Nature Methods: Points of View
The first Points of View column was about color coding in the July 2010 issue of Nature Methods. In its 5 year history, the column has established a significant legacy— it is one of the most frequently accessed parts of Nature Methods. The community sees the value in clear and effective visual communication and acknowledges the need for a forum in which best practices in the field are presented practically and accessibly.
2010–2012
Bang Wong, in collaboration with visiting authors (Noam Shoresh, Nils Gehlenborg, Cydney Nielsen and Rikke Schmidt Kjærgaard), has penned 29 columns in the period of August 2010 to December 2012, covering broad topics such as salience, Gestalt principles, color, typography, negative space, layout, and data integration.
2012–2014
The announcement of the return of the column, together with its history and a description of me, the new author, are available at the Nature Methods methagora blog. Humor is kept by repeated reference to my now-dead-but-once-famous pet rat.
When it was A.C. Greyling's turn to speak at a debate in which Christopher Hitchens and Richard Dawkins already made their points, Greyling said
When one gets up to speak this late in a debate, one is a bit tempated to quote that Hungarian M.P. who after a long, long, long discussion in the parliament in Budapest stood up and said, "Everything has been said but not everybody said it yet." (watch on YouTube)
Indeed, this is quite how I feel after being offered to be the new author of Nature Methods Point of View column. Both Bang and Hitchens provide significant inspiration for me, so Greyling's words are particularly fitting.
To improve on the column is impossible. My challenge is to identify useful topics that have not yet been covered. I will be working closely with Nature Methods and Bang to ensure that the columns strike the right balance of topic, tone and timbre.
In 2013 the Points of View column spawned the Points of Significance column, which deals with statistics in biological science.
For the month of August 2013, the entire set of 35 columns is available for free.
2015 and beyond
The column continues to run, though no longer monthly.
A PDF eBook of the 38 Points of View articles published between August 2010 and February 2015 is now available at the Nature Shop for $7.99 under the title Visual strategies for biological data: the collected Points of View.
Convolutional neural networks
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).
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
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.
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
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.
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.
Science Advances cover
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.
Kijima, Y. et al. A universal sequencing read interpreter (2023) Science Advances 9.
Browse my gallery of cover designs.