Genetics

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

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Combining Supervised and Unsupervised Machine Learning Methods for Phenotypic Functional Genomics Screening.

There has been an increase in the use of machine learning and artificial intelligence (AI) for the a...

CNN-Peaks: ChIP-Seq peak detection pipeline using convolutional neural networks that imitate human visual inspection.

ChIP-seq is one of the core experimental resources available to understand genome-wide epigenetic in...

RadAtlas 1.0: a knowledgebase focusing on radiation-associated genes.

Ionizing radiation has very complex biological effects, such as inducing damage to DNA and proteins...

Nonsurgical Prevention Strategies in and Mutation Carriers.

BACKGROUND: Female carriers of a or germline mutation face a high lifetime risk to develop breast ...

Haruspex: A Neural Network for the Automatic Identification of Oligonucleotides and Protein Secondary Structure in Cryo-Electron Microscopy Maps.

In recent years, three-dimensional density maps reconstructed from single particle images obtained b...

Sparsity-Penalized Stacked Denoising Autoencoders for Imputing Single-Cell RNA-Seq Data.

Single-cell RNA-seq (scRNA-seq) is quite prevalent in studying transcriptomes, but it suffers from e...

Deep learning enables accurate clustering with batch effect removal in single-cell RNA-seq analysis.

Single-cell RNA sequencing (scRNA-seq) can characterize cell types and states through unsupervised c...

iMethyl-Deep: N6 Methyladenosine Identification of Yeast Genome with Automatic Feature Extraction Technique by Using Deep Learning Algorithm.

One of the most common and well studied post-transcription modifications in RNAs is N6-methyladenosi...

COVID-19 on Chest Radiographs: A Multireader Evaluation of an Artificial Intelligence System.

Background Chest radiography may play an important role in triage for coronavirus disease 2019 (COVI...

Predicting cancer origins with a DNA methylation-based deep neural network model.

Cancer origin determination combined with site-specific treatment of metastatic cancer patients is c...

Deep Dive into Machine Learning Models for Protein Engineering.

Protein redesign and engineering has become an important task in pharmaceutical research and develop...

Analysis of Drug Effects on iPSC Cardiomyocytes with Machine Learning.

Patient-specific induced pluripotent stem cell-derived cardiomyocytes (iPSC-CMs) offer an attractive...

Machine learning-guided evolution of BMP-2 knuckle Epitope-Derived osteogenic peptides to target BMP receptor II.

Bone morphogenetic protein-2 (BMP-2) is a key regulator of bone formation, growth and regeneration, ...

Photosynthetic protein classification using genome neighborhood-based machine learning feature.

Identification of novel photosynthetic proteins is important for understanding and improving photosy...

Evaluation of off-targets predicted by sgRNA design tools.

The ease of programming CRISPR/Cas9 system for targeting a specific location within the genome has p...

Classification of COVID-19 patients from chest CT images using multi-objective differential evolution-based convolutional neural networks.

Early classification of 2019 novel coronavirus disease (COVID-19) is essential for disease cure and ...

Machine learning using intrinsic genomic signatures for rapid classification of novel pathogens: COVID-19 case study.

The 2019 novel coronavirus (renamed SARS-CoV-2, and generally referred to as the COVID-19 virus) has...

BioConceptVec: Creating and evaluating literature-based biomedical concept embeddings on a large scale.

A massive number of biological entities, such as genes and mutations, are mentioned in the biomedica...

Age estimation using bloodstain miRNAs based on massive parallel sequencing and machine learning: A pilot study.

Age estimation is one of the most important components in the practice of forensic science, especial...

Automatically Designing CNN Architectures Using the Genetic Algorithm for Image Classification.

Convolutional neural networks (CNNs) have gained remarkable success on many image classification tas...

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