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fun + Amusement

Dummer - Like Nothing Else / A Hummer Satire

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

Martin Krzywinski @MKrzywinski mkweb.bcgsc.ca
What's after worst? This. (Dummer. Like nothing else.)

The project was well received by The New York Times and very poorly by someone who felt sending me hate mail was a good idea. It was — I loved it.

Other Hummer satires include fuh2.com — there's some hope for us all.


The World's Most Popular Questions

What are the world's most popular questions? After all, what we know defines us as much as what we ask. So, let's look at who we are.

Using Google's autocomplete feature, which suggests the most similar searches to the one you have entered, I maintain a real-time compilation of the most common questions asked by millions of worldwide internet users.

This project (a) yields insight into the zeitgeist and (b) scares me. My reason for fright are questions such as these:

General Issues

How do people do extreme couponing?

Why can't I hold all these limes?

Why do I always feel like murdering everyone?

What's up with the World

Is the world really flat?

is the world being controlled by aliens?

Limits & Desires

What happens if I make a formal commitment to Satan?

Love & Heart

Why is my boyfriend so insecure?

Why is my girlfriend so emotional?

Health

My head is full of pretty lumps.

Pain & Suffering

my elbow is dark and dry

why do I continue to hit myself with a hammer?

when does my head stop growing?

Sizes & Extremes

Who is the most powerful Jedi?

Where is the hardest part of your head?

Religion & Faith

Can Jesus microwave a burrito?

Can I pray with my eyes open?

Should I pray for a husband?

Neologisms - New Words, Much Needed

I like words. The pleasure of effectively using acerebral and defenestrate in the same sentence cannot be understated.

On occassion I found myself in a situation where no word fit, existing or that I know about. Instead of rushing to the dictionary, I decided to make up my own, such as inconversible (a statement without a logical converse), mystific (unexplainably wonderful), postpetizer (course ordered after dessert), prenopsis (a summary of something formulated before it was experienced), suscitate (breathe life into, for the first time), and others.

The current list of my neologisms is circos plot, compure, culturally inconversible, dependers, ee spammings, existangsty, fezday, hilbertonian, hive panel, hive plot, inconversible, metaomome, mystific, naytheism, naytheist, nes, neuroterror, neuroterrorism, newgrade, noward, nonposter, oldgrade, omome, omeomics, omicsophy, over, piddle, port knocking, postpetizer, pregratulate, prekfast, prenopsis, prepetizer, quinty, ratio hive, spammings, suscitate, unappropriate .


HDTR: High Dynamic Time Range Photography - Visualizing the Flow of Time

The HDTR method is a new approach to depicting the passage of time. High Dynamic Time Range (HDTR) images and are a composite of many photos taken over a long period of time, such as a day or even longer. Each part of the HDTR image is sampled from a different photo, either by column or row.

Martin Krzywinski @MKrzywinski mkweb.bcgsc.ca
An HDTR is generated from a set of time-lapse images. Here, a simple HDTR is created from 5 images taken at different times. From each image, a strip representing 20% of the image is extracted and the strips are blended to reduce banding artefacts. (hires)

For example, the left part of the HDTR image might show the scene from 7am and the very right from 8pm, capturing the variation in light across an entire day.

Martin Krzywinski @MKrzywinski mkweb.bcgsc.ca
An HDTR image shows the flow of time across a scene. Here the Vancouver skyline is shown from about 6pm (left) to 9pm (right). (Download)
news + thoughts

How Analyzing Cosmic Nothing Might Explain Everything

Thu 18-01-2024

Huge empty areas of the universe called voids could help solve the greatest mysteries in the cosmos.

My graphic accompanying How Analyzing Cosmic Nothing Might Explain Everything in the January 2024 issue of Scientific American depicts the entire Universe in a two-page spread — full of nothing.

Martin Krzywinski @MKrzywinski mkweb.bcgsc.ca
How Analyzing Cosmic Nothing Might Explain Everything. Text by Michael Lemonick (editor), art direction by Jen Christiansen (Senior Graphics Editor), source: SDSS

The graphic uses the latest data from SDSS 12 and is an update to my Superclusters and Voids poster.

Michael Lemonick (editor) explains on the graphic:

“Regions of relatively empty space called cosmic voids are everywhere in the universe, and scientists believe studying their size, shape and spread across the cosmos could help them understand dark matter, dark energy and other big mysteries.

To use voids in this way, astronomers must map these regions in detail—a project that is just beginning.

Shown here are voids discovered by the Sloan Digital Sky Survey (SDSS), along with a selection of 16 previously named voids. Scientists expect voids to be evenly distributed throughout space—the lack of voids in some regions on the globe simply reflects SDSS’s sky coverage.”

voids

Sofia Contarini, Alice Pisani, Nico Hamaus, Federico Marulli Lauro Moscardini & Marco Baldi (2023) Cosmological Constraints from the BOSS DR12 Void Size Function Astrophysical Journal 953:46.

Nico Hamaus, Alice Pisani, Jin-Ah Choi, Guilhem Lavaux, Benjamin D. Wandelt & Jochen Weller (2020) Journal of Cosmology and Astroparticle Physics 2020:023.

Sloan Digital Sky Survey Data Release 12

constellation figures

Alan MacRobert (Sky & Telescope), Paulina Rowicka/Martin Krzywinski (revisions & Microscopium)

stars

Hoffleit & Warren Jr. (1991) The Bright Star Catalog, 5th Revised Edition (Preliminary Version).

cosmology

H0 = 67.4 km/(Mpc·s), Ωm = 0.315, Ωv = 0.685. Planck collaboration Planck 2018 results. VI. Cosmological parameters (2018).

Error in predictor variables

Tue 02-01-2024

It is the mark of an educated mind to rest satisfied with the degree of precision that the nature of the subject admits and not to seek exactness where only an approximation is possible. —Aristotle

In regression, the predictors are (typically) assumed to have known values that are measured without error.

Practically, however, predictors are often measured with error. This has a profound (but predictable) effect on the estimates of relationships among variables – the so-called “error in variables” problem.

Martin Krzywinski @MKrzywinski mkweb.bcgsc.ca
Nature Methods Points of Significance column: Error in predictor variables. (read)

Error in measuring the predictors is often ignored. In this column, we discuss when ignoring this error is harmless and when it can lead to large bias that can leads us to miss important effects.

Altman, N. & Krzywinski, M. (2024) Points of significance: Error in predictor variables. Nat. Methods 20.

Background reading

Altman, N. & Krzywinski, M. (2015) Points of significance: Simple linear regression. Nat. Methods 12:999–1000.

Lever, J., Krzywinski, M. & Altman, N. (2016) Points of significance: Logistic regression. Nat. Methods 13:541–542 (2016).

Das, K., Krzywinski, M. & Altman, N. (2019) Points of significance: Quantile regression. Nat. Methods 16:451–452.

Convolutional neural networks

Tue 02-01-2024

Nature uses only the longest threads to weave her patterns, so that each small piece of her fabric reveals the organization of the entire tapestry. – Richard Feynman

Following up on our Neural network primer column, this month we explore a different kind of network architecture: a convolutional network.

The convolutional network replaces the hidden layer of a fully connected network (FCN) with one or more filters (a kind of neuron that looks at the input within a narrow window).

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

Even through convolutional networks have far fewer neurons that an FCN, they can perform substantially better for certain kinds of problems, such as sequence motif detection.

Derry, A., Krzywinski, M & Altman, N. (2023) Points of significance: Convolutional neural networks. Nature Methods 20:1269–1270.

Background reading

Derry, A., Krzywinski, M. & Altman, N. (2023) Points of significance: Neural network primer. Nature Methods 20:165–167.

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

Neural network primer

Tue 10-01-2023

Nature is often hidden, sometimes overcome, seldom extinguished. —Francis Bacon

In the first of a series of columns about neural networks, we introduce them with an intuitive approach that draws from our discussion about logistic regression.

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

Simple neural networks are just a chain of linear regressions. And, although neural network models can get very complicated, their essence can be understood in terms of relatively basic principles.

We show how neural network components (neurons) can be arranged in the network and discuss the ideas of hidden layers. Using a simple data set we show how even a 3-neuron neural network can already model relatively complicated data patterns.

Derry, A., Krzywinski, M & Altman, N. (2023) Points of significance: Neural network primer. Nature Methods 20:165–167.

Background reading

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

Cell Genomics cover

Mon 16-01-2023

Our cover on the 11 January 2023 Cell Genomics issue depicts the process of determining the parent-of-origin using differential methylation of alleles at imprinted regions (iDMRs) is imagined as a circuit.

Designed in collaboration with with Carlos Urzua.

Martin Krzywinski @MKrzywinski mkweb.bcgsc.ca
Our Cell Genomics cover depicts parent-of-origin assignment as a circuit (volume 3, issue 1, 11 January 2023). (more)

Akbari, V. et al. Parent-of-origin detection and chromosome-scale haplotyping using long-read DNA methylation sequencing and Strand-seq (2023) Cell Genomics 3(1).

Browse my gallery of cover designs.

Martin Krzywinski @MKrzywinski mkweb.bcgsc.ca
A catalogue of my journal and magazine cover designs. (more)

Science Advances cover

Thu 05-01-2023

My cover design on the 6 January 2023 Science Advances issue depicts DNA sequencing read translation in high-dimensional space. The image showss 672 bases of sequencing barcodes generated by three different single-cell RNA sequencing platforms were encoded as oriented triangles on the faces of three 7-dimensional cubes.

More details about the design.

Martin Krzywinski @MKrzywinski mkweb.bcgsc.ca
My Science Advances cover that encodes sequence onto hypercubes (volume 9, issue 1, 6 January 2023). (more)

Kijima, Y. et al. A universal sequencing read interpreter (2023) Science Advances 9.

Browse my gallery of cover designs.

Martin Krzywinski @MKrzywinski mkweb.bcgsc.ca
A catalogue of my journal and magazine cover designs. (more)
Martin Krzywinski | contact | Canada's Michael Smith Genome Sciences CentreBC Cancer Research CenterBC CancerPHSA
Google whack “vicissitudinal corporealization”
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