i2d_R

"i2d_R" is an R package to bridge the gap between visual data and quantitative biomedical and biological research analysis. Recognizing the limitations imposed by human vision and the traditional challenges in extracting quantitative information from images, i2d_R offers a computational solution to transform images into simulated datasets. This transformation enables researchers to analyze and interpret complex information previously difficult to quantify.

Key Features and Functionalities:

- Image to Data Transformation: i2d_R facilitates the conversion of images into simulated datasets, making it possible to apply quantitative analysis techniques to data initially captured in visual formats.

- Digital Convolution for Data Simulation: The package employs digital convolution as the basis for simulating data from images, ensuring that the process captures the intricacies and details present in the original visual data.

Graph Clustering Methods: i2d_R includes three novel and efficient graph clustering methods based on the simulated data. These methods allow for the dissection of complex gene networks into sub-clusters, revealing groupings of genes that share similar biological functions.