Emerging applications of machine learning in genomic medicine and healthcare
The integration of artificial intelligence technologies has propelled the progress of clinical
and genomic medicine in recent years. The significant increase in computing power has …
and genomic medicine in recent years. The significant increase in computing power has …
A boosted SVM classifier trained by incremental learning and decremental unlearning approach
R Kashef - Expert Systems with Applications, 2021 - Elsevier
Abstract The Support Vector Machines (SVM) classifier is a margin-based supervised
machine learning method used for categorization and classification tasks. A Linear SVM …
machine learning method used for categorization and classification tasks. A Linear SVM …
Machine learning strategies in microRNA research: bridging genome to phenome
S Daniel Thomas, K Vijayakumar, L John… - OMICS: A Journal of …, 2024 - liebertpub.com
MicroRNAs (miRNAs) have emerged as a prominent layer of regulation of gene expression.
This article offers the salient and current aspects of machine learning (ML) tools and …
This article offers the salient and current aspects of machine learning (ML) tools and …
An ensemble soft weighted gene selection-based approach and cancer classification using modified metaheuristic learning
N Tavasoli, K Rezaee, M Momenzadeh… - Journal of …, 2021 - academic.oup.com
Hybrid algorithms are effective methods for solving optimization problems that rarely have
been used in the gene selection procedure. This paper introduces a novel modified model …
been used in the gene selection procedure. This paper introduces a novel modified model …
miRNAFold: a web server for fast miRNA precursor prediction in genomes
Computational methods are required for prediction of non-coding RNAs (ncRNAs), which
are involved in many biological processes, especially at post-transcriptional level. Among …
are involved in many biological processes, especially at post-transcriptional level. Among …
Parametrized division of exposure zone for marine reinforced concrete structures with a multi-class Boosting method
R Wu, J Xia, J Chen, K Chen, Y Zheng, J Mao… - Engineering …, 2023 - Elsevier
The analysis of marine reinforced concrete structures using chloride profile data is a
commonly used exposure zone classification method. However, chloride profile data is multi …
commonly used exposure zone classification method. However, chloride profile data is multi …
Deep recurrent neural network-based identification of precursor micrornas
MicroRNAs (miRNAs) are small non-coding ribonucleic acids (RNAs) which play key roles in
post-transcriptional gene regulation. Direct identification of mature miRNAs is infeasible due …
post-transcriptional gene regulation. Direct identification of mature miRNAs is infeasible due …
Multi-branch convolutional neural network for identification of small non-coding RNA genomic loci
Genomic regions that encode small RNA genes exhibit characteristic patterns in their
sequence, secondary structure, and evolutionary conservation. Convolutional Neural …
sequence, secondary structure, and evolutionary conservation. Convolutional Neural …
Computational resources for prediction and analysis of functional miRNA and their targetome
Abstract microRNAs are evolutionarily conserved, endogenously produced, noncoding
RNAs (ncRNAs) of approximately 19–24 nucleotides (nts) in length known to exhibit gene …
RNAs (ncRNAs) of approximately 19–24 nucleotides (nts) in length known to exhibit gene …
Computational prediction of functional microRNA–mRNA interactions
Proteins have a strong influence on the phenotype and their aberrant expression leads to
diseases. MicroRNAs (miRNAs) are short RNA sequences which posttranscriptionally …
diseases. MicroRNAs (miRNAs) are short RNA sequences which posttranscriptionally …