These factors can significantly influence the protein composition of a biofluid. In addition, simply looking at protein overlap would miss information transmission occurring through classes of proteins and protein-protein interactions. Instead, the proteins' projection onto functional, drug, and disease spaces allow measurement of the functional distance between tissue and biofluids. Proximity in these abstract spaces signifies a low level of distortion across the information channel (and, hence, high performance by the biofluid). However, current approaches to biomarker prediction have analyzed tissues and biofluids separately. There are four major methods for genomic analysis. First, a northern blot can be used to isolate a set of RNA sequences. Second and third, they can be analyzed by standard Gene expression techniques, or surveyed using SAGE. Lastly, a DNA microarray measurement can be taken, to determine the frequency of each gene; this information can be used to determine whether a gene is a biomarker. Often, a polymerase chain reaction is used to create many copies of the sequences to make them easier to work with. In February 2016, Dr. Laura Elnitski and company used this technique to detect a biomarker shared by five types of cancer. The term metabolomic has been recently introduced to address the global analysis of all metabolites in a biological sample. A related term, metabonomics, was introduced to refer specifically to the analysis of metabolic responses to drugs or diseases. Metabonomics has become a major area of research; it is the complex system biological study, used as a method to identify the biomarker for various disease. In general, in most disease cases, a metabolic pathway had or has been either activated or deactivated - this parameter can thus be used as a marker for some diseases. Serotonin production pathways, activated in a person who has recently consumed alcohol for instance, can be a metabolic marker of recent alcohol consumption. Lipidomics refers to the analysis of lipids. Since lipids have unique physical properties, they have been traditionally difficult to study. However, improvements in new analytical platforms have made it possible to identify and to quantify most of lipids metabolites from a single sample. Three key platforms used for lipid profiling include mass spectrometry, chromatography, and nuclear magnetic resonance. Mass spectrometry was used to delineate the relative concentration and composition of high-density lipoproteins (HDL) particles from lipid extracts isolated from coronary bypass patients and healthy volunteers. They found that HDL particles from coronary bypass patients contained significantly less sphingomyelin relative to phosphatidylcholine and higher triglycerides relative to cholesteryl esters.