Genetics

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

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Machine Learning Reveals the Critical Interactions for SARS-CoV-2 Spike Protein Binding to ACE2.

SARS-CoV and SARS-CoV-2 bind to the human ACE2 receptor in practically identical conformations, alth...

Enhancement of protein thermostability by three consecutive mutations using loop-walking method and machine learning.

We developed a method to improve protein thermostability, "loop-walking method". Three consecutive p...

Modeling of aquifer vulnerability index using deep learning neural networks coupling with optimization algorithms.

A reliable assessment of the aquifer contamination vulnerability is essential for the conservation a...

MILAMP: Multiple Instance Prediction of Amyloid Proteins.

Amyloid proteins are implicated in several diseases such as Parkinson's, Alzheimer's, prion diseases...

ILDMSF: Inferring Associations Between Long Non-Coding RNA and Disease Based on Multi-Similarity Fusion.

The dysregulation and mutation of long non-coding RNAs (lncRNAs) have been proved to result in a var...

Identifying genomic islands with deep neural networks.

BACKGROUND: Horizontal gene transfer is the main source of adaptability for bacteria, through which ...

MetaVelvet-DL: a MetaVelvet deep learning extension for de novo metagenome assembly.

BACKGROUND: The increasing use of whole metagenome sequencing has spurred the need to improve de nov...

A semi-supervised deep learning approach for predicting the functional effects of genomic non-coding variations.

BACKGROUND: Understanding the functional effects of non-coding variants is important as they are oft...

FTIR spectroscopy with machine learning: A new approach to animal DNA polymorphism screening.

Technological advances in recent decades, especially in molecular genetics, have enabled the detecti...

Large-scale machine-learning-based phenotyping significantly improves genomic discovery for optic nerve head morphology.

Genome-wide association studies (GWASs) require accurate cohort phenotyping, but expert labeling can...

Ultrasensitive biosensing platform based on luminescence quenching ability of fullerenol quantum dots.

An ultrasensitive biosensing platform for DNA and ochratoxin A (OTA) detection is constructed based ...

A sequence-based multiple kernel model for identifying DNA-binding proteins.

BACKGROUND: DNA-Binding Proteins (DBP) plays a pivotal role in biological system. A mounting number ...

EDLmAPred: ensemble deep learning approach for mRNA mA site prediction.

BACKGROUND: As a common and abundant RNA methylation modification, N6-methyladenosine (mA) is widely...

i4mC-EL: Identifying DNA N4-Methylcytosine Sites in the Mouse Genome Using Ensemble Learning.

As one of important epigenetic modifications, DNA N4-methylcytosine (4mC) plays a crucial role in co...

Enhancing CRISPR-Cas9 gRNA efficiency prediction by data integration and deep learning.

The design of CRISPR gRNAs requires accurate on-target efficiency predictions, which demand high-qua...

Application of artificial intelligence for detection of chemico-biological interactions associated with oxidative stress and DNA damage.

In recent years, various AI-based methods have been developed in order to uncover chemico-biological...

Artificial neural network analysis of microbial diversity in the central and southern Adriatic Sea.

Bacteria are an active and diverse component of pelagic communities. The identification of main fact...

Data-driven approaches to advance research and clinical care for pediatric cancer.

Pediatric cancer is a rare disease with a distinct etiology and mutational landscape compared with a...

RNA Backbone Torsion and Pseudotorsion Angle Prediction Using Dilated Convolutional Neural Networks.

RNA three-dimensional structure prediction has been relied on using a predicted or experimentally de...

A joint deep learning model enables simultaneous batch effect correction, denoising, and clustering in single-cell transcriptomics.

Recent developments of single-cell RNA-seq (scRNA-seq) technologies have led to enormous biological ...

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