Collection and Preprocessing Omic Data: We identify and select relevant data sources, clean and format the data, including identifying and handling missing values
Pathway Analysis Significantly expressed proteins compared with publicly available datasets to determine biological significance and function. Trends and patterns analysis to identify important features or variables that could potentially be used in a statistical or machine learning model
Determining SIgnificance: Visualization of statistically significant variation in protein expression Filtering and processing via R workflow for statistical output Volcano plots and heat map creation for visualization