Computing science researcher Siamak Ravanbakhsh (middle), with his co-supervisors Russell Greiner (left) and David Wishart. Ravanbakhsh has developed a computer system called Bayesil that could dramatically improve diagnosis and treatment of a wide spectrum of diseases. Siamak Ravanbakhsh, who recently completed his PhD in computing science at the University of Alberta and whose research was recently published in the scientific journal PLOS ONE, said Bayesil, the computer application resulting from this breakthrough, is pretty easy to explain in basic terms. "There is this technology called NMR spectrometry, which uses some of the same physical principles as MRI. This technology is very cool, because it can determine the concentration of certain compounds in your body," he said.

Many diseases cause significant changes to the concentrations of small molecules (aka metabolites) that appear in a person's biofluids, which means such diseases can often be readily detected from a person's "metabolic profile". This information can be extracted from a biofluid's NMR spectrum. Today, this is often done manually by trained human experts, which means this process is relatively slow, expensive and error-prone. This paper presents a tool, Bayesil, that can quickly, accurately and autonomously produce a complex biofluid's (e.g., serum or CSF) metabolic profile from a 1D1H NMR spectrum. This requires first performing several spectral processing steps then matching the resulting spectrum against a reference compound library, which contains the "signatures" of each relevant metabolite. Many of these steps are novel algorithms and our matching step views spectral matching as an inference problem within a probabilistic graphical model that rapidly approximates the most probable metabolic profile. Our extensive studies on a diverse set of complex mixtures, show that Bayesil can autonomously find the concentration of all NMR-detectable metabolites accurately (~90% correct identification and ~10% quantification error), in <5minutes on a single CPU. These results demonstrate that Bayesil is the first fully-automatic publicly-accessible system that provides quantitative NMR spectral profiling effectively -- with an accuracy that meets or exceeds the performance of trained experts. We anticipate this tool will usher in high-throughput metabolomics and enable a wealth of new applications of NMR in clinical settings. Available at http://www.bayesil.ca.