Archive by category | Multi-scale

Fascinating correlations or elegant theories?

Chris Anderson, Editor-in-Chief of Wired , wrote a few weeks ago a provocative piece “”http://www.wired.com/science/discoveries/magazine/16-07/pb_theory”>The End of Theory: The Data Deluge Makes the Scientific Method Obsolete“, arguing that in our Google-driven data-rich era (”The Petabyte Age”) the good old “approach to science —hypothesize, model, test — is becoming obsolete”, leaving place to a purely correlative vision of the world. There is a good dose of provocation in the essay and it was quite successful in spurring a flurry of skeptical reactions in the blogosphere, FriendFeed-land and lately in Edge’s Reality Club.  Read more

Semantic zooming of networks

One can only agree with Euan Adie, that “the way we present genomic and proteomic data on the web sucks” (read post on Nascent). And this holds for biological networks: depiction of protein-protein interactions as colorful hairballs results in impressive figures but is not obligatorily very useful. While the network representation is a powerful abstract representation of biological processes, it is trivial to say that a graph (with its jungle of nodes and edges) is far from resembling even remotely to an actual living cell as you see it under the microscope… In the crude visualization of biological process as simple graphs, space, time, multi-scale structure and biological context are missing.  Read more

Connecting disease state to genetic modules

Connecting disease state to genetic modules

Diseases such as cancer are often related to collaborative effects involving interactions of multiple genes within complex pathways, or to combinations of multiple SNPs. To understand the structure of such mechanisms, it is helpful to analyze genes in terms of the purely cooperative, as opposed to independent, nature of their contributions towards a phenotype (Anastassiou, 2007).  Read more