Though several deep learning approaches were developed to assist in CT analysis, nobody considered study triage directly as a computer science problem ...
AttentiveChrome is an attention-based deep learning model that uses histone modification signals covering the gene’s neighboring DNA region of Transcr ...
The model shows that mRNA abundance can be predicted from promoter sequence alone using deep neural networks. The residuals of these predictions make ...
BABEL is a deep learning model written in Python designed to translate between mutliple single cell modalities. It is designed to translate between sc ...
A crucial part of the cis-regulatory code is the arrangement of transcription factor binding motifs. But, identifying the critical bases that alter th ...
Machine Learning is becoming a powerful approach for integrative analysis of whole slide histology images. More recently, convolutional neural network ...
Predicting gene expression purely from DNA sequence has been a long-standing problem in regulatory genomics. Enformer is a novel transformer architect ...
Advanced machine learning models applied to large-scale genomics datasets hold the promise to be major drivers for genome science. Once trained, such ...
OncoNetExplainer, based on neural networks (NN) and VGG16 networks with a GradCAM++, take patients' Gene Expressions (GE) from The Cancer Genome Atlas ...
OmiEmbed is a unified multitask deep learning framework that captures biomedical information from high-dimensional omics data with the deep embedding ...