KODAMA - Knowledge Discovery by Accuracy Maximization

A self-guided, weakly supervised learning algorithm for feature extraction from noisy and high-dimensional data. It facilitates the identification of patterns that reflect underlying group structures across all samples in a dataset. The method incorporates a novel strategy to integrate spatial information, improving the clarity of results in spatially resolved data.

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openblascpp

6.08 score 1 stars 86 scripts 335 downloads

clinical - Clinical Metadata Exploration and Feature Matching

A collection of tools to easily analyze clinical data, including functions for correlation analysis, and statistical testing. The package facilitates the integration of clinical metadata with other omics layers, enabling exploration of quantitative variables. It also includes the utility for frequency matching samples across a dataset based on patient variables.

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4.00 score 1 stars 4 scripts 186 downloads

musicNMR - Conversion of Nuclear Magnetic Resonance Spectra in Audio Files

A collection of functions for converting and visualization the free induction decay of mono dimensional nuclear magnetic resonance (NMR) spectra into an audio file. It facilitates the conversion of Bruker datasets in files WAV. The sound of NMR signals could provide an alternative to the current representation of the individual metabolic fingerprint and supply equally significant information. The package includes also NMR spectra of the urine samples provided by four healthy donors. Based on Cacciatore S, Saccenti E, Piccioli M. Hypothesis: the sound of the individual metabolic phenotype? Acoustic detection of NMR experiments. OMICS. 2015;19(3):147-56. <doi:10.1089/omi.2014.0131>.

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1.00 score 4 scripts 182 downloads