In gene sequencing methods, the topological features of protein-protein interaction (PPI) networks are 
    often used, such as ToppNet <https://toppgene.cchmc.org>. In this study, a candidate gene prioritization method
    was proposed for non-communicable diseases considering disease risks transferred between genes in weighted disease 
    PPI networks with weights for nodes and edges based on functional information.

Three-dimensional systematic conservation planning, conducting
             nested prioritization analyses across multiple depth levels and
             ensuring efficient resource allocation throughout the water column.
             It provides a structured workflow designed to address biodiversity
             conservation and management challenges in the 3 dimensions, while
             facilitating users’ choices and parameterization (Doxa et al. 2025
             <doi:10.1016/j.ecolmodel.2024.110919>).

An innovative tool-set that incorporates graph community detection
             methods into systematic conservation planning. It is designed to
             enhance spatial prioritization by focusing on the protection of
             areas with high ecological connectivity. Unlike traditional
             approaches that prioritize individual planning units, 'priorCON'
             focuses on clusters of features that exhibit strong ecological
             linkages. The 'priorCON' package is built upon the 'prioritizr'
             package <doi:10.32614/CRAN.package.prioritizr>, using commercial
             and open-source exact algorithm solvers that ensure optimal
             solutions to prioritization problems.

Translates beliefs into prior information in the form of Beta and Gamma distributions. 
	It can be used for the generation of priors on the prevalence of disease and 
	the sensitivity/specificity of diagnostic tests and any other binomial experiment.

This uses a mixed integer mathematical programming (MIP)
        approach for building and solving multi-action planning problems, 
        where the goal is to find an optimal combination of management actions that
        abate threats, in an efficient way while accounting for spatial aspects. 
        Thus, optimizing the connectivity and conservation effectiveness of 
        the prioritized units and of the deployed actions. The package is capable of 
        handling different commercial (gurobi, CPLEX) and non-commercial (symphony, CBC) MIP solvers. 
        Gurobi optimization solver can be installed using comprehensive instructions in 
        the 'gurobi' installation vignette of the prioritizr package (available in 
        <https://prioritizr.net/articles/gurobi_installation_guide.html>). Instead, 'CPLEX'
        optimization solver can be obtain from IBM CPLEX web page (available here 
        <https://www.ibm.com/es-es/products/ilog-cplex-optimization-studio>). Additionally, 
        the 'rcbc' R package (available at
    <https://github.com/dirkschumacher/rcbc>) can be used to obtain solutions
    using the CBC optimization software (<https://github.com/coin-or/Cbc>). Methods used in the 
        package refers to Salgado-Rojas et al. (2020) <doi:10.1016/j.ecolmodel.2019.108901>,
        Beyer et al. (2016) <doi:10.1016/j.ecolmodel.2016.02.005>, Cattarino et al. (2015)
        <doi:10.1371/journal.pone.0128027> and Watts et al. (2009) <doi:10.1016/j.envsoft.2009.06.005>. 
        See the prioriactions website for more information, documentations and examples.