Robust computational tools represent a driving force behind all systems biology applications. “From my perspective, which is mainly computational, I am convinced that by using sophisticated algorithms we can really push the envelope of systems biology studies much further,” said Ron Shamir, Ph.D., professor of computer science and Sackler Chair in Bioinformatics at Tel Aviv University.
“I am a great believer in the power of using sophisticated ad-hoc tools based on approaches that combine good algorithmics and a solid understanding of the biology behind the question.”
At the CSHL meeting, Dr. Shamir discussed contributions his group made toward tool development. MATISSE, an algorithm that can analyze genome-scale interaction and expression data and detect functional modules, is already an important tool being used by research groups worldwide. Extending MATISSE and its capabilities, the Shamir lab most recently introduced CEZANNE, a new methodology to extract functionally co-expressed pathways.
One of the best demonstrations of the power these approaches hold is reflected by a recent collaborative study, conducted jointly with Jeanne Loring, Ph.D.’s group at Scripps, that categorized a collection of approximately 150 stem cell lines based on their expression profiles. That study found a protein-protein subnetwork, called Plurinet, which is strongly linked to pluripotency.
In addition, other algorithms developed in the Shamir lab were used in studies of patient data, and identified disease-specific dysregulated subnetworks. The analysis, which used case-control data along with various clinical parameters such as age at onset and time to metastasis, may lead to a better understanding of the disease process.
As opposed to previous studies that used predefined pathways, these systems biology tools rely on the rationale that sets of co-expressed genes forming small connected subnetworks should correspond to pathways or processes taking place in cells. Hence, the algorithms examine the full protein interaction network and look for subnetworks that are characterized by high response and are connected.
“An advantage of our approach is that you don’t need these predefined sets,” explained Dr. Shamir, “because there is always some ambiguity as to what constitutes a pathway. Our current knowledge on pathways is incomplete and, besides, it is difficult to set the boundary between a pathway and the rest of the network.
“Pathways overlap, there is always crosstalk, and we find that it is better to algorithmically identify the subnetwork based on data, using the whole protein interaction network as a source.”
As systems biology becomes an indispensable tool to interrogate dynamic cellular events, it promises to profoundly transform society in the years to come. While each approach is powerful in its own way, it is only by integrating multiple experimental tools spanning biology, physics, chemistry, mathematics, and computer sciences, or by “welding together the sum total of all that is known into a whole,” as Erwin Schrödinger wrote more than half a century ago, that the most accurate and meaningful picture can be obtained, regardless of the scientific question being pursued.