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


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


visualization + design

Scientific American Graphic Science - Martin Krzywinski. / Martin Krzywinski @MKrzywinski mkweb.bcgsc.ca

Working with senior graphics editor at Scientific American Jen Christiansen, I have designed three Graphic Science visualizations for the magazine.

Scientific American Graphic Science - Martin Krzywinski. / Martin Krzywinski @MKrzywinski mkweb.bcgsc.ca
December 2015. Composition of bacteria in household dust.
Scientific American Graphic Science - Martin Krzywinski. / Martin Krzywinski @MKrzywinski mkweb.bcgsc.ca
June 2015. Relationship between genes and traits.
Scientific American Graphic Science - Martin Krzywinski. / Martin Krzywinski @MKrzywinski mkweb.bcgsc.ca
September 2014. Similarity of human, Denisovan, chimp, bonobo, and gorilla genomes.

Men and Women Alter a Home's Bacteria Differently

An analysis of dust reveals how the presence of men, women, dogs and cats affects the variety of bacteria in a household

December 2015, Scientific American Volume 313, Issue 6

This collaboration with Jeanine Hunnicutt explored differences in household dust bacteria based on the gender and pet status of the occupants.

We have also written about the making of the graphic, for those interested in how these things come together.

Graphic by Martin Krzywinski and Barbara Jeanine Hunnicutt.

Catalogue of bacteria shapes by Barbara Jeanine Hunnicutt.

Source: Barberan A et al. (2015) The ecology of microscopic life in household dust. Proc. R. Soc. B 282: 20151139.

Scientific American Graphic Science - Martin Krzywinski. / Martin Krzywinski @MKrzywinski mkweb.bcgsc.ca

A Road Map to the "Volume Control" of Genes

Genes, traits and disease are linked in complex and surprising ways

June 2015, Scientific American Volume 312, Issue 6

Because sometimes only a network hairball will do.

Graphic by Martin Krzywinski.

Source: Integrative analysis of 111 reference human epigenomes. (2015) Nature 518:317.

Scientific American Graphic Science - Martin Krzywinski. / Martin Krzywinski @MKrzywinski mkweb.bcgsc.ca

Tiny Genetic Differences between Humans and Other Primates Pervade the Genome

Genome comparisons reveal the DNA that distinguishes Homo sapiens from its kin

September 2014, Scientific American Volume 311, Issue 3

A Scientific American blog entry "A Monkey's Blueprint" accompanies this piece. I also have a more detailed description with links to data sources.

You can also read more about Hilbert curves and creatures that live on it, Hilbertonians.

This design won a bronze award at Malofiej 23. For more information about Malofiej, see the SA Visual blog entry "There's No Infographic without Info (and other Lessons from Malofiej)".

Graphic by Martin Krzywinski, illustrations by Portia Sloan Rollings.

Scientific American Graphic Science - Martin Krzywinski. / Martin Krzywinski @MKrzywinski mkweb.bcgsc.ca
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news + thoughts

`k` index: a weightlighting and Crossfit performance measure

Wed 07-06-2017

Similar to the `h` index in publishing, the `k` index is a measure of fitness performance.

To achieve a `k` index for a movement you must perform `k` unbroken reps at `k`% 1RM.

The expected value for the `k` index is probably somewhere in the range of `k = 26` to `k=35`, with higher values progressively more difficult to achieve.

In my `k` index introduction article I provide detailed explanation, rep scheme table and WOD example.

Dark Matter of the English Language—the unwords

Wed 07-06-2017

I've applied the char-rnn recurrent neural network to generate new words, names of drugs and countries.

The effect is intriguing and facetious—yes, those are real words.

But these are not: necronology, abobionalism, gabdologist, and nonerify.

These places only exist in the mind: Conchar and Pobacia, Hzuuland, New Kain, Rabibus and Megee Islands, Sentip and Sitina, Sinistan and Urzenia.

And these are the imaginary afflictions of the imagination: ictophobia, myconomascophobia, and talmatomania.

And these, of the body: ophalosis, icabulosis, mediatopathy and bellotalgia.

Want to name your baby? Or someone else's baby? Try Ginavietta Xilly Anganelel or Ferandulde Hommanloco Kictortick.

When taking new therapeutics, never mix salivac and labromine. And don't forget that abadarone is best taken on an empty stomach.

And nothing increases the chance of getting that grant funded than proposing the study of a new –ome! We really need someone to looking into the femome and manome.

Dark Matter of the Genome—the nullomers

Wed 31-05-2017

An exploration of things that are missing in the human genome. The nullomers.

Julia Herold, Stefan Kurtz and Robert Giegerich. Efficient computation of absent words in genomic sequences. BMC Bioinformatics (2008) 9:167

Clustering

Wed 31-05-2017
Clustering finds patterns in data—whether they are there or not.

We've already seen how data can be grouped into classes in our series on classifiers. In this column, we look at how data can be grouped by similarity in an unsupervised way.

Martin Krzywinski @MKrzywinski mkweb.bcgsc.ca
Nature Methods Points of Significance column: Clustering. (read)

We look at two common clustering approaches: `k`-means and hierarchical clustering. All clustering methods share the same approach: they first calculate similarity and then use it to group objects into clusters. The details of the methods, and outputs, vary widely.

Altman, N. & Krzywinski, M. (2017) Points of Significance: Clustering. Nature Methods 14:545–546.

Background reading

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

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

...more about the Points of Significance column