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The Answer is Know

In the realm of computational biology, sometimes learning what isn鈥檛 possible is just as important as learning what is. That has been the case with recent research conducted by Professor Yi-Chieh (Jessica) Wu and her colleagues, who have presented an algorithm for assessing feasibility of gene families with multiple loci and samples.

Traditional methods of phylogenetic tree mapping have investigated gene families using methods that are restricted to using data from an individual sample. 鈥淚f you allow for multiple individuals, you get data that you can鈥檛 explain,鈥� Wu says. 鈥淭hat means that there is some explanation, but it can鈥檛 be explained by this model.鈥�

Wu鈥檚 publication bridges these models by considering a joint model and allowing for multiple loci聽and聽multiple samples per species. 鈥淩econciliation Feasibility in the Presence of Gene Duplication, Loss, and Coalescence with Multiple Individuals per Species,鈥� recently accepted to BMC Bioinformatics, was coauthored by Wu, Jennifer Rogers 鈥�16, Andrew Fishberg 鈥�16 and Nora Youngs (Colby College).

鈥淣ow we know that the current models are insufficient,鈥� says Wu. 鈥淪o we know that we have to develop new models or extend current models. It鈥檚 revealing a problem that before we could have intuited but couldn鈥檛 see. Now we have algorithms that can reconstruct evolutionary history or identify errors in the data that make your model insufficient.鈥�

This work is an extension of Wu鈥檚 postdoctoral work, which is already being used in the field. 鈥淢y work is driven by the idea that biologists might have specific questions to ask, and I want to help them answer them.聽As we sequence more genomes, data sets will increasingly call for the types of methods we present in this paper.鈥�