Report from 1992 in Nature on the cDNA controversy:
www.nature.com/articles/356...

Worth reading Baltimore's report at the time: genome.gov/sites/defaul...

"Consideration should be given to... cDNA maps. The Committee recognizes the many challenges... it is not yet known to what extent eukaryotic cells rely on control at the transcriptional level."

Watson's objection to cDNA sequencing was that the function of the genes was not yet known 👀

A strange take considering he did not have that objection to working on the structure of DNA when the function of DNA was not known.

Venter's paper on ESTs: www.science.org/doi/10.1126/...

link.springer.com/article/10.1...

link.springer.com/article/10.1...

link.springer.com/article/10.1...

Brilliant work by Joseph Rich and Conrad Oakes working out the math and implementing wompwomp. It has been submitted to @bioconductor.bsky.social and in the future we may also implement it in Python to facilitate usage with single-cell genomics packages. Any feedback will be appreciated. Thx!

he underlying optimization problems are NP-hard, but for many visualization tasks can probably be solved optimally. It was fun returning to Bryant and Huson's NeighborNet as a good heuristic, but there is certainly room for improvement.

The advantage of organizing with wompwomp is evident in the clarity one sees when tracing, say, the Lannisters vs. Westeros

The improvements produced by wompwomp are evident in the Game of Thrones dataset displayed at the opening of this thread. To the left is the alluvial plot without wompwomp, to the right with wompwomp.

The underlying optimization questions turned out to be really interesting. The methods underlying wompwomp are described in the accompanying preprint on @cscg-bot.bsky.social. arxiv.org/abs/2509.03761

Work on wompwomp was motivated by plots made for this paper, where we first implemented a naïve approach to optimizing an alluvial plot (Fig. 1 panel D)
bsky.app/profile/alii...

wompwomp sorts columns and blocks within columns to best reveal structure in data. For instance, this is a comparison of clustering algorithms viewed in a randomly organized alluvial plot, fixed columns (only blocks sorted), and fully optimized with wompwomp.