Emergent behavior of growing knowledge about molecular interactions

In the time of Isaac Newton (1643–1727), a prominent scientist could follow advances in multiple fields of knowledge—as far apart from each other as mathematics, astronomy, physics, history and theology. It took a talent of Newton's caliber, of course, to contribute to several of them during one lifetime. Today, with thousands of biomedical journals published in English alone, even Sir Isaac would not have the luxury of systematically following all that happens in biology, let alone in multiple research fields. Currently, millions of active biomedical researchers are scattered around the globe, most focusing on a small fragment of the enormous biological universe. Consequently, knowledge acquisition and validation by scientific communities is bound to have large-scale properties that are normally hidden from individual scientists. These large-scale properties would reveal themselves only at the level of a meta-analysis of large volumes of data produced by numerous scientists. The practical importance of such meta-analyses—besides satisfying academic curiosity—lies in their potential for indicating hidden opportunities lurking in the currently accessible knowledge