AIMC Topic: Mutation

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Using deep learning to identify bladder cancers with FGFR-activating mutations from histology images.

Cancer medicine Jun 10, 2021
BACKGROUND: In recent years, the fibroblast growth factor receptor (FGFR) pathway has been proven to be an important therapeutic target in bladder cancer. FGFR-targeted therapies are effective for patients with FGFR mutation, which can be discovered ...
Gene Expression Mutation Molecular Targeted Therapy Receptor, Fibroblast Growth Factor, Type 2 Receptors, Fibroblast Growth Factor Logistic Models Lymphocytes, Tumor-Infiltrating Urinary Bladder Neoplasms Receptor, Fibroblast Growth Factor, Type 3 Sensitivity and Specificity Male Deep Learning Humans Neural Networks, Computer Databases, Factual Female
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Machine learning analyses of antibody somatic mutations predict immunoglobulin light chain toxicity.

Nature communications Jun 10, 2021
In systemic light chain amyloidosis (AL), pathogenic monoclonal immunoglobulin light chains (LC) form toxic aggregates and amyloid fibrils in target organs. Prompt diagnosis is crucial to avoid permanent organ damage, but delayed diagnosis is common ...
Gene Expression Mutation Antibodies Amino Acid Sequence Animals Recombinant Proteins Databases, Genetic Models, Molecular Caenorhabditis elegans Immunoglobulin Light Chains Immunoglobulin Light-chain Amyloidosis Humans Machine Learning Algorithms
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A deep learning approach to identify gene targets of a therapeutic for human splicing disorders.

Nature communications Jun 7, 2021
Pre-mRNA splicing is a key controller of human gene expression. Disturbances in splicing due to mutation lead to dysregulated protein expression and contribute to a substantial fraction of human disease. Several classes of splicing modulator compound...
Animals Transcriptome Deep Learning Mice Humans Mice, Transgenic Cystic Fibrosis Transmembrane Conductance Regulator RNA Splicing Exons MutL Protein Homolog 1 Gene Targeting HEK293 Cells tau Proteins Sterol Esterase Pyridazines Computational Biology Mutation Phenethylamines
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Enhancement of protein thermostability by three consecutive mutations using loop-walking method and machine learning.

Scientific reports Jun 4, 2021
We developed a method to improve protein thermostability, "loop-walking method". Three consecutive positions in 12 loops of Burkholderia cepacia lipase were subjected to random mutagenesis to make 12 libraries. Screening allowed us to identify L7 as ...
Molecular Dynamics Simulation Enzyme Stability Plasmids Lipase Escherichia coli Proteins Mutation Machine Learning Kinetics Computational Biology Hydrolases Polymerase Chain Reaction Mutagenesis, Site-Directed Molecular Conformation Protein Engineering Hot Temperature Burkholderia cepacia Mutagenesis
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Data-driven approaches to advance research and clinical care for pediatric cancer.

Biochimica et biophysica acta. Reviews on cancer May 26, 2021
Pediatric cancer is a rare disease with a distinct etiology and mutational landscape compared with adult cancer. Multi-omics profiling of retrospective and prospective cohorts coupled with innovative computational analysis have been instrumental in u...
Genetic Predisposition to Disease Biomarkers, Tumor Humans Age of Onset Neoplasms Databases, Genetic Pediatrics Mutation Transcriptome Machine Learning Medical Oncology Data Mining Genomics Precision Medicine
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Detecting adaptive introgression in human evolution using convolutional neural networks.

eLife May 25, 2021
Studies in a variety of species have shown evidence for positively selected variants introduced into a population via introgression from another, distantly related population-a process known as adaptive introgression. However, there are few explicit ...
Mutation Humans Neural Networks, Computer Gene Frequency Genotype Evolution, Molecular
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Benchmarking deep learning splice prediction tools using functional splice assays.

Human mutation May 20, 2021
Hereditary disorders are frequently caused by genetic variants that affect pre-messenger RNA splicing. Though genetic variants in the canonical splice motifs are almost always disrupting splicing, the pathogenicity of variants in the noncanonical spl...
ATP-Binding Cassette Transporters Introns RNA Splicing Humans RNA Splice Sites Deep Learning Mutation Benchmarking
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EARN: an ensemble machine learning algorithm to predict driver genes in metastatic breast cancer.

BMC medical genomics May 7, 2021
BACKGROUND: Today, there are a lot of markers on the prognosis and diagnosis of complex diseases such as primary breast cancer. However, our understanding of the drivers that influence cancer aggression is limited.
Humans Machine Learning Biomarkers, Tumor Algorithms Mutation Prognosis Neoplasm Metastasis Female Breast Neoplasms
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CopulaNet: Learning residue co-evolution directly from multiple sequence alignment for protein structure prediction.

Nature communications May 5, 2021
Residue co-evolution has become the primary principle for estimating inter-residue distances of a protein, which are crucially important for predicting protein structure. Most existing approaches adopt an indirect strategy, i.e., inferring residue co...
Humans Neural Networks, Computer Machine Learning Computational Biology Proteins Models, Molecular Mutation Caspases Sequence Alignment Protein Structure, Tertiary
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Application of machine learning to large in vitro databases to identify drug-cancer cell interactions: azithromycin and KLK6 mutation status.

Oncogene May 5, 2021
Recent advances in machine learning promise to yield novel insights by interrogation of large datasets ranging from gene expression and mutation data to CRISPR knockouts and drug screens. We combined existing and new algorithms with available experim...
Kallikreins Databases, Pharmaceutical Drug Discovery Databases, Genetic Mutation Humans Azithromycin Machine Learning Anti-Bacterial Agents Neoplasms
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