Evidence map›Paper›PMID 31441146›Full record

ReviewProtein science : a publication of the Protein Society2019

Toward understanding the origin and evolution of cellular organisms.

Minoru Kanehisa

Abstract readReview
In one paragraph

Review in Protein science : a publication of the Protein Society, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3,561 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
3,561citing papers in PubMed, 1 pooled it
–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

3,561 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  7. ToxCompl completion of the DrugMatrix toxicogenomics database: an integrated resource for hypothesis generation.Toxicological sciences : an official journal of the Society of Toxicology · 2026
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  16. Biochemistry and biophysics reports · 2026
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  19. Deep tissue sequencing improves genetic diagnostic yield in focal cortical dysplasia.Progress in neuro-psychopharmacology & biological psychiatry · 2026
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  20. Article

3,501 more citing papers are in PubMed but not listed here.

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

1 author.

Minoru KanehisaInstitute for Chemical Research, Kyoto University, Uji, Kyoto, Japan.ORCID 0000-0001-6123-540X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In this era of high-throughput biology, bioinformatics has become a major discipline for making sense out of large-scale datasets. Bioinformatics is usually considered as a practical field developing databases and software tools for supporting other fields, rather than a fundamental scientific discipline for uncovering principles of biology. The KEGG resource that we have been developing is a reference knowledge base for biological interpretation of genome sequences and other high-throughput data. It is now one of the most utilized biological databases because of its practical values. For me personally, KEGG is a step toward understanding the origin and evolution of cellular organisms.

Indexed as

Computational BiologyDatabases, GeneticHigh-Throughput Screening AssaysHumansSoftwareKEGGKEGG MEDICUSKEGG modulepathway mappingreaction module

Identifiers

PMID31441146
PMCPMC6798127

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.