Final Projects

Overview

Class Date: 12/3/2024, 12/5/2024, 12/10/2024
Teaching: 145 min
Exercises: 0 min
Questions
  • What are the requirements of the MCB 585 individual class projects?

Objectives
  • Use the skills learned in MCB 585 to conduct a new (or reproduce an old) analysis on a large dataset.

Final project details

Overview & Goals

The final project is the capstone experience for MCB 585. It serves as an opportunity to synthesize and apply the quantitative and computational skills learned throughout the course to a novel, large dataset. The core objective is to use these skills to formally evaluate a hypothesis, design a quantitative experiment, or explore the behavior of a complex biological system. We strongly encourage you to use data from your own research, as a key goal of this course is to provide you with practical tools for your graduate work. However, several alternatives are available if you do not have a suitable dataset. The project is composed of three parts: (1) a proposal, (2) a final written report with code, and (3) an oral presentation. Together, these components account for 35% of your final MCB 585 grade.

Due Dates & Submission Instructures

Each project will consist of three parts:

The three parts of the final Project are due as follows:

Submission. Project proposals and written reports should be submitted to the corresponding D2L Assignment drop box. The oral presentation just needs to be delivered on your assigned day but does not need to be turned in separately.

Part 1: Project Proposal

The purpose of the proposal is to ensure your project has an appropriate scope and to allow instructors to provide early feedback. In some cases, instructors may request a brief meeting to clarify details or suggest alternative approaches.

Your proposal must outline the following:

Part 2: Written Report & Code

You will submit a written report of your findings, accompanied by the code used to perform the analysis.

The report should be structured like a brief scientific paper with the following sections:

Part 3: Oral Presentation

During the last few class meetings, each student will deliver a presentation on their project.

Your presentation should describe:

Additional Information

Choosing a Project Topic: You have several options for your project.

Example Project Ideas: Here are a few sample projects. You are free to use or adapt these examples if you are unable to find a suitable project on your own.

Use of Generative AI (e.g., ChatGPT, Gemini, Claude):

Project notes

  1. The goal of this project is to conduct analysis of datasets for which the tools in R and Matlab provide a signficant advantage. We prefer that datasets be selected that contain at least 1000 data points. Please ask in advance if you have a dataset in mind that does not meet this criteria.

  2. Projects should make use of at least one, and preferrably multiple, of the tools presented in the course.

  3. Projects that utilize webtools or other analysis pipelines are allowed; however, at least half of the analysis should be performed as original code created by the student using tools covered in class, and a full understanding of the algorithms underlying the webtools should be demonstrated in the writeup and presentation.

  4. The goal of this course is to provide you with a set of practical tools that can be employed in your own research. As such, we strongly encourage you to use your own data in your project. An alternative is to select a paper that conducts and interesting analysis and reproduce one of the figure (using their data or a similar dataset). If you do not currently have data useful for this purpose, you are welcome to use the datasets provided as part of the course (downloaded at the beginning of the course setup, or here). There are also many online resources with publically available datasets that you can use for your project. For example:

Key Points

  • MCB 585 individual final projects.