Book VI

Bioinformatics

single-cell data, gene regulatory networks, perturbation screens

Show how machine learning meets biological data, and where a perturbation turns a correlation into a causal question.

8 chapters0 propositions written

Chapter IBiological InformationThe substrate.DNA · RNA · Proteins · Genes · Genomes · Cellsnot yet written
Chapter IIBiological DataWhat a measurement of life looks like.Sequencing · Expression · Single-cell data · Imaging · Spatial transcriptomics · Perturbation datanot yet written
Chapter IIIGene RegulationHow a cell decides what to be.Transcription · Regulatory networks · Transcription factors · Enhancers · Gene regulatory networksnot yet written
Chapter IVSingle-Cell BiologyOne cell, one observation.scRNA-seq · Cells as observations · Gene-expression matrices · Dimensionality reduction · Clustering · Cell typesnot yet written
Chapter VRepresentation Learning for BiologyEmbedding a cell.Embeddings · Autoencoders · Variational autoencoders · Transformers · Foundation models for biologynot yet written
Chapter VIPerturbationChanging something on purpose.CRISPR · Perturb-seq · Interventions · Perturbation response · Causal interpretationnot yet written
Chapter VIIBiological NetworksBiology as a graph.Graphs · Protein interaction networks · Gene regulatory networks · Graph neural networksnot yet written
Chapter VIIIAI for Drug and Disease ResearchWhere the work is meant to land.Molecular representation · Protein structure · Drug discovery · Disease modelling · Biomarker discoverynot yet written