Evidence map›Paper›PMID 41028378›Full record

ArticleMethods in molecular biology (Clifton, N.J.)2026

A Multi-omics Approach for Microbiome Data Analysis in Legumes.

Rishav Sahil, Mukesh Jain

Abstract read
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In one paragraph

Article in Methods in molecular biology (Clifton, N.J.), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

2 authors.

Rishav SahilTranslational Genomics and Systems Biology Laboratory, School of Computational and Integrative Sciences, Jawaharlal Nehru University, New Delhi, Delhi, India.
Mukesh JainTranslational Genomics and Systems Biology Laboratory, School of Computational and Integrative Sciences, Jawaharlal Nehru University, New Delhi, Delhi, India. mjain@jnu.ac.in.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Microbiome plays a crucial role in influencing the health and function of living beings as well as in regulating the biogeochemical cycles. The plant microbiome, in particular, has garnered significant research interest aimed at exploring the microbes that play a crucial role in regulating plant growth and nutrient acquisition. Recent advancements in omics sciences have played a crucial role in uncovering the complexities of these relationships. While techniques such as amplicon and shotgun metagenomics provide taxonomic profiling up to the species level and even the strain level, metatranscriptomics further elucidates the functional roles of these microbes. These techniques are being rapidly and widely adopted to understand the influence of microbes on the host. However, the challenge lies in their integration. Most studies to date rely on only one of these techniques, which limits the scope of holistic understanding of host-microbe interactions. Additionally, there is currently no well-established workflow that effectively combines these techniques to provide comprehensive biological insights. In this work, we describe an integrated approach for microbiome data analysis to provide biologically meaningful insights.

Indexed as

Computational BiologyFabaceaeMetagenomicsMicrobiotaData AnalysisMetagenomeMultiomicsAmpliconMetatranscriptomicsMicrobiomePlantShotgun metagenomics

Identifiers

PMID41028378

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.