deep phenotyping
Deep Phenotyping of Parkinson’s Disease
... DIRECTIONS Deep phenotyping offers at least three great poten- tial ...First, deep clinical phenotyping will enhance our understanding of the nature of the dis- ease, including its expression, ...
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Automated deep-phenotyping of the vertebrate brain
... scalable phenotyping platform capable of high-resolution isotropic 3D imaging of chromogenic WISH-stained samples along with algorithms for precision registration and quantification of the resultant 3D gene ...
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Mass cytometry deep phenotyping of human mononuclear phagocytes and myeloid-derived suppressor cells from human blood and bone marrow
... Mass cytometry deep phenotyping of human mononuclear phagocytes and myeloid derived suppressor cells from human blood and bone marrow.. Mikael Roussel, *,†,‡,§,1 P.[r] ...
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Deep phenotyping of coarse root architecture in R. pseudoacacia reveals that tree root system plasticity is confined within its architectural model
... regard to the use of deep phenotyping to unravel the differences in root trait plasticity and architectural model. Materials and Methods Seeds of R. pseudoacacia (Vilmorin seed, Pusztavacs provenance, ...
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Subject‐specific segregation of functional territories based on deep phenotyping
... This article lays the ground for individual functional atlasing, a novel analytic approach that requires a specific strategy to avoid circular reasoning, i.e. delineating different topographies from functional contrasts is ...
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Deep phenotyping unstructured data mining in an extensive pediatric database to unravel a common KCNA2 variant in neurodevelopmental syndromes
... Warehouse, a biomedical data warehouse oriented toward clinical narrative reports, developed at Necker Children’s Hospital using around 500,000 patients’ records.. Through the use of thi[r] ...
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INPUT OF DEEP PHENOTYPING IN THE METABOLIC SYNDROME STRATIFICATION
... The metabolomics workflow [1,2] from experimental design and sample collection/preparation through data acquisition to data processing and statistical analysis is well defined though de[r] ...
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Deep active localization
... action. Deep Reinforcement Learning (DRL) (which uses deeper neural networks in RL paradigm, and hence it is sometimes considered a particular form of DL) has seen an incredible recent success on some robotics ...
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Distributed Management of Scientific Workflows for High-Throughput Plant Phenotyping
... High-throughput phenotyping platforms allow acquisition of quantitative data on thousands of plants required for genetic analyses in well-controlled environmental ...
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Étude du taux de formation d'étoiles dans les galaxies du Gemini Deep Deep Survey
... Du point de vue physique, la relation entre la luminosité de cette raie d’émission, L([On]), et le taux de formation d’étoiles, TFE([OH]), est moins directe que celle vue précédemment po[r] ...
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Deep Importance Sampling
... the Deep Importance Sampling algorithm, contrary to what we did in the paper, one might want to keep the values obtained during the training, so as to use them in the final Monte Carlo estimator, and thus not ...
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Deep Metaphysical Indeterminacy
... Let me emphasize that it is not part of my argument that the orthodox inter- pretation of quantum mechanics is, in fact, correct. There are many other inter- pretations of quantum mechanics (Bohmian mechanics, for ...
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Deep linguistic lensing
... Because deep learning is often a time consuming process, and in practice multiple ver- sions of a model are often trained in parallel with different hyper-parameters, it can be tedious or untenable for an expert ...
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Deep octonion networks
... Abstract: Deep learning is a hot research topic in the field of machine learning methods and ...especially deep real networks (DRNs), have been widely used in many research ...the deep complex ...
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Deep into Pharo
... package: 'CoolToolSet - Core' with: [ spec requires: 'CoolBrowser default' ]; package: 'CoolToolSet - Tests' with: [. spec requires: #('CoolToolSet - Core' 'CoolBrowser Tests') ].][r] ...
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3D Plant Phenotyping: All You Need is Labelled Point Cloud Data
... data for training the network. In order to overcome the scarcity of available datasets, different types of data augmentation strategies have been proposed to generate realistic synthetic data. Giuffrida et al. [ 13 ] ...
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Deep Research Submarine
... derived in Ship Structural Design that predict the behavior of stiffened panels under hydrostatic load. 19 The Payload Bay cap was modeled as a ring stiffened cylinder using Johnson’s MIT MathCAD Structural Model. The ...
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A deep ALMA image of the Hubble Ultra Deep Field
... the HST sources in the field enabled us to clean the source list to a final sample of 16 robust ALMA sources. In Section 5, we consider the implications of the number of sources we have detected, aided by the results of ...
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Behavioural phenotyping of SV2A lox/lox mice: Motor and anxiety-like features
... Behavioural phenotyping of SV2A lox/lox mice: Motor and anxiety-like features Serrano, ME 1,2 , Odile, B 3 , VanDenAckerveken, P 3 , Rogister, B 3 , Plenevaux, A 1 ...
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Deep neural networks are lazy : on the inductive bias of deep learning
... 2.1.3 Interpolation is not Equivalent to Overfitting Traditional statistical learning theory does not explain the empirical performance of deep learning. In fact, the bias-variance tradeoff is central to the ...
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