Package: MEIGOR 1.39.0

Jose A. Egea

MEIGOR: MEIGOR - MEtaheuristics for bIoinformatics Global Optimization

MEIGOR provides a comprehensive environment for performing global optimization tasks in bioinformatics and systems biology. It leverages advanced metaheuristic algorithms to efficiently search the solution space and is specifically tailored to handle the complexity and high-dimensionality of biological datasets. This package supports various optimization routines and is integrated with Bioconductor's infrastructure for a seamless analysis workflow.

Authors:Jose A. Egea [aut, cre], David Henriques [aut], Alexandre Fdez. Villaverde [aut], Thomas Cokelaer [aut]

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MEIGOR.pdf |MEIGOR.html
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NEWS

# Install 'MEIGOR' in R:
install.packages('MEIGOR', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Datasets:

On BioConductor:MEIGOR-1.39.0(bioc 3.20)MEIGOR-1.38.0(bioc 3.19)

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

bioconductor-package

8 exports 1.64 score 69 dependencies 1 mentions

Last updated 2 months agofrom:e62dc16747

Exports:CeSSRCeVNSRcur_paramsessRessR_multistartMEIGOrunBayesFitrvnds_hamming

Dependencies:base64encBHBiocGenericsbitopsbslibcachemCellNOptRcliCNORodecolorspacecpp11deSolvedigestevaluatefansifarverfastmapfontawesomefsgenalgggplot2gluegraphgtablehighrhtmltoolsigraphisobandjquerylibjsonliteknitrlabelinglatticelifecyclemagrittrMASSMatrixmemoisemgcvmimemunsellnlmepillarpkgconfigR6rappdirsRBGLRColorBrewerRCurlRgraphvizrlangrmarkdownRsolnpsassscalessnowsnowfallstringistringrtibbletinytextruncnormutf8vctrsviridisLitewithrxfunXMLyaml

MEIGOR: a software suite based on metaheuristics for global optimization in systems biology and bioinformatics

Rendered fromMEIGOR-vignette.Rmdusingknitr::rmarkdownon Jul 01 2024.

Last update: 2024-03-12
Started: 2024-03-12

Readme and manuals

Help Manual

Help pageTopics
Global optimization algorithm for MINLPs based on Scatter SearchessR-package
Global optimization ToolboxMEIGOR-package
BayesFitBayesFit-package BayesFit
Global optimization algorithm for MINLPs based on Scatter Search using a Cooperative StrategyCeSSR
Global optimization algorithm for MINLPs based on VNS using a Cooperative StrategyCeVNSR
A CNOlist from CellNOptR paclagecnolist
A CNOlist from CellNOptR paclagecnolist_cellnopt
Current values of all model parameterscur_params
Local search algorithm within eSSdhc
Global optimization algorithm for MINLPs based on Scatter SearchessR
Multistart function for eSSessR_multistart
Computes the euclidean distance between the rows of two different matriceseucl_dist
Auxiliary function to perform parallel runsith_essR
Auxiliary function to perform parallel runsith_VNSR
MEIGO main functionMEIGO
A model from CellNoptRmodel
A model from CellNoptRmodel_cellnopt
Auxiliary function to evaluate constraintsnls_fobj
Gateway function to evaluate the objective function when the local solvers are invoked.optim_fobj
Optimal parameters for simulation with CNORodeparamsOpt
Running the BayesFit optimisationrunBayesFit
Main VNS functionrvnds_hamming
Local search in VNSrvnds_local
Gateway function to evaluate the equality constraints when solnp is invoked as local solversolnp_eq
Gateway function to evaluate the objective function when solnp is invoked as local solversolnp_fobj
Gateway function to evaluate the inequality constraints when solnp is invoked as local solversolnp_ineq
Function that expands the search direction when a good offspring solution has been foundssm_beyond
Sets the default options for eSSRssm_defaults
Gateway function to evaluate the objective function in essRssm_evalfc
Calculates relative errors between two vectorsssm_isdif2
Configure local solverssm_localsolver
Assigns values to the options defined by the userssm_optset
Calculates the penalized objective function in constrained problemsssm_penalty_function
Rounds variables declared as integer of binaryssm_round_int
Default options for VNSvns_defaults
Set VNS optionsvns_optset