AIMC Topic: Mutation

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The Performance of Machine Learning for Prediction of H3K27 M Mutation in Midline Gliomas: A Systematic Review and Meta-Analysis.

World neurosurgery Nov 22, 2023
BACKGROUND: Diffuse midline gliomas (DMGs) encompass a set of tumors, and those tumors with H3K27 M mutation carry a poor prognosis. In recent years, machine learning (ML)-based radiomics have shown promising results in predicting gene mutation statu...
Histones Magnetic Resonance Imaging Mutation Humans Brain Neoplasms Glioma Machine Learning
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Deep learning precipitation prediction models combined with feature analysis.

Environmental science and pollution research international Nov 14, 2023
Precise rainfall forecasting modeling assumes a pivotal role in water resource planning and management. Conducting a comprehensive analysis of the rainfall time series and making appropriate adjustments to the forecast model settings based on the cha...
Forecasting China Mutation Meteorology Computer Simulation Deep Learning
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Predicting multiple conformations via sequence clustering and AlphaFold2.

Nature Nov 13, 2023
AlphaFold2 (ref. ) has revolutionized structural biology by accurately predicting single structures of proteins. However, a protein's biological function often depends on multiple conformational substates, and disease-causing point mutations often ca...
Mutation Proteins Protein Conformation Sequence Alignment Bacterial Proteins Protein Folding Rhodobacter sphaeroides Machine Learning Cluster Analysis
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The impact of misclassification errors on the performance of biomarkers based on next-generation sequencing, a simulation study.

Journal of biopharmaceutical statistics Oct 11, 2023
The development of next-generation sequencing (NGS) opens opportunities for new applications such as liquid biopsy, in which tumor mutation genotypes can be determined by sequencing circulating tumor DNA after blood draws. However, with highly dilute...
Computer Simulation Biomarkers, Tumor Mutation High-Throughput Nucleotide Sequencing Liquid Biopsy Genotype Machine Learning Humans Circulating Tumor DNA Algorithms
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Reliable interpretability of biology-inspired deep neural networks.

NPJ systems biology and applications Oct 10, 2023
Deep neural networks display impressive performance but suffer from limited interpretability. Biology-inspired deep learning, where the architecture of the computational graph is based on biological knowledge, enables unique interpretability where re...
Transcriptome Mutation Models, Biological Humans Neural Networks, Computer
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Patient Graph Deep Learning to Predict Breast Cancer Molecular Subtype.

IEEE/ACM transactions on computational biology and bioinformatics Oct 10, 2023
Breast cancer is a heterogeneous disease consisting of a diverse set of genomic mutations and clinical characteristics. The molecular subtypes of breast cancer are closely tied to prognosis and therapeutic treatment options. We investigate using deep...
Breast Deep Learning Mutation Female Breast Neoplasms Humans Neural Networks, Computer
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Embryonic cranial cartilage defects in the Fgfr3 mouse model of achondroplasia.

Anatomical record (Hoboken, N.J. : 2007) Sep 25, 2023
Achondroplasia, the most common chondrodysplasia in humans, is caused by one of two gain of function mutations localized in the transmembrane domain of fibroblast growth factor receptor 3 (FGFR3) leading to constitutive activation of FGFR3 and subseq...
Disease Models, Animal Receptor, Fibroblast Growth Factor, Type 3 Animals Mice Skull X-Ray Microtomography Achondroplasia Mutation Cartilage
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Tumor Mutation Burden-Related Histopathologic Features for Predicting Overall Survival in Gliomas Using Graph Deep Learning.

The American journal of pathology Sep 21, 2023
Tumor mutation burden (TMB) is a potential biomarker for evaluating the prognosis and response to immune checkpoint inhibitors, but its costly and time-consuming method of measurement limits its widespread application. This study aimed to identify th...
Humans Prognosis Cell Division Glioma Biomarkers, Tumor Mutation Deep Learning Cell Cycle
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NN-RNALoc: Neural network-based model for prediction of mRNA sub-cellular localization using distance-based sub-sequence profiles.

PloS one Sep 14, 2023
The localization of messenger RNAs (mRNAs) is a frequently observed phenomenon and a crucial aspect of gene expression regulation. It is also a mechanism for targeting proteins to a specific cellular region. Moreover, prior research and studies have ...
Benchmarking RNA, Messenger Mutation Neural Networks, Computer Software
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ProS-GNN: Predicting effects of mutations on protein stability using graph neural networks.

Computational biology and chemistry Aug 26, 2023
Predicting protein stability change upon variation through a computational approach is a valuable tool to unveil the mechanisms of mutation-induced drug failure and develop immunotherapy strategies. Some previous machine learning-based techniques exh...
Mutation Neural Networks, Computer Protein Stability Machine Learning Immunotherapy
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