Martin Krzywinski / Canada's Michael Smith Genome Sciences Centre / mkweb.bcgsc.ca Martin Krzywinski / Canada's Michael Smith Genome Sciences Centre / mkweb.bcgsc.ca - contact me Martin Krzywinski / Canada's Michael Smith Genome Sciences Centre / mkweb.bcgsc.ca on Twitter Martin Krzywinski / Canada's Michael Smith Genome Sciences Centre / mkweb.bcgsc.ca - Lumondo Photography Martin Krzywinski / Canada's Michael Smith Genome Sciences Centre / mkweb.bcgsc.ca - Pi Art Martin Krzywinski / Canada's Michael Smith Genome Sciences Centre / mkweb.bcgsc.ca - Hilbertonians - Creatures on the Hilbert CurveMartin Krzywinski / Canada's Michael Smith Genome Sciences Centre / mkweb.bcgsc.ca - Pi Day 2020 - Piku
Poetry is just the evidence of life. If your life is burning well, poetry is just the ashLeonard Cohenburn somethingmore quotes

understanding: enlightening


The Outbreak Poems — artistic emissions in a pandemic


data visualization + art

Martin Krzywinski @MKrzywinski mkweb.bcgsc.ca
To view the art you'll need a pair of red-blue 3D glasses.
The data will stand out—and you will too.

BD Genomics stereoscopic art exhibit — AGBT 2017

Art is science in love.
— E.F. Weisslitz

BD Genomics 3D art exhibit - AGBT 2017 / Martin Krzywinski @MKrzywinski mkweb.bcgsc.ca
Our art exhibit at AGBT 2017 asked new school questions in old school ways.
BD Genomics 3D art exhibit - AGBT 2017 / Martin Krzywinski @MKrzywinski mkweb.bcgsc.ca

the art of storytelling in science

BD Genomics 3D art exhibit - AGBT 2017 / Martin Krzywinski @MKrzywinski mkweb.bcgsc.ca
Instead of 'explain, not merely show,' seek to 'narrate, not merely explain.' Krzywinski M & Cairo A (2013) Points of View: Storytelling. Nat. Methods 10:687.

Science cannot move forward without storytelling. While we learn about the world and its patterns through science, it is through stories that we can organize and sort through the observations and conclusions that drive the generation of scientific hypotheses.

With Alberto Cairo, I've written about the importance of storytelling as a tool to explain and narrate in Storytelling (2013) Nat. Methods 10:687. There we suggest that instead of "explain, not merely show," you should seek to "narrate, not merely explain."

Our account received support (Should scientists tell stories. (2013) Nat. Methods 10:1037) but not from all (Against storytelling of scientific results. (2013) Nat. Methods 10:1045).

A good science story must present facts and conclusions within a hierarchy—a bag of unsorted observations isn't likely to engage your readers. But while a story must always inform, it should also delight (as much as possible), and inspire. It should make the complexity of the problem accessible—or, at least, approachable—without simplifications that preclude insight into how concepts connect (they always do).

the story of making science stories

Just like science, explaining science is a process—one that can be more vexing than the science itself!

In science one tries to tell people, in such a way as to be understood by everyone, something that no one ever knew before. But in poetry, it’s the exact opposite.
—Paul Dirac, Mathematical Circles Adieu by H. Eves [quoted]

I have previously written about the process of taking a scientific statement (Creating Scientific American Graphic Science graphics) and turning it into a data visualization or, more broadly, visual story.

BD Genomics 3D art exhibit - AGBT 2017 / Martin Krzywinski @MKrzywinski mkweb.bcgsc.ca
December 2015. Composition of bacteria in household dust.
BD Genomics 3D art exhibit - AGBT 2017 / Martin Krzywinski @MKrzywinski mkweb.bcgsc.ca
June 2015. Relationship between genes and traits.
BD Genomics 3D art exhibit - AGBT 2017 / Martin Krzywinski @MKrzywinski mkweb.bcgsc.ca
September 2014. Similarity of human, Denisovan, chimp, bonobo, and gorilla genomes.

The process of the creation of one of these visual stories is itself a story. A story about how the genome is not a blueprint, a discovery of Hilbertonians, which are creatures that live on the Hilbert curve, how algorithms for protein folding can be used to generate art based on the digits of `\pi`, or how we can make human genome art by humans with genomes. I've also written about my design process in creating the cover for Genome Research and the cover of PNAS. As always, not everything works out all the time—read about the EMBO Journal covers that never made it.

BD Genomics 3D art exhibit - AGBT 2017 / Martin Krzywinski @MKrzywinski mkweb.bcgsc.ca
Cover image accompanying our article on mouse vasculature development. Biology turns astrophysical. PNAS 1 May 2012; 109 (18)
BD Genomics 3D art exhibit - AGBT 2017 / Martin Krzywinski @MKrzywinski mkweb.bcgsc.ca
Cover image accompanying Spark: A navigational paradigm for genomic data exploration. Genome Research 22 (11).
BD Genomics 3D art exhibit - AGBT 2017 / Martin Krzywinski @MKrzywinski mkweb.bcgsc.ca
Pi Day 2014 poster | 132 paths with E=-23 of 64 digits of Pi, sorted by aspect ratio.

Here, I'd like to walk you through the process and sketches of creating a story based on the idea of differences in data and how the story can be used to understand the function of cells and disease.

the difference is in the differences

The visual story is a creative collaboration with Becton Dickinson and The Linus Group and its creation began with the concept of differences. The art was on display at AGBT 2017 conference and accompanies BD's launch of the Resolve platform and "Difference of One in Genomics".

Starting with the idea of the "difference of one", our goal was to create artistic representations of data sets generated using the BD Resolve platform, which generates single-cell transcriptomes, that captured a variety of differences that are relevant in genomics research.

The data art pieces were installed in a gallery style, with data visualization and artistic expression in equal parts.

The art itself is an old school take on virtual reality. Unlike modern VR, which isolates the participants from one another, we chose a low-tech route that not only brings the audience closer to the data but also to each other.

data in the art

The data were generated using the BD Resolve single-cell transcriptomics platform. For each of the three art pieces, we identified a data set that captured a variety of differences.

  1. disease onset—how does gene expression in tumor cells differ from normal cells?
  2. disease progression—as a tumor grows and spreads, how does expression change?
  3. background variation—how does gene expression change between normal cells that perform a different function?
BD Genomics 3D art exhibit - AGBT 2017 / Martin Krzywinski @MKrzywinski mkweb.bcgsc.ca

The real surprise and insight is in difference that ultimately advance our thinking (Data visualization: amgibuity as a fellow traveller. (2013) Nat. Methods 10:613-615).

Figuring out which differences are of this kind requires that instead of "What's new?" we ask "What's different?"

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news + thoughts

The SEIRS model for infectious disease dynamics

Thu 18-06-2020

Realistic models of epidemics account for latency, loss of immunity, births and deaths.

We continue with our discussion about epidemic models and show how births, deaths and loss of immunity can create epidemic waves—a periodic fluctuation in the fraction of population that is infected.

Martin Krzywinski @MKrzywinski mkweb.bcgsc.ca
Nature Methods Points of Significance column: The SEIRS model for infectious disease dynamics. (read)

This column has an interactive supplemental component (download code) that allows you to explore epidemic waves and introduces the idea of the phase plane, a compact way to understand the evolution of an epidemic over its entire course.

Martin Krzywinski @MKrzywinski mkweb.bcgsc.ca
Nature Methods Points of Significance column: The SEIRS model for infectious disease dynamics. (Interactive supplemental materials)

Bjørnstad, O.N., Shea, K., Krzywinski, M. & Altman, N. (2020) Points of significance: The SEIRS model for infectious disease dynamics. Nature Methods 17:557–558.

Background reading

Bjørnstad, O.N., Shea, K., Krzywinski, M. & Altman, N. (2020) Points of significance: Modeling infectious epidemics. Nature Methods 17:455–456.

Gene Machines

Fri 05-06-2020

Shifting soundscapes, textures and rhythmic loops produced by laboratory machines.

In commemoration of the 20th anniversary of Canada's Michael Smith Genome Sciences Centre, Segue was commissioned to create an original composition based on audio recordings from the GSC's laboratory equipment, robots and computers—to make “music” from the noise they produce.

Martin Krzywinski @MKrzywinski mkweb.bcgsc.ca
Gene Machines by Segue. Now available on vinyl.

Virus Mutations Reveal How COVID-19 Really Spread

Mon 01-06-2020

Genetic sequences of the coronavirus tell story of when the virus arrived in each country and where it came from.

Our graphic in Scientific American's Graphic Science section in the June 2020 issue shows a phylogenetic tree based on a snapshot of the data model from Nextstrain as of 31 March 2020.

Martin Krzywinski @MKrzywinski mkweb.bcgsc.ca
Virus Mutations Reveal How COVID-19 Really Spread. Text by Mark Fischetti (Senior Editor), art direction by Jen Christiansen (Senior Graphics Editor), source: Nextstrain (enabled by data from GISAID).

Cover of Nature Cancer April 2020

Mon 27-04-2020

Our design on the cover of Nature Cancer's April 2020 issue shows mutation spectra of patients from the POG570 cohort of 570 individuals with advanced metastatic cancer.

Martin Krzywinski @MKrzywinski mkweb.bcgsc.ca
Each ellipse system represents the mutation spectrum of an individual patient. Individual ellipses in the system correspond to the number of base changes in a given class and are layered by mutation count. Ellipse angle is controlled by the proportion of mutations in a class within the sample and its size is determined by a sigmoid mapping of mutation count scaled within the layer. The opacity of each system represents the duration since the diagnosis of advanced disease. (read more)

The cover design accompanies our report in the issue Pleasance, E., Titmuss, E., Williamson, L. et al. (2020) Pan-cancer analysis of advanced patient tumors reveals interactions between therapy and genomic landscapes. Nat Cancer 1:452–468.

Modeling infectious epidemics

Tue 16-06-2020

Every day sadder and sadder news of its increase. In the City died this week 7496; and of them, 6102 of the plague. But it is feared that the true number of the dead this week is near 10,000 ....
—Samuel Pepys, 1665

This month, we begin a series of columns on epidemiological models. We start with the basic SIR model, which models the spread of an infection between three groups in a population: susceptible, infected and recovered.

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

We discuss conditions under which an outbreak occurs, estimates of spread characteristics and the effects that mitigation can play on disease trajectories. We show the trends that arise when "flattenting the curve" by decreasing `R_0`.

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

This column has an interactive supplemental component (download code) that allows you to explore how the model curves change with parameters such as infectious period, basic reproduction number and vaccination level.

Martin Krzywinski @MKrzywinski mkweb.bcgsc.ca
Nature Methods Points of Significance column: Modeling infectious epidemics. (Interactive supplemental materials)

Bjørnstad, O.N., Shea, K., Krzywinski, M. & Altman, N. (2020) Points of significance: Modeling infectious epidemics. Nature Methods 17:455–456.

The Outbreak Poems

Sat 04-04-2020

I'm writing poetry daily to put my feelings into words more often during the COVID-19 outbreak.

Tears decline
the
plural of sad.
Souls look out
from
dark eye windows.

Read the poems and learn what a piku is.