Genetics

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

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Polyphony: an Interactive Transfer Learning Framework for Single-Cell Data Analysis.

Reference-based cell-type annotation can significantly reduce time and effort in single-cell analysi...

Water irradiation devoid pulses enhance the sensitivity of H,H nuclear Overhauser effects.

The nuclear Overhauser effect (NOE) is one of NMR spectroscopy's most important and versatile parame...

Symphonizing pileup and full-alignment for deep learning-based long-read variant calling.

Deep learning-based variant callers are becoming the standard and have achieved superior single nucl...

Calligraphy and Painting Identification 3D-CNN Model Based on Hyperspectral Image MNF Dimensionality Reduction.

As a kind of cultural art, calligraphy and painting are not only an important part of traditional cu...

Cross-species cell-type assignment from single-cell RNA-seq data by a heterogeneous graph neural network.

Cross-species comparative analyses of single-cell RNA sequencing (scRNA-seq) data allow us to explor...

Accuracy and data efficiency in deep learning models of protein expression.

Synthetic biology often involves engineering microbial strains to express high-value proteins. Thank...

Operon Finder: A Deep Learning-based Web Server for Accurate Prediction of Prokaryotic Operons.

Operons are groups of consecutive genes that transcribe together under the regulation of a common pr...

Application of Deep Learning on Single-cell RNA Sequencing Data Analysis: A Review.

Single-cell RNA sequencing (scRNA-seq) has become a routinely used technique to quantify the gene ex...

Opportunities and Challenges with Artificial Intelligence in Genomics.

The development of artificial intelligence and machine learning algorithms may allow for advances in...

Predicting Antigenic Distance from Genetic Data for PRRSV-Type 1: Applications of Machine Learning.

The control of porcine reproductive and respiratory syndrome (PRRS) remains a significant challenge ...

Predicting RNA secondary structure by a neural network: what features may be learned?

Deep learning is a class of machine learning techniques capable of creating internal representation ...

DeepTSS: multi-branch convolutional neural network for transcription start site identification from CAGE data.

BACKGROUND: The widespread usage of Cap Analysis of Gene Expression (CAGE) has led to numerous break...

Boosting tissue-specific prediction of active cis-regulatory regions through deep learning and Bayesian optimization techniques.

BACKGROUND: Cis-regulatory regions (CRRs) are non-coding regions of the DNA that fine control the sp...

Perspectives on the future of dysmorphology.

The field of clinical genetics and genomics continues to evolve. In the past few decades, milestones...

Deep-Learning Algorithm and Concomitant Biomarker Identification for NSCLC Prediction Using Multi-Omics Data Integration.

Early diagnosis of lung cancer to increase the survival rate, which is currently at a low range of m...

Pattern recognition of topologically associating domains using deep learning.

BACKGROUND: Recent increasing evidence indicates that three-dimensional chromosome structure plays a...

Prediction of Transcription Factor Binding Sites With an Attention Augmented Convolutional Neural Network.

Identification of transcription factor binding sites (TFBSs) is essential for revealing the rules of...

Protein-DNA Binding Residue Prediction via Bagging Strategy and Sequence-Based Cube-Format Feature.

Protein-DNA interactions play an important role in diverse biological processes. Accurately identify...

Accurate Prediction of Human Essential Proteins Using Ensemble Deep Learning.

Essential proteins are considered the foundation of life as they are indispensable for the survival ...

Predicting N6-Methyladenosine Sites in Multiple Tissues of Mammals through Ensemble Deep Learning.

N6-methyladenosine (mA) is the most abundant within eukaryotic messenger RNA modification, which pla...

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