Annotation|Free Deep Learning for Predicting Gene Mutations from ...

Annotation-Free Deep Learning for Predicting Gene Mutations from ...

We propose a deep learning model based on multiple instance learning (MIL) with ensemble learning to predict gene mutations from AML annotation-free WSIs.

Annotation-Free Deep Learning for Predicting Gene Mutations from ...

With the property of annotation-free, the proposed method eliminates the need for manual annotations, reducing the manpower and time costs ...

(PDF) Annotation-Free Deep Learning for Predicting Gene ...

To address this, we propose a deep learning model based on multiple instance learning (MIL) to predict gene mutations from AML WSIs with no ...

Benchmarking of deep neural networks for predicting personal gene ...

Deep learning methods have recently become the state-of-the-art in a variety of regulatory genomic tasks– including the prediction of gene expression from ...

GenNet framework: interpretable deep learning for predicting ...

Here, we propose GenNet, a novel open-source deep learning framework for predicting phenotypes from genetic variants. In this framework, ...

DeepChrome: deep-learning for predicting gene expression from ...

This paper develops a unified discriminative framework using a deep convolutional neural network to classify gene expression using histone modification data as ...

A deep learning model to predict RNA-Seq expression of ... - Nature

also been used to predict gene mutations ... Deep-learning convolutional neural networks accurately classify genetic mutations in gliomas.

Annotation-Free Deep Learning for Predicting Gene Mutations from ...

AbstractThe rapid development of deep learning in recent years has revolutionized the field of medical image processing, including the applications of using ...

A review of deep learning applications in human genomics using ...

Multiple genomic disciplines (e.g. variant calling and annotation, disease variant prediction, gene expression and regulation, epigenomics ...

Deep learning program to predict protein functions based on ...

After trained for monooxygenase activity, FUTUSA successfully predicted the impact of point mutations on phenylalanine hydroxylase, which is responsible for an ...

Annotation-Free Deep Learning-Based Prediction of Thyroid ... - MDPI

The proposed annotation-free deep learning framework for classification BRAF (V600E) status from Papanicolaou-stained thyroid FNA and TP WSIs. ( ...

a deep learning-based strategy to predict cancer driver mutations ...

H. ANNOVAR: functional annotation of genetic variants from high-throughput sequencing data . Nucleic Acids Res. 2010. ;. 38.

Mutation-Attention (MuAt): deep representation learning of somatic ...

predicted tumour types with a support vector machine using information on somatically mutated genes resulting in 49% accuracy in 28 tumour ...

Predicting Loss-of-Function Impact of Genetic Mutations: A Machine ...

Thus, this paper's aims were to train machine learning models on the attributes of a genetic mutation to predict LoFtool scores (which measure a ...

Predicting clinical impact of human mutation with deep neural ...

The Illumina team developed deep neural network algorithm, PrimateAI, to predict the clinical impact of human missense mutations.

Predicting oncogene mutations of lung cancer using deep learning ...

We developed our convolutional neural network-based models to analyze whole slides and predict five major genetic mutations, i.e., BRAF, EGFR, KRAS, STK11, and ...

Optimization of deep learning models for the prediction of gene ...

In this paper, we propose an unsupervised clustering-based multiple-instance deep learning model for the prediction of genetic mutations using WSIs of three ...

AI Accurately Predicts Effects of Genetic Mutations in Biological Dark ...

A new machine learning framework, dubbed ExPecto, can predict the effects of genetic mutations in the so-called “dark matter” regions of the human genome.

deepDriver: Predicting Cancer Driver Genes Based on Somatic ...

The method allows the convolutional neural network to learn information within mutation data and similarity networks simultaneously, which ...

Deep learning predicts therapy-relevant genetics in acute myeloid ...

Deep learning has recently been uncovered as a powerful tool to extract prognostic features and genetic aberrations from digital images of tumor ...