Learn More About Viology

  1. Virology Course taught by Dr. Vincent Racaniello http://www.virology.ws/course/

    XW: I really appreciate Dr. Racaniello sharing his course videos online!
  2. Here is his blog: https://www.virology.ws

    XW: I would highly recommend you to listen to Dr. Racaniello’s podcast if you are in the relative field, where virologists talk about recent outstanding papers and events. I benefit much from it.
  3. Video: TWiV 699 – Arboviruses at ASTMH

From the 2020 online meeting of the American Society for Tropical Medicine and Hygiene, Vincent speaks with Jonathan Auguste, Carol Blair, Desiree LaBeaud, Louis Lambrechts, and Mauricio Nogueira about their careers and their research on arthropod-borne viruses.

TWiV 699: Arboviruses at ASTMH
(https://www.microbe.tv/twiv/twiv-699/)

XW: It is a great converstation among scientits who work on different aspects of arboviruses sharing their careers and researches! BTW, Dr. Louise Lambrechts’s works are my favorites!

6.047/6.878/HST.507 Scribing Guide

(XW: It is also a good guidance for better learning!)

MITOPENCOURSEWARE: Computational Biology.

Where to listen? Dr. Manolis Kellis’s Youtube Channel!

XW: If you didn’t hear about that before, oh please, check out his youtube channel!! Dr. Kellis and all his courses and reseaches are fantastic!! Can’t say how much I love it!!

Here is the link to the scribing guide.

Some Questions I like to take to ask myself:

1. Before the lecture: You should carefully review the chapter that you will be improving.

• Is the background and motivation for the problem we are studying clearly conveyed?
• Do the sections divide the material into logical parts?
• Does the text flow and build up ideas in a logical order?
• Are figures and legends clear? Are equations and notation properly defined?
• Is current research, if mentioned, properly cited?
• Are there items marked TODO?

6.047 Computational Biology, Scribing Guide

2. During the lecture: As you attend lecture, you should pay particular attention to issues that the slides and existing notes don’t convey well, and to new material that is not covered in the existing notes.

• Is any material in the lecture not covered in the notes?
• Were equations/algorithms more clearly explained during lecture than in the notes?
• Are there assumptions or exceptions to a statement that were not clear in the notes?
• Were there insightful questions or interesting digressions in the lecture?
• Were there any common misunderstandings or points of confusion?

6.047 Computational Biology, Scribing Guide

3. After the lecture:

Add to or edit the text to address the issues you noted before the lecture and points you noted during the lecture as described below.

You should make sure to include in your scribe notes any new lecture material that the notes do not cover (you may want to check other chapters of the book to be sure that the material is not covered elsewhere). You should also be sure that all material in the lecture is clearly explained in your final draft, and add to the chapter any particularly insightful questions and responses that come up in lecture.

You may also decide to rework sections of the chapter for clarity, restructure the chapter to improve its flow, improve figures to make them clearer and more visually appealing, rework and expand figure legends, create or suggest additional tables or figures for the chapter, or add infoboxes containing worked example problems or summaries of recent publications.

6.047 Computational Biology, Scribing Guide

4. If you are writing a new chapter, we will provide the following outline:

1. Introduction
2. (Sections for the main points of the lecture, at your discretion)
3. Current Research Directions
4. Further Reading
5. Tools and Techniques
6. Current Research Directions
7. What Have We Learned?

We expect the introduction, main points of the lecture, and “What Have We Learned?” to be covered, and relevant figures from the lecture slides included. You are welcome to write other sections, especially if you have prior knowledge or more interest in the topic.

6.047 Computational Biology, Scribing Guide