ReviewBiodesign research2024
Multiomics Research: Principles and Challenges in Integrated Analysis.
Review in Biodesign research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 42 papers.
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.
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.
Who cites it
42 citing papers in PubMed.
- Multi-omics graph attention network reveals neuro-immune-tumor pathways in breast cancer liver depression syndrome.Frontiers in immunology · 2026Trial
- Fungi to the rescue: recent advances, mechanistic insights and omics-based perspectives in heavy metal mycoremediation.Archives of microbiology · 2026Review
- Quantitative imaging analysis in hypertrophic cardiomyopathy: phenotypic differentiation to prognostic stratification.European heart journal. Imaging methods and practice · 2026Review
- Review
- Epigenetic Perspectives on Maternal Gut Microbiota's Impact on Embryonic and Fetal Development.Comprehensive Physiology · 2026Review
- Local graph estimation with pathwise false discovery control.Nature communications · 2026Article
- Toward trustworthy artificial intelligence in multi-omics: a review of reproducibility, stability, and interpretability.Briefings in bioinformatics · 2026Review
- The BHARAT study: a multi-modal, multi-omics investigation of aging signatures in the Indian population.Aging · 2026Observational
- Water kefir as a paradigm for multi-omics and genome-scale metabolic modelling in fermented food.NPJ biofilms and microbiomes · 2026Review
- BioOne: a national-scale platform for integrated discovery and utilization of diverse biological resources in South Korea.Genomics & informatics · 2026Article
- Decoding plant physiology through systems biology: Integrative multi-omics and computational perspectives for next-generation crop design.Plant communications · 2026Review
- Role of Gut Microbiota in Psychiatric Disorders: From Mechanistic Insights to Therapeutic Strategies.Journal of Korean medical science · 2026Review
- Advancing prussian blue nanoparticle-mediated photothermal therapy through machine learning and multiomics integration.Nanomedicine (London, England) · 2026Review
- Advances in polyethylene biodegradation and bioconversion: Microbial, enzymatic, and biotechnological insights.Engineering microbiology · 2026Review
- Dissecting Normal and Abnormal Human Kidney Development Using Multiomics.Journal of the American Society of Nephrology : JASN · 2026Review
- Challenges and Opportunities in Multi-Omics Data Acquisition and Analysis: Toward Integrative Solutions.Biomolecules · 2026Review
- Intersection of Precision Nutrition and Bladder Cancer: A Narrative State-of-the-Art Review of Potential Applications and Challenges.Journal of clinical medicine · 2026Review
- Immune checkpoint blockade in cancer: current insights and future horizons.Discover oncology · 2026Review
- Genomic and integrative based progression biomarker discovery in adult sepsis: toward clinical stratification and precision medicine.Annals of intensive care · 2026Review
- Multiomics Approaches for Bacteriophage-Based Biocontrol Applications: A Review of Metabolomics, Transcriptomics, and Proteomics.BioMed research international · 2026Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Multiomics research is a transformative approach in the biological sciences that integrates data from genomics, transcriptomics, proteomics, metabolomics, and other omics technologies to provide a comprehensive understanding of biological systems. This review elucidates the fundamental principles of multiomics, emphasizing the necessity of data integration to uncover the complex interactions and regulatory mechanisms underlying various biological processes. We explore the latest advances in computational methodologies, including deep learning, graph neural networks (GNNs), and generative adversarial networks (GANs), which facilitate the effective synthesis and interpretation of multiomics data. Additionally, this review addresses the critical challenges in this field, such as data heterogeneity, scalability, and the need for robust, interpretable models. We highlight the potential of large language models to enhance multiomics analysis through automated feature extraction, natural language generation, and knowledge integration. Despite the important promise of multiomics, the review acknowledges the substantial computational resources required and the complexity of model tuning, underscoring the need for ongoing innovation and collaboration in the field. This comprehensive analysis aims to guide researchers in navigating the principles and challenges of multiomics research to foster advances in integrative biological analysis.
Identifiers
What OpenQuestion holds
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.