AIMC Topic: Mutation

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Deep learning predicts epidermal growth factor receptor mutation subtypes in lung adenocarcinoma.

Medical physics Nov 7, 2021
PURPOSE: This study aimed to explore the predictive ability of deep learning (DL) for the common epidermal growth factor receptor (EGFR) mutation subtypes in patients with lung adenocarcinoma.
Lung Neoplasms Mutation ErbB Receptors Adenocarcinoma of Lung Humans Retrospective Studies Deep Learning
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The viral expression and immune status in human cancers and insights into novel biomarkers of immunotherapy.

BMC cancer Nov 5, 2021
BACKGROUND: Viral infections are prevalent in human cancers and they have great diagnostic and theranostic values in clinical practice. Recently, their potential of shaping the tumor immune microenvironment (TIME) has been related to the immunotherap...
Mutation Leukocytes Genetic Variation DNA, Viral Epstein-Barr Virus Infections Herpesvirus 4, Human Kaplan-Meier Estimate Papillomaviridae Oncogenic Viruses High-Throughput Nucleotide Sequencing Genome, Viral Tumor Virus Infections Transcriptome RNA-Seq Immunotherapy Head and Neck Neoplasms Support Vector Machine Papillomavirus Infections Squamous Cell Carcinoma of Head and Neck Tumor Microenvironment Biomarkers, Tumor Neoplasms Humans Machine Learning Stomach Neoplasms
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Deep learning is widely applicable to phenotyping embryonic development and disease.

Development (Cambridge, England) Nov 5, 2021
Genome editing simplifies the generation of new animal models for congenital disorders. However, the detailed and unbiased phenotypic assessment of altered embryonic development remains a challenge. Here, we explore how deep learning (U-Net) can auto...
Neural Networks, Computer Xenopus Proteins Mutation Microscopy Embryonic Development Image Processing, Computer-Assisted Polycystic Kidney Diseases Mice Craniofacial Abnormalities Disease Models, Animal Phenotype Neurodevelopmental Disorders Animals Xenopus laevis Deep Learning
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Correspondence between neuroevolution and gradient descent.

Nature communications Nov 2, 2021
We show analytically that training a neural network by conditioned stochastic mutation or neuroevolution of its weights is equivalent, in the limit of small mutations, to gradient descent on the loss function in the presence of Gaussian white noise. ...
Computer Simulation Mutation Stochastic Processes Neural Networks, Computer Algorithms
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Deep Learning and Pathomics Analyses Reveal Cell Nuclei as Important Features for Mutation Prediction of BRAF-Mutated Melanomas.

The Journal of investigative dermatology Oct 30, 2021
Image-based analysis as a method for mutation detection can be advantageous in settings when tumor tissue is limited or unavailable for direct testing. In this study, we utilize two distinct and complementary machine-learning methods of analyzing who...
Humans Melanoma Cell Nucleus Proto-Oncogene Proteins B-raf Deep Learning Mutation
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Prediction of genetic alteration of phospholipase C isozymes in brain disorders: Studies with deep learning.

Advances in biological regulation Oct 29, 2021
Genetic mutations leading to the development of various diseases, such as cancer, diabetes, and neurodegenerative disorders, can be attributed to multiple mechanisms and exposure to diverse environments. These disorders further increase gene mutation...
Phosphoinositide Phospholipase C Mutation Brain Diseases Isoenzymes Humans Deep Learning
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Development and validation of a weakly supervised deep learning framework to predict the status of molecular pathways and key mutations in colorectal cancer from routine histology images: a retrospective study.

The Lancet. Digital health Oct 19, 2021
BACKGROUND: Determining the status of molecular pathways and key mutations in colorectal cancer is crucial for optimal therapeutic decision making. We therefore aimed to develop a novel deep learning pipeline to predict the status of key molecular pa...
Deep Learning ROC Curve Area Under Curve Rectum Microsatellite Instability Colorectal Neoplasms Humans Histological Techniques Mutation Biomarkers, Tumor Phenotype Colon Retrospective Studies
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Automatic Film Label Acquisition Method Based on Improved Neural Networks Optimized by Mutation Ant Colony Algorithm.

Computational intelligence and neuroscience Oct 11, 2021
Nowadays, with the constant change of public aesthetic standards, a large number of new types and themes of film programs have emerged. For this reason, this paper proposes an improved neural network optimized by mutation ant colony algorithm for aut...
Neural Networks, Computer Motion Pictures Algorithms Mutation
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ECNet is an evolutionary context-integrated deep learning framework for protein engineering.

Nature communications Sep 30, 2021
Machine learning has been increasingly used for protein engineering. However, because the general sequence contexts they capture are not specific to the protein being engineered, the accuracy of existing machine learning algorithms is rather limited....
beta-Lactam Resistance Genetic Fitness Mutation Amino Acid Sequence Deep Learning High-Throughput Screening Assays Protein Engineering beta-Lactamases Evolution, Molecular Datasets as Topic Sequence Homology, Amino Acid
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AI for the collective analysis of a massive number of genome sequences: various examples from the small genome of pandemic SARS-CoV-2 to the human genome.

Genes & genetic systems Sep 27, 2021
In genetics and related fields, huge amounts of data, such as genome sequences, are accumulating, and the use of artificial intelligence (AI) suitable for big data analysis has become increasingly important. Unsupervised AI that can reveal novel know...
Codon Usage Artificial Intelligence SARS-CoV-2 Time Factors Humans Metagenomics Computational Biology Genome, Viral Genome, Human Cluster Analysis RNA, Transfer Mutation
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