EDUCATION

Democratizing science education & training, leveling playing fields, and improving access to (& entry into) our work are intertwined core values of our group.

We actively engage in a number of education and outreach activities such as teaching non-traditional courses, offering professional development workshops to graduate students & postdocs, supporting diversity/inclusion initiatives, and giving public talks/lectures about our research.

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Teaching: Courses, Workshops

 
Bioiformatics and Computational Biology Course at Michigan State University

Bioinformatics and Computational Biology

CMSE 410-890 | This course is an introduction to the inner-workings of methods in bioinformatics and computational biology: analytical techniques, algorithms, and statistical/machine-learning approaches developed to address key questions in biology and medicine. In this course, students will also learn how to formulate problems for quantitative inquiry, design computational projects, think critically about data & methods, do reproducible research, and communicate findings.

Prerequisites: Programming experience + Introductory biology; Intro stats recommended

SPRING 2020

Schedule: MWF 11:00am-12:10pm

Location: 351 Natural Sciences Building

Gaps, Missteps, and Errors in Statistical Data Analysis

This is a short (1-credit) intermediate-to-advanced course designed to:
1) Discuss common misunderstandings & typical errors in the practice of statistical data analysis.
2) Provide a mental toolkit for critical thinking and enquiry of analytical methods and results.
Classes will involve lectures, discussions, hands-on exercises, and homework about concepts critical to the day-to-day use and consumption of quantitative/computational techniques.

Topics include:

Underpowered statistics • Pseudoreplication • P-hacking & multiple hypothesis correction • Difference in significance & significant differences • Base rates & permutation tests • Regression to the mean • Descriptive statistics & spurious correlations • Estimation of error and uncertainty • (Others under consideration; Subject to small changes)

Prerequisites:
This course builds on your introductory knowledge of statistics and programming. We will assume: 1) Familiarity with basic statistics & probability. 2) Ability to do basic data wrangling, analyses, & visualization using R or Python.
• Strongly recommended MSU courses: CMSE 201 and CMSE 890 Sec 301-or-304 and Sec 302.
• Contact Arjun for pointers to free online preparatory resources.

FALL 2019

Dates: Nov 6 – Dec 4 | Final exams: Dec 5 and 6

Schedule: Mon/Wed 3:00-4:50 p.m.

Location: A158 Plant & Soil Science Bldg

Modular Courses in Bioinformatics

We offer several modular bioinformatics courses each semester including:

  1. R Programming for Bioinformatics

  2. Python & HPCC for Bioinformatics

  3. Statistical Analysis and Visualization

  4. Transcriptomic Data Analysis


The bioinformatics modules are a set of introductory courses that help life science students learn basic skills in computation and bioinformatics. These modules are 1 graduate credit, one month long, and (mostly) flipped classroom (students watch video lectures online for homework and then come to class to solve problems and ask questions). Postdocs, staff, visiting scholars, faculty, and other MSU-affiliates who are not students can audit these modules for a nominal fee. Contact the Bioinformatics Program Coordinator to register. Undergraduates at the junior/senior level who wish to take the modules should also contact the Coordinator to discuss their eligibility. Undergraduates who are taking the CMSE minor and wish to take the modules should contact the CMSE Undergraduate Director.

[Past] Introduction to Computational Modeling & Data Analysis

In Fall 2019, Arjun taught CMSE’s flagship undergraduate course that uses the flipped class model to teach various aspects of computational science, a variety of practical, fundamental computational skills, and application-driven modeling of various systems, with applications to the physical, life, and social sciences, and also to engineering and mathematics. Each class throughout this course involves a range of activities – primarily by writing software both individually and in small groups, but also through discussion, presentations, and other types of exercises.

FALL 2019

Schedule: TTh 4:10pm-6:00pm

Location: 38 McDonel

[Past] University-wide Bioinformatics Workshops at MSU

In Spring 2017, I helped design the Modular Courses in Bioinformatics at CMSE and then piloted all the materials by conducting three 1-week Bioinformatics Workshops in Summer 2017. These bioinformatics workshops provided hands-on training in Linux/R/Python programming, Statistical data analysis and visualization, and Analysis of various types of genomic data (e.g. RNA-seq) to 32 members of the MSU community including undergraduates, PhD students, and faculty members. These course materials form the basis of the 1-credit Bioinformatics modular course subsequently taught every semester by others starting Fall 2017, which up to now has been taken by 142 students.
 

SUMMER 2017

Schedule: 8:30am - 12:30pm, Monday through Friday.

Location: 1502/1503 Engineering Building.

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Professional Development

 

Surviving and excelling in your PhD

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Planning and executing an effective postdoc

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Faculty job search

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Outreach

 

R-Ladies East Lansing

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Public Talks/Lectures

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K-12 Engagement

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