R-universe search: tanimoto

Showing 7 of total 7 results (show query)

ncchung

jaccard:Testing similarity between binary datasets using Jaccard/Tanimoto coefficients

Calculate statistical significance of Jaccard/Tanimoto similarity coefficients.

Maintained by Neo Christopher Chung. Last updated 5 years ago.

binary-data hypothesis-testing jaccard similarity statistics tanimoto cpp

21.4 match 5 stars 5.03 score 85 scripts

drostlab

philentropy:Similarity and Distance Quantification Between Probability Functions

Computes 46 optimized distance and similarity measures for comparing probability functions (Drost (2018) <doi:10.21105/joss.00765>). These comparisons between probability functions have their foundations in a broad range of scientific disciplines from mathematics to ecology. The aim of this package is to provide a core framework for clustering, classification, statistical inference, goodness-of-fit, non-parametric statistics, information theory, and machine learning tasks that are based on comparing univariate or multivariate probability functions.

Maintained by Hajk-Georg Drost. Last updated 4 months ago.

distance-measures distance-quantification information-theory jensen-shannon-divergence parametric-distributions similarity-measures statistics cpp

5.2 match 137 stars 12.44 score 484 scripts 24 dependents

bioc

bioassayR:Cross-target analysis of small molecule bioactivity

bioassayR is a computational tool that enables simultaneous analysis of thousands of bioassay experiments performed over a diverse set of compounds and biological targets. Unique features include support for large-scale cross-target analyses of both public and custom bioassays, generation of high throughput screening fingerprints (HTSFPs), and an optional preloaded database that provides access to a substantial portion of publicly available bioactivity data.

Maintained by Thomas Girke. Last updated 5 months ago.

immunooncology microtitreplateassay cellbasedassays visualization infrastructure dataimport bioinformatics proteomics metabolomics

1.6 match 5 stars 6.70 score 46 scripts

bioc

MetID:Network-based prioritization of putative metabolite IDs

This package uses an innovative network-based approach that will enhance our ability to determine the identities of significant ions detected by LC-MS.

Maintained by Zhenzhi Li. Last updated 5 months ago.

assaydomain biologicalquestion infrastructure researchfield statisticalmethod technology workflowstep network kegg

1.8 match 1 stars 5.74 score 110 scripts

frankiethull

maize:Specialty Kernels for SVMs

Bindings for svm kernels via kernlab for use with the 'parsnip' package. Specifically related to specialty kernels for support vector machines not available in parsnip. package includes interface for various kernlab kernels and custom kernels too.

Maintained by Frankie T. Hull. Last updated 4 days ago.

1.9 match 10 stars 5.08 score 3 scripts

kit-iism-em

partitionComparison:Implements Measures for the Comparison of Two Partitions

Provides several measures ((dis)similarity, distance/metric, correlation, entropy) for comparing two partitions of the same set of objects. The different measures can be assigned to three different classes: Pair comparison (containing the famous Jaccard and Rand indices), set based, and information theory based. Many of the implemented measures can be found in Albatineh AN, Niewiadomska-Bugaj M and Mihalko D (2006) <doi:10.1007/s00357-006-0017-z> and Meila M (2007) <doi:10.1016/j.jmva.2006.11.013>. Partitions are represented by vectors of class labels which allow a straightforward integration with existing clustering algorithms (e.g. kmeans()). The package is mostly based on the S4 object system.

Maintained by Fabian Ball. Last updated 2 years ago.

comparison dissimilarity-measures distance-measures partitions similarity-measures

2.0 match 2 stars 3.78 score 60 scripts

idslme

IDSL.CSA:Composite Spectra Analysis (CSA) for High-Resolution Mass Spectrometry Analyses

A fragmentation spectra detection pipeline for high-throughput LC/HRMS data processing using peaklists generated by the 'IDSL.IPA' workflow <doi:10.1021/acs.jproteome.2c00120>. The 'IDSL.CSA' package can deconvolute fragmentation spectra from Composite Spectra Analysis (CSA), Data Dependent Acquisition (DDA) analysis, and various Data-Independent Acquisition (DIA) methods such as MS^E, All-Ion Fragmentation (AIF) and SWATH-MS analysis. The 'IDSL.CSA' package was introduced in <doi:10.1021/acs.analchem.3c00376>.

Maintained by Dinesh Barupal. Last updated 2 years ago.

composite-spectra-analysis csa data-dependent-acquisition data-independent-acquisition dda dia mass-spectrometry metabolomics metabolomics-pipeline small-molecule spectral-entropy

1.8 match 5 stars 3.40 score