2025

Expanding the concept of ID conversion in TogoID by introducing multi-semantic and label features.

Shuya Ikeda, Kiyoko F Aoki-Kinoshita, Hirokazu Chiba, Susumu Goto, Masae Hosoda, Shuichi Kawashima, Jin-Dong Kim, Yuki Moriya, Tazro Ohta, Hiromasa Ono and 3 more

Abstract read
In one paragraph

Article in Journal of biomedical semantics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

13 authors.

Shuya IkedaDatabase Center for Life Science, Joint Support-Center for Data Science Research, Research Organization of Information and Systems, Kashiwa, Chiba, Japan. sikeda@dbcls.rois.ac.jp.
Kiyoko F Aoki-KinoshitaGraduate School of Science and Engineering, Soka University, Hachioji, Tokyo, Japan.
Hirokazu ChibaDatabase Center for Life Science, Joint Support-Center for Data Science Research, Research Organization of Information and Systems, Kashiwa, Chiba, Japan.
Susumu GotoDatabase Center for Life Science, Joint Support-Center for Data Science Research, Research Organization of Information and Systems, Kashiwa, Chiba, Japan.
Masae HosodaDatabase Center for Life Science, Joint Support-Center for Data Science Research, Research Organization of Information and Systems, Kashiwa, Chiba, Japan.
Shuichi KawashimaDatabase Center for Life Science, Joint Support-Center for Data Science Research, Research Organization of Information and Systems, Kashiwa, Chiba, Japan.
Jin-Dong KimDatabase Center for Life Science, Joint Support-Center for Data Science Research, Research Organization of Information and Systems, Kashiwa, Chiba, Japan.
Yuki MoriyaDatabase Center for Life Science, Joint Support-Center for Data Science Research, Research Organization of Information and Systems, Kashiwa, Chiba, Japan.
Tazro OhtaDatabase Center for Life Science, Joint Support-Center for Data Science Research, Research Organization of Information and Systems, Kashiwa, Chiba, Japan.
Hiromasa OnoDatabase Center for Life Science, Joint Support-Center for Data Science Research, Research Organization of Information and Systems, Kashiwa, Chiba, Japan.
Terue TakatsukiDatabase Center for Life Science, Joint Support-Center for Data Science Research, Research Organization of Information and Systems, Kashiwa, Chiba, Japan.
Yasunori YamamotoDatabase Center for Life Science, Joint Support-Center for Data Science Research, Research Organization of Information and Systems, Kashiwa, Chiba, Japan.
Toshiaki KatayamaDatabase Center for Life Science, Joint Support-Center for Data Science Research, Research Organization of Information and Systems, Kashiwa, Chiba, Japan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundTogoID ( https://togoid.dbcls.jp/ ) is an identifier (ID) conversion service designed to link IDs across diverse categories of life science databases. With its ability to obtain IDs related in different semantic relationships, a user-friendly web interface, and a regular automatic data update system, TogoID has been a valuable tool for bioinformatics.

resultsWe have recently expanded TogoID's ability to represent semantics between datasets, enabling it to handle multiple semantic relationships within dataset pairs. This enhancement enables TogoID to distinguish relationships such as "glycans bind to proteins" or "glycans are processed by proteins" between glycans and proteins. Additional new features include the ability to display labels corresponding to database IDs, making it easier to interpret the relationships between the various IDs available in TogoID, and the ability to convert labels to IDs, extending the entry point for ID conversion. The implementation of URL parameters, which reproduces the state of TogoID's web application, allows users to share complex search results through a simple URL.

conclusionsThese advancements improve TogoID's utility in bioinformatics, allowing researchers to explore complex ID relationships. By introducing the tool's multi-semantic and label features, TogoID expands the concept of ID conversion and supports more comprehensive and efficient data integration across life science databases.

Indexed as

Computational BiologySemanticsDatabases, FactualInternetSoftwareUser-Computer InterfaceDatabase IntegrationOntologyWeb Application

Identifiers

PMID39780290
PMCPMC11708180

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.