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.

R based genetic algorithm for binary and floating point
        chromosomes.

Defines classes and methods that can be used
  to implement genetic algorithms for feature selection.  The idea is
  that we want to select a fixed number of features to combine into a
  linear classifier that can predict a binary outcome, and can use a
  genetic algorithm heuristically to select an optimal set of features.

Provides the necessary functions to identify and extract a selection of already available barcode constructs (Cornils, K. et al. (2014) <doi:10.1093/nar/gku081>) and freely choosable barcode designs from next generation sequence (NGS) data. Furthermore, it offers the possibility to account for sequence errors, the calculation of barcode similarities and provides a variety of visualisation tools (Thielecke, L. et al. (2017) <doi:10.1038/srep43249>).

Density, distribution function, quantile function and random generation for the Generalized Binomial Distribution. Functions to compute the Clopper-Pearson Confidence Interval and the required sample size. Enhanced model for burn-in studies, where failures are tackled by countermeasures.

A comprehensive suite of helper functions designed to facilitate the analysis of genomic annotations from the 'GENCODE' database <https://www.gencodegenes.org/>, supporting both human and mouse genomes. This toolkit enables users to extract, filter, and analyze a wide range of annotation features including genes, transcripts, exons, and introns across different 'GENCODE' releases. It provides functionality for cross-version comparisons, allowing researchers to systematically track annotation updates, structural changes, and feature-level differences between releases. In addition, the package can generate high-quality FASTA files containing donor and acceptor splice site motifs, which are formatted for direct input into the 'MaxEntScan' tool (Yeo and Burge, 2004 <doi:10.1089/1066527041410418>), enabling accurate calculation of splice site strength scores.