Methods in Quantitative Biology Fall 2020
 
 
The Sackler Institute of Graduate Biomedical Sciences at NYU School of Medicine
 
Methods in Quantitative Biology (BMSC-GA 4449) and Methodological Foundations of BMI (BMIN-GA 1001) Fall 2020

Course Directors:
David Fenyö (David@FenyoLab.org)
Mark Grivainis (Mark.Grivainis@nyulangone.org)

Teaching Assistant:
Cooper Devlin (jcooperdevlin@gmail.com)
Grant Hussey (Grant.Hussey@nyulangone.org)

Course Overview

This course provides an overview of foundational knowledge and essential methods relevant for all areas of biomedical informatics. Students will explore recurring themes and application domains most frequently used in the field. The course will be technical and rigorous, and it will include a number of computer science topics. The course content has been selected by the curriculum committee, and the topics will change over time. The majority of the coursework will be programming assignments and readings.

Learning objectives

The student will learn and understand the most commonly used methodologies in the field of biomedical informatics.

Programming Languages

Working knowledge of R and Python is required:

Course Assessment
  • Programming Assignments (40%).
  • Discussions (40%)
  • Participation and Quizzes (20%)
Lectures

Lecture 1 Introduction (September 10, 2020, 5:30-7pm)
Lecturer: Devlin, Fenyo, Grivainis & Hussey

Lecture 2 Biomedical Data: NYU Data Catalog (September 15, 2020, 5:30-7pm)
Lecturer: Contaxis

Lecture 3 Biomedical Data: Molecular Data Lab I (September 17, 2020, 5:30-7pm)
Lecturer: Devlin
Reading List
  • Karczewski and Snyder. Integrative omics for health and disease. (2018) Nature Reviews


    Lecture 4 Biomedical Data: Molecular Data Lab II (September 22, 2020, 5:30-7pm)
    Lecturer: Devlin

    Lecture 5 Biomedical Data: Clinical Data (September 24, 2020, 5:30-7pm)
    Lecturer: Iturrate
    Reading List
  • Coorevits et al., Electronic health records: new opportunities for clinical research. (2013) Journal of Internal Medicine


    Lecture 6 Biomedical Data: Institutional Review Board (September 29, 2020, 5:30-7pm)
    Lecturer: More

    Lecture 7 Statistics I: Overview (October 1, 2020, 5:30-7pm)
    Lecturer: Hussey

    Reading List
  • Statistics for Biologists


    Lecture 8 Statistics II (October 6, 2020, 5:30-7pm)
    Lecturer: Hussey

    Lecture 9 Statistics III (October 8, 2020, 5:30-7pm)
    Lecturer: Hussey

    Lecture 10 Statistics IV (October 13, 2020, 5:30-7pm)
    Lecturer: Hussey

    Lecture 11 Biomedical Data: Clinical Data Lab (October 15, 2020, 5:30-7pm)
    Lecturer: Grivainis

    Lecture 12 Modeling/Simulation - COVID-19 Transmission (October 20, 2020, 5:30-7pm)
    Lecturer: Hussey & Cooper

    Lecture 13 Modeling/Simulation - COVID-19 Transmission (October 22, 2020, 5:30-7pm)
    Lecturer: Hussey & Cooper

    Lecture 14 Modeling/Simulation - Bacterial Interactions I (October 27, 2020, 5:30-7pm)
    Lecturer: Grivainis
    Reading: Kelsic ED, Zhao J, Vetsigian K, Kishony R: Counteraction of antibiotic production and degradation stabilizes microbial communities, Nature. 2015 May 28;521(7553):516-9.

    Lecture 15 Modeling/Simulation - Bacterial Interactions II (October 29, 2020, 5:30-7pm)
    Lecturer: Grivainis

    Lecture 16 Signal Processing: 1D (November 3, 2020, 5:30-7pm)
    Lecturer: Fenyo

    Lecture 17 Signal Processing - 2D (November 5, 2020, 5:30-7pm)
    Lecturer: Keegan

    Lecture 18 Signal Processing - NLP (November 10, 2020, 5:30-7pm)
    Quiz 5 (Signal Processing)
    Lecturer: Devlin

    Lecture 19 Data Visualization - Discussion (November 12, 2020, 5:30-7pm)
    Lecturer: Ruggles

    Reading List
  • Nature Methods Points of View
  • Assignment: Based on best-practices described by the reading, find a figure from a publication that you feel is particularly good. Each student will present 2 minutes on why their figure is the best choice and students will vote on their top pick.


    Lecture 20 Data Visualization - Illustrator Lab (November 17, 2020, 5:30-7pm)
    Lecturer: Devlin

    Reading List
  • Assignment: Given this figure, improve the formatting and layout of the figure and add a schematic drawing of the associated cellular pathway.


    Lecture 21 Data Visualization - Interactive (November 19, 2020, 5:30-7pm)
    Lecturer: Grivainis

    Lecture 22 Topics in data analysis (November 24, 2020, 5:30-7pm)
    Lecturer: Yanai

     

     

     

     

     

     

     

     

     

     

     

     

     

     

     

     

     

     

     

     

     

     

     

     

     

     

     

     

     

     

     

     

     

     

     

     

     

     

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