AIMC Topic: Mutation

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Computational studies of anaplastic lymphoma kinase mutations reveal common mechanisms of oncogenic activation.

Proceedings of the National Academy of Sciences of the United States of America Mar 9, 2021
Kinases play important roles in diverse cellular processes, including signaling, differentiation, proliferation, and metabolism. They are frequently mutated in cancer and are the targets of a large number of specific inhibitors. Surveys of cancer gen...
Molecular Dynamics Simulation Enzyme Activation Anaplastic Lymphoma Kinase Protein Conformation, alpha-Helical Machine Learning Mutation Humans
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An explainable machine learning platform for pyrazinamide resistance prediction and genetic feature identification of Mycobacterium tuberculosis.

Journal of the American Medical Informatics Association : JAMIA Mar 1, 2021
OBJECTIVE: Tuberculosis is the leading cause of death from a single infectious agent. The emergence of antimicrobial resistant Mycobacterium tuberculosis strains makes the problem more severe. Pyrazinamide (PZA) is an important component for short-co...
Drug Resistance, Bacterial Humans Microbial Sensitivity Tests Support Vector Machine Neural Networks, Computer Mycobacterium tuberculosis Tuberculosis Mutation Machine Learning Pyrazinamide Antitubercular Agents
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IDH glioma radiogenomics in the era of deep learning.

Neuro-oncology Feb 25, 2021
Mutation Isocitrate Dehydrogenase Deep Learning Glioma Humans
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Fully automated hybrid approach to predict the IDH mutation status of gliomas via deep learning and radiomics.

Neuro-oncology Feb 25, 2021
BACKGROUND: Glioma prognosis depends on isocitrate dehydrogenase (IDH) mutation status. We aimed to predict the IDH status of gliomas from preoperative MR images using a fully automated hybrid approach with convolutional neural networks (CNNs) and ra...
Humans Deep Learning Glioma Magnetic Resonance Imaging Retrospective Studies Brain Neoplasms Mutation Isocitrate Dehydrogenase
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On the critical review of five machine learning-based algorithms for predicting protein stability changes upon mutation.

Briefings in bioinformatics Jan 18, 2021
A review, recently published in this journal by Fang (2019), showed that methods trained for the prediction of protein stability changes upon mutation have a very critical bias: they neglect that a protein variation (A- > B) and its reverse (B- > A) ...
Machine Learning Algorithms Protein Stability Mutation
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Human and artificial intelligence to illuminate MDS.

Blood Nov 12, 2020
Humans Mutation Artificial Intelligence Myelodysplastic Syndromes Machine Learning
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Machine learning demonstrates that somatic mutations imprint invariant morphologic features in myelodysplastic syndromes.

Blood Nov 12, 2020
Morphologic interpretation is the standard in diagnosing myelodysplastic syndrome (MDS), but it has limitations, such as varying reliability in pathologic evaluation and lack of integration with genetic data. Somatic events shape morphologic features...
Machine Learning Mutation Female Myelodysplastic Syndromes Adult Middle Aged Male Humans Genetic Association Studies Aged
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[Prevalence of transmitted drug resistance in HIV-infected treatment-naive patients in Chile].

Revista medica de Chile Nov 1, 2020
BACKGROUND: Transmitted drug resistance (TDR) occurs in patients with HIV infection who are not exposed to antiretroviral drugs but who are infected with a virus with mutations associated with resistance.
Prevalence Drug Resistance, Viral HIV Infections Mutation Humans Aged Genotype Anti-HIV Agents HIV-1 Female Male Chile
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Prediction of clinically actionable genetic alterations from colorectal cancer histopathology images using deep learning.

World journal of gastroenterology Oct 28, 2020
BACKGROUND: Identifying genetic mutations in cancer patients have been increasingly important because distinctive mutational patterns can be very informative to determine the optimal therapeutic strategy. Recent studies have shown that deep learning-...
Deep Learning Mutation Genes, p53 Colonic Neoplasms Humans Colorectal Neoplasms
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Prediction of survival rate and effect of drugs on cancer patients with somatic mutations of genes: An AI-based approach.

Chemical biology & drug design Sep 1, 2020
The causal role of somatic mutation and its interrelationship with gene expression profile during tumor development has already been observed, which plays a major role to decide the cancer grades and overall survival. Accurate and robust prediction o...
Polymorphism, Single Nucleotide Mutation Humans Machine Learning Antineoplastic Agents Transcriptome Survival Rate Cohort Studies Neoplasms
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