Evidence map›Paper›PMID 38443594›Full record

ReviewExperimental & molecular medicine2024

Advances in single-cell omics and multiomics for high-resolution molecular profiling.

Jongsu Lim, Chanho Park, Minjae Kim, Hyukhee Kim, Junil Kim, Dong-Sung Lee

Open access · goldAbstract readReview
In one paragraph

Review in Experimental & molecular medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 100 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
100citing papers in PubMed, 1 pooled it
29.7field-weighted citation impact, top 1% of its field
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

100 citing papers in PubMed, 1 synthesis or guideline pooled it, 127 citations in OpenAlex.

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40 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

6 authors at 2 institutions in 1 country.

Jongsu Lim *Department of Life Science, University of Seoul, Seoul, 02504, Republic of Korea.
Chanho Park *Department of Life Science, University of Seoul, Seoul, 02504, Republic of Korea.
Minjae KimDepartment of Life Science, University of Seoul, Seoul, 02504, Republic of Korea.
Hyukhee KimDepartment of Life Science, University of Seoul, Seoul, 02504, Republic of Korea.
Junil KimSchool of Systems Biomedical Science, Soongsil University, Seoul, 06978, Republic of Korea.
Dong-Sung LeeDepartment of Life Science, University of Seoul, Seoul, 02504, Republic of Korea. eaststar0@gmail.com.ORCID 0000-0003-3815-7057
University of Seoul · KRSoongsil University · KR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Single-cell omics technologies have revolutionized molecular profiling by providing high-resolution insights into cellular heterogeneity and complexity. Traditional bulk omics approaches average signals from heterogeneous cell populations, thereby obscuring important cellular nuances. Single-cell omics studies enable the analysis of individual cells and reveal diverse cell types, dynamic cellular states, and rare cell populations. These techniques offer unprecedented resolution and sensitivity, enabling researchers to unravel the molecular landscape of individual cells. Furthermore, the integration of multimodal omics data within a single cell provides a comprehensive and holistic view of cellular processes. By combining multiple omics dimensions, multimodal omics approaches can facilitate the elucidation of complex cellular interactions, regulatory networks, and molecular mechanisms. This integrative approach enhances our understanding of cellular systems, from development to disease. This review provides an overview of the recent advances in single-cell and multimodal omics for high-resolution molecular profiling. We discuss the principles and methodologies for representatives of each omics method, highlighting the strengths and limitations of the different techniques. In addition, we present case studies demonstrating the applications of single-cell and multimodal omics in various fields, including developmental biology, neurobiology, cancer research, immunology, and precision medicine.

Indexed as

MultiomicsPrecision Medicine

Identifiers

PMID38443594
PMCPMC10984936
OpenAlexW4392472262

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.