Selenium (Se) is one of the essential micronutrients for performing vital body functions. This study aims at examining the influence of dietary supplementation of garlic clove-based green-synthesized selenium nanoparticles (GBGS-SeNPs, 48-87 nm) on c...
This study aims to propose a novel and high-accuracy prediction model of plastic limit (PL) based on soil particles passing through sieve # 200 (0.075 mm) using gene expression programming (GEP). PL is used for the classification of fine-grained soil...
Computational intelligence and neuroscience
35607459
Recently, bioinformatics and computational biology-enabled applications such as gene expression analysis, cellular restoration, medical image processing, protein structure examination, and medical data classification utilize fuzzy systems in offering...
Statistical applications in genetics and molecular biology
35848211
Gene selection is one of the key steps for gene expression data analysis. An SVM-based ensemble feature selection method is proposed in this paper. Firstly, the method builds many subsets by using Monte Carlo sampling. Secondly, ranking all the featu...
BACKGROUND: Machine learning is now a standard tool for cancer prediction based on gene expression data. However, deep learning is still new for this task, and there is no clear consensus about its performance and utility. Few experimental works have...
Genes to cells : devoted to molecular & cellular mechanisms
35996802
Unequal usage of synonymous codons is known as codon usage bias (CUB), which is generally different between the high-expression genes (HEG) and low-expression genes (LEG) in organisms is not yet adequately reported across different bacteria. In this ...
Progress in biophysics and molecular biology
35988771
Gene Expression Data is the biological data to extract meaningful hidden information from the gene dataset. This gene information is used for disease diagnosis especially in cancer treatment based on the variations in gene expression levels. DNA micr...
BACKGROUND: A key problem in bioinformatics is that of predicting gene expression levels. There are two broad approaches: use of mechanistic models that aim to directly simulate the underlying biology, and use of machine learning (ML) to empirically ...
Time-course single-cell RNA sequencing (scRNA-seq) data have been widely used to explore dynamic changes in gene expression of transcription factors (TFs) and their target genes. This information is useful to reconstruct cell-type-specific gene regul...
IEEE/ACM transactions on computational biology and bioinformatics
36223356
Learning representations from data is a fundamental step for machine learning. High-quality and robust drug representations can broaden the understanding of pharmacology, and improve the modeling of multiple drug-related prediction tasks, which furth...