ArticleInternational journal of molecular sciences2019
Analysis of Expression Pattern of snoRNAs in Different Cancer Types with Machine Learning Algorithms.
Article in International journal of molecular sciences, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 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
27 citing papers in PubMed, 40 citations in OpenAlex.
- Pervasive enhanced transcription in inflammatory breast cancer tumors and PBMCs impacts RNA splicing and intronic RNAs in plasma.Science advances · 2026Article
- Review
- Integrating AI and RNA biomarkers in cancer: advances in diagnostics and targeted therapies.Cell communication and signaling : CCS · 2025Review
- Small nucleolar RNA dysregulation and potential roles in bovine subclinical mastitis.Journal of animal science and biotechnology · 2025Article
- Small nucleolar RNAs: the hidden precursors of cancer ribosomes.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2025Review
- From Sequence to Solution: Intelligent Learning Engine Optimization in Drug Discovery and Protein Analysis.Biotech (Basel (Switzerland)) · 2024Article
- Analysis of Expression Pattern of snoRNAs in Human Cells A549 Infected by Influenza A Virus.International journal of molecular sciences · 2022Article
- Dysregulation of Small Nucleolar RNAs in B-Cell Malignancies.Biomedicines · 2022Review
- The role of OncoSnoRNAs and Ribosomal RNA 2'-O-methylation in Cancer.RNA biology · 2021Review
- Noncoding RNAs as potential biomarkers for DIPG diagnosis and prognosis: XIST and XIST-210 involvement.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2021Article
- Article
- snoRNAs Offer Novel Insight and Promising Perspectives for Lung Cancer Understanding and Management.Cells · 2020Review
- Computational Models in Non-Coding RNA and Human Disease.International journal of molecular sciences · 2020Article
- Multi-Omics Analysis of Acute Lymphoblastic Leukemia Identified the Methylation and Expression Differences Between BCP-ALL and T-ALL.Frontiers in cell and developmental biology · 2020Article
- Pathogenic Gene Prediction Algorithm Based on Heterogeneous Information Fusion.Frontiers in genetics · 2020Article
- The Functional Effects of Key Driver KRAS Mutations on Gene Expression in Lung Cancer.Frontiers in genetics · 2020Article
- Integrative Analysis of Methylation and Gene Expression in Lung Adenocarcinoma and Squamous Cell Lung Carcinoma.Frontiers in bioengineering and biotechnology · 2020Article
- The Serum MicroRNA Signatures for Pancreatic Cancer Detection and Operability Evaluation.Frontiers in bioengineering and biotechnology · 2020Article
- Identification of Post-myocardial Infarction Blood Expression Signatures Using Multiple Feature Selection Strategies.Frontiers in physiology · 2020Article
- Alternative Polyadenylation Modification Patterns Reveal Essential Posttranscription Regulatory Mechanisms of Tumorigenesis in Multiple Tumor Types.BioMed research international · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors at 5 institutions in 2 countries.
Funding
Abstract
Small nucleolar RNAs (snoRNAs) are a new type of functional small RNAs involved in the chemical modifications of rRNAs, tRNAs, and small nuclear RNAs. It is reported that they play important roles in tumorigenesis via various regulatory modes. snoRNAs can both participate in the regulation of methylation and pseudouridylation and regulate the expression pattern of their host genes. This research investigated the expression pattern of snoRNAs in eight major cancer types in TCGA via several machine learning algorithms. The expression levels of snoRNAs were first analyzed by a powerful feature selection method, Monte Carlo feature selection (MCFS). A feature list and some informative features were accessed. Then, the incremental feature selection (IFS) was applied to the feature list to extract optimal features/snoRNAs, which can make the support vector machine (SVM) yield best performance. The discriminative snoRNAs included HBII-52-14, HBII-336, SNORD123, HBII-85-29, HBII-420, U3, HBI-43, SNORD116, SNORA73B, SCARNA4, HBII-85-20, etc., on which the SVM can provide a Matthew's correlation coefficient (MCC) of 0.881 for predicting these eight cancer types. On the other hand, the informative features were fed into the Johnson reducer and repeated incremental pruning to produce error reduction (RIPPER) algorithms to generate classification rules, which can clearly show different snoRNAs expression patterns in different cancer types. The analysis results indicated that extracted discriminative snoRNAs can be important for identifying cancer samples in different types and the expression pattern of snoRNAs in different cancer types can be partly uncovered by quantitative recognition rules.
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.