And whatever I do will become forever what I've done.don't rehearsemore quotes

# making poetry out of spam is fun

The Outbreak Poems — artistic emissions in a pandemic

# things on the side

science + music
Hear the Gene machines: the music of a modern genomics laboratory. Music by Segue. Album release by ADSR Collective. Video by Sam King.
Segue Gene Machines - retro desktops.

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. (Vinyl crowdfunding, Digital preorder, Album preview)

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.

Machine noise is a challenging palette of musical ingredients - sharp, abrasive and whirring sounds are typically unpleasant. For one night, these machines are repurposed as acoustic performers.

In the process of creating “Gene Machines”, recordings were analyzed for their specific frequency profiles and then used to generate melodic or percussive sounds. Together with bass from a Moog synthesizer, the sounds were stretched, manipulated and sequenced into a series of compositions. Each composition is based on the recording from one specific laboratory machine, emphasizing the quality of its tone and timbre.

## vinyl crowdfunding

Analogue machines in analogue form.

## desktops

1920 × 1080 desktops of the album artwork.

# Points of Significance celebrates 50th column

Mon 24-08-2020

We are celebrating the publication of our 50th column!

To all our coauthors — thank you and see you in the next column!

Nature Methods Points of Significance: Celebrating 50 columns of clear explanations of statistics. (read)

# Uncertainty and the management of epidemics

Mon 24-08-2020

When modelling epidemics, some uncertainties matter more than others.

Public health policy is always hampered by uncertainty. During a novel outbreak, nearly everything will be uncertain: the mode of transmission, the duration and population variability of latency, infection and protective immunity and, critically, whether the outbreak will fade out or turn into a major epidemic.

The uncertainty may be structural (which model?), parametric (what is $R_0$?), and/or operational (how well do masks work?).

This month, we continue our exploration of epidemiological models and look at how uncertainty affects forecasts of disease dynamics and optimization of intervention strategies.

Nature Methods Points of Significance column: Uncertainty and the management of epidemics. (read)

We show how the impact of the uncertainty on any choice in strategy can be expressed using the Expected Value of Perfect Information (EVPI), which is the potential improvement in outcomes that could be obtained if the uncertainty is resolved before making a decision on the intervention strategy. In other words, by how much could we potentially increase effectiveness of our choice (e.g. lowering total disease burden) if we knew which model best reflects reality?

This column has an interactive supplemental component (download code) that allows you to explore the impact of uncertainty in $R_0$ and immunity duration on timing and size of epidemic waves and the total burden of the outbreak and calculate EVPI for various outbreak models and scenarios.

Nature Methods Points of Significance column: Uncertainty and the management of epidemics. (Interactive supplemental materials)

Bjørnstad, O.N., Shea, K., Krzywinski, M. & Altman, N. (2020) Points of significance: Uncertainty and the management of epidemics. Nature Methods 17.

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

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.

# Cover of Nature Genetics August 2020

Mon 03-08-2020

Our design on the cover of Nature Genetics's August 2020 issue is “Dichotomy of Chromatin in Color” . Thanks to Dr. Andy Mungall for suggesting this terrific title.

Dichotomy of Chromatin in Color. Nature Genetics, August 2020 issue. (read more)

The cover design accompanies our report in the issue Gagliardi, A., Porter, V.L., Zong, Z. et al. (2020) Analysis of Ugandan cervical carcinomas identifies human papillomavirus clade–specific epigenome and transcriptome landscapes. Nature Genetics 52:800–810.

# Poster Design Guidelines

Wed 15-07-2020

Clear, concise, legible and compelling.

The PDF template is a poster about making posters. It provides design, typography and data visualiation tips with minimum fuss. Follow its advice until you have developed enough design sobriety and experience to know when to go your own way.

Poster Design Guidelines — Clear, concise, legible and compelling..

# 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.

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.

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.