SimBA is a non-generative approach to population simulations based on a combination of stochastic techniques and discrete methods. Long Description (required)
SimBA is a non-generative approach to population simulations, based on a combination of stochastic techniques and discrete methods. The package contains a hill climbing algorithm and multiple subpopulation structures. SimBA is very sensitive to the input specifications, i.e., very similar but distinct input characteristics result in distinct outputs with high fidelity to the specified distributions. This property of the simulation is not explicitly modeled or studied by previous methods. https://github.com/ComputationalGenomics/SimBA u241918@bcm.edu
Step 1: Use the attribute tree to add new attributes or remove pre-selected attributes to describe the simulator.
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Summary of Proposed Changes Step 2: Review list of proposed attribute addition(s) and subtraction(s).
Can't Find the Attribute You Are Looking For? If you would like to propose an attribute that you cannot find in the tree above, or if you would like to add a clarification to one or more attributes for this simulator (e.g. a specific file format for attribute /Output/File Format/Other), please list them in the Additional Comment box of the Submit tab .
Summary of Proposed Changes Current Citations/Applications
[Pubmed ID: 25886895 ],
Parida L, Haiminen N ,
SimBA: simulation algorithm to fit extant-population distributions. ,
BMC Bioinformatics ,
03-14-2015 ,
https://www.ncbi.nlm.nih.gov/pubmed/?term=25886895, Primary Citation