Genetics

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

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Deciphering Necroptosis-Associated Molecular Subtypes in Acute Ischemic Stroke Through Bioinformatics and Machine Learning Analysis.

Acute ischemic stroke (AIS) is a severe disorder characterized by complex pathophysiological process...

Emulating Low-Dose PCCT Image Pairs With Independent Noise for Self-Supervised Spectral Image Denoising.

Photon counting CT (PCCT) acquires spectral measurements and enables generation of material decompos...

High-Risk Sequence Prediction Model in DNA Storage: The LQSF Method.

Traditional DNA storage technologies rely on passive filtering methods for error correction during s...

Deep learning predicts DNA methylation regulatory variants in specific brain cell types and enhances fine mapping for brain disorders.

DNA methylation (DNAm) is essential for brain development and function and potentially mediates the ...

Machine Learning-Based Pathomics Model Predicts Angiopoietin-2 Expression and Prognosis in Hepatocellular Carcinoma.

Angiopoietin-2 (ANGPT2) shows promise as prognostic marker and therapeutic target in hepatocellular ...

NovoRank: Refinement for Peptide Sequencing Based on Spectral Clustering and Deep Learning.

peptide sequencing is a valuable technique in mass-spectrometry-based proteomics, as it deduces pep...

Identification of Factors Influencing Donor-Derived Cell-Free DNA Levels up to One Year After Kidney Transplant.

Donor-derived cell-free DNA (dd-cfDNA) in the peripheral blood of allograft recipients has shown to...

Trans-m5C: A transformer-based model for predicting 5-methylcytosine (m5C) sites.

5-Methylcytosine (m5C) plays a pivotal role in various RNA metabolic processes, including RNA locali...

Machine learning enhances genotoxicity assessment using MultiFlow® DNA damage assay.

Genotoxicity is a critical determinant for assessing the safety of pharmaceutical drugs, their metab...

Identification of sepsis-associated encephalopathy biomarkers through machine learning and bioinformatics approaches.

Sepsis-associated encephalopathy (SAE) is common in septic patients, characterized by acute and long...

Analysis of diagnostic genes and molecular mechanisms of Crohn's disease and colon cancer based on machine learning algorithms.

Crohn's disease (CD) is a chronic inflammatory bowel condition, and colon adenocarcinoma (COAD), as ...

Bidirectional recurrent neural network approach for predicting cervical cancer recurrence and survival.

Cervical cancer is a deadly disease in women globally. There is a greater chance of getting rid of c...

Development of an individualized dementia risk prediction model using deep learning survival analysis incorporating genetic and environmental factors.

BACKGROUND: Dementia is a major public health challenge in modern society. Early detection of high-r...

Systematic benchmarking of deep-learning methods for tertiary RNA structure prediction.

The 3D structure of RNA critically influences its functionality, and understanding this structure is...

Using genomic data and machine learning to predict antibiotic resistance: A tutorial paper.

Antibiotic resistance is a global public health concern. Bacteria have evolved resistance to most an...

An appropriate DNA input for bisulfite conversion reveals LINE-1 and Alu hypermethylation in tissues and circulating cell-free DNA from cancers.

The autonomous and active Long-Interspersed Element-1 (LINE-1, L1) and the non-autonomous Alu retrot...

A Robust and Efficient Representation-based DNA Storage Architecture by Deep Learning.

As one main form of multimedia data, images play a critical role in various applications. In this pa...

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