AIMC Topic: Mutation

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Machine learning integrates genomic signatures for subclassification beyond primary and secondary acute myeloid leukemia.

Blood Nov 11, 2021
Although genomic alterations drive the pathogenesis of acute myeloid leukemia (AML), traditional classifications are largely based on morphology, and prototypic genetic founder lesions define only a small proportion of AML patients. The historical su...
Humans Machine Learning Neoplasms, Second Primary Gene Expression Regulation, Leukemic Translocation, Genetic Cytogenetics Leukemia, Myeloid, Acute Genomics Bayes Theorem Mutation
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Improving feature selection performance for classification of gene expression data using Harris Hawks optimizer with variable neighborhood learning.

Briefings in bioinformatics Sep 2, 2021
Gene expression profiling has played a significant role in the identification and classification of tumor molecules. In gene expression data, only a few feature genes are closely related to tumors. It is a challenging task to select highly discrimina...
Animals Neoplasms Gene Expression Profiling Computational Biology Algorithms Databases, Factual Reproducibility of Results Internet Gene Expression Regulation, Neoplastic Models, Genetic Cluster Analysis Mutation Humans Machine Learning
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Deep embedded clustering with multiple objectives on scRNA-seq data.

Briefings in bioinformatics Sep 2, 2021
In recent years, single-cell RNA sequencing (scRNA-seq) technologies have been widely adopted to interrogate gene expression of individual cells; it brings opportunities to understand the underlying processes in a high-throughput manner. Deep embedde...
Humans Neural Networks, Computer Algorithms Mutation Gene Ontology RNA-Seq Computational Biology Models, Genetic Reproducibility of Results Cluster Analysis Gene Expression Profiling Single-Cell Analysis
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Machine learning application for patient stratification and phenotype/genotype investigation in a rare disease.

Briefings in bioinformatics Sep 2, 2021
Alkaptonuria (AKU, OMIM: 203500) is an autosomal recessive disorder caused by mutations in the Homogentisate 1,2-dioxygenase (HGD) gene. A lack of standardized data, information and methodologies to assess disease severity and progression represents ...
Alkaptonuria Homogentisate 1,2-Dioxygenase Databases, Genetic Mutation Patient Selection Humans Rare Diseases Machine Learning Precision Medicine Female Male Genotype
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Radiogenomic and Deep Learning Network Approaches to Predict Mutation from Radiotherapy Plan CT.

Anticancer research Aug 1, 2021
BACKGROUND/AIM: We aimed to investigate the role of radiogenomic and deep learning approaches in predicting the KRAS mutation status of a tumor using radiotherapy planning computed tomography (CT) images in patients with locally advanced rectal cance...
Deep Learning Genomics Mutation Rectal Neoplasms Radiotherapy Planning, Computer-Assisted Proto-Oncogene Proteins p21(ras) Aged, 80 and over Adult Male Middle Aged Humans Female Aged
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DeepSSV: detecting somatic small variants in paired tumor and normal sequencing data with convolutional neural network.

Briefings in bioinformatics Jul 20, 2021
It is of considerable interest to detect somatic mutations in paired tumor and normal sequencing data. A number of callers that are based on statistical or machine learning approaches have been developed to detect somatic small variants. However, the...
Humans Neural Networks, Computer Software Mutation High-Throughput Nucleotide Sequencing Neoplasms Genomics Sequence Analysis, DNA
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Identification of pan-cancer Ras pathway activation with deep learning.

Briefings in bioinformatics Jul 20, 2021
The identification of hidden responders is often an essential challenge in precision oncology. A recent attempt based on machine learning has been proposed for classifying aberrant pathway activity from multiomic cancer data. However, we note several...
Deep Learning Humans RNA-Seq Neoplasms Signal Transduction Mutation Neoplasm Proteins Programming Languages Gene Dosage ras Proteins
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Deep representation learning improves prediction of LacI-mediated transcriptional repression.

Proceedings of the National Academy of Sciences of the United States of America Jul 6, 2021
Recent progress in DNA synthesis and sequencing technology has enabled systematic studies of protein function at a massive scale. We explore a deep mutational scanning study that measured the transcriptional repression function of 43,669 variants of ...
Transcription, Genetic Epistasis, Genetic Reproducibility of Results Deep Learning Lac Repressors Mutation Protein Domains Escherichia coli Proteins
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Editorial: Designing a Protocol Adopting an Artificial Intelligence (AI)-Driven Approach for Early Diagnosis of Late-Onset Alzheimer's Disease.

Journal of molecular neuroscience : MN Jul 1, 2021
Memory Behavior Mental Status and Dementia Tests Late Onset Disorders Clinical Trial Protocols as Topic Ethnicity Early Diagnosis Hong Kong Medical History Taking Humans Patient Selection Asian People Artificial Intelligence Cognition Alzheimer Disease Prospective Studies Language Observational Studies as Topic Biomarkers Case-Control Studies Mutation Wearable Electronic Devices Models, Biological Mobile Applications
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A novel machine learning approach (svmSomatic) to distinguish somatic and germline mutations using next-generation sequencing data.

Zoological research Mar 18, 2021
Somatic mutations are a large category of genetic variations, which play an essential role in tumorigenesis. Detection of somatic single nucleotide variants (SNVs) could facilitate downstream analysis of tumorigenesis. Many computational methods have...
DNA Copy Number Variations Humans Mutation Animals Machine Learning High-Throughput Nucleotide Sequencing Neoplasms Algorithms Computational Biology Gene Expression Regulation, Neoplastic
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