Syllabus
Please see last year’s syllabus (with slide packs at the bottom) for previews for this year’s lectures, which will be slightly different. For this year, an updated slide pack will be posted after the lecture. (If it is substantially different from ‘22, an updated video will also be posted.) Video recordings for this year’s lectures can be found in the Media Library tab in Canvas.
| Date | Topic | This year’s lecture | Last year’s lecture | Comment |
|---|---|---|---|---|
| 1/20 | *YALE* Spring term classes begin, 8.20 a.m. | |||
| 1/20 | Introduction | 23i1 | ||
| 1/22 | DATA 1 - Genomics I | 23d1 | ||
| 1/27 | DATA 2 - Genomics II | 23d2 | ||
| 1/29 | DATA 3 - Proteomics I | 23d3 | ||
| 2/3 | DATA 4 - Proteomics II | 23d4 | ||
| 2/5 | MINING 1 - Personal Genomes + Seq. Comparison + Multi-seq Alignment | 23i2a, 23m3, 23m4 | ||
| 2/10 | MINING 2 - Fast Alignment + Variant Calling (incl. a focused section on SVs) | 23m5,23m6a | ||
| 2/12 | MINING 3 - Basic Multi-Omics Supervised Mining #1 | 23m6b,23m7,23m8a | ||
| 2/17 | MINING 4 - Supervised Mining #2 + Unsupervised Mining #1 | 23m8b,23m8c,23m9a,23m9c | ||
| 2/19 | DATA 5 - Knowledge Representation & Databases | 23d5 | ||
| 2/24 | MINING 5 - Unsupervised Mining #2 + Single-Cell Analysis | 23m9d, 23m9e | ||
| 2/26 | Quiz on 1st Half | |||
| 3/3 | TOPICS 1 - Single-Cell Analysis (continues) + Privacy | 23t1, 23t2 | ||
| 3/5 | TOPICS 2 - Network Analysis | 23m10a, 23m10b, 23m10c, 23m10d, 23m10e | ||
| 3/10 | TOPICS 3 - Personal Genomes (from an individual’s perspective) | 23i2b | ||
| 3/14 | Spring break begins | |||
| 3/24 | TOPICS 4 - Deep Learning Fundamentals | 23m12a | ||
| 3/26 | TOPICS 5 - Deep Learning Fundamentals (continues) | 23m12b | ||
| 3/31 | TOPICS 6 - Deep Learning for Biology + Biosensor Data Analysis | 22t3, 22t4 | ||
| 4/2 | MODELING 1 - Protein Simulation I | 23s1 | ||
| 4/7 | MODELING 2 - Protein Simulation II | 23s2 | ||
| 4/9 | MODELING 3 - Protein Simulation III | 23s3 | ||
| 4/14 | MODELING 4 - Protein Simulation IV | 23s4 | ||
| 4/16 | MODELING 5 - Protein Simulation V | |||
| 4/21 | Quiz on 2nd Half | |||
| 4/23 | Final Presentations | |||
| 4/28 | *YALE* Classes end; Reading period begins | |||
| 4/30 | *YALE* Final examinations begin | |||
| 5/15 | *YALE* Final examinations end |
Lecture Slide Pack
See also additional readings for each topic: Additional Readings
| # | Topic | PPT | Youtube (‘21 unless indicated otherwise) |
MPEG (2021) | |
|---|---|---|---|---|---|
| 23i1 | Introduction to Biomedical Data Science | x | x | I1 | I1 |
| 23i2a | Introduction to Personal Genomes | x | x | I2a | |
| 23i2b | An Individual’s Perspective on Personal Genomes | x | x | I2b | i2b |
| 23d1 | DATA - Genomics I | x | D1 | D1 | |
| 23d2 | DATA - Genomics II | x | D2 | D2 | |
| 23d3 | DATA - Proteomics I - Proteins | x | D3 | ||
| 23d4 | DATA - Proteomics II - Structure | x | D4 | ||
| 23d5 | Knowledge Representation & Databases | x | x | D5 | D5 |
| 23m3 | Sequence Comparison | x | x | M3 | M3 |
| 23m4 | Multiple Sequence Comparison | x | x | M4 | M4 |
| 23m5 | Fast Alignment | x | x | M5 | M5 |
| 23m6a | Variant Identification, Focusing on SVs | x | x | M6a | M6a |
| 23m6b | 1000 Genome + PCAWG summary | x | x | M6b | M6b |
| 23m7 | Basic Multi-omics (pipeline processing) | x | x | M7 | M7 |
| 23m8a | Supervised Data Mining - Decision Trees | x | x | M8a | M8a |
| 23m8b | Supervised Data Mining - ROC & Cross-validation | x | x | M8b | M8b |
| 23m8c | Supervised Data Mining - SVMs | x | x | M8c | M8c |
| 23m9a | Unsupervised Data Mining - Clustering | x | x | M9a | M9a |
| 23m9c | Unsupervised Data Mining - SVD | x | x | M9c | M9c |
| 23m9d | Unsupervised Data Mining - SVD extensions | x | x | M9d | M9d |
| 23m9e | Single Cell Analysis | x | x | 23m9e | |
| 23t1 | Single Cell part 2 | x | x | 23t1 | |
| 23m10a | Networks - Intro | x | x | M10a | M10a |
| 23m10b | Networks - Network Quantities | x | x | M10b | M10b |
| 23m10c | Networks - Network Generation Models | x | x | M10c | M10c |
| 23m10d | Networks - Network Toplogy Analysis | x | x | M10d | M10d |
| 23m10e | Networks - Network Prediction | x | x | 23m10e | |
| 23i3 | Transition - Mining to Modeling | x | x | 23i3 | |
| 23t2 | Privacy in Biomedical Data Science (esp. Genomic Privacy) | x | x | ||
| 23t3 | Biosensor Analysis | x | x | 22m11 | |
| 23m12a | Deep Learning I | x | M12a | M12a | |
| 23m12b | Deep Learning II | x | M12b | M12b | |
| 23t4 | Deep Learning for Biology | x | 23t4 | ||
| 23s1 | Protein Folding | x | x | S1 | S1 |
| 23s2 | Core Repacking | x | x | S2 | S2 |
| 23s3 | NMR Structures | x | x | S3 | S3 |
| 23s4 | Intrinsically Disordered Proteins | x | x | S4 | S4 |
| 23s5 | Simulation |
See lab permissions statement in relation to resusing any of the above material.