Editing Proteomics (section)

===Computational methods in studying protein biomarkers===
One example of the use of bioinformatics and the use of computational methods is the study of protein biomarkers. Computational predictive models<ref>{{cite journal | vauthors = Maron JL, Alterovitz G, Ramoni M, Johnson KL, Bianchi DW | title = High-throughput discovery and characterization of fetal protein trafficking in the blood of pregnant women | journal = Proteomics. Clinical Applications | volume = 3 | issue = 12 | pages = 1389–1396 | date = December 2009 | pmid = 20186258 | pmc = 2825712 | doi = 10.1002/prca.200900109 }}</ref> have shown that extensive and diverse feto-maternal protein trafficking occurs during pregnancy and can be readily detected non-invasively in maternal whole blood. This computational approach circumvented a major limitation, the abundance of maternal proteins interfering with the detection of [[fetal protein]]s, to fetal proteomic analysis of maternal blood. Computational models can use fetal gene transcripts previously identified in maternal [[whole blood]] to create a comprehensive proteomic network of the term [[neonate]]. Such work shows that the fetal proteins detected in pregnant woman's blood originate from a diverse group of tissues and organs from the developing fetus. The proteomic networks contain many [[biomarker (medicine)|biomarkers]] that are proxies for development and illustrate the potential clinical application of this technology as a way to monitor normal and abnormal fetal development.

An information-theoretic framework has also been introduced for [[biomarker (medicine)|biomarker]] discovery, integrating biofluid and tissue information.<ref name="Alterovitz_2008">{{cite book | vauthors = Alterovitz G, Xiang M, Liu J, Chang A, Ramoni MF |title=Biocomputing 2008 |chapter=System-wide peripheral biomarker discovery using information theory |journal=Pacific Symposium on Biocomputing |pages=231–42 |year=2008 |pmid=18229689 |chapter-url=http://psb.stanford.edu/psb-online/proceedings/psb08/abstracts/2008_p231.html |doi=10.1142/9789812776136_0024 |isbn=9789812776082 }}</ref> This new approach takes advantage of functional synergy between certain biofluids and tissues with the potential for clinically significant findings not possible if tissues and biofluids were considered individually. By conceptualizing tissue-biofluid as information channels, significant biofluid proxies can be identified and then used for the guided development of clinical diagnostics. Candidate biomarkers are then predicted based on information transfer criteria across the tissue-biofluid channels. Significant biofluid-tissue relationships can be used to prioritize clinical validation of biomarkers.<ref name="Alterovitz_2008" />