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.
Topic | 2025 Spring’s Lecture | 2023 Spring’s Lecture | Comment | Lecture Summary | |
---|---|---|---|---|---|
1/13 | *YALE* Spring term classes begin, 8.20 a.m. | ||||
1/13 | Introduction | 25i1-25i2a | 23i1, 23i2a | ||
1/15 | DATA - Proteomics I | 25d3 | 23d3 | Suggested Reading | 25d3 |
1/22 | DATA - Proteomics II | 25d4 | 23d4 | Suggested Reading | 25d4 |
1/27 | DATA - Genomics I | 25d1 | 23d1 | 25d1 | |
1/29 | DATA - Genomics II | 25d2 | 23d2 | 25d2 | |
2/3 | DATA - Knowledge Representation & Databases | 25d5 | 23d5 | 25d5 | |
2/5 | MINING - Personal Genomes + Seq. Comparison | 25i2b,25m3 | 23i2b,23m3 | ||
2/10 | MINING - Seq. Comparison (con’t) + Multi-seq Alignment + Fast Alignment | 25m3, 25m4, 25m5 | 23m3, 23m4, 23m5 | ||
2/12 | MINING - Variant Calling (incl. a focused section on SVs)+ Basic Multi-Omics | 25m6a,23m6b, 23m7-pt1 | 23m6a, 23m6b,23m7 | ||
2/17 | Quiz on 1st Half | quiz1 study guide | |||
2/19 | MINING - Supervised Mining #2 + Deep Learning Fundamentals #1 | 23m8b,23m8c | |||
2/24 | MINING - Deep Learning Fundamentals #2 + Unsupervised Mining #1 | 23m9a,23m9c | |||
2/26 | MINING - Unsupervised Mining #2 + Single-Cell Analysis #1 | 23m9d, 23m9e | |||
3/3 | MINING - Single-Cell Analysis #2 + Biomedical Image Analysis | 23t1 | |||
3/5 | MINING - Network Analysis | 23m10a, 23m10b, 23m10c, 23m10d, 23m10e | |||
3/7 | Spring break begins | ||||
3/24 | MINING - Privacy | 23m11a, 23m11b | |||
3/26 | MINING/MODELING - Deep Learning Advanced I | 23m12a | |||
3/31 | MINING/MODELING - Deep Learning Advanced II | 23m12b | |||
4/2 | SIMULATION - Protein Simulation I | 23s1 | |||
4/7 | SIMULATION - Protein Simulation II | 23s2 | |||
4/9 | SIMULATION - Protein Simulation III | 23s3 | |||
4/14 | SIMULATION - Protein Simulation IV | 23s4 | |||
4/16 | SIMULATION - Protein Simulation V | 23s5 | |||
4/21 | Quiz on 2nd Half | ||||
4/23 | Final Presentations | ||||
4/25 | *YALE* Classes end; Reading period begins | ||||
5/1 | *YALE* Final examinations begin | ||||
5/7 | *YALE* Final examinations end |
Lecture Slide Pack
Lecture Slide Pack and Video | |||||
---|---|---|---|---|---|
# | Topic | PPT | Youtube (‘21 unless indicated otherwise) |
MPEG (2021) | |
25i1 | Introduction to Biomedical Data Science | x | x | I1 | I1 |
25i2a | Introduction to Personal Genomes | I2a | |||
25i2b | An Individual’s Perspective on Personal Genomes | x | x | I2b | i2b |
23d3 | DATA - Proteomics I - Proteins | x | D3 | ||
23d4 | DATA - Proteomics II - Structure | x | D4 | ||
25d1 | DATA - Genomics I | x | D1 | D1 | |
25d2 | DATA - Genomics II | x | D2 | D2 | |
25d5 | Knowledge Representation & Databases | x | D5 | D5 | |
25m3 | Sequence Comparison | x | x | M3 | M3 |
25m4 | Multiple Sequence Comparison | x | x | M4 | M4 |
25m5 | Fast Alignment | x | x | M5 | M5 |
25m6a | Variant Identification | x | x | M6a | M6a |
25m6b | 1000 Genome + PCAWG summary | x | x | M6b | M6b |
25m7 | Basic Pipeline Processing for Genomics & Multi-omics | part1 | part1 | M7 | M7 |
25m8a | Supervised Data Mining - Decision Trees | M8a | M8a | ||
25m8b | Supervised Data Mining - ROC & Cross-validation | M8b | M8b | ||
25m8c | Supervised Data Mining - SVMs | M8c | M8c | ||
25t3 | Deep Learning Fundamentals I | ||||
25t4 | Deep Learning Fundamentals II | ||||
25m9a | Unsupervised Data Mining - Clustering | M9a | M9a | ||
25m9c | Unsupervised Data Mining - SVD | M9c | M9c | ||
25m9d | Unsupervised Data Mining - SVD extensions | M9d | M9d | ||
25m9e | Single Cell Analysis | 23m9e | |||
25t1 | Single Cell part 2 (mabye should renumber this!!) | 23t1 | |||
25m10a | Networks - Intro | M10a | M10a | ||
25m10b | Networks - Network Quantities | M10b | M10b | ||
25m10c | Networks - Network Generation Models | M10c | M10c | ||
25m10d | Networks - Network Toplogy Analysis | M10d | M10d | ||
25m10e | Networks - Network Prediction | 23m10e | |||
25i3 | Transition - Mining to Modeling | 23i3 | |||
25m11a | Privacy in Biomedical Data Science (esp. Genomic Privacy) | ||||
25m11b | Privacy in Biomedical Data Science (esp. Genomic Privacy) | ||||
25t2 | Image Analysis | 22m11 | |||
25m12a | Deep Learning III | M12a | M12a | ||
25m12b | Deep Learning IV | M12b | M12b | ||
25s1 | Protein Folding | S1 | S1 | ||
25s2 | Core Repacking | S2 | S2 | ||
25s3 | NMR Structures | S3 | S3 | ||
25s4 | Intrinsically Disordered Proteins | S4 | S4 | ||
25s5 | Simulation |
See lab permissions statement in relation to resusing any of the above material.