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MicroRNA prediction based on 3D graphical representation of RNA secondary structures
(TUBITAK SCIENTIFIC & TECHNICAL RESEARCH COUNCIL TURKEY, ATATURK BULVARI NO 221, KAVAKLIDERE, ANKARA, 00000, TURKEY, 2019)
MicroRNAs (miRNAs) are posttranscriptional regulators of gene expression. While a miRNA can target hundreds of messenger RNA (mRNAs), an mRNA can be targeted by different miRNAs, not to mention that a single miRNA might ...
IGPRED-MultiTask: A Deep Learning Model to Predict Protein Secondary Structure, Torsion Angles and Solvent Accessibility
(IEEE COMPUTER SOC, 2023)
Protein secondary structure, solvent accessibility and torsion angle predictions are preliminary steps to predict 3D structure of a protein. Deep learning approaches have achieved significant improvements in predicting ...
Recent Advances in Machine Learning for Network Automation in the O-RAN
(MDPI, 2023)
The evolution of network technologies has witnessed a paradigm shift toward open and intelligent networks, with the Open Radio Access Network (O-RAN) architecture emerging as a promising solution. O-RAN introduces ...
GeNetOntology: identifying affected gene ontology terms via grouping, scoring, and modeling of gene expression data utilizing biological knowledge-based machine learning
(FRONTIERS MEDIA SA, 2023)
Introduction: Identifying significant sets of genes that are up/downregulated under specific conditions is vital to understand disease development mechanisms at the molecular level. Along this line, in order to analyze ...
miRModuleNet: Detecting miRNA-mRNA Regulatory Modules
(RONTIERS MEDIA SAAVENUE DU TRIBUNAL FEDERAL 34, LAUSANNE CH-1015, SWITZERLAND, 2022)
Increasing evidence that microRNAs (miRNAs) play a key role in carcinogenesis has revealed the need for elucidating the mechanisms of miRNA regulation and the roles of miRNAs in gene-regulatory networks. A better understanding ...
Recursive Cluster Elimination based Rank Function (SVM-RCE-R) implemented in KNIME
(F1000 Research, 2020)
In our earlier study, we proposed a novel feature selection approach, Recursive Cluster Elimination with Support Vector Machines (SVM-RCE) and implemented this approach in Matlab. Interest in this approach has grown over ...
Circular RNA-MicroRNA-MRNA interaction predictions in SARS-CoV-2 infection
(WALTER DE GRUYTER GMBHGENTHINER STRASSE 13, D-10785 BERLIN, GERMANY, 2021)
Different types of noncoding RNAs like microRNAs (miRNAs) and circular RNAs (circRNAs) have been shown to take part in various cellular processes including post-transcriptional gene regulation during infection. MiRNAs are ...
Statistical and Machine Learning Techniques in Human Microbiome Studies: Contemporary Challenges and Solutions
(FRONTIERS MEDIA SAAVENUE DU TRIBUNAL FEDERAL 34, LAUSANNE CH-1015, SWITZERLAND, 2021)
The human microbiome has emerged as a central research topic in human biology and biomedicine. Current microbiome studies generate high-throughput omics data across different body sites, populations, and life stages. Many ...
Discovering Potential Taxonomic Biomarkers of Type 2 Diabetes From Human Gut Microbiota via Different Feature Selection Methods
(FRONTIERS MEDIA SAAVENUE DU TRIBUNAL FEDERAL 34, LAUSANNE CH-1015, SWITZERLAND, 2021)
Human gut microbiota is a complex community of organisms including trillions of bacteria. While these microorganisms are considered as essential regulators of our immune system, some of them can cause several diseases. In ...
miRdisNET: Discovering microRNA biomarkers that are associated with diseases utilizing biological knowledge-based machine learning
(Frontiers Media S.A., 2023)
During recent years, biological experiments and increasing evidence have shown that microRNAs play an important role in the diagnosis and treatment of human complex diseases. Therefore, to diagnose and treat human complex ...