Evidence map›Paper›PMID 40003933›Full record

ReviewInternational journal of molecular sciences2025

Integrative Multi-Omics Approaches for Identifying and Characterizing Biological Elements in Crop Traits: Current Progress and Future Prospects.

Bing-Liang Fan, Lin-Hua Chen, Ling-Ling Chen, Hao Guo

Abstract readReview
In one paragraph

Review in International journal of molecular sciences, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers.

0numbers the graph read from it
0cells of the map it votes in
30citing 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

30 citing papers in PubMed.

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  19. Advances in Beet (Plants (Basel, Switzerland) · 2025
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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

4 authors.

Bing-Liang FanState Key Laboratory for Conservation and Utilization of Subtropical Agro-Bioresources, College of Life Science and Technology, Guangxi University, Nanning 530004, China.ORCID 0009-0005-0960-8340
Lin-Hua ChenState Key Laboratory for Conservation and Utilization of Subtropical Agro-Bioresources, College of Life Science and Technology, Guangxi University, Nanning 530004, China.ORCID 0009-0000-2640-4749
Ling-Ling ChenState Key Laboratory for Conservation and Utilization of Subtropical Agro-Bioresources, College of Life Science and Technology, Guangxi University, Nanning 530004, China.
Hao GuoState Key Laboratory for Conservation and Utilization of Subtropical Agro-Bioresources, College of Life Science and Technology, Guangxi University, Nanning 530004, China.

Funding

Guangxi Natural Science Foundation 2024GXNSFGA010003Guangxi Science and Technology Major Program AA23062085National Natural Science Foundation of China 32270712
6 · The paper itself

Abstract

The advancement of multi-omics tools has revolutionized the study of complex biological systems, providing comprehensive insights into the molecular mechanisms underlying critical traits across various organisms. By integrating data from genomics, transcriptomics, metabolomics, and other omics platforms, researchers can systematically identify and characterize biological elements that contribute to phenotypic traits. This review delves into recent progress in applying multi-omics approaches to elucidate the genetic, epigenetic, and metabolic networks associated with key traits in plants. We emphasize the potential of these integrative strategies to enhance crop improvement, optimize agricultural practices, and promote sustainable environmental management. Furthermore, we explore future prospects in the field, underscoring the importance of cutting-edge technological advancements and the need for interdisciplinary collaboration to address ongoing challenges. By bridging various omics platforms, this review aims to provide a holistic framework for advancing research in plant biology and agriculture.

Indexed as

Crops, AgriculturalGenomicsMetabolomicsAgricultureMultiomicsPhenotypeTranscriptomebiological elementscrop improvementintegrative approachesmulti-omicstrait mining

Identifiers

PMID40003933
PMCPMC11855028

What OpenQuestion holds

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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.