Evidence map›Paper›PMID 33362867›Full record

ReviewFrontiers in genetics2020

State of the Field in Multi-Omics Research: From Computational Needs to Data Mining and Sharing.

Michal Krassowski, Vivek Das, Sangram K Sahu, Biswapriya B Misra

Registry-linked trialAbstract readReview
In one paragraph

Review in Frontiers in genetics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT05631119 (Biorepository of Biospecimen Samples in Matched Healthy Control Participants and Participants Diagnosed With Diabetic Kidney Disease, Chronic Kidney Disease, or Type 2 Diabetes), which is not on this map. Cited by 188 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
188citing papers in PubMed, 3 pooled it
–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.

NCT05631119 completednot on this mapstarted 2022, after this paper: background citation

Biorepository of Biospecimen Samples in Matched Healthy Control Participants and Participants Diagnosed With Diabetic Kidney Disease, Chronic Kidney Disease, or Type 2 Diabetes

Typeobservational_patient_registrySponsorSanguine BiosciencesRan2022 to 2023Enrolled40ConditionsDiabetic Kidney Disease, Diabetes Type 2, Chronic Kidney Diseases, Healthy
3 · Its place in the literature

Who cites it

188 citing papers in PubMed, 3 syntheses or guidelines pooled it.

  1. Pooled it
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  12. Integrating multi-omics data for next-generation cancer research and precision medicine.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2026
    Review
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128 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

4 authors.

Michal KrassowskiNuffield Department of Women's & Reproductive Health, University of Oxford, Oxford, United Kingdom.
Vivek DasNovo Nordisk Research Center Seattle, Inc, Seattle, WA, United States.
Sangram K SahuIndependent Researcher, Bengaluru, India.
Biswapriya B MisraIndependent Researcher, Namburu, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Multi-omics, variously called integrated omics, pan-omics, and trans-omics, aims to combine two or more omics data sets to aid in data analysis, visualization and interpretation to determine the mechanism of a biological process. Multi-omics efforts have taken center stage in biomedical research leading to the development of new insights into biological events and processes. However, the mushrooming of a myriad of tools, datasets, and approaches tends to inundate the literature and overwhelm researchers new to the field. The aims of this review are to provide an overview of the current state of the field, inform on available reliable resources, discuss the application of statistics and machine/deep learning in multi-omics analyses, discuss findable, accessible, interoperable, reusable (FAIR) research, and point to best practices in benchmarking. Thus, we provide guidance to interested users of the domain by addressing challenges of the underlying biology, giving an overview of the available toolset, addressing common pitfalls, and acknowledging current methods' limitations. We conclude with practical advice and recommendations on software engineering and reproducibility practices to share a comprehensive awareness with new researchers in multi-omics for end-to-end workflow.

Indexed as

benchmarkingdata heterogeneityFAIRintegrated omicsmachine learningmulti-omicsreproducibilityvisualization

Identifiers

PMID33362867
PMCPMC7758509

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

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.