Abstract: This talk has two disparate topics: the biology of the regenerative axolotl and data mining of large datasets.
The axolotl is a salamander endemic to Mexico. Salamanders have the ability to regenerate limbs, lens, portions of the heart and brain, and other tissues and are the vertebrate champions of regeneration . The molecular aspects of axolotl limb regeneration and early development are understudied. We examined the genes expressed during limb regeneration and early development via RNA-seq. Challenges arise during RNA-seq data analysis as the axolotl has no genome sequence and very poor gene annotation. We developed comparative transcriptomic methods to annotate axolotl genes. In the first half of the talk, I’ll discuss this comparative method and the results with insights about the limb regeneration process and early development in this fascinating species.
In the second half of the talk, I’ll discuss a relatively simple algorithm we have developed for mining very large text datasets. We apply it to an extended version of PubMed containing over 30 million abstracts and 3 million full text articles. This algorithm provides scientists with a powerful entry point to literature and should be useful in accelerating discoveries in the wet lab by clarifying avenues of study and likely targets for the next experiment.