The Independent Activities Period (IAP) is a special four-week term at MIT that runs from the first week of January until the end of the month. We offer both credit and non-credit opportunities.
For Credit
7.102 -- Introduction to Molecular Biology Techniques
Building 68, Room 089
Level: U | 6 units (0-5-1) | Can be repeated for credit.
Instructors: Prof. Adam Martin, Dr. Mandana Sassanfar
Prerequisites: None – Note that this course is not a substitute for 7.002 or 7.003
This intensive “boot-camp” style lab course introduces students to basic research and teach them many fundamental laboratory skills by providing hands-on instruction in basic molecular biology and microbiology techniques including sterile techniques, bacterial cultures, isolation and quantification of nucleic acid (DNA) and protein, agarose and SDS-PAGE gel electrophoresis, PCR, gene cloning, spectroscopy, microscopy, ultracentrifugation, DNA sequence analysis, and curve fitting using python. Students will learn to grow bacteria, purify viruses that infect bacteria using advanced techniques such as ultracentrifugation and learn about electron microscopy. Emphasis will be on real-world application in preparation for a successful UROP experience. This lab course will also improve students troubleshooting and problem-solving skills.
Priority will be given to freshmen with no prior research experience.
Participants are expected to spend every afternoon from 12:30 to 5pm in the lab. As in a real lab situation, some experiments will take longer than expected, or will need to be repeated. Students will work in teams (which makes it fun and enjoyable) and should divide work load.
Apply by November 28 by filling out this form and emailing it to Dr. Mandana Sassanfar. The class is limited to 16 students. No listeners. Applicants will be informed of their registration status by December 9.
Non-Credit
Skills to Enhance Your Career
“Smart Data Management for Biologists”
“Cultivating Everyday Mindfulness: Discovering Your Path to a Fulfilling Life and Career”
“Hatha Yoga Class (Bring your own mat)”
Hatha yoga is a mindful meditation practice that consists of gentle stretching, strengthening, and balancing exercises with a focus on awareness of the breath and sensations in the body. In this session, we will experiment with a series of restorative postures for the body and mind. Participants are expected to bring their own mats.
“Communicating your science visually”
In this interactive workshop, participants will learn how to use Adobe Illustrator and apply skills and tricks to present their research on slides, figures, or posters. With degrees in both science and art, Sebastian Lourido will equip participants with skills needed for illustrating their science and sharing it with the public. Participants are encouraged to bring a laptop with Adobe Illustrator already installed.
“Searching Successfully in PubMed”
“Quantitative Image Analysis”
Learn how to use CellProfiler, an open-source software for automated microscopy image analysis. This hands-on workshop introduces basic workflows and practical applications for beginners. Please bring a laptop with CellProfiler installed.
“New tools for managing scientific information”
As the volume of research information grows, tools for organizing, visualizing, and synthesizing data can spark new understanding. In this session, creators of innovative open science tools will share how their solutions can enhance your research workflows. Paricipants will gain hands-on exposure to new tools to benefit their research, as well as to learn about additional career opportunities in the computational tool development space.
Finding the Right Path for You
“Preparing for the Job Market: CVs and Resume”
This workshop will teach you the foundations of building a CV and resume for academic and non-academic jobs. At the end of the session, you will be able to identify the key differences and similarities found in these two documents and the purposes for using one versus the other. You will also learn how to tailor CVs and resumes based on job descriptions and how to adapt a CV into a resume. Please note this workshop focuses namely on U.S. versions of CVs and resumes.
“Taking science from bench to business”
“Preparing for the Job Market: Strategically Engaging in the Job Search”
This workshop focuses on strategically aligning your job search with your skills and interests. In this workshop, you will reflect on your own professional skills, interests, and goals to create a list of strengths and values. By identifying these priorities, you can then use this list to match yourself with jobs and ask specific, focused questions during job interviews. These strategies are applicable to both academic and non-academic job searches and are helpful across cultural contexts when pursuing career exploration.
“Teaching with a PhD”
Curious about careers in teaching? Join our panel of educators as they share their experiences teaching at different academic institutions. Learn firsthand about teaching-focused career paths and discover opportunities in higher education.
“Entering a Career Outside Academia”
Cellular Organization
“Probing mechanical selection through accurate prediction of DNA mechanics in 3D”
“Nucleic Acid-driven Self-Assemblies: from viral RNA sensors to transcription factors”
“Mechanisms of Aging: MICROS Complex and Mitochondrial Remodeling in Health and Disease”
Science and Society Seminar Series
This lecture series is designed to help educate and inform department members about the current and historical intersections of race, gender, and class with scientific research. Specifically, we are interested in exploring this area in terms of how scientific research is conducted, how choices are made about where research efforts and funds are directed, and who benefits from research. Attendance is required for first-year PhD students and is open to all in the Biology community.
All talks organized by Hallie Dowling-Francisco, Diversity, Equity, and Inclusion (DEI) Officer, and the Graduate Committee
“Complete erasure’ to ‘there is a place for us here’: How narratives in life science courses influence the experiences of trans-spectrum and intersex undergraduates”
Dr. Sarah Eddy
Associate Professor, Department of Biology Teaching and Learning, University of Minnesota-Twin Cities
Tuesday, January 21stat 1pm in 68-181
“The NIH Common Fund’s Replication to Enhance Research Impact Initiative”
The talk will cover the importance of reproducibility in scientific research, what the NIH Common Fund’s Replication Initiative is, what we hope to learn from the Replication Initiative, and discuss other NIH efforts to promote research rigor and reproducibility.
Dr. Rebecca Black
Health Science Policy Analyst, Office of Strategic Coordination, National Institutes of Heath
CANCELED
“Effective and Ineffective Mentorship: Utilizing the Power of Saying “No”
Dr. Antentor Hinton
Assistant Professor, Molecular Physiology and Biophysics, Vanderbilt University
Wednesday, January 29th at 1pm in 68-181
Python IAP Bootcamp
Course Information
Meeting times: Tuesdays/Thursdays January 7th – 30th
- Sessions 1-4: 3:30 – 4:30 pm
- Sessions 5-8: 3:30 – 5 pm
*Please note the change in end time*
Classroom: 52-124 (Stata center)
Instructor Information
Julia Dierksheide (she/her) and Hannah LeBlanc (she/they)
Julia’s email: kjulia@mit.edu
Hannah’s email: leblanch@mit.edu
Feel free to reach out with any questions or concerns!
Course description
This Python bootcamp is designed to introduce students to the basics of computer programming, with a focus on the skills required to use Python for data analysis applications in biological research. Over the course of eight sessions, students will learn how to leverage Python’s functionality to manipulate and visualize biological datasets, using packages such as numpy and pandas that are frequently used in bioinformatics and computational biology. No prior coding experience is required.
The bootcamp is specifically intended for first-year biology students who will enroll in 7.571-2, and we will focus on the skills required to successfully complete the coursework. However, we think that the concepts covered in the bootcamp will be broadly applicable to anyone looking to use Python to analyze and visualize data. Please reach out to us if you’d like to talk more about whether this bootcamp is for you!
If you are already familiar with programming Python, but would like to develop familiarity with the use of Python for data analysis and visualization, we recommend that you join us for the later sessions (7 and 8). It may also be useful to refer to Problem Set 0, which was designed to assess preparedness for the Python coding skills required for 7.571-2.
Intended Learning Outcomes
By the end of the bootcamp, students will be able to:
- Read code
- Identify code blocks within a program and annotate the function of each block (variables, conditional statements, loops, etc.)
- Given a program with or without annotations, describe the overall purpose of the program and predict the outputs for given inputs.
- Use function documentation to apply pre-written functions or packages.
- Troubleshoot code
- Read error codes to identify the location and reason for the error in the code.
- Write tests for code to check it is performing as expected for all possible inputs.
- Use resources such as ChatGPT and Stack Exchange to diagnose and fix errors.
- Write code
- Use google collab notebooks to run Python code
- Apply the process of pseudocoding to break down a high-level goal for a program into a sequence of smaller coding tasks.
- Use basic functionality in Python to analyze data:
- Define variables, write conditional (if/then/else) statements, define lists, arrays, and dictionaries.
- Write and document functions.
- Perform basic data analysis (ie. compute summary statistics) and visualization using numpy, pandas, matplotlib, and seaborn packages.
Describe the pros and cons of possible data representations and identify the optimal data representation for a given task
What to expect in this bootcamp
This bootcamp will take the form of a flipped classroom, where students will be expected to watch a few short (5-10 minute) videos before each session. During class time, students will work in small groups to complete a set of exercises that draw on the material covered in the videos. Course instructors will be available for support as questions arise.
Students will be expected to bring their own laptop to each session – ideally charged, it looks like outlets are limited in the classroom.
Course schedule (topics subject to change)
Day 1: Tuesday, January 7th 3:30 – 4:30pm (52-124)
- Goal setting
- Introduction to Google collab notebooks
- Computing basics and variables
- Additional resources: Variables
Day 2: Thursday, January 9th 3:30 – 4:30pm (52-124)
- Logic operators (>, <, ==, etc.)
- If/else statements
- Additional resources: Conditional statements and operators
Day 3: Tuesday, January 14th 3:30 – 4:30pm (52-124)
Day 4: Thursday, January 16th 3:30 – 4:30pm (52-124)
- Lists and dictionaries
- Additional resources: Lists (section 3.1), Dictionaries
Day 5: Tuesday, January 21st 3:30 – 5pm (52-124)
- Using functions
- Reading function documentation
- Additional resources: Functions
Day 6: Thursday, January 23rd 3:30 – 5pm (52-124)
- Writing functions and testing code
- Troubleshooting and reading errors
- Additional resources: Functions
Day 7: Tuesday, January 28th: 3:30 – 5pm (52-124)
- Numpy arrays
- Pandas dataframes
- Additional resources: Arrays (section 3.2), More arrays, Dataframes
Day 8: Thursday, January 30th: 3:30 – 5pm (52-124)
- Data visualization and plotting
- Additional resources: Plotting, More plotting
Getting ahead
The bootcamp will move somewhat quickly, so if you have very little coding experience and want to dip your toes in over break, it could be useful to read through some of the material listed as additional resources in the course schedule above. But this is absolutely not required!