Genetics

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

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Predicting phenotypes from genetic, environment, management, and historical data using CNNs.

Convolutional Neural Networks (CNNs) can perform similarly or better than standard genomic predictio...

Identifying novel transcript biomarkers for hepatocellular carcinoma (HCC) using RNA-Seq datasets and machine learning.

BACKGROUND: Hepatocellular carcinoma (HCC) is one of the leading causes of cancer death in the world...

NGS and phenotypic ontology-based approaches increase the diagnostic yield in syndromic retinal diseases.

Syndromic retinal diseases (SRDs) are a group of complex inherited systemic disorders, with challeng...

Machine Learning-Based Radiomics Signatures for EGFR and KRAS Mutations Prediction in Non-Small-Cell Lung Cancer.

Early identification of epidermal growth factor receptor (EGFR) and Kirsten rat sarcoma viral oncoge...

Using machine learning and big data to explore the drug resistance landscape in HIV.

Drug resistance mutations (DRMs) appear in HIV under treatment pressure. DRMs are commonly transmitt...

Review of machine learning methods for RNA secondary structure prediction.

Secondary structure plays an important role in determining the function of noncoding RNAs. Hence, id...

Generation of Chow Parameters and Reduced Variables Through Nearest Neighbor Relations in Threshold Networks.

Generation of useful variables and features is an important issue throughout the machine learning, a...

Predicting base editing outcomes with an attention-based deep learning algorithm trained on high-throughput target library screens.

Base editors are chimeric ribonucleoprotein complexes consisting of a DNA-targeting CRISPR-Cas modul...

Assigning function to SNPs: Considerations when interpreting genetic variation.

Assigning function to single nucleotide polymorphisms (SNPs) to understand the mechanisms that link ...

Transcorneal delivery of topically applied silver nanoparticles does not delay epithelial wound healing.

Silver nanoparticles (AgNPs) are a common antimicrobial additive for a variety of applications, incl...

EMONAS-Net: Efficient multiobjective neural architecture search using surrogate-assisted evolutionary algorithm for 3D medical image segmentation.

Deep learning plays a critical role in medical image segmentation. Nevertheless, manually designing ...

Refined UNet v3: Efficient end-to-end patch-wise network for cloud and shadow segmentation with multi-channel spectral features.

Semantic segmentation is one of the essential prerequisites for computer vision tasks, but edge-prec...

Machine Learning Approach to Analyze the Surface Properties of Biological Materials.

Similar to how CRISPR has revolutionized the field of molecular biology, machine learning may drasti...

Informed training set design enables efficient machine learning-assisted directed protein evolution.

Directed evolution of proteins often involves a greedy optimization in which the mutation in the hig...

A machine learning approach to identify predictive molecular markers for cisplatin chemosensitivity following surgical resection in ovarian cancer.

Ovarian cancer is associated with poor prognosis. Platinum resistance contributes significantly to t...

Easy-Prime: a machine learning-based prime editor design tool.

Prime editing is a revolutionary genome-editing technology that can make a wide range of precise edi...

Cancer-associated fibroblasts are associated with poor prognosis in solid type of lung adenocarcinoma in a machine learning analysis.

Cancer-associated fibroblasts (CAFs) participate in critical processes in the tumor microenvironment...

Optimization and Simulation of Manuscript Management System Based on Fuzzy Genetic Neural Network.

Manuscript management plays an important role in the whole periodical industry. Journals and magazin...

Identification of biomarkers for acute leukemia via machine learning-based stemness index.

Traditional methods to understand leukemia stem cell (LSC)'s biological characteristics include cons...

Comparative analysis of machine learning approaches to classify tumor mutation burden in lung adenocarcinoma using histopathology images.

Both histologic subtypes and tumor mutation burden (TMB) represent important biomarkers in lung canc...

Chromatin interaction neural network (ChINN): a machine learning-based method for predicting chromatin interactions from DNA sequences.

Chromatin interactions play important roles in regulating gene expression. However, the availability...

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