Safe, fallen down this way, I want to be just what I am.safe at lastmore quotes

# vizbi: exciting

EMBO Practical Course: Bioinformatics and Genome Analysis, 5–17 June 2017.

# Visualization Principles Tutorial

This tutorial took place on Monday Mar 5th 2012 at VIZBI 2012 in Heidelberg Germany.

## Introduction

Jessie Kennedy · We will present fundamental principles of graphic design and visual communication that will help you create more effective interactive and print visualizations. You will learn how the purposeful use of salience, color, consistency and layout can help communicate large data sets and complex ideas with greater immediacy and clarity.

Cydney Nielsen · We will illustrate how these principles were implemented in ABySS-Explorer to visualize genome assemblies, an example to show you ways to apply design ideas to your own project.

Martin Krzywinski · At the end of the tutorial, you will apply what you have learned in an interactive group session in which you will design a figure illustrating a biological process.

## Agenda

 9:30 – 10:15 45 min Jessie KennedyPrinciples 10:15 – 10:25 10 min break 10:25 – 11:10 45 min Cydney NielsenDesign Process 11:10 – 11:20 10 min form teams + select figure to critique 11:20 – 11:30 10 min break 11:30 – 12:00 30 min Martin KrzywinskiPractical — Breakout sessiondownload papers 12:00 – 13:00 60 min team presentationsInteractive suggested solutions

It is not necessary to read the paper from which your figure was selected. I have included the papers only if you are interested in learning about the figure's context.

## Visualization and Design Resources

Designing effective visualizations in the biological sciences (PSA Genomics Workshop, Seattle, 12 July 2011)

Designing effective visualizations in the biological sciences (Genome Sciences Center bioinformatics seminar, 26 August 2011)

Drawing Data: Creaing information-rich, informative and appealing figures for publication and presentation (BCCA workshop, 8 Jun 2011)

Behind a great figure is a design principle (BCB Spring Seminar, Iowa State, 27 Feb 2012)

Visualizing Quantitative Information (Genome Sciences Center bioinformatics seminar)

## Visualization Principles VIZBI Book Chapter

Look for my chapter on visualization principles in the upcoming Visualizing Biological Data — a Practical Guide. This book is being written by VIZBI 2011 participants and edited by Sean O'Donoghue and Jim Procter.

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# $k$ index: a weightlighting and Crossfit performance measure

Wed 07-06-2017

Similar to the $h$ index in publishing, the $k$ index is a measure of fitness performance.

To achieve a $k$ index for a movement you must perform $k$ unbroken reps at $k$% 1RM.

The expected value for the $k$ index is probably somewhere in the range of $k = 26$ to $k=35$, with higher values progressively more difficult to achieve.

In my $k$ index introduction article I provide detailed explanation, rep scheme table and WOD example.

# Dark Matter of the English Language—the unwords

Wed 07-06-2017

I've applied the char-rnn recurrent neural network to generate new words, names of drugs and countries.

The effect is intriguing and facetious—yes, those are real words.

But these are not: necronology, abobionalism, gabdologist, and nonerify.

These places only exist in the mind: Conchar and Pobacia, Hzuuland, New Kain, Rabibus and Megee Islands, Sentip and Sitina, Sinistan and Urzenia.

And these are the imaginary afflictions of the imagination: ictophobia, myconomascophobia, and talmatomania.

And these, of the body: ophalosis, icabulosis, mediatopathy and bellotalgia.

Want to name your baby? Or someone else's baby? Try Ginavietta Xilly Anganelel or Ferandulde Hommanloco Kictortick.

When taking new therapeutics, never mix salivac and labromine. And don't forget that abadarone is best taken on an empty stomach.

And nothing increases the chance of getting that grant funded than proposing the study of a new –ome! We really need someone to looking into the femome and manome.

# Dark Matter of the Genome—the nullomers

Wed 31-05-2017

An exploration of things that are missing in the human genome. The nullomers.

Julia Herold, Stefan Kurtz and Robert Giegerich. Efficient computation of absent words in genomic sequences. BMC Bioinformatics (2008) 9:167

# Clustering

Wed 31-05-2017
Clustering finds patterns in data—whether they are there or not.

We've already seen how data can be grouped into classes in our series on classifiers. In this column, we look at how data can be grouped by similarity in an unsupervised way.

Nature Methods Points of Significance column: Clustering. (read)

We look at two common clustering approaches: $k$-means and hierarchical clustering. All clustering methods share the same approach: they first calculate similarity and then use it to group objects into clusters. The details of the methods, and outputs, vary widely.

Altman, N. & Krzywinski, M. (2017) Points of Significance: Clustering. Nature Methods 14:545–546.