AIMC Topic: Mutation

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Multi omics analysis of mitophagy subtypes and integration of machine learning for predicting immunotherapy responses in head and neck squamous cell carcinoma.

Aging Jun 21, 2024
Mitophagy serves as a critical mechanism for tumor cell death, significantly impacting the progression of tumors and their treatment approaches. There are significant challenges in treating patients with head and neck squamous cell carcinoma, undersc...
Mutation Mitophagy Squamous Cell Carcinoma of Head and Neck Head and Neck Neoplasms DNA Copy Number Variations Humans Machine Learning Multiomics Gene Expression Regulation, Neoplastic Prognosis Immunotherapy
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Improving the Detection of Potential Cases of Familial Hypercholesterolemia: Could Machine Learning Be Part of the Solution?

Journal of the American Heart Association Jun 15, 2024
BACKGROUND: Familial hypercholesterolemia (FH), while highly prevalent, is a significantly underdiagnosed monogenic disorder. Improved detection could reduce the large number of cardiovascular events attributable to poor case finding. We aimed to ass...
Humans Machine Learning Middle Aged Genetic Predisposition to Disease Predictive Value of Tests Mutation Female Adult Male Genetic Testing Exome Sequencing Apolipoprotein B-100 Hyperlipoproteinemia Type II Proprotein Convertase 9 United Kingdom Receptors, LDL
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A Machine Learning Approach to Identify Key Residues Involved in Protein-Protein Interactions Exemplified with SARS-CoV-2 Variants.

International journal of molecular sciences Jun 13, 2024
Human infection with the coronavirus disease 2019 (COVID-19) is mediated by the binding of the spike protein of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) to the human angiotensin-converting enzyme 2 (ACE2). The frequent mutatio...
Protein Interaction Domains and Motifs Molecular Dynamics Simulation Angiotensin-Converting Enzyme 2 Binding Sites Protein Binding Spike Glycoprotein, Coronavirus Mutation COVID-19 SARS-CoV-2 Humans Machine Learning
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Prediction of Epidermal Growth Factor Receptor Mutation Subtypes in Non-Small Cell Lung Cancer From Hematoxylin and Eosin-Stained Slides Using Deep Learning.

Laboratory investigation; a journal of technical methods and pathology Jun 11, 2024
Accurate assessment of epidermal growth factor receptor (EGFR) mutation status and subtype is critical for the treatment of non-small cell lung cancer patients. Conventional molecular testing methods for detecting EGFR mutations have limitations. In ...
Eosine Yellowish-(YS) Hematoxylin Carcinoma, Non-Small-Cell Lung Mutation ErbB Receptors Humans Female Aged Male Deep Learning Middle Aged Lung Neoplasms
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GMILT: A Novel Transformer Network That Can Noninvasively Predict EGFR Mutation Status.

IEEE transactions on neural networks and learning systems Jun 3, 2024
Noninvasively and accurately predicting the epidermal growth factor receptor (EGFR) mutation status is a clinically vital problem. Moreover, further identifying the most suspicious area related to the EGFR mutation status can guide the biopsy to avoi...
Humans Neural Networks, Computer Deep Learning Lung Neoplasms Mutation Tomography, X-Ray Computed ErbB Receptors Female Male
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Interpretable deep learning reveals the role of an E-box motif in suppressing somatic hypermutation of AGCT motifs within human immunoglobulin variable regions.

Frontiers in immunology May 28, 2024
INTRODUCTION: Somatic hypermutation (SHM) of immunoglobulin variable (V) regions by activation induced deaminase (AID) is essential for robust, long-term humoral immunity against pathogen and vaccine antigens. AID mutates cytosines preferentially wit...
Cytidine Deaminase Nucleotide Motifs Somatic Hypermutation, Immunoglobulin Humans Amino Acid Motifs AICDA (Activation-Induced Cytidine Deaminase) Deep Learning Immunoglobulin Variable Region Mutation
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Advancing automatic text summarization: Unleashing enhanced binary multi-objective grey wolf optimization with mutation.

PloS one May 24, 2024
Automatic Text Summarization (ATS) is gaining popularity as there is a growing demand for a system capable of processing extensive textual content and delivering a concise, yet meaningful, relevant, and useful summary. Manual summarization is both ex...
Humans Natural Language Processing Algorithms Mutation
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Respiratory Syncytial Virus Vaccine Design Using Structure-Based Machine-Learning Models.

Viruses May 22, 2024
When designing live-attenuated respiratory syncytial virus (RSV) vaccine candidates, attenuating mutations can be developed through biologic selection or reverse-genetic manipulation and may include point mutations, codon and gene deletions, and geno...
Mutation Respiratory Syncytial Virus Vaccines Virus Replication Respiratory Syncytial Virus Infections Amino Acid Substitution Respiratory Syncytial Virus, Human Humans Vaccines, Attenuated Viral Nonstructural Proteins Machine Learning Cell Line
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Machine learning and radiomics analysis by computed tomography in colorectal liver metastases patients for RAS mutational status prediction.

La Radiologia medica May 18, 2024
PURPOSE: To assess the efficacy of machine learning and radiomics analysis by computed tomography (CT) in presurgical setting, to predict RAS mutational status in colorectal liver metastases.
Colorectal Neoplasms Radiomics Male Predictive Value of Tests Humans Aged Mutation Middle Aged Machine Learning Tomography, X-Ray Computed Aged, 80 and over Liver Neoplasms Adult Retrospective Studies Female Sensitivity and Specificity Reproducibility of Results
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Machine learning analysis of gene expression reveals TP53 Mutant-like AML with wild type TP53 and poor prognosis.

Blood cancer journal May 14, 2024
Mutation Tumor Suppressor Protein p53 Gene Expression Regulation, Leukemic Female Humans Leukemia, Myeloid, Acute Male Machine Learning Middle Aged Prognosis
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