The expanding landscape of alternative splicing variation in human populations
Alternative splicing is a tightly regulated biological process by which the number of gene
products for any given gene can be greatly expanded. Genomic variants in splicing …
products for any given gene can be greatly expanded. Genomic variants in splicing …
[HTML][HTML] Integrating Molecular Perspectives: Strategies for Comprehensive Multi-Omics Integrative Data Analysis and Machine Learning Applications in …
Simple Summary Recent high-throughput technologies such as transcriptomics, proteomics,
and metabolomics have allowed progress in understanding biological systems at different …
and metabolomics have allowed progress in understanding biological systems at different …
A deep learning approach to identify gene targets of a therapeutic for human splicing disorders
Pre-mRNA splicing is a key controller of human gene expression. Disturbances in splicing
due to mutation lead to dysregulated protein expression and contribute to a substantial …
due to mutation lead to dysregulated protein expression and contribute to a substantial …
DEGnext: classification of differentially expressed genes from RNA-seq data using a convolutional neural network with transfer learning
Background A limitation of traditional differential expression analysis on small datasets
involves the possibility of false positives and false negatives due to sample variation …
involves the possibility of false positives and false negatives due to sample variation …
Pathway-guided analysis identifies Myc-dependent alternative pre-mRNA splicing in aggressive prostate cancers
We sought to define the landscape of alternative pre-mRNA splicing in prostate cancers and
the relationship of exon choice to known cancer driver alterations. To do so, we compiled a …
the relationship of exon choice to known cancer driver alterations. To do so, we compiled a …
A feature selection-based framework to identify biomarkers for cancer diagnosis: A focus on lung adenocarcinoma
Lung cancer (LC) represents most of the cancer incidences in the world. There are many
types of LC, but Lung Adenocarcinoma (LUAD) is the most common type. Although RNA-seq …
types of LC, but Lung Adenocarcinoma (LUAD) is the most common type. Although RNA-seq …
Machine learning classifiers for endometriosis using transcriptomics and methylomics data
Endometriosis is a complex and common gynecological disorder yet a poorly understood
disease affecting about 176 million women worldwide and causing significant impact on …
disease affecting about 176 million women worldwide and causing significant impact on …
PCA model for RNA-Seq malaria vector data classification using KNN and decision tree algorithm
Malaria parasites adopt unresolved discrepancy of life segments as they grow through
various mosquito vector stratospheres. Transcriptomes of thousands of individual parasites …
various mosquito vector stratospheres. Transcriptomes of thousands of individual parasites …
Comparative study of classification algorithms for various DNA microarray data
Microarrays are applications of electrical engineering and technology in biology that allow
simultaneous measurement of expression of numerous genes, and they can be used to …
simultaneous measurement of expression of numerous genes, and they can be used to …
A hybrid heuristic dimensionality reduction methods for classifying malaria vector gene expression data
Malaria is the world's leading cause of death, spread by Anopheles mosquitoes. Gene
expression is a fundamental level where the effects of unseen vital revealing genes and …
expression is a fundamental level where the effects of unseen vital revealing genes and …