Abstract
MicroRNAs (miRNAs) are 19 to 25 nucleotides non-coding RNAs known to possess important posttranscriptional regulatory functions. Identifying targeting genes that miRNAs regulate are important for understanding their specific biological functions. Usually, miRNAs down-regulate target genes through binding to the complementary sites in the 3 untranslated region (UTR) of the targets. In part, due to the large number of miRNAs and potential targets, an experimental based prediction design would be extremely laborious and economically unfavorable. However, since the bindings of the animal miRNAs are not a perfect one-to-one match with the complementary sites of their targets, it is difficult to predict targets of animal miRNAs by accessing their alignment to the 3 UTRs of potential targets. Consequently, sophisticated computational approaches for miRNA target prediction are being considered as essential methods in miRNA research. We surveyed most of the current computational miRNA target prediction algorithms in this paper. Particularly, we provided a mathematical definition and formulated the problem of target prediction under the framework of statistical classification. Moreover, we summarized the features of miRNA-target pairs in target prediction approaches and discussed these approaches according to two categories, which are the rule-based and the data-driven approaches. The rule-based approach derives the classifier mainly on biological prior knowledge and important observations from biological experiments, whereas the data driven approach builds statistic models using the training data and makes predictions based on the models. Finally, we tested a few different algorithms on a set of experimentally validated true miRNA-target pairs [1] and a set of false miRNA-target pairs, derived from miRNA overexpression experiment [2]. Receiver Operating Characteristic (ROC) curves were drawn to show the performances of these algorithms.
Current Genomics
Title: Survey of Computational Algorithms for MicroRNA Target Prediction
Volume: 10 Issue: 7
Author(s): Dong Yue, Hui Liu and Yufei Huang
Affiliation:
Abstract: MicroRNAs (miRNAs) are 19 to 25 nucleotides non-coding RNAs known to possess important posttranscriptional regulatory functions. Identifying targeting genes that miRNAs regulate are important for understanding their specific biological functions. Usually, miRNAs down-regulate target genes through binding to the complementary sites in the 3 untranslated region (UTR) of the targets. In part, due to the large number of miRNAs and potential targets, an experimental based prediction design would be extremely laborious and economically unfavorable. However, since the bindings of the animal miRNAs are not a perfect one-to-one match with the complementary sites of their targets, it is difficult to predict targets of animal miRNAs by accessing their alignment to the 3 UTRs of potential targets. Consequently, sophisticated computational approaches for miRNA target prediction are being considered as essential methods in miRNA research. We surveyed most of the current computational miRNA target prediction algorithms in this paper. Particularly, we provided a mathematical definition and formulated the problem of target prediction under the framework of statistical classification. Moreover, we summarized the features of miRNA-target pairs in target prediction approaches and discussed these approaches according to two categories, which are the rule-based and the data-driven approaches. The rule-based approach derives the classifier mainly on biological prior knowledge and important observations from biological experiments, whereas the data driven approach builds statistic models using the training data and makes predictions based on the models. Finally, we tested a few different algorithms on a set of experimentally validated true miRNA-target pairs [1] and a set of false miRNA-target pairs, derived from miRNA overexpression experiment [2]. Receiver Operating Characteristic (ROC) curves were drawn to show the performances of these algorithms.
Export Options
About this article
Cite this article as:
Yue Dong, Liu Hui and Huang Yufei, Survey of Computational Algorithms for MicroRNA Target Prediction, Current Genomics 2009; 10 (7) . https://dx.doi.org/10.2174/138920209789208219
DOI https://dx.doi.org/10.2174/138920209789208219 |
Print ISSN 1389-2029 |
Publisher Name Bentham Science Publisher |
Online ISSN 1875-5488 |
Call for Papers in Thematic Issues
Advanced Computational Algorithms and Artificial Intelligence in Clinical Pharmacogenomics
In the era of personalized medicine, understanding the relationship between genetics and drug response is crucial. This issue delves into innovative methodologies, leveraging deep computational analysis and artificial intelligence, to enhance the field of Clinical Pharmacogenomics. The interdisciplinary approach harnesses the power of advanced high-throughput genotyping technologies, sophisticated computational analysis, ...read more
Applications of Single-cell Sequencing Technology in Reproductive Medicine
Single cell sequencing (SCS) technology utilizes individual cells' genetic material to sequence their genome, transcriptome, and epigenetics at the molecular level. It offers insights into cell heterogeneity and enables the study of limited biological materials. Since its recognition as a valuable technique in 2011, single cell sequencing has yielded numerous ...read more
Big Data in Cancer Research
Cancer is a significant threat to human life and health, remaining a highly aggressive killer. It is a leading cause of death worldwide and represents a crucial medical issue for humanity. However, in the past decade, the effectiveness of new synthetic anticancer agents has not matched the current clinical speculation. ...read more
Current Genomics in Cardiovascular Research
Cardiovascular diseases are the main cause of death in the world, in recent years we have had important advances in the interaction between cardiovascular disease and genomics. In this Research Topic, we intend for researchers to present their results with a focus on basic, translational and clinical investigations associated with ...read more
Related Journals
- Author Guidelines
- Graphical Abstracts
- Fabricating and Stating False Information
- Research Misconduct
- Post Publication Discussions and Corrections
- Publishing Ethics and Rectitude
- Increase Visibility of Your Article
- Archiving Policies
- Peer Review Workflow
- Order Your Article Before Print
- Promote Your Article
- Manuscript Transfer Facility
- Editorial Policies
- Allegations from Whistleblowers
- Announcements
Related Articles
-
GH-Inhibitory Activity of Novel Somatostatin Agonists: Potential Applications in Acromegaly
Current Medicinal Chemistry - Immunology, Endocrine & Metabolic Agents Volume Measurement in the Diagnosis of Mounier Kuhn Syndrome and an Unknown Accompanying Pathology: Pulmonary Artery Enlargement
Current Medical Imaging The Clinical and Immunological Features of Patients with Primary Antibody Deficiencies
Endocrine, Metabolic & Immune Disorders - Drug Targets De Novo Malignancies After Organ Transplantation: Focus on Viral Infections
Current Molecular Medicine Clinical Experience with Antiangiogenic Therapy in Leukemia
Current Cancer Drug Targets Immune Therapy in Pancreatic Cancer: Now and the Future?
Reviews on Recent Clinical Trials A Review on CRISPR-mediated Epigenome Editing: A Future Directive for Therapeutic Management of Cancer
Current Drug Targets Whole Organism Based Techniques and Approaches in Early Stage Oncology Drug Discovery-Patents and Trends
Recent Patents on Endocrine, Metabolic & Immune Drug Discovery Chemokines and their Receptors in Gut Homeostasis and Disease
Current Immunology Reviews (Discontinued) CDC25A: A Rebel Within the CDC25 Phosphatases Family?
Anti-Cancer Agents in Medicinal Chemistry Modulation of Tumour-Related Signaling Pathways by Natural Pentacyclic Triterpenoids and their Semisynthetic Derivatives
Current Medicinal Chemistry The Biology of TRAIL and the Role of TRAIL-Based Therapeutics in Infectious Diseases
Anti-Infective Agents in Medicinal Chemistry Roles of microRNAs in HIV-1 Replication and Latency
MicroRNA The History and Rationale for Monoclonal Antibodies in the Treatment of Hematologic Malignancy
Current Pharmaceutical Biotechnology PIM1 Kinase as a Target in Prostate Cancer: Roles in Tumorigenesis, Castration Resistance, and Docetaxel Resistance
Current Cancer Drug Targets Nutrition, Nitrogen Requirements, Exercise and Chemotherapy-Induced Toxicity in Cancer Patients. A puzzle of Contrasting Truths?
Anti-Cancer Agents in Medicinal Chemistry Advances in Nanocarriers for Anticancer Drugs Delivery
Current Medicinal Chemistry Translational Multimodality Neuroimaging
Current Drug Targets Innate Immunity and the Heart
Current Pharmaceutical Design Innovative Strategies in In Vivo Apoptosis Imaging
Current Medicinal Chemistry