Artificial Intelligence Technique for Gene Expression by Tumor RNA ...

Researchers flip genes on and off with AI-designed DNA switches

The new method could revolutionize gene therapy and biotechnology by allowing precise activation or repression of genes in specific tissues.

Gene Expression Analysis With AI | Restackio

Gene expression analysis using machine learning techniques has become increasingly important in genomics. By leveraging algorithms that can ...

RNA-seq assistant: machine learning based methods to identify ...

In addition, the epigenetic regulation plays critical roles in gene expression, therefore, DNA and histone methylation data has been shown to be ...

Artificial Intelligence in Pathomics and Genomics of Renal Cell ...

75 ML models were used to analyze gene expression (RNA), DNA methylation, and clinical information. AI techniques facilitated the analysis of various ...

Tumor Classification using Gene Expression Data - Medium

Tumor Classification using Gene Expression Data — poking at a problem using Fast.AI again · Recently high-throughput RNA sequencing (RNA-seq) has ...

aiGeneR 1.0: An Artificial Intelligence Technique for the Revelation ...

Building an AI protocol for identifying the ARG using gene expression data is essential. Gene expression data are typically complicated and nonlinear in nature.

AI-powered tool predicts gene activity in cancer cells from biopsy ...

Now, Stanford Medicine researchers have developed an artificial intelligence-powered computational program that can predict the activity of ...

Artificial Intelligence in Cancer Research and Precision Medicine

AI is gradually paving its path toward early detection of cancer from emerging minimally invasive techniques as well, such as liquid biopsies ...

Deep Learning Based Tumor Type Classification Using Gene ...

In this paper, we embedded the high dimensional RNA-Seq data into 2-D images and used a convolutional neural network to make classification of the 33 tumor ...

MLSeq: Machine Learning Interface to RNA-Seq Data - Bioconductor

method for RNA-Seq based ... Comparison of discrimination methods for the classification of tumors using gene expression data.

Transforming lung cancer care: Synergizing artificial intelligence and

(2020) Artificial intelligence technique for gene expression by tumor RNA-Seq data: a novel optimized deep learning approach. IEEE Access 8 ...

ABEILLE: a novel method for ABerrant Expression Identification ...

Hence, we developed ABerrant Expression Identification empLoying machine LEarning from sequencing data (ABEILLE) a variational autoencoder (VAE)- ...

Gene Selection for Cancer Classification using Support Vector ...

In this paper, we address the problem of selection of a small subset of genes from broad patterns of gene expression data, recorded on DNA micro-arrays. Using ...

Transcriptomics 3: Supervised Machine Learning for RNA-seq Data

Transcriptomics 3 is a course dedicated to advanced methods of analysis, that will allow us to find meaningful patterns in data -especially ...

Machine Learning for Designing Next-Generation mRNA Therapeutics

As a result, our Fast SeqProp method converges rapidly in a variety of design tasks, including maximizing transcription factor binding, ...

How AI can accelerate R&D for cell and gene therapies

For viral therapeutics that aim to edit the genome, algorithms to predict CRISPR target sites can help identify genomic sites with genetic ...

Exploring the Unknown: The Application and Prospects of Artificial ...

AI applications extend beyond gene identification, gene expression pattern prediction, and genomic structural variant analysis, encompassing key areas such as ...

A Survey of Machine Learning Approaches Applied to Gene ...

Comparing the performance of MLP, RSS and SMO to classify lung cancer data. A novel multi-view feature selection method was used to analyze gene expression (RNA ...

From Images to Genes: Radiogenomics Based on Artificial ...

Epigenetic modifications, encompassing DNA, RNA, and protein modifications, are variable and can alter gene expression, affecting tumor ...

Applications of deep learning in understanding gene regulation

Developments in microarray, DNA and RNA sequencing, mass spectrometry, and single-cell technologies have provided foundations for experimental techniques to ...