Showing posts with label bioinformatics. Show all posts
Showing posts with label bioinformatics. Show all posts

Thursday, April 30, 2020

"Community Matters"

Some art that arose from our research was published recently in the collection The Art of Theoretical Biology. Here are some details about our contribution.

Title: Community Matters

Authors: Anna C. F. Lewis, Nick S. Jones, Mason A. Porter, and Charlotte M. Deane

Saturday, June 06, 2015

What Happens in Singapore Stays in Singapore

This evening, I'll be taking my first trip to Singapore. I'm going to give a talk in a workshop on protein interaction networks, and I also made arrangements to get together with a fellow Lloydie who I have only seen once (in 2007) since 2000. It should be fun!

Thursday, September 20, 2012

"What Evidence Is There for the Homology of Protein-Protein Interactions?"

Another of my papers has appeared in final form. Here are the details.

Title: What Evidence Is There for the Homology of Protein-Protein Interactions?

Authors: Anna C. F. Lewis, Nick S. Jones, Mason A. Porter, and Charlotte M. Deane

Abstract: The notion that sequence homology implies functional similarity underlies much of computational biology. In the case of protein-protein interactions, an interaction can be inferred between two proteins on the basis that sequence-similar proteins have been observed to interact. The use of transferred interactions is common, but the legitimacy of such inferred interactions is not clear. Here we investigate transferred interactions and whether data incompleteness explains the lack of evidence found for them. Using definitions of homology associated with functional annotation transfer, we estimate that conservation rates of interactions are low even after taking interactome incompleteness into account. For example, at a blastp E-value threshold of 10^{-70}, we estimate the conservation rate to be about 11% between S. cerevisiae and H. sapiens. Our method also produces estimates of interactome sizes (which are similar to those previously proposed). Using our estimates of interaction conservation we estimate the rate at which protein-protein interactions are lost across species. To our knowledge, this is the first such study based on large-scale data. Previous work has suggested that interactions transferred within species are more reliable than interactions transferred across species. By controlling for factors that are specific to within-species interaction prediction, we propose that the transfer of interactions within species might be less reliable than transfers between species. Protein-protein interactions appear to be very rarely conserved unless very high sequence similarity is observed. Consequently, inferred interactions should be used with care.



Update (9/21/12): Nick discusses this paper on his group's blog.