BF528 - Applications in Translational Bioinformatics

Welcome to the homepage of BF528.

Meeting time: Monday/Friday 10:10-11:55

Location: EPC 207 and Zoom

Office hours: By appointment


The objective of this course is expose students to the topics and technologies used in modern bioinformatics studies. The course covers a mix of biological and computational topics, including:

  • High throughput genomics techniques (microarrays, 2nd generation sequencing)
  • Current high throughput sequencing assays (DNA-Seq, RNA-Seq, ChIP-Seq)
  • Differential gene expression techniques
  • Microbiome/metagenomics techniques
  • Metabolomics
  • Proteomics
  • Systems, network, and integrative biology
  • Basic linux cluster usage
  • Python and R scripting
  • Computational workflow and replication strategies
  • Genomics data visualization techniques
  • Biological databases

This is highly hands-on course, where a portion of in-class periods are dedicated to concerted group work and interactive discussions. The course materials are focused on real-world applications of the high throughput genomics techniques and organized into structured group projects. Students are organized into groups of three or four for the entire semester, where they will work together to replicate results from published studies. The tasks for each project have been divided into four ‘roles’:

Data curator: identify, download, and describe relevant datasets and literature

Programmer: write code to transform the downloaded data into an interpretable form

Analyst: examine and visualize processed data to aid in interpretation

Biologist: connect the processed data into meaningful biological interpretation

Each group will complete four projects over the course of the semester, and for each project the roles of the members rotate, such that each member fulfills each role once. Each group will produce a full report describing their work on each project, including biological background, methods, results, and interpretation.

The first half of each in-class period will be dedicated to interactive discussions on special topics germane to the project material. The second half is dedicated to either special topics as indicated in the schedule below, or to discussion of the projects, sharing ideas, and communicating challenges both within and between groups, with the assistance of the instructors.

There are no homeworks or exams, only projects.

Course Values, and Policies

Everyone is welcome. Every background, race, color, creed, religion, ethnic origin, age, sex, sexual orientation, gender identity, nationality is welcome and celebrated in this course. Everyone deserves respect, patience, and kindness. Disrespectful language, discrimination, or harassment of any kind are not tolerated, and may result in removal from class or the University. This is not merely BU policy. The instructors deem these principles to be inviolable human rights. Students should feel safe reporting any and all instances of discrimination or harassment to the instructor, to any of the Bioinformatics Program leadership, or the BU Equal Opportunity Office.

Everyone brings value. Each of us brings unique experiences, skills, and creativity to this course. Our diversity is our greatest asset.

Collaboration is highly encouraged. All students are encouraged to work together and seek out any and all available resources when completing projects in all aspects of the course, including sharing both ideas and code as well as those found on the internet. Any and all available resources may be brought to bear. However, consistent with BU policy, your reports should be written in your own words and represent your own work and understanding of the material.

A safe space for dissent. For complex topics such as those covered in this class, there is seldom one correct answer, approach, or solution. Disagreement fosters innovation. All in the course, including students and TAs, are encouraged to express constructive criticism and alternative ideas on any aspect of the content.

We are always learning. Our knowledge and understanding is always incomplete. Even experts are fallible. The bioinformatics field evolves rapidly, and “Rome was not built in a day.” Be kind to yourself and to others. You are always smarter and more knowledgable today than you were yesterday.


Basic understanding of biology and genomics. Any of these courses are adequate prerequisites for this course: BF527, BE505/BE605. Students should have some experience programming in a modern programming language (R, python, C, Java, etc).


Adam Labadorf

My pledge to foster Diversity, Inclusion, Anti-racism

This course is a judgement free and anti-racist learning environment. Our cohort consists of students from a wide variety of social identities and life circumstances. Everyone will treat one another with respect and consideration at all times or be asked to leave the classroom.

As instructor, I pledge to

  1. Learn and correctly pronounce everyone’s preferred name/nickname
  2. Use preferred pronouns for those who wish to indicate this to me/the class
  3. Work to accommodate/prevent language related challenges (for instance I will do my best to avoid the use of idioms and slang)

Project Overview

The four projects are as follows:

  1. Microarray Based Tumor Classification
  2. Transcriptional Profile of Mammalian Cardiac Regeneration with mRNA-Seq
  3. Concordance of microarray and RNA-Seq differential gene expression
  4. Single Cell RNA-Seq Analysis of Pancreatic Cells
  5. Individual Project

In the individual project, you will choose (at least) two roles from any of the projects that you did not previously do. This will give you an opportunity to gain experience with tools and skills you may have missed while playing other roles.

The roles in each project require varying amounts of effort. Since you must do each role exactly once, below is information about the rating of each role in each project with respect to the amount of computational skill/time commitment required to help you choose your sequence of roles:

Role Project 1 Project 2 Project 3 Project 4
Data Curator ⚫ ⚪ ⚪ ⚪ ⚫ ⚫ ⚪ ⚪ ⚫ ⚫ ⚪ ⚪ ⚫ ⚫ ⚫ 🔴
Programmer ⚫ ⚪ ⚪ ⚪ ⚫ ⚫ ⚪ ⚪ ⚫ ⚫ ⚫ ⚪ ⚫ ⚫ ⚪ ⚪
Analyst ⚫ ⚫ ⚪ ⚪ ⚫ ⚪ ⚪ ⚪ ⚫ ⚫ ⚫ ⚪ ⚫ ⚫ ⚫ ⚪
Biologist ⚫ ⚪ ⚪ ⚪ ⚫ ⚪ ⚪ ⚪ ⚫ ⚪ ⚪ ⚪ ⚫ ⚫ ⚪ ⚪
⚫ ⚪ ⚪ ⚪ – least skill required; ⚫ ⚫ ⚫ 🔴 – most skill required

Taking these ratings into account, we provide four possible sequences for each member of each group. Sequence 1 through 4 involve increasingly difficult computational tasks:

  Project 1 Project 2 Project 3 Project 4
Sequence 1 Programmer Analyst Data Curator Biologist
Sequence 2 Data Curator Biologist Analyst Programmer
Sequence 3 Biologist Data Curator Programmer Analyst
Sequence 4 Analyst Programmer Biologist Data Curator

These are only suggestions. These suggested sequences also only reflect the computational skill involved in each role; those with less biological background may find the biologist roles more conceptually challenging.

Project guidelines for group reports (1, 2, 3, and 4) are here: Project Writeup Instructions

Grading and Assessment

Group report assessment will be the same for all group members. Assessment is made based on the process completed by the group, not whether the study results were successfully replicated or not. Each students’ grade may be adjusted based upon the quality of their final individual project relative to their group reports.


Important: Note that some weeks have a secondary topic and others do not. In weeks with a secondary topic, class is split into two lectures. In weeks without a secondary topic, the second half of class is allocated for you to work together in your groups/roles and with your TA. Days without a secondary topic will be delivered via zoom only to facilitate these interactions.

Class Day Date Topic Secondary Project Out/Due
1 Fri 1/21/2022 Introduction Command Line Interface  
2 Mon 1/24/2022 Genomics, Genes, and Genomes Cluster Usage  
3 Fri 1/28/2022 Array Technologies git 1
4 Mon 1/31/2022 Gene sets and enrichment R+RStudio Primer  
5 Fri 2/4/2022 2nd Gen Sequencing    
6 Mon 2/7/2022 Sequence Analysis Fundamentals    
7 Fri 2/11/2022 Sequence Analysis - RNA-Seq 1    
8 Mon 2/14/2022 Sequence Analysis - RNA-Seq 2    
9 Fri 2/18/2022 Genomic Variation and SNP Analysis Project 1 Review 1/2
10 Tue 2/22/2022 Biological Data Formats Genome Browsers  
11 Fri 2/25/2022 Sequence Visualization    
12 Mon 2/28/2022 Sequence Analysis - ChIP-Seq    
13 Fri 3/4/2022 Biological Databases    
  Mon 3/7/2022 Spring Break    
  Fri 3/11/2022 Spring Break    
14 Mon 3/14/2022 Replicability vs Reproducibility Strategies    
15 Fri 3/18/2022 Computational Environment Management Project 2 Review 2/3
16 Mon 3/21/2022 Computational Pipeline Strategies Conda+Snakemake  
17 Fri 3/25/2022 Single Cell Techniques    
18 Mon 3/28/2022 Single Cell Analysis Part 1    
19 Fri 4/1/2022 Single Cell Analysis Part 2    
20 Mon 4/4/2022 Microbiome: 16S    
21 Fri 4/8/2022 Microbiome: Metagenomics Project 3 Review 3/4
22 Mon 4/11/2022 Proteomics Something Fancy  
23 Fri 4/15/2022 Metabolomics    
24 Wed 4/20/2022 Integrative Genomics    
  Fri 4/22/2022 Project work, no class    
  Mon 4/25/2022 TBD    
  Fri 4/29/2022 TBD Project 4 Review 4/5
28 Mon 5/2/2022 The Future + retrospective, end of classes    
  Fri 5/13/2022 Final projects due   5