ReviewHuman genomics2022
A review of deep learning applications in human genomics using next-generation sequencing data.
Review in Human genomics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 57 papers, 2 of them syntheses that pooled 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.
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
57 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Quantum bioinformatics: a systematic review of methods, trends, and challenges.Briefings in bioinformatics · 2026Pooled it
- A systematic review of biologically-informed deep learning models for cancer: fundamental trends for encoding and interpreting oncology data.BMC bioinformatics · 2023Pooled it
- Graph in Graph (GiG): A novel graph AI framework for integrating and interpreting medical and omics data.bioRxiv : the preprint server for biology · 2026Article
- Pipettes and Pipelines: The Weapons of Omics Sciences for a New Age of Clinical Studies.Current issues in molecular biology · 2026Review
- Review
- Recovery and analysis of ancient DNA: challenges, methods, and applications in forensic and archaeological science.Journal, genetic engineering & biotechnology · 2026Article
- Convolutional neural networks quantify antibiotic resistance in Mycobacterium tuberculosis with diagnostic grade accuracy and predict treatment response.Nature communications · 2026Article
- Artificial Intelligence Design for Race-Based Prostate Cancer Stage Classification With Multilayer Perceptron: Feature Selection Optimization Approach.JMIR formative research · 2026Article
- Interpreting artificial neural networks to detect genome-wide association signals for complex traits.NAR genomics and bioinformatics · 2026Article
- In silico genome transplants and the cis-regulatory basis of biodiversity.Trends in genetics : TIG · 2026Review
- Review
- Deep Learning-Based Identification of Pathogenicity Genes inPlants (Basel, Switzerland) · 2026Article
- Predicting Physical Appearance from Low Template: State of the Art and Future Perspectives.Genes · 2026Review
- inMOTIFin: a lightweight end-to-end simulation software for regulatory sequences.Bioinformatics (Oxford, England) · 2026Article
- Deep learning for genomic insights into athletic performance in sports education.Frontiers in genetics · 2026Article
- A Systematic Review: Deep Learning for Analyzing Genomic Data to Discover Evolutionary Patterns.Scientifica · 2026Review
- From Protein Structure to Drug Discovery: Bioinformatics Breakthroughs in 2024-2025.Current issues in molecular biology · 2025Article
- Artificial intelligence-driven digital pathology in urological cancers: current trends and future directions.Prostate international · 2025Review
- Theranostics 2.0: Target-driven, artificial intelligence-enabled cancer therapy across tumor types.Diagnostic and interventional imaging · 2025Review
- ResNet50 and Single-Cell Multi-Omics analysis identify key cellular and molecular features in pediatric acute lymphoblastic leukemia.Annals of hematology · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Genomics is advancing towards data-driven science. Through the advent of high-throughput data generating technologies in human genomics, we are overwhelmed with the heap of genomic data. To extract knowledge and pattern out of this genomic data, artificial intelligence especially deep learning methods has been instrumental. In the current review, we address development and application of deep learning methods/models in different subarea of human genomics. We assessed over- and under-charted area of genomics by deep learning techniques. Deep learning algorithms underlying the genomic tools have been discussed briefly in later part of this review. Finally, we discussed briefly about the late application of deep learning tools in genomic. Conclusively, this review is timely for biotechnology or genomic scientists in order to guide them why, when and how to use deep learning methods to analyse human genomic data.
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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.