ReviewJournal of medical systems2018
A Survey of Data Mining and Deep Learning in Bioinformatics.
Review in Journal of medical systems, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 65 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
65 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Sensing Apps and Public Data Sets for Digital Phenotyping of Mental Health: Systematic Review.Journal of medical Internet research · 2022Pooled it
- Prevalence and Diagnosis of Neurological Disorders Using Different Deep Learning Techniques: A Meta-Analysis.Journal of medical systems · 2020Pooled it
- Artificial intelligence in plant salt stress research: from predictive models to multi-omics integration.Journal of experimental botany · 2026Review
- Enhancing Clinical Workflow Efficiency in Flow Cytometry Reporting with LLMs.Journal of clinical immunology · 2026Article
- Screening of potential oxidative stress-related biomarkers and therapeutic drugs in rheumatoid arthritis based on integrative bioinformatics, machine learning, and molecular dynamics simulations.Frontiers in molecular biosciences · 2026Article
- Digital epidemiology and public health surveillance: scientometric mapping of emerging technologies and challenges (2000-2025).Frontiers in digital health · 2026Review
- Enhancing crayfish sex identification with Kolmogorov-Arnold networks and stacked autoencoders.Scientific reports · 2025Article
- Transformer-Based Classification of Transposable Element Consensus Sequences with TEclass2.Biology · 2025Article
- On the recurrent neural network model with robust expectile-based loss function in economic data forecasting.MethodsX · 2025Article
- Integrating bulk and single-cell RNA sequencing data to dissect genetic links between periodontitis and obstructive sleep apnea.Sleep & breathing = Schlaf & Atmung · 2025Article
- Identification and validation of aryl hydrocarbon receptor-associated hub genes in ulcerative colitis via integrated bioinformatics analysis.Human genomics · 2025Article
- Functional effect of adiponectin and body composition assessment in lung cancer subjects after video-assisted thoracoscopic surgery (VATS) lobectomy.Thoracic cancer · 2025Article
- Unsupervised Clustering of Vertebral Hounsfield Units in Opportunistic Chest CT for Stratifying Bone Mass Subtypes in a 2 Years' Period.Clinical interventions in aging · 2025Article
- Domain adaptation in small-scale and heterogeneous biological datasets.Science advances · 2024Review
- Visualization Methods for DNA Sequences: A Review and Prospects.Biomolecules · 2024Review
- DPNN-ac4C: a dual-path neural network with self-attention mechanism for identification of N4-acetylcytidine (ac4C) in mRNA.Bioinformatics (Oxford, England) · 2024Article
- Deep learning assisted cancer disease prediction from gene expression data using WT-GAN.BMC medical informatics and decision making · 2024Article
- Generative language models on nucleotide sequences of human genes.Scientific reports · 2024Article
- CT radiomics-based biomarkers can predict response to immunotherapy in hepatocellular carcinoma.Scientific reports · 2024Article
- scGREAT: Transformer-based deep-language model for gene regulatory network inference from single-cell transcriptomics.iScience · 2024Article
5 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
6 authors.
Funding
Abstract
The fields of medicine science and health informatics have made great progress recently and have led to in-depth analytics that is demanded by generation, collection and accumulation of massive data. Meanwhile, we are entering a new period where novel technologies are starting to analyze and explore knowledge from tremendous amount of data, bringing limitless potential for information growth. One fact that cannot be ignored is that the techniques of machine learning and deep learning applications play a more significant role in the success of bioinformatics exploration from biological data point of view, and a linkage is emphasized and established to bridge these two data analytics techniques and bioinformatics in both industry and academia. This survey concentrates on the review of recent researches using data mining and deep learning approaches for analyzing the specific domain knowledge of bioinformatics. The authors give a brief but pithy summarization of numerous data mining algorithms used for preprocessing, classification and clustering as well as various optimized neural network architectures in deep learning methods, and their advantages and disadvantages in the practical applications are also discussed and compared in terms of their industrial usage. It is believed that in this review paper, valuable insights are provided for those who are dedicated to start using data analytics methods in bioinformatics.
Indexed as
Identifiers
29956014What 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.