Evidence map›Paper›PMID 39627904›Full record

ReviewGenomics & informatics2024

Rare disease genomics and precision medicine.

Juhyeon Hong, Dajun Lee, Ayoung Hwang, Taekeun Kim, Hong-Yeoul Ryu, Jungmin Choi

Abstract readReview
In one paragraph

Review in Genomics & informatics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 citing papers in PubMed.

  1. Review
  2. Review
  3. Genomics in Health and Biomedicine.Advances in experimental medicine and biology · 2026
    Review
  4. Review
  5. Review
  6. Review
  7. Article
  8. Review
  9. Review
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

6 authors.

Juhyeon Hong *Department of Biomedical Sciences, Korea University College of Medicine, Seoul, 02841, Republic of Korea.
Dajun Lee *Department of Biomedical Sciences, Korea University College of Medicine, Seoul, 02841, Republic of Korea.
Ayoung HwangDepartment of Biomedical Sciences, Korea University College of Medicine, Seoul, 02841, Republic of Korea.
Taekeun KimDepartment of Biomedical Sciences, Korea University College of Medicine, Seoul, 02841, Republic of Korea.
Hong-Yeoul RyuSchool of Life Sciences, BK21 FOUR KNU Creative BioResearch Group, College of Natural Sciences, Kyungpook National University, Daegu, 41566, Republic of Korea.
Jungmin ChoiDepartment of Biomedical Sciences, Korea University College of Medicine, Seoul, 02841, Republic of Korea. jungminchoi@korea.ac.kr.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Rare diseases, though individually uncommon, collectively affect millions worldwide. Genomic technologies and big data analytics have revolutionized diagnosing and understanding these conditions. This review explores the role of genomics in rare disease research, the impact of large consortium initiatives, advancements in extensive data analysis, the integration of artificial intelligence (AI) and machine learning (ML), and the therapeutic implications in precision medicine. We also discuss the challenges of data sharing and privacy concerns, emphasizing the need for collaborative efforts and secure data practices to advance rare disease research.

Indexed as

Big data analyticsPrecision medicineRare disease genomics

Identifiers

PMID39627904
PMCPMC11616305

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.