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Identification of coenzyme-binding proteins with machine learning algorithms.

Computational biology and chemistry Jan 28, 2019
The coenzyme-binding proteins play a vital role in the cellular metabolism processes, such as fatty acid biosynthesis, enzyme and gene regulation, lipid synthesis, particular vesicular traffic, and β-oxidation donation of acyl-CoA esters. Based on th...
Esters Acyl Coenzyme A Humans Machine Learning Proteins Software Models, Molecular Molecular Structure
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tRNA-DL: A Deep Learning Approach to Improve tRNAscan-SE Prediction Results.

Human heredity Jan 25, 2019
BACKGROUND: tRNAscan-SE is the leading tool for transfer RNA (tRNA) annotation, which has been widely used in the field. However, tRNAscan-SE can return a significant number of false positives when applied to large sequences. Recently, conventional m...
Models, Theoretical Algorithms Humans Area Under Curve Deep Learning Neural Networks, Computer RNA, Transfer ROC Curve Software
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Xrare: a machine learning method jointly modeling phenotypes and genetic evidence for rare disease diagnosis.

Genetics in medicine : official journal of the American College of Medical Genetics Jan 24, 2019
PURPOSE: Despite the successful progress next-generation sequencing technologies has achieved in diagnosing the genetic cause of rare Mendelian diseases, the current diagnostic rate is still far from satisfactory because of heterogeneity, imprecision...
Genetic Variation Humans High-Throughput Nucleotide Sequencing Machine Learning Rare Diseases Software Exome Phenotype Computational Biology Genomics Genotype Mutation Genetic Testing
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Models Matter, So Does Training: An Empirical Study of CNNs for Optical Flow Estimation.

IEEE transactions on pattern analysis and machine intelligence Jan 22, 2019
We investigate two crucial and closely-related aspects of CNNs for optical flow estimation: models and training. First, we design a compact but effective CNN model, called PWC-Net, according to simple and well-established principles: pyramidal proces...
Humans Image Processing, Computer-Assisted Neural Networks, Computer Software Databases, Factual
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Incorporation of a spectral model in a convolutional neural network for accelerated spectral fitting.

Magnetic resonance in medicine Jan 21, 2019
PURPOSE: MRSI has shown great promise in the detection and monitoring of neurologic pathologies such as tumor. A necessary component of data processing includes the quantitation of each metabolite, typically done through fitting a model of the spectr...
Computer Graphics Creatine Echo-Planar Imaging White Matter Magnetic Resonance Spectroscopy Aspartic Acid Humans Neural Networks, Computer Image Processing, Computer-Assisted Models, Theoretical Brain Neoplasms Brain Mapping Deep Learning Glioblastoma User-Computer Interface Artifacts Choline Software Signal-To-Noise Ratio Algorithms Databases, Factual
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GOTrapper: a tool to navigate through branches of gene ontology hierarchy.

BMC bioinformatics Jan 11, 2019
BACKGROUND: Gene Ontology (GO) is a useful resource of controlled vocabulary that provides information about annotated genes. Based on such resource, finding the biological function is useful for biologists to come up with different hypotheses and he...
Information Storage and Retrieval Gene Ontology User-Computer Interface Humans Computational Biology Software High-Throughput Nucleotide Sequencing Gene Expression Profiling
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Improving the Quality of Synthetic FLAIR Images with Deep Learning Using a Conditional Generative Adversarial Network for Pixel-by-Pixel Image Translation.

AJNR. American journal of neuroradiology Jan 10, 2019
BACKGROUND AND PURPOSE: Synthetic FLAIR images are of lower quality than conventional FLAIR images. Here, we aimed to improve the synthetic FLAIR image quality using deep learning with pixel-by-pixel translation through conditional generative adversa...
Software Brain Female Humans Deep Learning Magnetic Resonance Imaging Image Interpretation, Computer-Assisted Artifacts Adult Male Middle Aged Neuroimaging
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BO-LSTM: classifying relations via long short-term memory networks along biomedical ontologies.

BMC bioinformatics Jan 7, 2019
BACKGROUND: Recent studies have proposed deep learning techniques, namely recurrent neural networks, to improve biomedical text mining tasks. However, these techniques rarely take advantage of existing domain-specific resources, such as ontologies. I...
Natural Language Processing Drug Interactions Data Mining Biological Ontologies Gene Ontology Software Humans Databases, Factual Neural Networks, Computer Deep Learning
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funbarRF: DNA barcode-based fungal species prediction using multiclass Random Forest supervised learning model.

BMC genetics Jan 7, 2019
BACKGROUND: Identification of unknown fungal species aids to the conservation of fungal diversity. As many fungal species cannot be cultured, morphological identification of those species is almost impossible. But, DNA barcoding technique can be empl...
DNA Barcoding, Taxonomic DNA, Fungal Computational Biology Software Supervised Machine Learning Fungi
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OMeta: an ontology-based, data-driven metadata tracking system.

BMC bioinformatics Jan 7, 2019
BACKGROUND: The development of high-throughput sequencing and analysis has accelerated multi-omics studies of thousands of microbial species, metagenomes, and infectious disease pathogens. Omics studies are enabling genotype-phenotype association stu...
Software Whole Genome Sequencing Databases, Factual Metadata Metagenomics Phylogeny Biological Ontologies User-Computer Interface
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