Stanford's New Algorithm Compares Cells Across Species To Find Similarities

A Group of bioengineers from Stanford University has developed a new algorithm with a unique and specialized function. The algorithm was designed to compare cells across different species. The algorithm can identify similar cellular types no matter the species and can be used in creatures including fish, mice, flatworms, and sponges that have been diverged evolutionarily for millions of years.

The goal of the new algorithm is to help scientists fill in gaps in human understanding of evolution. Comparing cells from different species helps biologists to understand how cell types arose and how they adapted to function in different kinds of life. Evolutionary biologists have sought in recent years to leverage technology to make it possible to sequence and identify all cells throughout the entire organism.

Scientists are looking to classify all types of cells in a wide variety of organisms. Bo Wang, assistant professor of bioengineering at Stanford University, and his team developed the algorithm to link similar cell types across evolutionary distances. In the research, the team used seven different species to compare 21 pairings and were able to identify cell types present in all species along with their similarities and differences.

Lead researcher on the project is Alexander Tarashansky, and he says the idea for the algorithm came from Professor Wang when he was asked to analyze cell-type data sets from two different worms being studied in the lab. Tarashansky said he was "struck by how stark" differences between the two worms were, and while the team believed they should have been similar cell types, standard techniques used to study them didn't recognize them as being similar.

That problem started the development of an algorithm to better match cell types across species. Rather than finding a one-to-one gene match, which is how previous data matching worked, the new algorithm can match one gene in a sponge to all potentially corresponding human genes and determine the correct one. The new algorithm will allow researchers to collect data on a wide variety of species for analysis. Over time the ability of biologists to recognize the trajectory of cell types in different organisms will improve.