Evidence map›Paper›PMID 41703124›Full record

ReviewNature reviews. Genetics2026

Annotating genomes at increased scale and resolution.

Hyun Joo Ji, Mihaela Pertea, Steven L Salzberg

Abstract readReview
PubMed Publisher
In one paragraph

Review in Nature reviews. Genetics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Review
  2. Article
  3. 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

3 authors.

Hyun Joo JiCenter for Computational Biology, Johns Hopkins University, Baltimore, MD, USA.
Mihaela PerteaCenter for Computational Biology, Johns Hopkins University, Baltimore, MD, USA.ORCID http://orcid.org/0000-0003-0762-8637
Steven L SalzbergCenter for Computational Biology, Johns Hopkins University, Baltimore, MD, USA. salzberg@jhu.edu.ORCID http://orcid.org/0000-0002-8859-7432

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Genome annotation captures the essence of a genome by cataloguing its genes, transcripts, proteins and other functional elements of the DNA sequence. Accurate annotation serves as the foundation for a wide range of downstream analyses and discoveries, ranging from basic biology to an understanding of the linkage between genes and disease. Over the past two decades, advances in high-throughput sequencing techniques have enabled faster and more accurate capture of diverse genomic features, generating data at an unprecedented scale. Concurrently, computational methods for translating these data into evidence for genome annotation have steadily improved, leading to better automated genome annotation systems. As such, the growing number of sequenced genomes provides a positive feedback loop, in which database searches become more effective and shared sequence patterns emerge more clearly. These advances are promising steps towards annotating the functions of many poorly understood genes, particularly non-coding RNA genes, for which more research is needed.

Indexed as

GenomeGenomicsMolecular Sequence AnnotationAnimalsComputational BiologyDatabases, GeneticHigh-Throughput Nucleotide SequencingHumans

Identifiers

PMID41703124

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.