AIMC Topic: Transcriptome

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Drug Repurposing Prediction for Immune-Mediated Cutaneous Diseases using a Word-Embedding-Based Machine Learning Approach.

The Journal of investigative dermatology Oct 17, 2018
Immune-mediated diseases affect more than 20% of the population, and many autoimmune diseases affect the skin. Drug repurposing (or repositioning) is a cost-effective approach for finding drugs that can be used to treat diseases for which they are cu...
Algorithms Transcriptome Cohort Studies Humans Machine Learning Skin Skin Diseases PubMed Immune System Diseases ROC Curve Computational Biology Drug Repositioning
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Deep learning-based transcriptome data classification for drug-target interaction prediction.

BMC genomics Sep 24, 2018
BACKGROUND: The ability to predict the interaction of drugs with target proteins is essential to research and development of drug. However, the traditional experimental paradigm is costly, and previous in silico prediction paradigms have been impeded...
Algorithms Databases, Factual Computer Simulation Humans Machine Learning Models, Theoretical Proteins Drug Interactions Drug Discovery Gene Expression Profiling Transcriptome Molecular Targeted Therapy
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Universal method for robust detection of circadian state from gene expression.

Proceedings of the National Academy of Sciences of the United States of America Sep 10, 2018
Circadian clocks play a key role in regulating a vast array of biological processes, with significant implications for human health. Accurate assessment of physiological time using transcriptional biomarkers found in human blood can significantly imp...
Genes Biomarkers Transcriptome Circadian Rhythm Humans Models, Statistical Reproducibility of Results Sleep Machine Learning Gene Expression Gene Expression Profiling Circadian Clocks
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Classification of lung adenocarcinoma transcriptome subtypes from pathological images using deep convolutional networks.

International journal of computer assisted radiology and surgery Aug 29, 2018
PURPOSE: Convolutional neural networks have become rapidly popular for image recognition and image analysis because of its powerful potential. In this paper, we developed a method for classifying subtypes of lung adenocarcinoma from pathological imag...
Humans Neural Networks, Computer Transcriptome Image Processing, Computer-Assisted Adenocarcinoma of Lung Biopsy
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MCRiceRepGP: a framework for the identification of genes associated with sexual reproduction in rice.

The Plant journal : for cell and molecular biology Aug 16, 2018
Rice is an important cereal crop, being a staple food for over half of the world's population, and sexual reproduction resulting in grain formation underpins global food security. However, despite considerable research efforts, many of the genes, esp...
Genes, Plant Machine Learning Transcriptome Genome-Wide Association Study Oryza Reproduction Genome, Plant
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Integration of Gene Expression Profile Data to Screen and Verify Hub Genes Involved in Osteoarthritis.

BioMed research international Aug 14, 2018
Osteoarthritis (OA) is one of the most common diseases worldwide, but the pathogenic genes and pathways are largely unclear. The aim of this study was to screen and verify hub genes involved in OA and explore potential molecular mechanisms. The expre...
Osteoarthritis China Humans Gene Regulatory Networks Gene Ontology Gene Expression Profiling Computational Biology Transcriptome
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Machine Learning Based Toxicity Prediction: From Chemical Structural Description to Transcriptome Analysis.

International journal of molecular sciences Aug 10, 2018
Toxicity prediction is very important to public health. Among its many applications, toxicity prediction is essential to reduce the cost and labor of a drug's preclinical and clinical trials, because a lot of drug evaluations (cellular, animal, and c...
Gene Expression Profiling Transcriptome Natural Language Processing Humans Machine Learning Animals
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Deep Neural Networks for In Situ Hybridization Grid Completion and Clustering.

IEEE/ACM transactions on computational biology and bioinformatics Aug 7, 2018
Transcriptome in brain plays a crucial role in understanding the cortical organization and the development of brain structure and function. Two challenges, incomplete data and high dimensionality of transcriptome, remain unsolved. Here, we present a ...
Image Processing, Computer-Assisted Mice Computational Biology Cluster Analysis Animals Atlases as Topic Neural Networks, Computer Gene Expression Profiling Brain In Situ Hybridization Transcriptome
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Machine learning models to predict the progression from early to late stages of papillary renal cell carcinoma.

Computers in biology and medicine Jun 28, 2018
Papillary Renal Cell Carcinoma (PRCC) is a heterogeneous disease with variations in disease progression and clinical outcomes. The advent of next generation sequencing techniques (NGS) has generated data from patients that can be analysed to develop ...
Carcinoma, Renal Cell Female Male Disease Progression Predictive Value of Tests Transcriptome Humans Models, Biological Sequence Analysis, RNA Machine Learning Kidney Neoplasms Gene Expression Regulation, Neoplastic
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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...
Humans Neoplasms Models, Genetic Protein Kinase Inhibitors Machine Learning Drug Resistance, Neoplasm Algorithms Transcriptome Reproducibility of Results ErbB Receptors Cell Line, Tumor
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