Genesis

Genesis performs large-scale microarray gene expression data processing and analysis, providing filtering, normalization, distance measures, visualization, clustering (hierarchical clustering, self-organizing maps, k-means, principal component analysis (PCA), support vector machines (SVM)), and chromosomal mapping to support promoter and transcriptional control studies.

Key Features:

• Data Processing Tools: Implements filtering and normalization preprocessing to improve quality and comparability of microarray gene expression data.
• Visualization Capabilities: Provides visualization of complex expression datasets to aid detection of patterns and anomalies.
• Clustering Algorithms: Supports hierarchical clustering, self-organizing maps, k-means, principal component analysis (PCA), and support vector machines (SVM) for grouping or analyzing expression data.
• Transparent Clustering Results: Presents clustering results across implemented methods to enable comparative analysis of outcomes and parameter effects.
• Chromosomal Mapping: Maps gene expression data onto chromosomal sequences to support promoter analysis and investigation of transcriptional control.

Scientific Applications:

• Gene Expression Profiling: Enables analysis of gene expression patterns across conditions or time points for profiling studies.
• Transcriptional Regulation Studies: Facilitates promoter analysis and investigation of transcriptional control via chromosomal mapping of expression data.
• Comparative Genomics: Supports comparison of expression profiles between species or strains to identify conserved regulatory elements.
• Disease Research: Assists identification of differentially expressed genes associated with diseases for biomarker or therapeutic target discovery.

Methodology:

Computational methods include filtering, normalization, application of distance measures, visualization, hierarchical clustering, self-organizing maps, k-means, principal component analysis (PCA), support vector machines (SVM), and chromosomal mapping for promoter analysis.