ReviewComputational and structural biotechnology journal2020
Deep learning models in genomics; are we there yet?
Review in Computational and structural biotechnology journal, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 56 papers.
What it found
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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
56 citing papers in PubMed.
- In silico generation of gene expression profiles using diffusion models.BMC bioinformatics · 2026Article
- Large language models for bioinformatics.Quantitative biology (Beijing, China) · 2026Review
- The impact of deep learning and omics data in transforming precision therapy for brain cancer.Frontiers in bioinformatics · 2026Review
- ACmix-Swin Deep Learning of 4-Day-OldGenes · 2025Article
- Decoding the genomic symphony: unravelling brain disorders through data integration and machine learning.Molecular psychiatry · 2025Review
- Advances and challenges in the integration of artificial intelligence in microbial biosurfactant bioprocess.AMB Express · 2025Review
- Metabolic reprogramming and functional crosstalk within the tumor microenvironment (TME) and A Multi-omics anticancer approach.Medical oncology (Northwood, London, England) · 2025Review
- From Serendipity to Precision: Integrating AI, Multi-Omics, and Human-Specific Models for Personalized Neuropsychiatric Care.Biomedicines · 2025Review
- Understanding artificial intelligence in critical care: opportunities, risks, and practical applications.Critical care science · 2025Review
- Transforming Cancer Care: Genomic Profiling, AI, and Next-Generation Drug Delivery Systems.Current genomics · 2025Review
- Explainable artificial intelligence for stroke prediction through comparison of deep learning and machine learning models.Scientific reports · 2024Article
- Article
- A survey of k-mer methods and applications in bioinformatics.Computational and structural biotechnology journal · 2024Review
- Prediction of Deleterious Single Amino Acid Polymorphisms with a Consensus Holdout Sampler.Current genomics · 2024Article
- Machine Learning Model in Obesity to Predict Weight Loss One Year after Bariatric Surgery: A Pilot Study.Biomedicines · 2024Article
- Optimized model architectures for deep learning on genomic data.Communications biology · 2024Article
- Structural Landscape of nsp Coding Genomic Regions of SARS-CoV-2-ssRNA Genome: A Structural Genomics Approach Toward Identification of Druggable Genome, Ligand-Binding Pockets, and Structure-Based Druggability.Molecular biotechnology · 2024Article
- Effect of tokenization on transformers for biological sequences.Bioinformatics (Oxford, England) · 2024Article
- Benchmarking machine learning and parametric methods for genomic prediction of feed efficiency-related traits in Nellore cattle.Scientific reports · 2024Article
- Enhancing intrusion detection performance using explainable ensemble deep learning.PeerJ. Computer science · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author.
Funding
No grant is acknowledged in the PubMed record.
Abstract
With the evolution of biotechnology and the introduction of the high throughput sequencing, researchers have the ability to produce and analyze vast amounts of genomics data. Since genomics produce big data, most of the bioinformatics algorithms are based on machine learning methodologies, and lately deep learning, to identify patterns, make predictions and model the progression or treatment of a disease. Advances in deep learning created an unprecedented momentum in biomedical informatics and have given rise to new bioinformatics and computational biology research areas. It is evident that deep learning models can provide higher accuracies in specific tasks of genomics than the state of the art methodologies. Given the growing trend on the application of deep learning architectures in genomics research, in this mini review we outline the most prominent models, we highlight possible pitfalls and discuss future directions. We foresee deep learning accelerating changes in the area of genomics, especially for multi-scale and multimodal data analysis for precision medicine.
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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.