AIMC Topic: Organ Specificity

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Bioimage-Based Prediction of Protein Subcellular Location in Human Tissue with Ensemble Features and Deep Networks.

IEEE/ACM transactions on computational biology and bioinformatics Dec 8, 2020
Prediction of protein subcellular location has currently become a hot topic because it has been proven to be useful for understanding both the disease mechanisms and novel drug design. With the rapid development of automated microscopic imaging techn...
Humans Algorithms Proteins Organ Specificity Intracellular Space Deep Learning Image Processing, Computer-Assisted Proteomics
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Methods for correcting inference based on outcomes predicted by machine learning.

Proceedings of the National Academy of Sciences of the United States of America Nov 18, 2020
Many modern problems in medicine and public health leverage machine-learning methods to predict outcomes based on observable covariates. In a wide array of settings, predicted outcomes are used in subsequent statistical analysis, often without accoun...
Organ Specificity Machine Learning Computer Simulation Humans Cause of Death
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lncRNAKB, a knowledgebase of tissue-specific functional annotation and trait association of long noncoding RNA.

Scientific data Oct 5, 2020
Long non-coding RNA Knowledgebase (lncRNAKB) is an integrated resource for exploring lncRNA biology in the context of tissue-specificity and disease association. A systematic integration of annotations from six independent databases resulted in 77,19...
RNA, Long Noncoding Molecular Sequence Annotation Humans Knowledge Bases Phylogeny Organ Specificity Quantitative Trait Loci
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A supervised learning framework for chromatin loop detection in genome-wide contact maps.

Nature communications Jul 9, 2020
Accurately predicting chromatin loops from genome-wide interaction matrices such as Hi-C data is critical to deepening our understanding of proper gene regulation. Current approaches are mainly focused on searching for statistically enriched dots on ...
Supervised Machine Learning Species Specificity Organ Specificity Humans Databases, Genetic Sequence Analysis, DNA Chromatin K562 Cells Genome
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A Novel Radial Basis Neural Network-Leveraged Fast Training Method for Identifying Organs in MR Images.

Computational and mathematical methods in medicine May 5, 2020
We propose a new method for fast organ classification and segmentation of abdominal magnetic resonance (MR) images. Magnetic resonance imaging (MRI) is a new type of high-tech imaging examination fashion in recent years. Recognition of specific targe...
Liver Image Interpretation, Computer-Assisted Organ Specificity Abdomen Support Vector Machine Magnetic Resonance Imaging Humans Neural Networks, Computer Algorithms Computational Biology Kidney
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DeePathology: Deep Multi-Task Learning for Inferring Molecular Pathology from Cancer Transcriptome.

Scientific reports Nov 11, 2019
Despite great advances, molecular cancer pathology is often limited to the use of a small number of biomarkers rather than the whole transcriptome, partly due to computational challenges. Here, we introduce a novel architecture of Deep Neural Network...
Pathology, Molecular Data Mining Disease Susceptibility Organ Specificity Computational Biology Gene Expression Regulation, Neoplastic Algorithms Reproducibility of Results Neoplasms Gene Expression Profiling Transcriptome Deep Learning Humans Neural Networks, Computer
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Extended-wavelength diffuse reflectance spectroscopy with a machine-learning method for in vivo tissue classification.

PloS one Oct 10, 2019
OBJECTIVES: An extended-wavelength diffuse reflectance spectroscopy (EWDRS) technique was evaluated for its ability to differentiate between and classify different skin and tissue types in an in vivo pig model.
Organ Specificity Swine Machine Learning Principal Component Analysis Animals Spectrum Analysis
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Cell Type Classification and Unsupervised Morphological Phenotyping From Low-Resolution Images Using Deep Learning.

Scientific reports Sep 17, 2019
Convolutional neural networks (ConvNets) have proven to be successful in both the classification and semantic segmentation of cell images. Here we establish a method for cell type classification utilizing images taken with a benchtop microscope direc...
Neural Networks, Computer Algorithms Phenotype Deep Learning Single-Cell Analysis Cell Tracking Models, Theoretical Microscopy Organ Specificity
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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...
Cell Line, Tumor Genomics Regression Analysis Antineoplastic Agents Deep Learning Humans Inhibitory Concentration 50 Neural Networks, Computer Phenotype Organ Specificity Databases, Factual Neoplasms
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Cross-Cell-Type Prediction of TF-Binding Site by Integrating Convolutional Neural Network and Adversarial Network.

International journal of molecular sciences Jul 12, 2019
Transcription factor binding sites (TFBSs) play an important role in gene expression regulation. Many computational methods for TFBS prediction need sufficient labeled data. However, many transcription factors (TFs) lack labeled data in cell types. W...
Binding Sites Transcription Factors Gene Expression Regulation Organ Specificity Protein Binding Algorithms Computational Biology Deep Learning ROC Curve Neural Networks, Computer
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