Evidence map›Paper›PMID 38919019›Full record

ArticleBMB reports2024

Multi-omics analysis sandbox toolkit for swift derivations of clinically relevant genesets and biomarkers.

Jin-Young Lee, Won Park, Hyunjoong Kim, Hong Seok Lee, Tae-Wook Kang, Dong-Hun Shin, Kyung Su Kim, Yoon Kyeong Lee, Seon-Young Kim, Ji Hwan Park and 1 more

Abstract read
In one paragraph

Article in BMB reports, 2024. 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. 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

11 authors.

Jin-Young LeeDepartment of Biochemistry, College of Life Science and Biotechnology, Yonsei University, Seoul 03722, Korea.
Won ParkThe Moagen, Inc., Daejeon 35368, Korea.
Hyunjoong KimCoreIT, Inc., Cheongju 28125, Korea.
Hong Seok LeeDepartment of Biochemistry, College of Life Science and Biotechnology, Yonsei University, Seoul 03722, Korea.
Tae-Wook KangThe Moagen, Inc., Daejeon 35368, Korea.
Dong-Hun ShinThe Moagen, Inc., Daejeon 35368, Korea.
Kyung Su KimCoreIT, Inc., Cheongju 28125, Korea.
Yoon Kyeong LeeCoreIT, Inc., Cheongju 28125, Korea.
Seon-Young KimKorea Bioinformation Center (KOBIC), Korea Research Institute of Bioscience and Biotechnology, Daejeon 34141, Korea.
Ji Hwan ParkKorea Bioinformation Center (KOBIC), Korea Research Institute of Bioscience and Biotechnology, Daejeon 34141, Korea.
Young-Joon KimDepartment of Biochemistry, College of Life Science and Biotechnology, Yonsei University, Seoul 03722, Korea.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The utilization of multi-omics research has gained popularity in clinical investigations. However, effectively managing and merging extensive and diverse datasets presents a challenge due to its intricacy. This research introduces a Multi-Omics Analysis Sandbox Toolkit, an online platform designed to facilitate the exploration, integration, and visualization of datasets ranging from single-omics to multi-omics. This platform establishes connections between clinical data and omics information, allowing for versatile analysis and storage of both single and multi-omics data. Additionally, users can repeatedly utilize and exchange their findings within the platform. This toolkit offers diverse alternatives for data selection and gene set analysis. It also presents visualization outputs, potential candidates, and annotations. Furthermore, this platform empowers users to collaborate by sharing their datasets, analyses, and conclusions with others, thus enhancing its utility as a collaborative research tool. This Multi-Omics Analysis Sandbox Toolkit stands as a valuable asset in comprehensively grasping the influence of diverse factors in diseases and pinpointing potential biomarkers. [BMB Reports 2024; 57(12): 521-526].

Indexed as

BiomarkersComputational BiologyGenomicsHumansMultiomicsProteomicsSoftwareBiomarkers

Identifiers

PMID38919019
PMCPMC11693602

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.