BMI Course

Course Name: Analysis and Applications of Genome‐Scale Data

Course Number: BMI 8130

Classroom: Biological Sciences Bldg 676

Time: Autumn, 2019; Tuesday & Thursday, 9:35‐10:55 am

Director: Kin Fai Au and Qin Ma

TA: Tara Eicher (

TA Office Hour: 9:00 – 10:00 A.M, Monday

TA Desk: 340-09 Lincoln Tower

Introduction: The goal of this course is to introduce trainees to the fundamental algorithms and data analysis skills needed to understand and analyze genome-scale data sets, including genomics, transcriptomics, epigenetics, single-cell sequencing data and long-read sequencing data. For each data types, the course will cover the fundamental algorithms and software usage, including three major kinds of applications: (1) Class Comparison seeks to describe which features differ between two or more known classes of patient samples (such as differential expression for normal vs. tumor). (2) Class Discovery seeks to discuss the inherent structure present in a data set (such as t-SNE and principal component analysis for cell clustering based on single-cell RNA-seq). (3) Class Prediction seeks to discover and validate models that can accurately predict the class or the outcome of new samples (such as prediction of methylation status). The course will include an introduction to, and hands-on experience with, the R statistical software and Linux environment and to the use of R packages that can be applied to these kinds of problems.

Course Name: Fundamentals of Grant Writing

Course Number: BSGP 7070

Time: Autumn, 2019; Monday, 3:00‐5:30 pm

Director: Qin Ma

Learning Objectives:

  • Understand basic grant writing steps and procedures.
  • Define a single overall goal for your research project that is attainable.
  • Define the gap in knowledge that prevents getting to your goal.
  • Propose an objective that defines what your study will produce to fill gap and attain goal.
  • Establish a hypothesis that is linked to the objective and is your “best bet answer”.
  • Propose aims that test the hypothesis and are related to your overall goal and objective.
  • Develop a research strategy and define expected outcomes and limitations.
  • Learn to think like a reviewer.
  • Create a grant application for submission and review by your peers.