An automated framework for efficiently designing deep convolutional neural networks in genomics
Convolutional neural networks (CNNs) have become a standard for analysis of biological
sequences. Tuning of network architectures is essential for a CNN's performance, yet it …
sequences. Tuning of network architectures is essential for a CNN's performance, yet it …
Mapping RNA splicing variations in clinically accessible and nonaccessible tissues to facilitate Mendelian disease diagnosis using RNA-seq
Purpose RNA-seq is a promising approach to improve diagnoses by detecting pathogenic
aberrations in RNA splicing that are missed by DNA sequencing. RNA-seq is typically …
aberrations in RNA splicing that are missed by DNA sequencing. RNA-seq is typically …
Big data and deep learning for RNA biology
H Hwang, H Jeon, N Yeo, D Baek - Experimental & Molecular Medicine, 2024 - nature.com
The exponential growth of big data in RNA biology (RB) has led to the development of deep
learning (DL) models that have driven crucial discoveries. As constantly evidenced by DL …
learning (DL) models that have driven crucial discoveries. As constantly evidenced by DL …
Alternative splicing in cancer and immune cells
Simple Summary Alternative splicing is one of the most fabulous and important mechanism
in the cell. Alternative splicing is capable of generating many proteins from a single gene …
in the cell. Alternative splicing is capable of generating many proteins from a single gene …
The hitchhikers' guide to RNA sequencing and functional analysis
DNA and RNA sequencing technologies have revolutionized biology and biomedical
sciences, sequencing full genomes and transcriptomes at very high speeds and reasonably …
sciences, sequencing full genomes and transcriptomes at very high speeds and reasonably …
Learning the regulatory code of gene expression
Data-driven machine learning is the method of choice for predicting molecular phenotypes
from nucleotide sequence, modeling gene expression events including protein-DNA …
from nucleotide sequence, modeling gene expression events including protein-DNA …
Intron retention as a mode for RNA-seq data analysis
Intron retention (IR) is an alternative splicing mode whereby introns, rather than being
spliced out as usual, are retained in mature mRNAs. It was previously considered a …
spliced out as usual, are retained in mature mRNAs. It was previously considered a …
A multi-scale expression and regulation knowledge base for Escherichia coli
CR Lamoureux, KT Decker, AV Sastry… - Nucleic Acids …, 2023 - academic.oup.com
Transcriptomic data is accumulating rapidly; thus, scalable methods for extracting
knowledge from this data are critical. Here, we assembled a top-down expression and …
knowledge from this data are critical. Here, we assembled a top-down expression and …
Emerging molecular subtypes and therapeutic targets in B-cell precursor acute lymphoblastic leukemia
B-cell precursor acute lymphoblastic leukemia (BCP-ALL) is characterized by genetic
alterations with high heterogeneity. Precise subtypes with distinct genomic and/or gene …
alterations with high heterogeneity. Precise subtypes with distinct genomic and/or gene …
Splicing defects in rare diseases: transcriptomics and machine learning strategies towards genetic diagnosis
Genomic variants affecting pre-messenger RNA splicing and its regulation are known to
underlie many rare genetic diseases. However, common workflows for genetic diagnosis …
underlie many rare genetic diseases. However, common workflows for genetic diagnosis …