Martin Krzywinski / Genome Sciences Center / mkweb.bcgsc.ca Martin Krzywinski / Genome Sciences Center / mkweb.bcgsc.ca - contact me Martin Krzywinski / Genome Sciences Center / mkweb.bcgsc.ca on Twitter Martin Krzywinski / Genome Sciences Center / mkweb.bcgsc.ca - Lumondo Photography Martin Krzywinski / Genome Sciences Center / mkweb.bcgsc.ca - Pi Art Martin Krzywinski / Genome Sciences Center / mkweb.bcgsc.ca - Hilbertonians - Creatures on the Hilbert Curve
And she looks like the moon. So close and yet, so far.Future Islandsaim highmore quotes

satire: beautiful


EMBO Practical Course: Bioinformatics and Genome Analysis, 5–17 June 2017.


fun + amusement

Dummer — Like Nothing Else


The Hummer font is a slightly modified Antique Olive Nord. The Like Nothing Else tag line is Trade Gothic. Both have character widths increased to 110-120% and individually adjusted kerning. Get the Illustrator CS5 file for both logos.

Martin Krzywinski @MKrzywinski mkweb.bcgsc.ca
Hummer logo. (EPS, PNG)
Martin Krzywinski @MKrzywinski mkweb.bcgsc.ca
Dummer logo. (EPS, PNG)
Download high-resolution images.

This project might give you the impression that I don't like Hummers. You'd be right.

Martin Krzywinski @MKrzywinski mkweb.bcgsc.ca
It could be worse. But not by much. (zoom)
Martin Krzywinski @MKrzywinski mkweb.bcgsc.ca
It could be worse. But not by much. (zoom)
Martin Krzywinski @MKrzywinski mkweb.bcgsc.ca
It could be worse. But not by much. (zoom)

update

The Maurauder. Over 25,000 lb — five times what an H3 weighs. Enough said.

Martin Krzywinski @MKrzywinski mkweb.bcgsc.ca
There is always someone with a bigger one. (Manufacturer's page.)

Dummer - Like Nothing Else

Hummers are a cultural equivalent of a toxic warning label and have the same effect on me as bug spray on mosquitoes.

I am not the first one to satirize this automotive aberration, so there's some hope.

Martin Krzywinski @MKrzywinski mkweb.bcgsc.ca
Dummer. Like Nothing Else. (New York Times — Laugh Lines)

GM's advertisement images require no modification for the satire, which makes it all that much better.

Martin Krzywinski @MKrzywinski mkweb.bcgsc.ca
Dumb and Dumber. (New York Times — Laugh Lines)

I could have just as well used the Lincoln Navigator or Cadillac Escalade, but they don't embody the superlative like the Hummer.

The Hummer brand proved itself to be aesthetically, rationally and economically unsustainable and collapsed after a failed attempt to sell it to China. There continues to be a robust market for used Hummers. Let the farce continue.

I'm hated

It delights me that this project produced my first hate mail.

I want to meet Doug and give him a hug for adding another dimension to this project.

I'm loved

The images got picked up by the New York Times laughlines blog, which drew a couple of fan mails.

But neither made me feel as good as Doug's email.

Dummer Images

Dummer. Like nothing else. A pretty good Hummer satire. / Martin Krzywinski @MKrzywinski mkweb.bcgsc.ca
Dummer. Like nothing else. (zoom)
Dummer. Like nothing else. A pretty good Hummer satire. / Martin Krzywinski @MKrzywinski mkweb.bcgsc.ca
Dummer. Like nothing else. (zoom)
Dummer. Like nothing else. A pretty good Hummer satire. / Martin Krzywinski @MKrzywinski mkweb.bcgsc.ca
Dummer. Like nothing else. (zoom)
Dummer. Like nothing else. A pretty good Hummer satire. / Martin Krzywinski @MKrzywinski mkweb.bcgsc.ca
Dummer. Like nothing else. (zoom)
Dummer. Like nothing else. A pretty good Hummer satire. / Martin Krzywinski @MKrzywinski mkweb.bcgsc.ca
Dummer. Like nothing else. (zoom)
Dummer. Like nothing else. A pretty good Hummer satire. / Martin Krzywinski @MKrzywinski mkweb.bcgsc.ca
Dummer. Like nothing else. (zoom)
Dummer. Like nothing else. A pretty good Hummer satire. / Martin Krzywinski @MKrzywinski mkweb.bcgsc.ca
Dummer. Like nothing else. (zoom)
Dummer. Like nothing else. A pretty good Hummer satire. / Martin Krzywinski @MKrzywinski mkweb.bcgsc.ca
Dummer. Like nothing else. (zoom)
Dummer. Like nothing else. A pretty good Hummer satire. / Martin Krzywinski @MKrzywinski mkweb.bcgsc.ca
Dummer. Like nothing else. (zoom)
VIEW ALL

news + thoughts

Snowflake simulation

Tue 14-11-2017
Symmetric, beautiful and unique.

Just in time for the season, I've simulated a snow-pile of snowflakes based on the Gravner-Griffeath model.

Martin Krzywinski @MKrzywinski mkweb.bcgsc.ca
A few of the beautiful snowflakes generated by the Gravner-Griffeath model. (explore)

Gravner, J. & Griffeath, D. (2007) Modeling Snow Crystal Growth II: A mesoscopic lattice map with plausible dynamics.

Genes that make us sick

Thu 02-11-2017
Where disease hides in the genome.

My illustration of the location of genes in the human genome that are implicated in disease appears in The Objects that Power the Global Economy, a book by Quartz.

Martin Krzywinski @MKrzywinski mkweb.bcgsc.ca
The location of genes implicated in disease in the human genome, shown here as a spiral. (more...)

Ensemble methods: Bagging and random forests

Mon 16-10-2017
Many heads are better than one.

We introduce two common ensemble methods: bagging and random forests. Both of these methods repeat a statistical analysis on a bootstrap sample to improve the accuracy of the predictor. Our column shows these methods as applied to Classification and Regression Trees.

Martin Krzywinski @MKrzywinski mkweb.bcgsc.ca
Nature Methods Points of Significance column: Ensemble methods: Bagging and random forests. (read)

For example, we can sample the space of values more finely when using bagging with regression trees because each sample has potentially different boundaries at which the tree splits.

Random forests generate a large number of trees by not only generating bootstrap samples but also randomly choosing which predictor variables are considered at each split in the tree.

Krzywinski, M. & Altman, N. (2017) Points of Significance: Ensemble methods: bagging and random forests. Nature Methods 14:933–934.

Background reading

Krzywinski, M. & Altman, N. (2017) Points of Significance: Classification and regression trees. Nature Methods 14:757–758.

...more about the Points of Significance column

Classification and regression trees

Mon 16-10-2017
Decision trees are a powerful but simple prediction method.

Decision trees classify data by splitting it along the predictor axes into partitions with homogeneous values of the dependent variable. Unlike logistic or linear regression, CART does not develop a prediction equation. Instead, data are predicted by a series of binary decisions based on the boundaries of the splits. Decision trees are very effective and the resulting rules are readily interpreted.

Trees can be built using different metrics that measure how well the splits divide up the data classes: Gini index, entropy or misclassification error.

Martin Krzywinski @MKrzywinski mkweb.bcgsc.ca
Nature Methods Points of Significance column: Classification and decision trees. (read)

When the predictor variable is quantitative and not categorical, regression trees are used. Here, the data are still split but now the predictor variable is estimated by the average within the split boundaries. Tree growth can be controlled using the complexity parameter, a measure of the relative improvement of each new split.

Individual trees can be very sensitive to minor changes in the data and even better prediction can be achieved by exploiting this variability. Using ensemble methods, we can grow multiple trees from the same data.

Krzywinski, M. & Altman, N. (2017) Points of Significance: Classification and regression trees. Nature Methods 14:757–758.

Background reading

Lever, J., Krzywinski, M. & Altman, N. (2016) Points of Significance: Logistic regression. Nature Methods 13:541-542.

Altman, N. & Krzywinski, M. (2015) Points of Significance: Multiple Linear Regression Nature Methods 12:1103-1104.

Lever, J., Krzywinski, M. & Altman, N. (2016) Points of Significance: Classifier evaluation. Nature Methods 13:603-604.

Lever, J., Krzywinski, M. & Altman, N. (2016) Points of Significance: Model Selection and Overfitting. Nature Methods 13:703-704.

Lever, J., Krzywinski, M. & Altman, N. (2016) Points of Significance: Regularization. Nature Methods 13:803-804.

...more about the Points of Significance column