GINSA: an accumulator for paired locality and next-generation small ribosomal subunit sequence data.

Eric Odle, Samuel Kahng, Siratee Riewluang, Kyoko Kurihara, Kevin C Wakeman

Abstract read

In one paragraph

Article in Bioinformatics (Oxford, England), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0cells of the map it votes in

0citing 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

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3 · Its place in the literature

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0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

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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

5 authors.

Eric OdleDepartment of Natural History Sciences, Graduate School of Science, Hokkaido University, Sapporo, Hokkaido 060-0810, Japan.ORCID 0000-0002-3141-042X

Samuel KahngDepartment of Oceanography, University of Hawaii at Manoa, Honolulu, HI 96822, United States.ORCID 0000-0001-8299-8908

Siratee RiewluangDepartment of Natural History Sciences, Graduate School of Science, Hokkaido University, Sapporo, Hokkaido 060-0810, Japan.

Kyoko KuriharaDepartment of Natural History Sciences, Graduate School of Science, Hokkaido University, Sapporo, Hokkaido 060-0810, Japan.

Kevin C WakemanInstitute for the Advancement of Higher Education, Hokkaido University, Sapporo, Hokkaido 060-0817, Japan.

Funding

DX Fellowship Code PH8D230001

6 · The paper itself

Abstract

motivationMotivated by the challenges of decentralized genetic data spread across multiple international organizations, GINSA leverages the Global Biodiversity Information Facility infrastructure to automatically retrieve and link small ribosomal subunit sequences with locality information.

resultsTesting on taxa from major organism groups demonstrates broad applicability across taxonomic levels and dataset sizes. AVAILABILITY AND IMPLEMENTATION: GINSA is a freely accessible Python program under the MIT License and can be installed from PyPI via pip.

Indexed as

BiodiversitySoftware

Identifiers

PMID38502961

DOI10.1093/bioinformatics/btae152

PMCPMC10987208

What OpenQuestion holds

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LicenceCC BY

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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.