Genetics

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

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PILOT: Deep Siamese network with hybrid attention improves prediction of mutation impact on protein stability.

Evaluating the mutation impact on protein stability (ΔΔG) is essential in the study of protein engin...

A comprehensive review of computational methods for Protein-DNA binding site prediction.

Accurately identifying protein-DNA binding sites is essential for understanding the molecular mechan...

A high-throughput differential chemical genetic screen uncovers genotype-specific compounds altering plant growth.

The identification of chemical compounds regulating plant growth in a genetic context can greatly en...

DeepMethyGene: a deep-learning model to predict gene expression using DNA methylations.

Gene expression is the basis for cells to achieve various functions, while DNA methylation constitut...

Unique and shared transcriptomic signatures underlying localized scleroderma pathogenesis identified using interpretable machine learning.

Using transcriptomic profiling at single-cell resolution, we investigated cell-intrinsic and cell-ex...

Subtractive genomics approach: A guide to unveiling therapeutic targets across pathogens.

Subtractive genomics is an adaptable bioinformatics technique that is used to identify potential the...

Integrated bioinformatics analysis to develop diagnostic models for malignant transformation of chronic proliferative diseases.

The combined analysis of dual diseases can provide new insights into pathogenic mechanisms, identify...

An integrated AI knowledge graph framework of bacterial enzymology and metabolism.

The study of bacterial metabolism holds immense significance for improving human health and advancin...

CNRein: an evolution-aware deep reinforcement learning algorithm for single-cell DNA copy number calling.

Low-pass single-cell DNA sequencing technologies and algorithmic advancements have enabled haplotype...

Common genetic variants do not impact clinical prediction of methotrexate treatment outcomes in early rheumatoid arthritis.

BACKGROUND: Methotrexate (MTX) is the mainstay initial treatment of rheumatoid arthritis (RA), but i...

CGLoop: a neural network framework for chromatin loop prediction.

BACKGROUND: Chromosomes of species exhibit a variety of high-dimensional organizational features, an...

TransBind allows precise detection of DNA-binding proteins and residues using language models and deep learning.

Identifying DNA-binding proteins and their binding residues is critical for understanding diverse bi...

Predicting genes associated with ossification of the posterior longitudinal ligament using graph attention network.

Ossification of the posterior longitudinal ligament is a degenerative disease that severely impacts ...

Gap-App: A sex-distinct AI-based predictor for pancreatic ductal adenocarcinoma survival as a web application open to patients and physicians.

In this study, using RNA-Seq gene expression data and advanced machine learning techniques, we ident...

Directed Evolution of Fluorescent Genetically Encoded Biosensors: Innovative Approaches for Development and Optimization of Biosensors.

Fluorescent protein-based biosensors are indispensable molecular tools in cell biology and biomedica...

101 Machine Learning Algorithms for Mining Esophageal Squamous Cell Carcinoma Neoantigen Prognostic Models in Single-Cell Data.

Esophageal squamous cell carcinoma (ESCC) is one of the most aggressive malignant tumors in the dige...

Design and Implementation of Pavlovian Associative Memory Based on DNA Neurons.

In the field of biocomputing and neural networks, deoxyribonucleic acid (DNA) strand displacement (D...

SeqNovo: De Novo Peptide Sequencing Prediction in IoMT via Seq2Seq.

In the Internet of Medical Things (IoMT), de novo peptide sequencing prediction is one of the most i...

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