This guest lecture by Prof. George Church is on the topic of causality, in particular, how to use genomic data and the tools of natural computing to differentiate between correlation and causation.

Lecture 22: Causality, Natural Computing, and Engineering Genomes

This lecture begins with the epigenetic state, which regulates gene function without changing DNA. Then, how to estimate the protein occupancy of the genome via computational methods. Lastly, how to map enhancers to their regulatory targets.

Lecture 18: Analysis of Chromatin Structure

This lecture is guided by the question "Where is missing heritability found?" Prof. David Gifford discusses computational models that can predict phenotype from genotype. He then discusses how to discover and model quantitative trait loci.

Lecture 19: Discovering Quantitative Trait Loci (QTLs)

Prof. Doug Lauffenburger delivers a guest lecture on the topic of logic modeling of cell signaling networks. He begins by giving a conceptual background of the subject, and then discusses an example involving hepatocyes (liver cells).

Lecture 17: Logic Modeling of Cell Signaling Networks

This lecture by Prof. Ernest Fraenkel is about gene regulatory networks. He begins by finishing Lecture 14's discussion of protein-protein interactions.

Lecture 15: Gene Regulatory Networks

This lecture is on predicting protein interactions. He discusses structural predictions of protein-protein interactions. He then talks about how measurements of protein-protein interactions are made and Bayes Net prediction of protein-protein interactions.

Lecture 14: Predicting Protein Interactions

This guest lecture by Prof. Ron Weiss is on synthetic biology. Prof. Weiss describes how he came to be a synthetic biologist, followed by an overview of the field. He covers basic , technologies for scalability, and programmable therapeutics.

Lecture 21: Synthetic Biology: From Parts to Modules to Therapeutic Systems

This lecture by Prof. David Gifford is on human genetics. He covers how scientists discover variation in the human genome. He discusses how to prioritize variants based on their importance. And then covers how to prove causation, not just correlation.

Lecture 20: Human Genetics, SNPs, and Genome Wide Associate Studies

In this lecture, Professor Burge reviews classical and next-generation sequencing. He then introduces local alignment (BLAST) and some of the associated statistics.

Lecture 2: Local Alignment (BLAST) and Statistics

This lecture by Prof. Christopher Burge covers modeling and discovery of sequence motifs. He gives the example of the Gibbs sampling algorithm. He covers information content of a motif, and he ends with parameter estimation for motif models.

Lecture 9: Modeling and Discovery of Sequence Motifs

Foundations of Computational and Systems Biology

This lecture by Prof. Ernest Fraenkel is on protein interaction networks. He covers network models, including their structure and an analysis. He asks, "can we use networks to predict function?" He ends with a data integration example.

Lecture 16: Protein Interaction Networks

This lecture on predicting protein structure covers refining a partially correct structure. Methods include energy minimization, molecular dynamics, and simulated annealing. He moves on to methods for predicting structure from a sequence of amino acid.

Lecture 13: Predicting Protein Structure

In this lecture, Prof. Burge discusses global sequence alignment and gapped local sequence alignment. He later talks about substitution matrices for protein comparison.

Lecture 3: Global Alignment of Protein Sequences (NW, SW, PAM, BLOSUM)

Prof. Burge discusses comparative genomics. He begins with a review of global alignment of protein sequences, then talks about Markov models, the Jukes-Cantor model, and Kimura models. He discusses types of selection: natural, negative, and positive.

Lecture 4: Comparative Genomic Analysis of Gene Regulation

Prof. Gifford talks about library complexity as it relates to genome sequencing. He explains how to create a full-text minute-size (FM) index, which involves a Burrows-Wheeler transform (BWT). He ends with how to deal with the problem of mismatching.

Lecture 5: Library Complexity and Short Read Alignment (Mapping)

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Best Episodes on Global Issues

The best podcasts about ourselves as well as the world through the lense of Science. Specific topics include things about our brain, emotions to biology, physics and more!