The course, which spans two thirds of a semester, provides students with a research-inspired laboratory experience that introduces standard biochemical techniques in the context of investigating a current and exciting research topic, acquired resistance to the cancer drug Gleevec. Techniques include protein expression, purification, and gel analysis, PCR, site-directed mutagenesis, kinase activity assays, and protein structure viewing.
This class is part of the new laboratory curriculum in the MIT Department of Chemistry. Undergraduate Research-Inspired Experimental Chemistry Alternatives (URIECA) introduces students to cutting edge research topics in a modular format.
Acknowledgments
Development of this course was funded through an HHMI Professors grant to Professor Catherine L. Drennan.

Data Carpentry lesson to learn how to use command-line tools to perform quality control, align reads to a reference genome, and identify and visualize between-sample variation. A lot of genomics analysis is done using command-line tools for three reasons: 1) you will often be working with a large number of files, and working through the command-line rather than through a graphical user interface (GUI) allows you to automate repetitive tasks, 2) you will often need more compute power than is available on your personal computer, and connecting to and interacting with remote computers requires a command-line interface, and 3) you will often need to customize your analyses, and command-line tools often enable more customization than the corresponding GUI tools (if in fact a GUI tool even exists). In a previous lesson, you learned how to use the bash shell to interact with your computer through a command line interface. In this lesson, you will be applying this new knowledge to carry out a common genomics workflow - identifying variants among sequencing samples taken from multiple individuals within a population. We will be starting with a set of sequenced reads (.fastq files), performing some quality control steps, aligning those reads to a reference genome, and ending by identifying and visualizing variations among these samples. As you progress through this lesson, keep in mind that, even if you aren’t going to be doing this same workflow in your research, you will be learning some very important lessons about using command-line bioinformatic tools. What you learn here will enable you to use a variety of bioinformatic tools with confidence and greatly enhance your research efficiency and productivity.

Data Carpentry lesson to learn to navigate your file system, create, copy, move, and remove files and directories, and automate repetitive tasks using scripts and wildcards with genomics data. Command line interface (OS shell) and graphic user interface (GUI) are different ways of interacting with a computer’s operating system. The shell is a program that presents a command line interface which allows you to control your computer using commands entered with a keyboard instead of controlling graphical user interfaces (GUIs) with a mouse/keyboard combination. There are quite a few reasons to start learning about the shell: For most bioinformatics tools, you have to use the shell. There is no graphical interface. If you want to work in metagenomics or genomics you’re going to need to use the shell. The shell gives you power. The command line gives you the power to do your work more efficiently and more quickly. When you need to do things tens to hundreds of times, knowing how to use the shell is transformative. To use remote computers or cloud computing, you need to use the shell.

This course provides an introduction to the chemistry of biological, inorganic, and organic molecules. The emphasis is on basic principles of atomic and molecular electronic structure, thermodynamics, acid-base and redox equilibria, chemical kinetics, and catalysis.
In an effort to illuminate connections between chemistry and biology, a list of the biology-, medicine-, and MIT research-related examples used in 5.111 is provided in Biology-Related Examples.
Acknowledgements
Development and implementation of the biology-related materials in this course were funded through an HHMI Professors grant to Prof. Catherine L. Drennan. Videos and captioning were made possible and supported by the MIT Class of 2009.

In the fall of 2021, students in Pseudoscience courses started creating this open educational resource (OER), which has been built upon by subsequent classes. Our intention is to create a free textbook for this course that might also be used by students of critical thinking elsewhere and of all ages, whether in a classroom or not. Our growing, interactive textbook employs the Paul-Elder Model and other critical-thinking resources, and is freely available to all, learners and educators alike.

The topic of pseudoscience offers a rewarding way for students to learn the value of thinking critically, even as they get to argue things, like Flat Earth Theory and astrology, that may seem trivial at first. At a time when truth is understood as largely subjective, we have, not surprisingly, seen a resurgence in the popularity of pseudosciences and conspiracy theories, which many consider to hold significant truth value, just as valid as physical evidence. It is our aim here to demonstrate the reasoned analysis process — weighing truth, belief, opinion, and fact — so that others may be able to replicate this process and reason through their own questions about vaccines, extra-terrestrials, genetic modification, or the first people to arrive in the Americas.