AIMC Topic: Mutation

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Cancer classification and pathway discovery using non-negative matrix factorization.

Journal of biomedical informatics Jul 2, 2019
OBJECTIVES: Extracting genetic information from a full range of sequencing data is important for understanding disease. We propose a novel method to effectively explore the landscape of genetic mutations and aggregate them to predict cancer type.
Reproducibility of Results Neoplasms Diagnosis, Computer-Assisted Pilot Projects Humans Algorithms Sequence Analysis, DNA Regression Analysis Mutation Exome Cell Line, Tumor Gene Expression Regulation, Neoplastic Support Vector Machine Databases, Genetic
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Identification of a Multiplex Biomarker Panel for Hypertrophic Cardiomyopathy Using Quantitative Proteomics and Machine Learning.

Molecular & cellular proteomics : MCP Jun 26, 2019
Hypertrophic cardiomyopathy (HCM) is defined by pathological left ventricular hypertrophy (LVH). It is the commonest inherited cardiac condition and a significant number of high risk cases still go undetected until a sudden cardiac death (SCD) event....
Mutation Cardiomyopathy, Hypertrophic Hypertrophy, Left Ventricular Female Sarcomeres Case-Control Studies Aged Male Machine Learning Proteomics Young Adult Humans Middle Aged Adult Predictive Value of Tests Phenotype Peptides Prospective Studies Severity of Illness Index Biomarkers
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A Self-Consistent Sonification Method to Translate Amino Acid Sequences into Musical Compositions and Application in Protein Design Using Artificial Intelligence.

ACS nano Jun 26, 2019
We report a self-consistent method to translate amino acid sequences into audible sound, use the representation in the musical space to train a neural network, and then apply it to generate protein designs using artificial intelligence (AI). The soni...
Protein Folding Humans Artificial Intelligence Proteins Models, Molecular Mutation Amino Acid Sequence Sound Protein Conformation
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Analysis of the Deleterious Single Nucleotide Polymorphisms Impact on Estrogen Receptor Alpha-p53 Interaction: A Machine Learning Approach.

International journal of molecular sciences Jun 18, 2019
Breast cancer is a leading cancer type and one of the major health issues faced by women around the world. Some of its major risk factors include body mass index, hormone replacement therapy, family history and germline mutations. Of these risk facto...
Machine Learning Molecular Docking Simulation Protein Binding Polymorphism, Single Nucleotide Humans Neural Networks, Computer Tumor Suppressor Protein p53 Protein Conformation Estrogen Receptor alpha Protein Interaction Domains and Motifs Computational Biology Structure-Activity Relationship Mutation Molecular Dynamics Simulation
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Detection of the BRAF V600E Mutation in Colorectal Cancer by NIR Spectroscopy in Conjunction with Counter Propagation Artificial Neural Network.

Molecules (Basel, Switzerland) Jun 15, 2019
This paper proposes a sensitive, sample preparation-free, rapid, and low-cost method for the detection of the B-rapidly accelerated fibrosarcoma (BRAF) gene mutation involving a substitution of valine to glutamic acid at codon 600 (V600E) in colorect...
Humans Neural Networks, Computer Reproducibility of Results Colorectal Neoplasms Amino Acid Substitution Spectroscopy, Near-Infrared Proto-Oncogene Proteins B-raf Mutation Alleles DNA Mutational Analysis
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Prediction of Enzyme Function Based on Three Parallel Deep CNN and Amino Acid Mutation.

International journal of molecular sciences Jun 11, 2019
During the past decade, due to the number of proteins in PDB database being increased gradually, traditional methods cannot better understand the function of newly discovered enzymes in chemical reactions. Computational models and protein feature rep...
Humans Neural Networks, Computer Animals Databases, Protein Mutation Amino Acid Sequence Enzymes
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Whole-genome deep-learning analysis identifies contribution of noncoding mutations to autism risk.

Nature genetics May 27, 2019
We address the challenge of detecting the contribution of noncoding mutations to disease with a deep-learning-based framework that predicts the specific regulatory effects and the deleterious impact of genetic variants. Applying this framework to 1,7...
RNA, Untranslated Genes, Reporter RNA Processing, Post-Transcriptional Autism Spectrum Disorder Alleles Deep Learning Genetic Association Studies Humans Gene Expression Regulation Genomics Computational Biology Algorithms Genome, Human Genetic Predisposition to Disease Gene Expression Phenotype Transcription, Genetic Mutation
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Level of neo-epitope predecessor and mutation type determine T cell activation of MHC binding peptides.

Journal for immunotherapy of cancer May 22, 2019
BACKGROUND: Targeting epitopes derived from neo-antigens (or "neo-epitopes") represents a promising immunotherapy approach with limited off-target effects. However, most peptides predicted using MHC binding prediction algorithms do not induce a CD8 +...
Humans Machine Learning Protein Binding Epitopes, T-Lymphocyte Immunotherapy Lymphocyte Activation Mutation Oligopeptides
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Real-time analysis of the behaviour of groups of mice via a depth-sensing camera and machine learning.

Nature biomedical engineering May 20, 2019
Preclinical studies of psychiatric disorders use animal models to investigate the impact of environmental factors or genetic mutations on complex traits such as decision-making and social interactions. Here, we introduce a method for the real-time an...
Autistic Disorder Machine Learning Behavior, Animal Phenotype Microfilament Proteins Male Behavioral Research Nerve Tissue Proteins Mice Social Behavior Disease Models, Animal Mice, Knockout Mutation Video Recording Female Animals
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NeoMutate: an ensemble machine learning framework for the prediction of somatic mutations in cancer.

BMC medical genomics May 16, 2019
BACKGROUND: The accurate screening of tumor genomic landscapes for somatic mutations using high-throughput sequencing involves a crucial step in precise clinical diagnosis and targeted therapy. However, the complex inherent features of cancer tissue,...
Neoplasms Genomics Mutation Workflow Supervised Machine Learning High-Throughput Nucleotide Sequencing
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