AIMC Topic: Cell Line, Tumor

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Optimized CRISPR guide RNA design for two high-fidelity Cas9 variants by deep learning.

Nature communications Sep 19, 2019
Highly specific Cas9 nucleases derived from SpCas9 are valuable tools for genome editing, but their wide applications are hampered by a lack of knowledge governing guide RNA (gRNA) activity. Here, we perform a genome-scale screen to measure gRNA acti...
Humans Animals Deep Learning Cell Line, Tumor HEK293 Cells Base Sequence Clustered Regularly Interspaced Short Palindromic Repeats Gene Editing Mice CRISPR-Cas Systems Internet HeLa Cells RNA, Guide, CRISPR-Cas Systems Promoter Regions, Genetic Endonucleases INDEL Mutation
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Three-dimensional convolutional neural networks for simultaneous dual-tracer PET imaging.

Physics in medicine and biology Sep 19, 2019
Dual-tracer positron emission tomography (PET) is a promising technique to measure the distribution of two tracers in the body by a single scan, which can improve the clinical accuracy of disease diagnosis and can also serve as a research tool for sc...
Tomography, X-Ray Computed Humans Female Cell Line, Tumor Animals Mice, Inbred BALB C Imaging, Three-Dimensional Deep Learning Neural Networks, Computer Positron-Emission Tomography Image Processing, Computer-Assisted Algorithms Monte Carlo Method Mice Brain Neoplasm Transplantation
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Growth Inhibitory and Pro-Apoptotic Effects of Ornamental Pomegranate Extracts in Du145 Human Prostate Cancer Cells.

Nutrition and cancer Sep 5, 2019
Prostate cancer is the most common form of cancer in the male. Epidemiological studies have associated increased cancer incidence with reduced consumption of fruit and vegetables. This study was aimed to investigate the influence of dwarf pomegranat...
Pomegranate Plant Extracts Fruit Cell Proliferation Humans Apoptosis Male Prostatic Neoplasms Cell Line, Tumor
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Profiling of Exosomal Biomarkers for Accurate Cancer Identification: Combining DNA-PAINT with Machine- Learning-Based Classification.

Small (Weinheim an der Bergstrasse, Germany) Sep 3, 2019
Exosomes are endosome-derived vesicles enriched in body fluids such as urine, blood, and saliva. So far, they have been recognized as potential biomarkers for cancer diagnostics. However, the present single-variate analysis of exosomes has greatly li...
Neoplasms Humans Silicon Dioxide Cell Line, Tumor Machine Learning Exosomes Nanoparticles Biomarkers, Tumor Nanotechnology DNA
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Deep Learning Diffuse Optical Tomography.

IEEE transactions on medical imaging Aug 20, 2019
Diffuse optical tomography (DOT) has been investigated as an alternative imaging modality for breast cancer detection thanks to its excellent contrast to hemoglobin oxidization level. However, due to the complicated non-linear photon scattering physi...
Mice Mice, Inbred C57BL Neoplasms, Experimental Phantoms, Imaging Tomography, Optical Animals Deep Learning Cell Line, Tumor Image Processing, Computer-Assisted Algorithms
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Multigene signatures of responses to chemotherapy derived by biochemically-inspired machine learning.

Molecular genetics and metabolism Aug 19, 2019
Pharmacogenomic responses to chemotherapy drugs can be modeled by supervised machine learning of expression and copy number of relevant gene combinations. Such biochemical evidence can form the basis of derived gene signatures using cell line data, w...
Gene Dosage Drug Therapy Female Breast Neoplasms Gene Expression Profiling Transcriptome Cell Line, Tumor Urinary Bladder Neoplasms Humans Metabolic Networks and Pathways Supervised Machine Learning
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Network as a Biomarker: A Novel Network-Based Sparse Bayesian Machine for Pathway-Driven Drug Response Prediction.

Genes Aug 9, 2019
With the advances in different biological networks including gene regulation, gene co-expression, protein-protein interaction networks, and advanced approaches for network reconstruction, analysis, and interpretation, it is possible to discover relia...
Gene Regulatory Networks Bayes Theorem Drug Resistance, Neoplasm Humans Machine Learning Cell Line, Tumor
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Improving prediction of phenotypic drug response on cancer cell lines using deep convolutional network.

BMC bioinformatics Jul 29, 2019
BACKGROUND: Understanding the phenotypic drug response on cancer cell lines plays a vital role in anti-cancer drug discovery and re-purposing. The Genomics of Drug Sensitivity in Cancer (GDSC) database provides open data for researchers in phenotypic...
Genomics Neural Networks, Computer Regression Analysis Phenotype Inhibitory Concentration 50 Databases, Factual Humans Organ Specificity Antineoplastic Agents Neoplasms Deep Learning Cell Line, Tumor
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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.
Humans Algorithms Reproducibility of Results Neoplasms Diagnosis, Computer-Assisted Pilot Projects Cell Line, Tumor Gene Expression Regulation, Neoplastic Regression Analysis Mutation Support Vector Machine Exome Databases, Genetic Sequence Analysis, DNA
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A high-throughput screening and computation platform for identifying synthetic promoters with enhanced cell-state specificity (SPECS).

Nature communications Jun 28, 2019
Cell state-specific promoters constitute essential tools for basic research and biotechnology because they activate gene expression only under certain biological conditions. Synthetic Promoters with Enhanced Cell-State Specificity (SPECS) can be supe...
Promoter Regions, Genetic Lentivirus Cell Separation Gene Library Humans Neoplastic Stem Cells Regulatory Elements, Transcriptional Software Machine Learning Glioblastoma Induced Pluripotent Stem Cells Female Gene Expression Regulation Breast Neoplasms Organoids Cell Line, Tumor
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