AIMC Topic: Cell Line, Tumor

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Drug response prediction by ensemble learning and drug-induced gene expression signatures.

Genomics Jul 6, 2018
Chemotherapeutic response of cancer cells to a given compound is one of the most fundamental information one requires to design anti-cancer drugs. Recently, considerable amount of drug-induced gene expression data has become publicly available, in ad...
Animals Cell Line, Tumor Drug Resistance, Neoplasm Antineoplastic Agents Cell Survival Gene Expression Profiling Humans Inhibitory Concentration 50 Machine Learning Software
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Machine Learning Helps Identify New Drug Mechanisms in Triple-Negative Breast Cancer.

IEEE transactions on nanobioscience Jul 2, 2018
This paper demonstrates the ability of mach- ine learning approaches to identify a few genes among the 23,398 genes of the human genome to experiment on in the laboratory to establish new drug mechanisms. As a case study, this paper uses MDA-MB-231 b...
Female Antineoplastic Agents Gene Expression Profiling Triple Negative Breast Neoplasms Single-Cell Analysis Cluster Analysis Cell Line, Tumor Unsupervised Machine Learning Humans Genomics Metformin Gene Expression Regulation, Neoplastic
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Drug Selection via Joint Push and Learning to Rank.

IEEE/ACM transactions on computational biology and bioinformatics Jun 25, 2018
Selecting the right drugs for the right patients is a primary goal of precision medicine. In this article, we consider the problem of cancer drug selection in a learning-to-rank framework. We have formulated the cancer drug selection problem as to ac...
Humans Machine Learning Algorithms Clinical Decision-Making Computational Biology Pharmaceutical Preparations Neoplasms Antineoplastic Agents Cell Line, Tumor
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Cancer Drug Response Profile scan (CDRscan): A Deep Learning Model That Predicts Drug Effectiveness from Cancer Genomic Signature.

Scientific reports Jun 11, 2018
In the era of precision medicine, cancer therapy can be tailored to an individual patient based on the genomic profile of a tumour. Despite the ever-increasing abundance of cancer genomic data, linking mutation profiles to drug efficacy remains a cha...
Drug Repositioning Databases, Pharmaceutical Precision Medicine Humans Computational Biology Deep Learning Neoplasms Computer Simulation Databases, Genetic Antineoplastic Agents Cell Line, Tumor
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Host Cell Prediction of Exosomes Using Morphological Features on Solid Surfaces Analyzed by Machine Learning.

The journal of physical chemistry. B May 31, 2018
Exosomes are extracellular nanovesicles released from any cells and found in any body fluid. Because exosomes exhibit information of their host cells (secreting cells), their analysis is expected to be a powerful tool for early diagnosis of cancers. ...
Cell Line, Tumor Support Vector Machine Principal Component Analysis Silicon Dioxide Humans Titanium Exosomes Microscopy, Atomic Force
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Machine learning identifies a core gene set predictive of acquired resistance to EGFR tyrosine kinase inhibitor.

Journal of cancer research and clinical oncology May 25, 2018
PURPOSE: Acquired resistance (AR) to epidermal growth factor receptor tyrosine kinase inhibitors (EGFR-TKIs) is a major issue worldwide, for both patients and healthcare providers. However, precise prediction is currently infeasible due to the lack o...
ErbB Receptors Protein Kinase Inhibitors Algorithms Reproducibility of Results Neoplasms Models, Genetic Drug Resistance, Neoplasm Transcriptome Cell Line, Tumor Humans Machine Learning
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Deconvolution of subcellular protrusion heterogeneity and the underlying actin regulator dynamics from live cell imaging.

Nature communications Apr 27, 2018
Cell protrusion is morphodynamically heterogeneous at the subcellular level. However, the mechanism of cell protrusion has been understood based on the ensemble average of actin regulator dynamics. Here, we establish a computational framework called ...
Humans Vasodilator-Stimulated Phosphoprotein Machine Learning Microfilament Proteins Potoroidae Phosphoproteins Pseudopodia Software Intravital Microscopy Cell Line Indoles Cell Movement Animals Cell Adhesion Molecules Models, Biological Actins Actin-Related Protein 2-3 Complex Cluster Analysis Cell Line, Tumor Actin Cytoskeleton
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ANTENNA, a Multi-Rank, Multi-Layered Recommender System for Inferring Reliable Drug-Gene-Disease Associations: Repurposing Diazoxide as a Targeted Anti-Cancer Therapy.

IEEE/ACM transactions on computational biology and bioinformatics Mar 16, 2018
Existing drug discovery processes follow a reductionist model of "one-drug-one-gene-one-disease," which is inadequate to tackle complex diseases involving multiple malfunctioned genes. The availability of big omics data offers opportunities to transf...
Cell Line, Tumor Data Mining Algorithms Machine Learning Computational Biology Diazoxide Reproducibility of Results Cell Survival Software Antineoplastic Agents Humans Drug Repositioning
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Using machine learning and quantum chemistry descriptors to predict the toxicity of ionic liquids.

Journal of hazardous materials Mar 15, 2018
Large-scale application of ionic liquids (ILs) hinges on the advancement of designable and eco-friendly nature. Research of the potential toxicity of ILs towards different organisms and trophic levels is insufficient. Quantitative structure-activity ...
Models, Theoretical Ionic Liquids Quantitative Structure-Activity Relationship Reproducibility of Results Animals Machine Learning Cell Line, Tumor Rats
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Repurposing High-Throughput Image Assays Enables Biological Activity Prediction for Drug Discovery.

Cell chemical biology Mar 1, 2018
In both academia and the pharmaceutical industry, large-scale assays for drug discovery are expensive and often impractical, particularly for the increasingly important physiologically relevant model systems that require primary cells, organoids, who...
Antineoplastic Agents Cell Line, Tumor Image Processing, Computer-Assisted Drug Repositioning High-Throughput Screening Assays Humans Neural Networks, Computer Machine Learning Neoplasms
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