The article introduces Genesis, a versatile and platform-independent Java suite for large-scale gene expression analysis. Genesis integrates various tools for microarray data analysis, including filters, normalization, visualization, and clustering algorithms such as hierarchical clustering, self-organizing maps, k-means, principal component analysis, and support vector machines. The software enables transparent comparison of clustering results across different methods, enhancing the analysis of gene expression patterns and regulatory mechanisms. Additionally, it supports the mapping of gene expression data onto chromosomal sequences to investigate coexpression patterns. The tool is designed to be user-friendly and has been tested on multiple platforms, including Windows 2000, LINUX, Thru64 Unix, Solaris, and Irix.The article introduces Genesis, a versatile and platform-independent Java suite for large-scale gene expression analysis. Genesis integrates various tools for microarray data analysis, including filters, normalization, visualization, and clustering algorithms such as hierarchical clustering, self-organizing maps, k-means, principal component analysis, and support vector machines. The software enables transparent comparison of clustering results across different methods, enhancing the analysis of gene expression patterns and regulatory mechanisms. Additionally, it supports the mapping of gene expression data onto chromosomal sequences to investigate coexpression patterns. The tool is designed to be user-friendly and has been tested on multiple platforms, including Windows 2000, LINUX, Thru64 Unix, Solaris, and Irix.