Editing and reading early modern mathematical texts in the digital age

The advent of digital technology has brought a world of new possibilities for editors of historical texts. Though much has been written about conventions for digital editing, relatively little attention has been paid to the particular question of how best to deal with texts with heavily mathematical content. This essay outlines some ways of encoding mathematics in digital form, and then discusses three recent digital editions of collections of early modern mathematical manuscripts

Mutation analysis of the NSD1 gene in patients with autism spectrum disorders and macrocephaly

<p>Abstract</p> <p>Background</p> <p>Sotos syndrome is an overgrowth syndrome characterized by macrocephaly, advanced bone age, characteristic facial features, and learning disabilities, caused by mutations or deletions of the <it>NSD1 </it>gene, located at 5q35. Sotos syndrome has been described in a number of patients with autism spectrum disorders, suggesting that <it>NSD1 </it>could be involved in other cases of autism and macrocephaly.</p> <p>Methods</p> <p>We screened the <it>NSD1 </it>gene for mutations and deletions in 88 patients with autism spectrum disorders and macrocephaly (head circumference 2 standard deviations or more above the mean). Mutation analysis was performed by direct sequencing of all exons and flanking regions. Dosage analysis of <it>NSD1 </it>was carried out using multiplex ligation-dependent probe amplification.</p> <p>Results</p> <p>We identified three missense variants (R604L, S822C and E1499G) in one patient each, but none is within a functional domain. In addition, segregation analysis showed that all variants were inherited from healthy parents and in two cases were also present in unaffected siblings, indicating that they are probably nonpathogenic. No partial or whole gene deletions/duplications were observed.</p> <p>Conclusion</p> <p>Our findings suggest that Sotos syndrome is a rare cause of autism spectrum disorders and that screening for <it>NSD1 </it>mutations and deletions in patients with autism and macrocephaly is not warranted in the absence of other features of Sotos syndrome.</p

Computational biology of RNA interactions

The biodiversity of the RNA world has been underestimated for decades. RNA molecules are key building blocks, sensors, and regulators of modern cells. The biological function of RNA molecules cannot be separated from their ability to bind to and interact with a wide space of chemical species, including small molecules, nucleic acids, and proteins. Computational chemists, physicists, and biologists have developed a rich tool set for modeling and predicting RNA interactions. These interactions are to some extent determined by the binding conformation of the RNA molecule. RNA binding conformations are approximated with often acceptable accuracy by sequence and secondary structure motifs. Secondary structure ensembles of a given RNA molecule can be efficiently computed in many relevant situations by employing a standard energy model for base pair interactions and dynamic programming techniques. The case of bi-molecular RNARNA interactions can be seen as an extension of this approach. However, unbiased transcriptome-wide scans for local RNARNA interactions are computationally challenging yet become efficient if the binding motif/mode is known and other external information can be used to confine the search space. Computational methods are less developed for proteins and small molecules, which bind to RNA with very high specificity. Binding descriptors of proteins are usually determined by in vitro high-throughput assays (e.g., microarrays or sequencing). Intriguingly, recent experimental advances, which are mostly based on light-induced cross-linking of binding partners, render in vivo binding patterns accessible yet require new computational methods for careful data interpretation. The grand challenge is to model the in vivo situation where a complex interplay of RNA binders competes for the same target RNA molecule. Evidently, bioinformaticians are just catching up with the impressive pace of these developments