MCB128: AI in Molecular Biology (Spring 2026)

(Under construction)

(Now hiring TFs Fall 2026)

__block 0: 2-11 Sep: A single neuron as a classifier; [b0 Lecture notes]; [b0 Lecture slides]; [[b0 Homework]]; [[b0 Answers]]
__b0-w1: 2 Sep: A single neuron; [[b0_section]]
__b0-w2: 9 Sep: RNA functional classification; [[b0_section]]

__block 1: 14-25 Sep: Feed Forward Networks; [b1 Lecture notes]; [b1 Lecture slides]; [[b1 Homework]]; [[b1 Answers]]
__b1-w1: 14,16 Sep: Multilayer perceptron / Protein 2D structure; [[b1_section1]]
__b1-w2: 21,23 Sep: Fundamentals of neural network training; [[b1_section2]]

__block 2: 28-09 Sep-Oct: CNNs/RNNs and DNA/RNA binding motifs; [b2 Lecture notes]; [b2 Lecture slides]; [[b2 Homework]]; [[b2 Answers]]
__b2-w1: 28,30 Sep: Convolutional neural networks (CNNs); [[b2_section1]]
__b2-w2: 05,07 Oct: Residual networks (RN) and Recurrent neural netowrks (RNNs); [[b2_section2]]

__block 3: 14-23 Oct: Attention/Transformers; [b3 Lecture notes]; [b3 Lecture slides]; [[b3 Homework]]; [[b3 Answers]]
__b3-w1: 14 Oct: Attention/Transformers; [[b3_section1]]
__b3-w2: 19,21 Oct: Protein folding/AlphaFold2; [[b3_section2]]

__block 4: 26-06 Oct-Nov: Large language models (LLMs); [b4 Lecture notes]; [b4 Lecture slides]; [[b4 Homework]]; [[b4 Answers]]
__b4-w1: 26,28 Oct: LLMs; [[b4_section1]]
__b4-w2: 02,04 Nov: LLMs for DNA, RNA, Protein, genomes; [[b4__section2]]

__block 5: 09-20 Nov: AutoEncoders, Variational AutoEncoders; [b5 Lecture notes]; [b5 Lecture slides]; [[b5 Homework]]; [[b5 Answers]]
__B5-w1: 09,11 Nov: AutoEncoders/ Gene expression profiles; [[b5_section1]]
__b5-w2: 16,18 Nov: Variational AutoEncoders / scRNA-seq; [[b5_section2]]

__block 6: 23-04 Nov-Dec: Diffusion Models / Graph Neural Networkss; [b6 Lecture notes]; [b6 Lecture slides]; [b6 Project]
__b6-w1: 23 Nov: Diffusion models / Protein design; [[b6_section]]
__b6-w2: 30 Nov, 02 Dec: Flow Matching / RNA seq&structure generation / The virtual cell; [b6 vc slides]