BenchToModel

From the Laboratory Bench ⟹ To Computational Models

Exploring Machine Learning, Deep Learning, and Their Applications in Biology.

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Machine Learning

• Linear Regression
• Logistic Regression
• Decision Tree
• Random Forest
• Support Vector Machine (SVM)
• XGBoost
• Principal Component Analysis (PCA)

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Deep Learning

• Multi-Layer Perceptron (MLP)
• Convolutional Neural Networks (CNN)
• Recurrent Neural Networks (RNN)
• Long Short-Term Memory (LSTM)
• Gated Recurrent Units (GRU)
• Autoencoders
• Transformers

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Computational Biology Applications

• Bulk RNA-seq
• Single-cell RNA-seq
• Microbiome Analysis
• Metabolomics
• Multiomics Integration
• Bioimage Analysis

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Goal

To connect machine learning and deep learning concepts to biological questions — one architecture at a time.

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Author

Nikhil Kirtipal