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Distractions and amusements, with a sandwich and coffee.

Lips that taste of tears, they say, are the best for kissing.
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They serve as the form for The Outbreak Poems.

Numbers are a lot of fun. They can start conversations—the interesting number paradox is a party favourite: every number must be interesting because the first number that wasn't would be very interesting! Of course, in the wrong company they can just as easily end conversations.

It is not yet known whether the digits of π are normal—determining this is an important problem in mathematics. In other words, is the distribution of digit frequencies in π uniform? Do each of the digits 0–9 appear exactly 1/10th of the time, does every two-digit string appear exactly 1/100th of the time and so on for every finite-length string^{1}?

^{1} One interesting finite-length string is the 6-digit Fenyman Point (...999999...) which appears at digit 762 in π. The Feynman Point was the subject of 2014 `\pi` Day art.

This question can be posed for different representations of π—in different bases. The distribution frequencies of 1/10, 1/100, and so on above refer to the representation of π in base 10. This is the way we're used to seeing numbers. However, if π is encoded as binary (base 2), would all the digits in 11.00100100001111... be normal? The table below shows the first several digits of π in each base from 2 to 16, as well as the natural logarithm base, `e`.

base, `b` | `\pi_b` | base, `b` | `\pi_b` |

2 | 11.00100100001111 | 10 | 3.14159265358979 |

3 | 10.01021101222201 | 11 | 3.16150702865A48 |

4 | 3.02100333122220 | 12 | 3.184809493B9186 |

5 | 3.03232214303343 | 13 | 3.1AC1049052A2C7 |

6 | 3.05033005141512 | 14 | 3.1DA75CDA813752 |

7 | 3.06636514320361 | 15 | 3.21CD1DC46C2B7A |

8 | 3.11037552421026 | 16 | 3.243F6A8885A300 |

`e` | 10.10100202000211 | ||

source: virtuescience.com |

Because the digits in the numbers are essentially random (this is a conjecture), the essence of the art is based on randomness.

A vexing consequence of π being normal is that, because it is non-terminating, π would contain *all* patterns. Any word you might think of, encoded into numbers in any way, would appear infinitely many times. The entire works of Shakespeare, too. As well, all his plays in which each sentence is reversed, or has one spelling mistake, or two! In fact, you would eventually find π within π, but only if you have infinite patience.

This is why any attempts to use the digits of `\pi` to infer meaning about anything is ridiculous. The exact opposite of what you find is also in `\pi`.

A number can be normal in one base, but another. For example, Stoneham's constant,

`\alpha_{2,3} = 1/2 + 1/(2^{3^1} 3^1) + 1/(2^{3^2} 3^2) + 1/(2^{3^3} 3^3) + ... + 1/(2^{3^k} 3^k) + ... `

is 0.54188368083150298507... in base 10 and 0.100010101011100011100011100... in base 2.

Stoneham's constant is provably normal in base 2. In some other bases, such 6, Stoneham's constant is provably not normal.

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

Patience but know where to put it.

Favourite looks words tastes phrases ex foreign origins.

Melody same feelings different.

Desire life remote control.

Sun rays burn off night dust into day.

Sanitize in perfection now.

Door closes next next door closes next nothing is left open.

One of the pair is from the other.

Eyes look at eyes and see themselves.

Look back and pass destinations.

A poster full of epidemiological worry and statistics. Now updated with the genome of SARS-CoV-2 and COVID-19 case statistics as of 3 March 2020.

Bacterial and viral genomes of various diseases are drawn as paths with color encoding local GC content and curvature encoding local repeat content. Position of the genome encodes prevalence and mortality rate.

The deadly genomes collection has been updated with a posters of the genomes of SARS-CoV-2, the novel coronavirus that causes COVID-19.

A workshop in using the Circos Galaxy wrapper by Hiltemann and Rasche. Event organized by Australian Biocommons.

Galaxy wrapper training materials, Saskia Hiltemann, Helena Rasche, 2020 Visualisation with Circos (Galaxy Training Materials).

My webinar on fundamental concepts in data visualization and visual communication of scientific data and concepts. Event organized by Australian Biocommons.

*With one eye you are looking at the outside world, while with the other you are looking within yourself.*

—Amedeo Modigliani

Following up with our Markov Chain column and Hidden Markov model column, this month we look at how Markov models are trained using the example of biased coin.

We introduce the concepts of forward and backward probabilities and explicitly show how they are calculated in the training process using the Baum-Welch algorithm. We also discuss the value of ensemble models and the use of pseudocounts for cases where rare observations are expected but not necessarily seen.

Grewal, J., Krzywinski, M. & Altman, N. (2019) Points of significance: Markov models — training and evaluation of hidden Markov models. *Nature Methods* **17**:121–122.

Altman, N. & Krzywinski, M. (2019) Points of significance: Hidden Markov models. *Nature Methods* **16**:795–796.

Altman, N. & Krzywinski, M. (2019) Points of significance: Markov Chains. *Nature Methods* **16**:663–664.

*Science. Timeliness. Respect.*

Read about the design of the clothing, music, drinks and art for the Genome Sciences Center 20th Anniversary Celebration, held on 15 November 2019.

As part of the celebration and with the help of our engineering team, we framed 48 flow cells from the lab.

Each flow cell was accompanied by an interpretive plaque explaining the technology behind the flow cell and the sample information and sequence content.