Evidence map›Paper›PMID 37873876›Full record

ReviewProteomes2023

Multi-Omics Integration for the Design of Novel Therapies and the Identification of Novel Biomarkers.

Tonci Ivanisevic, Raj N Sewduth

Abstract readReview
In one paragraph

Review in Proteomes, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 67 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
67citing papers in PubMed, 1 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.

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

67 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  7. Antioxidants (Basel, Switzerland) · 2026
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  11. 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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7 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

2 authors.

Tonci IvanisevicVIB-KU Leuven Center for Cancer Biology (VIB), 3000 Leuven, Belgium.ORCID 0000-0003-4389-0114
Raj N SewduthVIB-KU Leuven Center for Cancer Biology (VIB), 3000 Leuven, Belgium.ORCID 0000-0002-9238-3242

Funding

RNS, Stichting tegen Kanker 2021 13TI, Children's Tumor Foundation 2022-01-004
6 · The paper itself

Abstract

Multi-omics is a cutting-edge approach that combines data from different biomolecular levels, such as DNA, RNA, proteins, metabolites, and epigenetic marks, to obtain a holistic view of how living systems work and interact. Multi-omics has been used for various purposes in biomedical research, such as identifying new diseases, discovering new drugs, personalizing treatments, and optimizing therapies. This review summarizes the latest progress and challenges of multi-omics for designing new treatments for human diseases, focusing on how to integrate and analyze multiple proteome data and examples of how to use multi-proteomics data to identify new drug targets. We also discussed the future directions and opportunities of multi-omics for developing innovative and effective therapies by deciphering proteome complexity.

Indexed as

cancerdata analysisdata integrationOMICsproteomics

Identifiers

PMID37873876
PMCPMC10594525

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.