R-universe search: exports:rings

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bioc

ChemmineR:Cheminformatics Toolkit for R

ChemmineR is a cheminformatics package for analyzing drug-like small molecule data in R. Its latest version contains functions for efficient processing of large numbers of molecules, physicochemical/structural property predictions, structural similarity searching, classification and clustering of compound libraries with a wide spectrum of algorithms. In addition, it offers visualization functions for compound clustering results and chemical structures.

Maintained by Thomas Girke. Last updated 5 months ago.

cheminformatics biomedicalinformatics pharmacogenetics pharmacogenomics microtitreplateassay cellbasedassays visualization infrastructure dataimport clustering proteomics metabolomics cpp

15 stars 10.45 score 253 scripts 12 dependents

predictiveecology

SpaDES.tools:Additional Tools for Developing Spatially Explicit Discrete Event Simulation (SpaDES) Models

Provides GIS and map utilities, plus additional modeling tools for developing cellular automata, dynamic raster models, and agent based models in 'SpaDES'. Included are various methods for spatial spreading, spatial agents, GIS operations, random map generation, and others. See '?SpaDES.tools' for an categorized overview of these additional tools. The suggested package 'NLMR' can be installed from the following repository: (<https://PredictiveEcology.r-universe.dev>).

Maintained by Alex M Chubaty. Last updated 4 months ago.

cpp

4 stars 7.53 score 52 scripts 7 dependents

larmarange

prevR:Estimating Regional Trends of a Prevalence from a DHS and Similar Surveys

Spatial estimation of a prevalence surface or a relative risks surface, using data from a Demographic and Health Survey (DHS) or an analog survey, see Larmarange et al. (2011) <doi:10.4000/cybergeo.24606>.

Maintained by Joseph Larmarange. Last updated 6 months ago.

5 stars 6.26 score 46 scripts

maarten14c

coffee:Chronological Ordering for Fossils and Environmental Events

While individual calibrated radiocarbon dates can span several centuries, combining multiple dates together with any chronological constraints can make a chronology much more robust and precise. This package uses Bayesian methods to enforce the chronological ordering of radiocarbon and other dates, for example for trees with multiple radiocarbon dates spaced at exactly known intervals (e.g., 10 annual rings). For methods see Christen 2003 <doi:10.11141/ia.13.2>. Another example is sites where the relative chronological position of the dates is taken into account - the ages of dates further down a site must be older than those of dates further up (Buck, Kenworthy, Litton and Smith 1991 <doi:10.1017/S0003598X00080534>; Nicholls and Jones 2001 <doi:10.1111/1467-9876.00250>). The paper accompanying this R package is Blaauw et al. 2024 <doi:10.1017/RDC.2024.56>.

Maintained by Maarten Blaauw. Last updated 3 months ago.

7 stars 6.02 score 6 scripts