Researchers have devised a computer algorithm that takes intermittent samples -- for example, the number of prey and predating species in a forest once a year, or the concentration of different species in a chemical bath once an hour -- and infer the likely reactions that led to that result. They're working backward from traditional stochastic modeling, which they say could help unravel the hidden laws in fields as diverse as molecular biology to population ecology to basic chemistry.
