My PhD thesis was called “Multiscale analysis of infectious diseases: integrating omics and clinical informatics data into patient care” and I wrote it under the dedicated guidance of Andrew Kasarskis, PhD, my thesis advisor. It was a dissertation comprising exclusively computational work. The motivating premise is that “big data” on infectious diseases are becoming more prevalent, and we should attempt new and ambitious methods to combine these data to solve urgent problems affecting our patients. Some examples of these new data sources are:
Next-generation sequencing of pathogen genomes
Electronic medical records
Mass cytometry of immune cell subpopulations during infection
RNA-seq of host gene expression changes during infection
Some of the problems that I tackled in this thesis were:
Using bacterial genome sequencing to explain the development of antibiotic resistance in patients undergoing treatment in the hospital
Tracking the patient-to-patient spread of hospital-acquired infections with nearly real-time analysis of genomic surveillance data
Estimating the cost of a hospital-acquired infection from electronic medical record data
Dissecting the human immune response to a recently emerging viral infection in the Americas (Chikungunya) in unprecedented depth
read a little more about the details of the thesis, its abstract, and links to the publications derived from its chapters.
I’ve also put the source code for typesetting the thesis on my GitHub.
Although Molecular Systems Biology is an open access journal and is fairly liberal about accepting work already posted online, even encouraging posts to preprint servers and explicitly exempting theses as prior publication, many journals reserve the right to reject manuscripts that were disseminated in any way prior to submission. And until an article is published, you never know what other journals you might submit it to. Therefore, at least in the life sciences, I’d still recommend caution on putting thesis chapters online until they are accepted somewhere, or unless you’ve reviewed the editorial policies of every possible target journal. ↩
I’ve been using Anki to generate flashcards for just about every class in medical school since the second semester, and it’s been clutch for trying to memorize the insane amounts of material that we’re given. I’d say that Anki is almost perfect for medical students and the reasons why deserve a post all to themselves. This post, rather, is about something that I thought was missing from Anki—namely, publishing the content to the web—and how I wrote some code to fix it, all thanks to Anki being open source and extensible.
Most people think using open source software is an ideological consideration, but as a student, it can be just as much a practical benefit. Students are already reliant on so much software, from office programs to course management systems, much of it proprietary. It can be disastrous when those apps become unsupported, stop working on your new device, or worse, lose data. Imagine taking a semester’s worth of notes on a shiny new website or app that you tried because it was free or had some killer feature that you couldn’t resist. Then the company goes out of business, and the website shuts down. Or, your computer breaks, and the app doesn’t work on your new one. Maybe the company decides to disable support for exporting content unless you pay a huge fee. These situations are terrifying—especially if you have a test, much less a career licensing exam, right around the corner.
With Anki, not only is the desktop program free, but all notes are stored permanently on your own computer. Also, because it is open source, your data will always be retrievable, even if that means some tooling around with some Python libraries or firing up an SQLite console. It’s literally impossible for the developers to shut you out, and even if they tried, somebody could fork Anki and fix it. For these reasons, data in open source software is inherently much more future-proof than something like Microsoft Office. In case you didn’t know, Office still has no complete specifications for its legacy file formats, and probably never will. (And now it’s moving to the cloud with Office 365, where you will have even less control over preserving your content.)
As it turns out, Anki is exceptionally customizable. Since the desktop app is written in Python with bindings to Qt for the GUI, not only is it cross-platform, but it supports writing plugins as Python scripts, called “addons”. That means: no compiling, everything lives in one text file, and live objects can be debugged in a console. Sweet! You can do everything from GUI alterations to enhancing internal data structures or the scheduling algorithm. There are quite a few addons already available online.
That brings us to my problem: most kinds of content have a “natural” online destination for sharing: Flickr and Instagram for photos, YouTube for video, Slideshare for slide decks, and Scribd for office documents. Anki doesn’t really have anything in the same league. Yes, there’s AnkiWeb, but it’s designed to be used primarily as a sync backend. An account is required to do anything, it has less features than the desktop app, and the sharing functions are pretty limited. There are a fewgems hidden in there for medical students, but in general it’s hard to find, share, and show off good Anki material.
And so, I was struck with the idea of creating a way to do exactly this. I spend most of my time in lecture writing flashcards, and I don’t want them locked up on my computer forever. It would be nice to have them right here on this blog, not only for me so I can watch them when I’m bored, but so that others might do the same. Sometimes it’s nice to passively browse through content. Why watch cat videos when you can watch Pathology flashcards? (Har har.)
The vision was to create a menu item within Anki that you click, and then everything gets synced to the web server, which plays the cards like a slideshow. The Anki component fits entirely in one short Python script. There are only 5 functions, the key one being exportCardsToWeb(). In short, the mw.col object, which represents the current collection of Anki notes, is dumped into a JSON file holding the decks and the cards within them, rendered to HTML by the renderQA() method. Then, the whole mess is copied using rsync to a destination of your choice. Adding these functions into the Anki GUI is as easy as the following lines at the end of the script:
This throws an extra section with two items onto the end of the Tools menu of the main window. Clicking on these items runs the functions written at the beginning of the script.
In short, this means that if you go to the bare domain, you’re redirected to a random deck; if you fetch a URL ending in “.jpg”, it grabs the picture (if there is one) and serves it. If the URL is anything else, it looks for a deck with that name and serves a random card from it.
The rest of the hard work is done by some jQuery in the interface. Once it is time to fetch a new card, a request is sent via AJAX to the same /:deck URL route, which provides the full HTML for a new random card. To avoid a distracting transition, the new card is parsed out of the HTML and inserted in the current page. If the user changed the deck they want to view, we can even gracefully update the URL in the address bar using the HTML5 History API. A lot of this is made straightforward by the jQuery .load() method, as can be seen in the excerpt below:
That $.scrollTo() call provides a nice animated transition to the reverse side of the card in case it is off the edge of the screen, using the very nice scrollTo jQuery plugin.
To embed the web app into another page, an <iframe/> element with a src attribute pointing to one of the decks can be used. For example, this is how I can embed my Cardiovascular deck.
It produces the following, which I’ve highlighted with the frameborder="2" attribute so you can see where its edges are. But those can be turned off by setting frameborder="0".
And there you have it. Hopefully this inspires other projects that try to use Anki content in larger web apps, since it is a powerful tool that deserves more integration into so many other things. The code is on Github, and you can see the slideshow in action with my medical school decks on this site or as a standalone website. Some ideas I currently have for improving it are:
A better front page for it that explains the UI and deck content before jumping into a deck
Upgrading the timer drawing to SVG so it looks better on high-res screens
Adding tag support, so you can filter by subtopic and by lecture (I tag in Anki by lecture number)
Having the server remember your recent cards, so it tries not to repick them
I was happy to be featured in a video produced by my medical school about life as a first year student here.
Since it was filmed throughout the entirety of first year starting from the white coat ceremony, and now I’m knee-deep in the second, it’s interesting to look back and remember snippets of how it all went down. It was shot in a hands-off style: besides coordinating when the crew would be where, and the “debriefing” interviews, we as students pretty much did our thing and the cameras rolled.
The video is sincere about the culture and mission of the school, with the essence of our experience as first-years conveyed quite honestly. There are a lot of special things about Mount Sinai that I’ve already discovered in the short time that I’ve been here. Most of all, what makes Sinai especially great are the students and faculty here, and I was happy to see the video let the students’ thoughts and personalities speak for themselves. Ultimately medical education is about the people around you, so you should never underestimate the impact of a happy and well-rounded student body.
Hopefully applicants see the video and get a more personal sense of what Sinai is like. If you’re applying to Sinai and are interested in anything that you saw or heard about, feel free to email me!