To register for this course, please complete this form by Wednesday, April 10, 2024

Course description

Biomedical researchers often build and use experimental rigs consisting of several interconnected electronic instruments. These rigs are typically used to make high-quality...

Course description

Cellular heterogeneity has become an increasingly important topic in many areas of cell biology on a wide range of spatiotemporal scales. This course will introduce important concepts of computational image analysis and machine learning that help us characterize cellular heterogeneity within cell images. After the formal lectures, we will utilize the standard software such as MATLAB, CellProfiler, ImageJ in hands-on experiences. The topics will include image processing, segmentation, tracking, feature extraction, and...

Course Description
In order to go from a set of data to a published paper, it’s key to learn the framework of the manuscript building process, develop skills in writing, and find a community of peers who can help you articulate the importance of your research. In this Nanocourse, Dr. Marie Bao (BCMP, Harvard Medical School; former Editor-In-Chief of Developmental Cell), Dr. Milka Kostic (Chemical Biology, DFCI; former Senior Editor of Cell Chemical Biology & Structure), and Dr. Vivian Siegel (Scientific Communications, Biology, MIT; former Editor-In-...

Course Description

AlphaFold represents a dramatic increase in the power of AI systems to predict a protein’s 3D structure from its amino acid sequence. This nanocourse will introduce how predictive models like Alphafold/Collab work, their strengths and limitations, and how to interpret their predictive results.

This is a hands-on workshop; participants will use Alphafold and ColabFold, submit computing jobs to the O2 computing platform, and visualize 3D structures. No prior computational experience is required – the workshop will introduce...

SESSIONS 1 and 2 HAVE BEEN MOVED ONLINE. ZOOM INFORMATION WILL BE PROVIDED TO REGISTERED STUDENTS.

This course is an introduction to the skills and frameworks necessary for success as a graduate student teaching fellow (TF) or teaching assistant (TA). After completing this 6 hour introduction, students will be able to:

- describe core pedagogy concepts including backwards design, formative assessment, active learning, alignment, and inclusive teaching
- identify ways these core concepts may influence their work as graduate student TFs/TAs...

Course Description
The field of cancer metabolism has grown tremendously in the past decade, contributing major advancements in our understanding of how to diagnose and treat tumors. Despite this, some of the tools required to study cancer metabolism remain out of reach for many labs. This is particularly true for metabolomics, as it...