Ara
Toplam kayıt 12, listelenen: 1-10
Invention of 3Mint for feature grouping and scoring in multi-omics
(FRONTIERS MEDIA SA, 2023)
Advanced genomic and molecular profiling technologies accelerated the enlightenment of the regulatory mechanisms behind cancer development and progression, and the targeted therapies in patients. Along this line, intense ...
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 ...
Zenginleştirilmiş Öznitelikler ve Makine Öğrenmesi Yöntemleriyle Protein Yerel Yapı Tahmini
(TUBİTAK, 2017)
Projenin amacı proteinlerde bulunan ikincil yapı, dihedral açı ve çözücü erişilirlik gibi bir boyutlu yapısal özelliklerin başarılı olarak tahmin edilmesi ve bu tahminleri kullanarak parçacık seçimi yapan yeni bir yöntem ...
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 ...
microBiomeGSM: the identification of taxonomic biomarkers from metagenomic data using grouping, scoring and modeling (G-S-M) approach
(FRONTIERS MEDIA SA, 2023)
Numerous biological environments have been characterized with the advent of metagenomic sequencing using next generation sequencing which lays out the relative abundance values of microbial taxa. Modeling the human microbiome ...
Prediction of Linear Cationic Antimicrobial Peptides Active against Gram-Negative and Gram-Positive Bacteria Based on Machine Learning Models
(MDPI, 2022)
Antimicrobial peptides (AMPs) are considered as promising alternatives to conventional antibiotics in order to overcome the growing problems of antibiotic resistance. Computational prediction approaches receive an increasing ...
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 ...
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 ...