AIMC Topic: Genes, Neoplasm

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Wx: a neural network-based feature selection algorithm for transcriptomic data.

Scientific reports Jul 19, 2019
Next-generation sequencing (NGS), which allows the simultaneous sequencing of billions of DNA fragments simultaneously, has revolutionized how we study genomics and molecular biology by generating genome-wide molecular maps of molecules of interest. ...
Neural Networks, Computer Algorithms Biomarkers, Tumor High-Throughput Nucleotide Sequencing RNA, Neoplasm Humans Datasets as Topic Genes, Neoplasm Neoplasms Gene Expression Profiling Transcriptome
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Method for Identifying Cancer-Related Genes Using Gene Similarity-Based Collaborative Filtering.

Journal of computational biology : a journal of computational molecular cell biology May 22, 2019
Models, Genetic Genes, Neoplasm Humans Machine Learning Biomarkers, Tumor Female RNA-Seq Breast Neoplasms
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Capsule Network Based Modeling of Multi-omics Data for Discovery of Breast Cancer-Related Genes.

IEEE/ACM transactions on computational biology and bioinformatics Apr 9, 2019
Breast cancer is one of the most common cancers all over the world, which bring about more than 450,000 deaths each year. Although this malignancy has been extensively studied by a large number of researchers, its prognosis is still poor. Since thera...
Humans Prognosis Female Breast Neoplasms Genes, Neoplasm Computational Biology DNA Methylation DNA Copy Number Variations Biomarkers, Tumor Transcriptome Deep Learning
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Predicting drug-target interaction network using deep learning model.

Computational biology and chemistry Mar 25, 2019
BACKGROUND: Traditional methods for drug discovery are time-consuming and expensive, so efforts are being made to repurpose existing drugs. To find new ways for drug repurposing, many computational approaches have been proposed to predict drug-target...
Amino Acid Sequence Databases, Chemical Genes, Neoplasm Molecular Structure Models, Chemical Protein Domains Proteins Databases, Protein Drug Repositioning Breast Neoplasms Computational Biology Antineoplastic Agents Deep Learning Support Vector Machine Protein Binding
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Deep convolutional neural networks for accurate somatic mutation detection.

Nature communications Mar 4, 2019
Accurate detection of somatic mutations is still a challenge in cancer analysis. Here we present NeuSomatic, the first convolutional neural network approach for somatic mutation detection, which significantly outperforms previous methods on different...
Mutation DNA Mutational Analysis Sequence Alignment Computational Biology Databases, Genetic Sequence Analysis, DNA Genes, Neoplasm Exome Diploidy Machine Learning Neoplasms Humans Neural Networks, Computer
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A novel gene selection algorithm for cancer classification using microarray datasets.

BMC medical genomics Jan 15, 2019
BACKGROUND: Microarray datasets are an important medical diagnostic tool as they represent the states of a cell at the molecular level. Available microarray datasets for classifying cancer types generally have a fairly small sample size compared to t...
Genes, Neoplasm Support Vector Machine Neoplasms Mutation Gene Expression Profiling Oligonucleotide Array Sequence Analysis Computational Biology
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CamurWeb: a classification software and a large knowledge base for gene expression data of cancer.

BMC bioinformatics Oct 15, 2018
BACKGROUND: The high growth of Next Generation Sequencing data currently demands new knowledge extraction methods. In particular, the RNA sequencing gene expression experimental technique stands out for case-control studies on cancer, which can be ad...
Base Sequence Genome, Human Genes, Neoplasm Humans Gene Expression Regulation, Neoplastic Neoplasms Software Knowledge Bases Sequence Analysis, RNA
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PBMDR: A particle swarm optimization-based multifactor dimensionality reduction for the detection of multilocus interactions.

Journal of theoretical biology Oct 5, 2018
Studies on multilocus interactions have mainly investigated the associations between genetic variations from the related genes and histopathological tumor characteristics in patients. However, currently, the identification and characterization of sus...
Breast Neoplasms Genetic Predisposition to Disease Polymorphism, Single Nucleotide Multifactor Dimensionality Reduction Genes, Neoplasm Humans Genotype Algorithms Genetic Loci Female
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Identification of synthetic lethality based on a functional network by using machine learning algorithms.

Journal of cellular biochemistry Aug 20, 2018
Synthetic lethality is the synthesis of mutations leading to cell death. Tumor-specific synthetic lethality has been targeted in research to improve cancer therapy. With the advances of techniques in molecular biology, such as RNAi and CRISPR/Cas9 ge...
Gene Ontology Humans Genes, Neoplasm Synthetic Lethal Mutations Computational Biology HeLa Cells Machine Learning RNA Interference A549 Cells Sensitivity and Specificity Data Accuracy Neoplasms Gene Editing
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Identification of the functional alteration signatures across different cancer types with support vector machine and feature analysis.

Biochimica et biophysica acta. Molecular basis of disease Dec 19, 2017
Cancers are regarded as malignant proliferations of tumor cells present in many tissues and organs, which can severely curtail the quality of human life. The potential of using plasma DNA for cancer detection has been widely recognized, leading to th...
Genes, Neoplasm Support Vector Machine DNA, Neoplasm Humans Gene Ontology Neoplasms Gene Expression Regulation, Neoplastic
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