Search Results for "cite space"
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Showing 4 open source projects for "cite space"
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Alphafold
Open source code for AlphaFold
This package provides an implementation of the inference pipeline of AlphaFold v2.0. This is a completely new model that was entered in CASP14 and published in Nature. For simplicity, we refer to this model as AlphaFold throughout the rest of this document. Any publication that discloses findings arising from using this source code or the model parameters should cite the AlphaFold paper. Please also refer to the Supplementary Information for a detailed description of the method. You can use... -
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18F-DOPA & 123I-FP-CIT templates
18F-DOPA & 123I-FP-CIT (Ioflupane - DaTSCAN) human templates for SPM.
The 18F-DOPA and 123I-FP-CIT (Ioflupane - DaTSCAN) templates are intended for use as templates for SPM automated normalisation. Created for SPM8 but SPM12 compatible. Available in NifTI file format. The updated Templates are symmetrical and adjusted to MNI-space templates from 12 (18F-DOPA) and 30 controls without evidence of nigrostriatal degeneration (123I-FP-CIT). Authors: I. Huertas, J.A. Lojo, F.J. García-Gómez & D. García-Solís. Contact: javier191185@gmail.com Terms of use... -
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MRiLab
A Numerical MRI Simulation Platform
The MRiLab project is moving to GitHub, the latest version can be obtained from https://leoliuf.github.io/MRiLab/ The MRiLab is a numerical MRI simulation package. It has been developed and optimized to simulate MR signal formation, k-space acquisition and MR image reconstruction. MRiLab provides several dedicated toolboxes to analyze RF pulse, design MR sequence, configure multiple transmitting and receiving coils, investigate magnetic field related properties and evaluate real-time imaging...">
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LWPR
Locally Weighted Projection Regression (LWPR)
Locally Weighted Projection Regression (LWPR) is a fully incremental, online algorithm for non-linear function approximation in high dimensional spaces, capable of handling redundant and irrelevant input dimensions. At its core, it uses locally linear models, spanned by a small number of univariate regressions in selected directions in input space. A locally weighted variant of Partial Least Squares (PLS) is employed for doing the dimensionality reduction. Please cite: [1] Sethu Vijayakumar... -
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