Genetics

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

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SCONES: Self-Consistent Neural Network for Protein Stability Prediction Upon Mutation.

Engineering proteins to have desired properties by mutating amino acids at specific sites is commonp...

Non-invasive diagnostic tool for Parkinson's disease by sebum RNA profile with machine learning.

Parkinson's disease (PD) is a progressive neurodegenerative disease presenting with motor and non-mo...

LightGBM: accelerated genomically designed crop breeding through ensemble learning.

LightGBM is an ensemble model of decision trees for classification and regression prediction. We dem...

Change of Cytokines in Chronic Hepatitis B Patients and HBeAg are Positively Correlated with HBV RNA, Based on Real-world Study.

BACKGROUND AND AIMS: The natural course of chronic hepatitis B virus (HBV) infection is widely studi...

GenNet framework: interpretable deep learning for predicting phenotypes from genetic data.

Applying deep learning in population genomics is challenging because of computational issues and lac...

MIDGET:Detecting differential gene expression on microarray data.

Backgound and Objective: Detecting differentially expressed genes is an important step in genome wid...

RDDSVM: accurate prediction of A-to-I RNA editing sites from sequence using support vector machines.

Adenosine to inosine (A-to-I) editing in RNA is involved in various biological processes like gene e...

Hybrid Deep Learning Based on a Heterogeneous Network Profile for Functional Annotations of Genes.

Functional annotation of unknown function genes reveals unidentified functions that can enhance our ...

Identifying digenic disease genes via machine learning in the Undiagnosed Diseases Network.

Rare diseases affect millions of people worldwide, and discovering their genetic causes is challengi...

Biomolecular simulation based machine learning models accurately predict sites of tolerability to the unnatural amino acid acridonylalanine.

The incorporation of unnatural amino acids (Uaas) has provided an avenue for novel chemistries to be...

Evaluation of deep learning approaches for modeling transcription factor sequence specificity.

As a key component of gene regulation, transcription factors (TFs) play an important role in a numbe...

Weakly supervised learning on unannotated H&E-stained slides predicts BRAF mutation in thyroid cancer with high accuracy.

Deep neural networks (DNNs) that predict mutational status from H&E slides of cancers can enable ine...

An pipeline for the discovery of multitarget ligands: A case study for epi-polypharmacology based on DNMT1/HDAC2 inhibition.

The search for novel therapeutic compounds remains an overwhelming task owing to the time-consuming ...

Repurposing non-oncology small-molecule drugs to improve cancer therapy: Current situation and future directions.

Drug repurposing or repositioning has been well-known to refer to the therapeutic applications of a ...

SWnet: a deep learning model for drug response prediction from cancer genomic signatures and compound chemical structures.

BACKGROUND: One of the major challenges in precision medicine is accurate prediction of individual p...

Predicting drug sensitivity of cancer cells based on DNA methylation levels.

Cancer cell lines, which are cell cultures derived from tumor samples, represent one of the least ex...

RF-SVM: Identification of DNA-binding proteins based on comprehensive feature representation methods and support vector machine.

Protein-DNA interactions play an important role in biological progress, such as DNA replication, rep...

Diagnostic classification of coronavirus disease 2019 (COVID-19) and other pneumonias using radiomics features in CT chest images.

We propose a classification method using the radiomics features of CT chest images to identify patie...

Deep learning detects acute myeloid leukemia and predicts NPM1 mutation status from bone marrow smears.

The evaluation of bone marrow morphology by experienced hematopathologists is essential in the diagn...

Research on RNA secondary structure predicting via bidirectional recurrent neural network.

BACKGROUND: RNA secondary structure prediction is an important research content in the field of biol...

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