ReviewFrontiers in genetics2019
Recent Advances of Deep Learning in Bioinformatics and Computational Biology.
Review in Frontiers in genetics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 79 papers, 1 of them a synthesis 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
79 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Classifying primary central nervous system lymphoma from glioblastoma using deep learning and radiomics based machine learning approach - a systematic review and meta-analysis.Frontiers in oncology · 2022Pooled it
- Unveiling the role of Jagged2 in hypoxic pulmonary arterial hypertension: A NOX2-mediated pathway.Journal of cell communication and signaling · 2025Article
- DeepHVI: A multimodal deep learning framework for predicting human-virus protein-protein interactions using protein language models.Biosafety and health · 2025Article
- Interpretable discovery of patterns in tabular data via spatially semantic topographic maps.Nature biomedical engineering · 2025Article
- Artificial Intelligence and Computational Biology in Gene Therapy: A Review.Biochemical genetics · 2025Review
- A deep learning model trained on expressed transcripts across different tissue types reveals cell-type codon-optimization preferences.Nucleic acids research · 2025Article
- Artificial intelligence-, organoid-, and organ-on-chip-powered models to improve pre-clinical animal testing of vaccines and immunotherapeutics: potential, progress, and challenges.Frontiers in artificial intelligence · 2025Review
- Making sense of expanding transcriptomic data: network-based approaches for studying reproduction in domestic and wild animal species.Frontiers in veterinary science · 2025Review
- AllerTrans: a deep learning method for predicting the allergenicity of protein sequences.Biology methods & protocols · 2025Article
- Optimizing gene selection and module identification via ontology-based scoring and deep learning.Bioinformatics advances · 2025Article
- Assessing the Inhibitory Potential of Natural Compounds for Targeting the CrtM Proteins in Methicillin-ResistantCurrent medicinal chemistry · 2025Article
- Visualization Methods for DNA Sequences: A Review and Prospects.Biomolecules · 2024Review
- Identification of TFRC as a biomarker for pulmonary arterial hypertension based on bioinformatics and experimental verification.Respiratory research · 2024Article
- NNICE: a deep quantile neural network algorithm for expression deconvolution.Scientific reports · 2024Article
- Quantitative proteomic profiling in brain subregions of mice exposed to open-field low-intensity blast reveals position-dependent blast effects.Shock waves · 2024Article
- Comparative analysis of feature-based ML and CNN for binucleated erythroblast quantification in myelodysplastic syndrome patients using imaging flow cytometry data.Scientific reports · 2024Article
- Role of Optimization in RNA-Protein-Binding Prediction.Current issues in molecular biology · 2024Article
- LSTM-SAGDTA: Predicting Drug-target Binding Affinity with an Attention Graph Neural Network and LSTM Approach.Current pharmaceutical design · 2024Article
- Revolutionizing cross-border e-commerce: A deep dive into AI and big data-driven innovations for the straw hat industry.PloS one · 2024Article
- Application of machine learning for mass spectrometry-based multi-omics in thyroid diseases.Frontiers in molecular biosciences · 2024Review
19 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Extracting inherent valuable knowledge from omics big data remains as a daunting problem in bioinformatics and computational biology. Deep learning, as an emerging branch from machine learning, has exhibited unprecedented performance in quite a few applications from academia and industry. We highlight the difference and similarity in widely utilized models in deep learning studies, through discussing their basic structures, and reviewing diverse applications and disadvantages. We anticipate the work can serve as a meaningful perspective for further development of its theory, algorithm and application in bioinformatic and computational biology.
Indexed as
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.