Implements the Bi-objective Lexicographical Classification method and Performance Assessment Ratio at 10% metric for algorithm classification. Constructs matrices representing algorithm performance under multiple criteria, facilitating decision-making in algorithm selection and evaluation. Analyzes and compares algorithm performance based on various metrics to identify the most suitable algorithms for specific tasks. This package includes methods for algorithm classification and evaluation, with examples provided in the documentation. Carvalho (2019) presents a statistical evaluation of algorithmic computational experimentation with infeasible solutions <doi:10.48550/arXiv.1902.00101>. Moreira and Carvalho (2023) analyze power in preprocessing methodologies for datasets with missing values <doi:10.1080/03610918.2023.2234683>.

Provides an integrated data management solution for assets installed via the 'Biobricks.ai' platform. Streamlines the process of loading and interacting with diverse datasets in a consistent manner. A list of bricks is available at <https://status.biobricks.ai>. Documentation for 'Biobricks.ai' is available at <https://docs.biobricks.ai>.

Download stats reported from the BioConductor.org stats website.

Implement in 'R' interactive Circos-like visualizations of genomic data, to map information
	such as genetic variants, genomic fusions and aberrations to a circular genome, as proposed by the
	'JavaScript' library 'BioCircos.js', based on the 'JQuery' and 'D3' technologies. The output is by 
	default displayed in stand-alone HTML documents or in the 'RStudio' viewer pane. Moreover it can be
	integrated in 'R Markdown' documents and 'Shiny' applications.

Using numeric or raster data, this package contains functions to 
    calculate: complete water balance, bioclimatic balance, bioclimatic 
    intensities, reports for individual locations, multi-layered rasters for
    spatial analysis.

A convenient tool to install and update Bioconductor packages.

Tools to create, validate, and export BioCompute Objects
    described in King et al. (2019) <doi:10.17605/osf.io/h59uh>.
    Users can encode information in data frames, and compose
    BioCompute Objects from the domains defined by the standard.
    A checksum validator and a JSON schema validator are provided.
    This package also supports exporting BioCompute Objects as JSON,
    PDF, HTML, or 'Word' documents, and exporting to cloud-based platforms.