Genetics

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

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DNN-Boost: Somatic mutation identification of tumor-only whole-exome sequencing data using deep neural network and XGBoost.

Detection of somatic mutation in whole-exome sequencing data can help elucidate the mechanism of tum...

Predicting deleterious missense genetic variants via integrative supervised nonnegative matrix tri-factorization.

Among an assortment of genetic variations, Missense are major ones which a small subset of them may ...

Profiling epigenetic age in single cells.

DNA methylation dynamics emerged as a promising biomarker of mammalian aging, with multivariate mach...

A Pan-Cancer Analysis of Predictive Methylation Signatures of Response to Cancer Immunotherapy.

Recently, tumor immunotherapy based on immune checkpoint inhibitors (ICI) has been introduced and wi...

EnTSSR: A Weighted Ensemble Learning Method to Impute Single-Cell RNA Sequencing Data.

The advancements of single-cell RNA sequencing (scRNA-seq) technologies have provided us unprecedent...

GapPredict - A Language Model for Resolving Gaps in Draft Genome Assemblies.

Short-read DNA sequencing instruments can yield over 10 bases per run, typically composed of reads 1...

FexRNA: Exploratory Data Analysis and Feature Selection of Non-Coding RNA.

Non-coding RNA (ncRNA) is involved in many biological processes and diseases in all species. Many nc...

Unsupervised Learning Framework With Multidimensional Scaling in Predicting Epithelial-Mesenchymal Transitions.

Clustering tumor metastasis samples from gene expression data at the whole genome level remains an a...

Improved Predicting of The Sequence Specificities of RNA Binding Proteins by Deep Learning.

RNA-binding proteins (RBPs) have a significant role in various regulatory tasks. However, the mechan...

BiLSTM-5mC: A Bidirectional Long Short-Term Memory-Based Approach for Predicting 5-Methylcytosine Sites in Genome-Wide DNA Promoters.

An important reason of cancer proliferation is the change in DNA methylation patterns, characterized...

Application and Development of Intelligent Medicine in Traditional Chinese Medicine.

As modern science and technology constantly progresses, the fields of artificial intelligence, mixed...

Label-free multiplexed microtomography of endogenous subcellular dynamics using generalizable deep learning.

Simultaneous imaging of various facets of intact biological systems across multiple spatiotemporal s...

The identification of gene signatures in patients with extranodal NK/T-cell lymphoma from a pair of twins.

BACKGROUND: There is no unified treatment standard for patients with extranodal NK/T-cell lymphoma (...

What makes a good prediction? Feature importance and beginning to open the black box of machine learning in genetics.

Genetic data have become increasingly complex within the past decade, leading researchers to pursue ...

Machine learning modeling of genome-wide copy number alteration signatures reliably predicts IDH mutational status in adult diffuse glioma.

Knowledge of 1p/19q-codeletion and IDH1/2 mutational status is necessary to interpret any investigat...

Biofilm inhibition in Candida albicans with biogenic hierarchical zinc-oxide nanoparticles.

The present study demonstrates lignin (L), fragments of lignin (FL), and oxidized fragmented lignin ...

Optimization of Data Mining and Analysis System for Chinese Language Teaching Based on Convolutional Neural Network.

Chinese language is also an important way to understand Chinese culture and an important carrier to ...

Genome-Wide Mutation Scoring for Machine-Learning-Based Antimicrobial Resistance Prediction.

The prediction of antimicrobial resistance (AMR) based on genomic information can improve patient ou...

Application of information theoretic feature selection and machine learning methods for the development of genetic risk prediction models.

In view of the growth of clinical risk prediction models using genetic data, there is an increasing ...

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