AIMC Topic: Mutation

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Predicting EGFR mutation status by a deep learning approach in patients with non-small cell lung cancer brain metastases.

Journal of neuro-oncology Feb 4, 2022
PURPOSE: Non-small cell lung cancer (NSCLC) tends to metastasize to the brain. Between 10 and 60% of NSCLCs harbor an activating mutation in the epidermal growth-factor receptor (EGFR), which may be targeted with selective EGFR inhibitors. However, d...
Humans Prospective Studies Retrospective Studies Carcinoma, Non-Small-Cell Lung Mutation ErbB Receptors Deep Learning Lung Neoplasms Brain Neoplasms
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Achieving robust somatic mutation detection with deep learning models derived from reference data sets of a cancer sample.

Genome biology Jan 7, 2022
BACKGROUND: Accurate detection of somatic mutations is challenging but critical in understanding cancer formation, progression, and treatment. We recently proposed NeuSomatic, the first deep convolutional neural network-based somatic mutation detecti...
Humans Neural Networks, Computer Genomics Mutation Neoplasms Deep Learning
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Deep Unfolding for Non-Negative Matrix Factorization with Application to Mutational Signature Analysis.

Journal of computational biology : a journal of computational molecular cell biology Jan 5, 2022
Non-negative matrix factorization (NMF) is a fundamental matrix decomposition technique that is used primarily for dimensionality reduction and is increasing in popularity in the biological domain. Although finding a unique NMF is generally not possi...
Humans Supervised Machine Learning DNA Mutational Analysis Deep Learning Computer Simulation Unsupervised Machine Learning Databases, Genetic Neural Networks, Computer Computational Biology Mutation Female Algorithms Breast Neoplasms
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Combination of liquid crystal and deep learning reveals distinct signatures of Parkinson's disease-related wild-type α-synuclein and six pathogenic mutants.

Chemistry, an Asian journal Dec 21, 2021
α-Synuclein is a central player in Parkinson's disease (PD) pathology. Various point mutations in α-synuclein have been identified to alter the protein-phospholipid binding behavior and cause PD. Therefore, exploration of α-synuclein-phospholipid int...
Liquid Crystals alpha-Synuclein Mutation Deep Learning Parkinson Disease Humans
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Clinical feature-related single-base substitution sequence signatures identified with an unsupervised machine learning approach.

BMC medical genomics Dec 20, 2021
BACKGROUND: Mutation processes leave different signatures in genes. For single-base substitutions, previous studies have suggested that mutation signatures are not only reflected in mutation bases but also in neighboring bases. However, because of th...
Mutation, Missense Cluster Analysis Unsupervised Machine Learning Mutation Humans Algorithms
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Artificial intelligence challenges for predicting the impact of mutations on protein stability.

Current opinion in structural biology Dec 15, 2021
Stability is a key ingredient of protein fitness, and its modification through targeted mutations has applications in various fields, such as protein engineering, drug design, and deleterious variant interpretation. Many studies have been devoted ove...
Artificial Intelligence Algorithms Mutation Machine Learning Protein Stability
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DNN-Boost: Somatic mutation identification of tumor-only whole-exome sequencing data using deep neural network and XGBoost.

Journal of bioinformatics and computational biology Dec 13, 2021
Detection of somatic mutation in whole-exome sequencing data can help elucidate the mechanism of tumor progression. Most computational approaches require exome sequencing for both tumor and normal samples. However, it is more common to sequence exome...
High-Throughput Nucleotide Sequencing Exome Sequencing Exome Neural Networks, Computer Neoplasms Humans Mutation
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Genome-Wide Mutation Scoring for Machine-Learning-Based Antimicrobial Resistance Prediction.

International journal of molecular sciences Dec 2, 2021
The prediction of antimicrobial resistance (AMR) based on genomic information can improve patient outcomes. Genetic mechanisms have been shown to explain AMR with accuracies in line with standard microbiology laboratory testing. To translate genetic ...
Pseudomonas aeruginosa Genome, Bacterial Anti-Infective Agents Escherichia coli Machine Learning Mutation Genomics Drug Resistance, Bacterial Whole Genome Sequencing
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Evaluation of the Association of Transferrin Receptor Type 2 Gene Mutation (Y250X) with Iron Overload in Major β- Thalassemia.

Archives of Razi Institute Nov 30, 2021
Thalassemia is an inherited blood disorder in which the body produces defective hemoglobin. One of the important processes to reduce the complication of major β-thalassemia is blood transfusion that leads to elevated ferritin levels in the blood. Man...
Thalassemia beta-Thalassemia Humans Iron Overload Mutation Receptors, Transferrin
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Machine learning of genomic features in organotropic metastases stratifies progression risk of primary tumors.

Nature communications Nov 18, 2021
Metastatic cancer is associated with poor patient prognosis but its spatiotemporal behavior remains unpredictable at early stage. Here we develop MetaNet, a computational framework that integrates clinical and sequencing data from 32,176 primary and ...
Disease Progression Humans Neoplasm Metastasis Genomics Biomarkers, Tumor Prognosis Kaplan-Meier Estimate Mutation Computational Biology Neoplasms Risk Factors Organ Specificity High-Throughput Nucleotide Sequencing Machine Learning
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