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lipidr:Data Mining and Analysis of Lipidomics Datasets
lipidr an easy-to-use R package implementing a complete workflow for downstream analysis of targeted and untargeted lipidomics data. lipidomics results can be imported into lipidr as a numerical matrix or a Skyline export, allowing integration into current analysis frameworks. Data mining of lipidomics datasets is enabled through integration with Metabolomics Workbench API. lipidr allows data inspection, normalization, univariate and multivariate analysis, displaying informative visualizations. lipidr also implements a novel Lipid Set Enrichment Analysis (LSEA), harnessing molecular information such as lipid class, total chain length and unsaturation.
Maintained by Ahmed Mohamed. Last updated 5 months ago.
lipidomicsmassspectrometrynormalizationqualitycontrolvisualizationbioconductor
30 stars 7.46 score 40 scriptsarthurleroy
MagmaClustR:Clustering and Prediction using Multi-Task Gaussian Processes with Common Mean
An implementation for the multi-task Gaussian processes with common mean framework. Two main algorithms, called 'Magma' and 'MagmaClust', are available to perform predictions for supervised learning problems, in particular for time series or any functional/continuous data applications. The corresponding articles has been respectively proposed by Arthur Leroy, Pierre Latouche, Benjamin Guedj and Servane Gey (2022) <doi:10.1007/s10994-022-06172-1>, and Arthur Leroy, Pierre Latouche, Benjamin Guedj and Servane Gey (2023) <https://jmlr.org/papers/v24/20-1321.html>. Theses approaches leverage the learning of cluster-specific mean processes, which are common across similar tasks, to provide enhanced prediction performances (even far from data) at a linear computational cost (in the number of tasks). 'MagmaClust' is a generalisation of 'Magma' where the tasks are simultaneously clustered into groups, each being associated to a specific mean process. User-oriented functions in the package are decomposed into training, prediction and plotting functions. Some basic features (classic kernels, training, prediction) of standard Gaussian processes are also implemented.
Maintained by Arthur Leroy. Last updated 3 months ago.
gaussian-processesmulti-task-learningmulti-task-predictioncpp
16 stars 4.86 score 15 scriptsbiagolini
bwimage:Describe Image Patterns in Natural Structures
A computational tool to describe patterns in black and white images from natural structures. 'bwimage' implemented functions for exceptionally broad subject. For instance, 'bwimage' provide examples that range from calculation of canopy openness, description of patterns in vertical vegetation structure, to patterns in bird nest structure.
Maintained by Carlos Biagolini-Jr.. Last updated 5 years ago.
3.70 scorezahra-heidari-gh
RHC:Rangeland Health and Condition
The evaluation criteria of rangeland health, condition and landscape function analysis based on species diversity and functional diversity of rangeland plant communities.
Maintained by Zahra Heidari Ghahfarrokhi. Last updated 28 days ago.
1.00 score