Genetics

Latest AI and machine learning research in genetics for healthcare professionals.

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Deep learning-based cross-classifications reveal conserved spatial behaviors within tumor histological images.

Histopathological images are a rich but incompletely explored data type for studying cancer. Manual ...

Systematic evaluation of supervised machine learning for sample origin prediction using metagenomic sequencing data.

BACKGROUND: The advent of metagenomic sequencing provides microbial abundance patterns that can be l...

How wide is the application of genetic big data in biomedicine.

In the era of big data, massive genetic data, as a new industry, has quickly swept almost all indust...

Artificial intelligence and hybrid imaging: the best match for personalized medicine in oncology.

Artificial intelligence (AI) refers to a field of computer science aimed to perform tasks typically ...

Immune profile of the tumor microenvironment and the identification of a four-gene signature for lung adenocarcinoma.

The composition and relative abundances of immune cells in the tumor microenvironment are key factor...

RBPsuite: RNA-protein binding sites prediction suite based on deep learning.

BACKGROUND: RNA-binding proteins (RBPs) play crucial roles in various biological processes. Deep lea...

miRNA-Based Feature Classifier Is Associated with Tumor Mutational Burden in Head and Neck Squamous Cell Carcinoma.

Tumor mutation burden (TMB) is considered to be an independent genetic biomarker that can predict th...

New Approach for Risk Estimation Algorithms of Negativeness Detection with Modelling Supervised Machine Learning Techniques.

gene testing is a difficult, expensive, and time-consuming test which requires excessive work load....

A machine learning toolkit for genetic engineering attribution to facilitate biosecurity.

The promise of biotechnology is tempered by its potential for accidental or deliberate misuse. Relia...

Neuronal differentiation strategies: insights from single-cell sequencing and machine learning.

Neuronal replacement therapies rely on the differentiation of specific cell types from embryonic or...

Bioimage-Based Prediction of Protein Subcellular Location in Human Tissue with Ensemble Features and Deep Networks.

Prediction of protein subcellular location has currently become a hot topic because it has been prov...

Deep Learning Benchmarks on L1000 Gene Expression Data.

Gene expression data can offer deep, physiological insights beyond the static coding of the genome a...

Performance-weighted-voting model: An ensemble machine learning method for cancer type classification using whole-exome sequencing mutation.

BACKGROUND: With improvements in next-generation DNA sequencing technology, lower cost is needed to ...

DeepA-RBPBS: A hybrid convolution and recurrent neural network combined with attention mechanism for predicting RBP binding site.

It's important to infer the binding site of RNA-binding proteins (RBP) for understanding the interac...

Transfer learning efficiently maps bone marrow cell types from mouse to human using single-cell RNA sequencing.

Biomedical research often involves conducting experiments on model organisms in the anticipation tha...

Parameter estimation of the homodyned K distribution based on an artificial neural network for ultrasound tissue characterization.

The homodyned K (HK) distribution allows a general description of ultrasound backscatter envelope st...

Deep learning suggests that gene expression is encoded in all parts of a co-evolving interacting gene regulatory structure.

Understanding the genetic regulatory code governing gene expression is an important challenge in mol...

Artificial intelligence applications for oncological positron emission tomography imaging.

Positron emission tomography (PET), a functional and dynamic molecular imaging technique, is general...

DeepACEv2: Automated Chromosome Enumeration in Metaphase Cell Images Using Deep Convolutional Neural Networks.

Chromosome enumeration is an essential but tedious procedure in karyotyping analysis. To automate th...

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