by Angela Herring

The human genome is a vast parts list for the inner works of our biology. It codes for thou­sands of pro­teins that make us who we are and keep our bodies up and run­ning. Though that parts list was worked out a decade ago, its utility remains lim­ited by the fact that we still don’t have a wiring dia­gram to go with it. That is, we don’t know how all the parts interact.

“This is where true rich­ness of phe­nomena orig­i­nates,” said Baruch Barzel, a post­doc­toral researcher in the Center for Com­plex Net­work Research, the lab run by world-​​renowned net­work sci­en­tist and Dis­tin­guished Uni­ver­sity Pro­fessor Albert-​​László Barabasi. “Dis­ease mech­a­nisms, as well as our healthy func­tion­ality, are all encoded not just in the genes and pro­teins, but also in how they interact to form a network.”

But unlike many networks—like the com­po­nents inside your car engine or the wires inside a mechan­ical doll—biological sys­tems are black boxes. We can observe the out­come of their inter­ac­tions, but not the inter­ac­tions themselves.

In work pub­lished online Sunday in the journal Nature Biotech­nology, Barzel devel­oped a math­e­mat­ical method for peering inside that box. The research moves the team a step closer in its quest to under­stand, pre­dict, and con­trol human disease.

It is esti­mated that a mere 0.01 per­cent of all pos­sible inter­ac­tions in the human genome actu­ally take place, Barzel said. But with 20,000 genes, that still leaves room for up to a 100,000 inter­ac­tions. Since a blind search for these would be infea­sible, sci­en­tists have devel­oped high-​​throughput exper­i­mental methods to effi­ciently detect them. The only problem is, once again, that black box.

The exper­i­mental data pro­vides the global pic­ture of the cell after all inter­ac­tions have taken place. For instance, if pro­tein A affects pro­tein B, which in turn affects pro­tein C, the link between pro­teins A and C would also reg­ister. Barzel’s method allows him to “silence” those indi­rect links.

“After silencing, what you are left with is the pre­cise wiring dia­gram of the system,” said Barzel. “In a sense we get a peek into the black box.”

To test the method, Barzel applied it to a net­work of 4,511 Escherichia coli genes. He found that the approach per­formed up to 67 per­cent better at iden­ti­fying real inter­ac­tions than stan­dard cor­re­la­tion methods.

But their wiring dia­gram is just the begin­ning. “You don’t only want to know which com­po­nent acts on which other com­po­nent, but also how they act on each other. What is the mech­a­nism by which their inter­ac­tion is real­ized,” said Barzel. “This is a com­pletely fresh problem in the area, and our method can help solve it.”

The research con­tinues Northeastern’s leading work in net­work sci­ence, as its researchers are tack­ling a range of projects in this emerging field that involves under­standing the com­plexity that gov­erns all sys­tems. This work spans from studying the global spread of dis­ease to ana­lyzing social media data as a way to better under­stand fields ranging from polit­ical sci­ence to dis­aster preparedness.

North­eastern also announced the launch of the nation’s first doc­toral pro­gram in net­work sci­ence. The uni­ver­sity will begin recruit­ment in the fall.

Originally published in news@Northeastern on July 15, 2013