Application of biological domain knowledge based feature selection on gene expression data
In the last two decades, there have been massive advancements in high throughput
technologies, which resulted in the exponential growth of public repositories of gene …
technologies, which resulted in the exponential growth of public repositories of gene …
Review of feature selection approaches based on grouping of features
With the rapid development in technology, large amounts of high-dimensional data have
been generated. This high dimensionality including redundancy and irrelevancy poses a …
been generated. This high dimensionality including redundancy and irrelevancy poses a …
Inflammatory bowel disease biomarkers of human gut microbiota selected via different feature selection methods
The tremendous boost in next generation sequencing and in the “omics” technologies
makes it possible to characterize the human gut microbiome—the collective genomes of the …
makes it possible to characterize the human gut microbiome—the collective genomes of the …
GediNET for discovering gene associations across diseases using knowledge based machine learning approach
The most common approaches to discovering genes associated with specific diseases are
based on machine learning and use a variety of feature selection techniques to identify …
based on machine learning and use a variety of feature selection techniques to identify …
TextNetTopics: text classification based word grouping as topics and topics' scoring
M Yousef, D Voskergian - Frontiers in Genetics, 2022 - frontiersin.org
Medical document classification is one of the active research problems and the most
challenging within the text classification domain. Medical datasets often contain massive …
challenging within the text classification domain. Medical datasets often contain massive …
PriPath: identifying dysregulated pathways from differential gene expression via grouping, scoring, and modeling with an embedded feature selection approach
Background Cell homeostasis relies on the concerted actions of genes, and dysregulated
genes can lead to diseases. In living organisms, genes or their products do not act alone but …
genes can lead to diseases. In living organisms, genes or their products do not act alone but …
Prediction of linear cationic antimicrobial peptides active against gram-negative and gram-positive bacteria based on machine learning models
Antimicrobial peptides (AMPs) are considered as promising alternatives to conventional
antibiotics in order to overcome the growing problems of antibiotic resistance …
antibiotics in order to overcome the growing problems of antibiotic resistance …
miRdisNET: discovering microRNA biomarkers that are associated with diseases utilizing biological knowledge-based machine learning
During recent years, biological experiments and increasing evidence have shown that
microRNAs play an important role in the diagnosis and treatment of human complex …
microRNAs play an important role in the diagnosis and treatment of human complex …
miRModuleNet: detecting miRNA-mRNA regulatory modules
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 …
revealed the need for elucidating the mechanisms of miRNA regulation and the roles of …
miRcorrNet: machine learning-based integration of miRNA and mRNA expression profiles, combined with feature grouping and ranking
A better understanding of disease development and progression mechanisms at the
molecular level is critical both for the diagnosis of a disease and for the development of …
molecular level is critical both for the diagnosis of a disease and for the development of …