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Gene Cultures — MIT Museum Exhibit

Scale and structure of the human genome

1 · The MIT museum reopens

The MIT Museum reopens at its new location on 2nd October 2022.

My art appears in the new Gene Cultures exhibit.

2 · Gene Cultures Exhibit

As the pace of technological advances in the field of genetic discovery quickens, questions arise.

Who decides how and when transformative new biotechnologies will be used? What questions do we need to ask before making decisions leading to irrevocable results?

Join the conversation as you explore dramatic breakthroughs in genetic technologies and engage with artworks — wiitty, provocative, absurd, and profound — that prompt us to consider our future — now.

The Gene Cultures exhibit is Located in the Henri A. Termeer Gallery

Text by MIT museum

3 · My art at the genome exibit

Gene Cultures exhibit at the MIT Museum - Martin Krzywinski / Martin Krzywinski @MKrzywinski mkweb.bcgsc.ca
The plaque explaining the projection that shows the scale of structures in the human genome.

To find my exhibit, look for the pink chicken. You can't miss it.

Gene Cultures exhibit at the MIT Museum - Martin Krzywinski / Martin Krzywinski @MKrzywinski mkweb.bcgsc.ca
The animated projection is on a large wall at the entrance to the exhibit. Right next to the pink chicken. (photo Martin Krzywinski)
Gene Cultures exhibit at the MIT Museum - Martin Krzywinski / Martin Krzywinski @MKrzywinski mkweb.bcgsc.ca
The animated projection is on a large wall at the entrance to the exhibit. Right next to the pink chicken. (photo Anna Olivella)

3.1 · Animation sequence

Gene Cultures exhibit at the MIT Museum - Martin Krzywinski / Martin Krzywinski @MKrzywinski mkweb.bcgsc.ca
The opening sequence cycles through the layers to be explained.
Gene Cultures exhibit at the MIT Museum - Martin Krzywinski / Martin Krzywinski @MKrzywinski mkweb.bcgsc.ca
The genome is big. We count up to 3,088,269,832 bases, which is the total length of chromosomes 1–22,X,Y in the hg38 human genome assembly.
Gene Cultures exhibit at the MIT Museum - Martin Krzywinski / Martin Krzywinski @MKrzywinski mkweb.bcgsc.ca
The contents of the genome are grouped into chromosomes.
Gene Cultures exhibit at the MIT Museum - Martin Krzywinski / Martin Krzywinski @MKrzywinski mkweb.bcgsc.ca
The bands reflect density of chromatin packing.
Gene Cultures exhibit at the MIT Museum - Martin Krzywinski / Martin Krzywinski @MKrzywinski mkweb.bcgsc.ca
About 20,000 genes represent the key functional components.
Gene Cultures exhibit at the MIT Museum - Martin Krzywinski / Martin Krzywinski @MKrzywinski mkweb.bcgsc.ca
Genes (and the proteins that the encode) are key targets for therapies.

The size and position of elements in the animation is based on the hg38 assembly, which is (as of 2022) the canonical reference.

The very latest human genome assembly (CHM13v2 telomere-to-telomere) has 3,117,275,501 bases.

4 · Credits

concept and art direction
Exhibit developer (Life Sciences)
concept & design
Martin Krzywinski
Staff Scientist
Canada's Michael Smith Genome Sciences Centre
creative lead
Kim Gim
motion designer
Devon Burgoyne
designer
An Bui
content strategist
Ksenia Dynkin
Canada's Michael Smith Genome Sciences Centre (GSC) at BC Cancer is an international leader in genomics, proteomics and bioinformatics for precision medicine. By developing and deploying cutting-edge genome sequencing, computational and analytical technology, we are creating novel strategies to prevent and diagnose cancers and other diseases, uncovering new therapeutic targets and helping the world realize the social and economic benefits of genome science.
We are the Canadian node of the Earth Biogenome Project.
news + thoughts

Convolutional neural networks

Thu 17-08-2023

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:.

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)

Regression modeling of time-to-event data with censoring

Thu 17-08-2023

If you sit on the sofa for your entire life, you’re running a higher risk of getting heart disease and cancer. —Alex Honnold, American rock climber

In a follow-up to our Survival analysis — time-to-event data and censoring article, we look at how regression can be used to account for additional risk factors in survival analysis.

We explore accelerated failure time regression (AFTR) and the Cox Proportional Hazards model (Cox PH).

Martin Krzywinski @MKrzywinski mkweb.bcgsc.ca
Nature Methods Points of Significance column: Regression modeling of time-to-event data with censoring. (read)

Dey, T., Lipsitz, S.R., Cooper, Z., Trinh, Q., Krzywinski, M & Altman, N. (2022) Points of significance: Regression modeling of time-to-event data with censoring. Nature Methods 19:1513–1515.


© 1999–2023 Martin Krzywinski | contact | Canada's Michael Smith Genome Sciences CentreBC Cancer Research CenterBC CancerPHSA