Preparing Biological Datasets for ML

• Data collection and annotation techniques for biological datasets.
• Preprocessing steps: handling missing values, outliers, and normalization.
• Handling imbalanced datasets in the biological context.
• Dealing with noisy data and techniques for data cleaning.
• Feature engineering techniques specific to biological data.
• Data integration and fusion of different biological modalities.
• Examples to avoid.