Syllabus

Readings and assignments should be completed before each class session. Assignments, and instructions for submitting assignments, can be found at at the Assignments page.

Date Number Topic Reading Video Slides+ Assignment Solutions
Part I Data Science
Sept 8 L0 Introduction and orientation
Sept 10 L1 Information technology for managing science
Sept 15 L2 Modern computing paradigms
Sept 17 L3 Visualizing breast cancer transcriptomes
Sept 22 L4 Representing & manipulating data
Sept 24 L5 Transformations of breast cancer transcriptomes
Sept 28 -- Assignment 1 due
Sept 29 L6 Exploratory data analysis of breast cancer transcriptomes
Part II Bioinformatics
Oct 1 L7 The NCBI: a rich resource for the life sciences
Oct 6 L8 How to wrangle with marine microbes
Oct 8 -- Midterm 1 (1hr; open book; Zoom)
Oct 13 L9 Organzing the Tara Ocean’s data
Oct 15 L10 Exploring microbial diversity across our oceans
Oct 19 -- Assignment 2 due
Oct 20 L11 Representing genomes in R
Oct 22 L12 Genome annotations
Oct 22 -- Quiz 2
Oct 22 -- Project outline due for genomics diploma and grad students (1 page)
Part III Computational Biology
Oct 27 L13 Transcription factor binding sites in Baker’s yeast
Oct 26 -- Quiz 3
Oct 29 -- Midterm 2 (1hr, open book, Zoom)
Nov 3 L14 Gene finding with Hidden Markov Models
Nov 5 L15 Gene finding continued
Nov 5 -- Quiz 4
Nov 9 -- Assignment 3 due
Nov 10 L16 Models of sequence evolution
Nov 12 L17 Phylogenies and alignments
Nov 12 -- Quiz 5
Nov 17 L18 Basics of machine learning
Nov 19 L19 Discovery breast cancer subtypes: unsupervised analysis
Nov 19 -- Quiz 6
Nov 24 L20 Predicting breast cancer patient outcome from expression data: supervised analysis
Nov 26 L21 Deep learning: proliferative index of a cancer cell with microscopy
Nov 26 -- Quiz 7
Nov 27 -- Assignment 4 due
Dec 1 L22 Computational challenges of single cell profiling
Part IV Reproducible Science and Communication
Dec 3 L23 Reproducibility in life science research
Dec 10 -- Project due
Dec TBA -- Final (2hr, take home, open book)