Syllabus

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# Day Date Topic
M 2/1 -- *YALE* Spring term classes begin, 8.20 a.m.
1st Half
1 M 2/1 MG Introduction
2 W 2/3 MDS DATA 1 - Genomics I
3 M 2/8 MDS DATA 2 - Genomics II
4 W 2/10 JR DATA 3 - Proteomics I
5 M 2/15 JR DATA 4 - Proteomics II
6 W 2/17 KC DATA 5 - Knowledge Representation & Databases
M 2/22 -- *YALE* First break day
7 W 2/24 MG MINING 1 - Personal Genomes Intro. (with an individual's perspective)
8 M 3/1 MG MINING 2 - Seq. Comparison + Multi-seq Alignment
9 W 3/3 MG MINING 3 - Fast Alignment + Variant Calling (incl. a focused section on SVs)
10 M 3/8 MG MINING 4 - Basic Multi-Omics + Supervised Mining #1
11 W 3/10 MG+TF Quiz on 1st Half
12 M 3/15 MG MINING 5 - Supervised Mining #2 + Unsupervised Mining #1
13 W 3/17 MG MINING 6 - Unsupervised Mining #2 + Network Analysis #1
14 M 3/22 DG MININIG 7 - Privacy
W 3/24 -- *YALE* Third break day
15 M 3/29 MG+TF TF short lecture + Network Analysis #2
2nd Half
16 W 3/31 RM MINING 8 - Deep Learning I
17 M 4/5 RM Deep Learning II
18 W 4/7 RM Deep Learning III
19 M 4/12 MG+TF TF short lecture + Guest Lecture
20 M 4/19 CO Protein Simulation I
21 W 4/21 CO Protein Packing
22 Th 4/22 CO Protein Packing
23 M 4/26 CO Protein Simulation II
24 W 4/28 CO+TF Q & A on Simulation
25 M 5/3 MG+TF Quiz on 2nd Half
26 W 5/5 MG Final Presentations
F 5/7 -- *YALE* Classes end; Reading period begins
Th 5/13 -- *YALE* Final examinations begin
W 5/19 -- *YALE* Final examinations end
Lecture Slide Pack and Video
# Topic PDF PPT Youtube MPEG
INTRO 2/1 I1 Introduction to Biomedical Data Science x x x x
INTRO 2/24 I2a Introduction to Personal Genomes x x x x
INTRO 2/24 I2b A subject perspective on the personal genome x x x x
DATA 2/3 D1 Genomics I x x x
DATA 2/8 D2 Genomics II x x x
DATA 2/10 D3 Proteomics I x x x
DATA 2/15 D4 Proteomics II x x x
DATA 2/17 D5 Knowledge Representation & Databases x x x
MINING 3/1 M3 Pairwise Sequence Comparison x x x x
MINING 3/1 M4 Multiple Sequence Comparison x x x x
MINING 3/3 M5 Fast Alignment x x x x
MINING 3/3 M6a Variant Identification, Focusing on SVs x x x x
MINING 3/8 M6b 1000 Genome + PCAWG summary x x x x
MINING 3/8 M7 Basic Multi-omics (pipeline processing) x x x x
MINING 3/8 M8a Supervised Data Mining - Decision Trees x x x x
MINING 3/15 M8b Supervised Data Mining - ROC & Cross-validation x x x x
MINING 3/15 M8c Supervised Data Mining - SVMs x x x x
MINING 3/15 M9a Unsupervised Data Mining - Clustering x x x x
MINING 3/15 M9b Unsupervised Data Mining - Community Detection x x x x
MINING 3/17 M9c Unsupervised Data Mining - SVD x x x x
MINING 3/17 M9d Unsupervised Data Mining - RCA & CCA x x x x
MINING 3/17 M9e Unsupervised Data Mining - tSNE & LDA x x x x
MINING 3/29 M10a Networks - Introduction x x x x
MINING 3/29 M10b Networks - Network Quantities x x x x
MINING 3/29 M10c Networks - Network Generation Models x x x x
MINING 3/29 M10d Networks - Central Points x x x x
MINING 3/22 M11 Privacy x x x
MINING 3/31 M12a Deep Learning I x x x
MINING 4/5 M12b Deep Learning II x x x
MINING 4/7 M12c Deep Learning III x x x
MINING 4/12 M13a Applying Deep Learning to Textmining (Mining biological literature) x x x
MINING 4/12 M13b Applying Deep Learning to Regulatory & Single Cell Genomics x x x
SIMULATION 4/19 S1 Analysis of Globular Protein Structure x x x
SIMULATION 4/21 S2a Random close packing in protein cores #1 x x x
SIMULATION 4/22 S2b Random close packing in protein cores #2 x x x
SIMULATION 4/26 S3 Molecular simulations of intrinsically disordered proteins x x x