An explanation of the Higgs Boson with cartoons

Over the past 48 hours, my twitter and Google News feeds have been filled with nothing but the Higgs Boson.  Seriously awesome stuff.  But why is it awesome?  Here’s my favorite primer on Higgs and the experiment behind its discovery.

Cancer in the news

I was cruising through my morning news update on research and clinical trials (yup, I’m a nerd). There were several tidbits about cancer with a more general interest. Thought I’d share and give my perspectives.

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Google and Cancer, AKA, that is not a small number

A presentation at the Google I/O developers conference blew my mind today.  While the videos from I/O conferences are always fun to watch, the particularly mind-explody bit for me was the release of Google Compute Engine.  They showcased the technology by launching a 600000 core cluster in a matter of minutes. That is not a small cluster.  That is, decidedly, the opposite of a small cluster. Then the cool stuff started.

They used it to perform, in a mere matter of seconds, an all-pairs gene expression analysis (an extremely important tool in understanding cancer).  I’m a systems biologist. I work everyday with computers, big computers, to try and grapple with understanding cancer. So, as someone in-the-know, let me be clear.  This. Is. Epic.

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Learn something for free. Change the world.

Udacity started another round of courses this past week.  In case you’ve not heard of it yet, you should know, it’s going to change the world.  Udacity is a free online university, so far presenting courses that teach programming at several levels.  Over the next 7 weeks they’re bridging out into statistics, physics and discrete math.  This program is not the only one of its kind on the forefront of this new educational model.  In addition to Udacity, Khan Academy, EdX, OpenClassroom, Coursera, and Codecademy are some of the better known players in this field.

These startups should not be underestimated.  They represent a revolutionary change in the educational model of this world.

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The N-Queens problem

I’ve been thinking about depth first backtracking algorithms recently (more on what those are in a moment).  So when I couldn’t sleep on a recent over night train trip I decided to dust off a classic programming problem to pass the time.

How many ways can you place 8 queens on a chessboard so that no two of them are mutually attacking?  The first step of this problem is to determine what constitutes a really bad idea.

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Gender differences, Twitter and Videogames

I was recently introduced to Tweet-o-Life via the quite amazing Nathan Yau over at Flowing Data.  The Tweet-o-Life project was a study by Amaç Herdağdelen and Marco Baroni of habits on Twitter.  They looked at millions of tweets to identify behaviors of two kinds, ones based on gender and ones based on time of day.  They’ve since made their data and analysis tools freely available on the web.

I’ve spent several hours on the site playing with different queries.  Along the way I became fascinated with gender differences in videogames.  Here’s some of my more interesting findings.

First off, we see not all….

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Text Message Analysis, Chapter 3

So far in our exploration text messaging, we’ve analyzed the time of day each message arrives and the structure of each message.  We’ve been able to pick out typical behaviors like timing of sleep cycles and life events like a trip to Switzerland.  We’ve found a relationship between the structure of messages and the kind of content they contain.  In the next part of our analysis we begin to look into the actual content of the message and along the way discover some interesting things about the nature of language.

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Text message analysis, chapter 2

Let’s continue with our analysis of text message behavior by shifting over into content.  One of the first things to understand is the form of each message.  What’s the length of each message? As a function of length, how does the content of the message change?  To begin with…

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Text message analysis, chapter 1

A couple of months ago I read Stephen Wolfram’s article about analyzing his emails and saved files.  If you’ve not seen it yet, it’s definitely worth a read.  I was intrigued and wanted to apply a few of these analysis ideas to my own life.  I don’t have 30 years of saved email (yet), but I do have a database of text messages. Last time I posted about how to get that database off of an iPhone and format it into a text file for further analysis. Now for the fun part, the analysis.

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