Identifying common transcriptome signatures of cancer by interpreting deep learning models, Genome Biology
Por um escritor misterioso
Last updated 31 março 2025

Background Cancer is a set of diseases characterized by unchecked cell proliferation and invasion of surrounding tissues. The many genes that have been genetically associated with cancer or shown to directly contribute to oncogenesis vary widely between tumor types, but common gene signatures that relate to core cancer pathways have also been identified. It is not clear, however, whether there exist additional sets of genes or transcriptomic features that are less well known in cancer biology but that are also commonly deregulated across several cancer types. Results Here, we agnostically identify transcriptomic features that are commonly shared between cancer types using 13,461 RNA-seq samples from 19 normal tissue types and 18 solid tumor types to train three feed-forward neural networks, based either on protein-coding gene expression, lncRNA expression, or splice junction use, to distinguish between normal and tumor samples. All three models recognize transcriptome signatures that are consistent across tumors. Analysis of attribution values extracted from our models reveals that genes that are commonly altered in cancer by expression or splicing variations are under strong evolutionary and selective constraints. Importantly, we find that genes composing our cancer transcriptome signatures are not frequently affected by mutations or genomic alterations and that their functions differ widely from the genes genetically associated with cancer. Conclusions Our results highlighted that deregulation of RNA-processing genes and aberrant splicing are pervasive features on which core cancer pathways might converge across a large array of solid tumor types.

Frontiers A Brief Review on Deep Learning Applications in

IJMS, Free Full-Text

Splicing signature database development to delineate cancer

An integral genomic signature approach for tailored cancer therapy

Identifying tumor cells at the single-cell level using machine

Deep learning model accurately classifies metastatic tumors from

Identifying common transcriptome signatures of cancer by

Biologically informed deep learning to query gene programs in

Frontiers Machine Learning: A New Prospect in Multi-Omics Data
Recomendado para você
-
Lengkap Ada Video, Brain Test Level 367 Saatnya Mancari cuan! ✓31 março 2025
-
Solved In a study of fast food drive-through orders31 março 2025
-
UTRGV Office For Sustainability - The Rio Grande Valley - Society For Neuroscience- Chapter (RGV-SFN-C) is organizing several events in its mission of promoting: Outreach, Education, Research in the Neuroscience31 março 2025
-
Από το Brain Drain στο Brain Gain: Έτσι μπορεί να αναστραφεί το φαινόμενο (fortunegreece.gr)31 março 2025
-
Neuroimaging and deep learning for brain stroke detection - A review of recent advancements and future prospects - ScienceDirect31 março 2025
-
JCDD, Free Full-Text31 março 2025
-
Right Of Way: Traffic Rules Quiz! - ProProfs Quiz31 março 2025
-
Effectiveness of management strategies for uninvestigated dyspepsia: systematic review and network meta-analysis31 março 2025
-
Lion's Mane and Chaga Supplements Review & Top Picks31 março 2025
-
Page 6 1,000+ Logo Alzheimers Care Pictures31 março 2025
você pode gostar
-
Microsoft discontinues Xbox 36031 março 2025
-
Scp-049 Minecraft Skin31 março 2025
-
desenho para colorir e imprimir pokemon lendario31 março 2025
-
New 'Game of the Day' Cards Spotted in Chrome for Android31 março 2025
-
Minecraft - NARUTO LEGACY ! 🔴 - O NOVO TIME 7 ! SASUKE , KAWAKI , HIMAWARE E TREVOR UCHIHA ! EP 2 - BiliBili31 março 2025
-
How To Play Retro Games on iPhone - Explosion Of Fun31 março 2025
-
Jogo Caixa de Mágicas – Grow - RioMar Aracaju Online31 março 2025
-
Sons of the Forest: How to get Virginia as a companion - Polygon31 março 2025
-
Chrome Dinosaur Game Ending Dino Jumps Out from Chrome ( Dino vs31 março 2025
-
O que é Pronomes O que são Pronomes Classes Gramticais Pronomes31 março 2025