Contains an engine for spatially-explicit eco-evolutionary mechanistic models with a modular implementation and several support functions. It allows exploring the consequences of ecological and macroevolutionary processes across realistic or theoretical spatio-temporal landscapes on biodiversity patterns as a general term. Reference: Oskar Hagen, Benjamin Flueck, Fabian Fopp, Juliano S. Cabral, Florian Hartig, Mikael Pontarp, Thiago F. Rangel, Loic Pellissier (2021) "gen3sis: A general engine for eco-evolutionary simulations of the processes that shape Earth's biodiversity" <doi:10.1371/journal.pbio.3001340>.

A collection of functions for processing 'Gen5' 2.06 exported data.
    'Gen5' is an essential data analysis software for BioTek plate readers <https://www.biotek.com/products/software-robotics-software/gen5-microplate-reader-and-imager-software/>. This package contains functions for data cleaning, 
    modeling and plotting using exported data from 'Gen5' version 2.06. It exports
    technically correct data defined in (Edwin de Jonge and Mark van der Loo 
    (2013) <https://cran.r-project.org/doc/contrib/de_Jonge+van_der_Loo-Introduction_to_data_cleaning_with_R.pdf>) for customized analysis. It 
    contains Boltzmann fitting for general kinetic analysis.  
    See <https://www.github.com/yanxianUCSB/gen5helper> for more information,
    documentation and examples.

Implements genetic algorithm and particle swarm algorithm for real-valued functions. Various modifications (including hybridization and elitism) of these algorithms are provided. Implemented functions are based on ideas described in S. Katoch, S. Chauhan, V. Kumar (2020) <doi:10.1007/s11042-020-10139-6> and M. Clerc (2012) <https://hal.archives-ouvertes.fr/hal-00764996>.

Utilizing Generative Artificial Intelligence models like 'GPT-4' and 'Gemini Pro' as coding and writing assistants for 'R' users. Through these models, 'GenAI' offers a variety of functions, encompassing text generation, code optimization, natural language processing, chat, and image interpretation. The goal is to aid 'R' users in streamlining laborious coding and language processing tasks.