miRNA‐disease association prediction with collaborative matrix factorization
As one of the factors in the noncoding RNA family, microRNAs (miRNAs) are involved in the
development and progression of various complex diseases. Experimental identification of …
development and progression of various complex diseases. Experimental identification of …
Multi-level gene/MiRNA feature selection using deep belief nets and active learning
Selecting the most discriminative genes/miRNAs has been raised as an important task in
bioinformatics to enhance disease classifiers and to mitigate the dimensionality curse …
bioinformatics to enhance disease classifiers and to mitigate the dimensionality curse …
A self-training subspace clustering algorithm under low-rank representation for cancer classification on gene expression data
CQ **a, K Han, Y Qi, Y Zhang… - IEEE/ACM transactions on …, 2017 - ieeexplore.ieee.org
Accurate identification of the cancer types is essential to cancer diagnoses and treatments.
Since cancer tissue and normal tissue have different gene expression, gene expression …
Since cancer tissue and normal tissue have different gene expression, gene expression …
Classification of cancer types based on microRNA expression using a hybrid radial basis function and particle swarm optimization algorithm
M Soleimani, A Harooni, N Erfani… - Microscopy …, 2024 - Wiley Online Library
The diagnosis and treatment of cancer is one of the most challenging aspects of the medical
profession, despite advances in disease diagnosis. MicroRNAs are small noncoding RNA …
profession, despite advances in disease diagnosis. MicroRNAs are small noncoding RNA …
Multi-view Co-training for microRNA Prediction
M Sheikh Hassani, JR Green - Scientific reports, 2019 - nature.com
MicroRNA (miRNA) are short, non-coding RNAs involved in cell regulation at post-
transcriptional and translational levels. Numerous computational predictors of miRNA been …
transcriptional and translational levels. Numerous computational predictors of miRNA been …
Semi-supervised ensemble learning for efficient cancer sample classification from miRNA gene expression data
Traditional classifiers often fail to produce desired classification accuracy because of
inadequate training samples present in microRNA (miRNA) gene expression cancer …
inadequate training samples present in microRNA (miRNA) gene expression cancer …
A semi-supervised machine learning framework for microRNA classification
M Sheikh Hassani, JR Green - Human genomics, 2019 - Springer
Background MicroRNAs (miRNAs) are a family of short, non-coding RNAs that have been
linked to critical cellular activities, most notably regulation of gene expression. The …
linked to critical cellular activities, most notably regulation of gene expression. The …
Prediction of carcinoma cancer type using deep reinforcement learning technique from gene expression data
In recent decades, the investigation based on the molecular level for the classification of
cancer is becoming trending research topic for several researchers to identify the type of …
cancer is becoming trending research topic for several researchers to identify the type of …
Deep learning-based cancer disease classification through MicroRNA expression
I Slimene, I Messaoudi, AE Oueslati… - 2022 IEEE Information …, 2022 - ieeexplore.ieee.org
MicroRNAs (miRNAs) are an RNAs with 22 to 25 nucleotides that are involved in gene
regulation by inhibiting the translation or degrading messenger RNA (mRNA). In recent …
regulation by inhibiting the translation or degrading messenger RNA (mRNA). In recent …
RSSalg software: A tool for flexible experimenting with co-training based semi-supervised algorithms
RSSalg software is a tool for experimenting with Semi-Supervised Learning (SSL), a set of
machine learning techniques able to use both labeled and unlabeled data for training. The …
machine learning techniques able to use both labeled and unlabeled data for training. The …