Developing computational model-based diagnostics to analyse clinical chemistry data

Developing computational model-based diagnostics to analyse clinical chemistry data

This article provides methodological and technical considerations to researchers starting to develop computational model-based diagnostics using clinical chemistry data. These models are of increasing importance, since novel metabolomics and proteomics measuring technologies are able to produce large amounts of data that are difficult to interpret at first sight, but have high diagnostic potent...

Developing a Fuzzy Logic Model to Predict Asphaltene Precipitation during Natural Depletion based on Experimental Data

developing a fuzzy logic model to predict asphaltene precipitation during natural depletion based on experimental data

Sigma diagnostics: pioneer of kits for clinical chemistry.

Having graduated in chemical engineering from Washington University in St. Louis in September, 1939, I started work in its Biochemistry Department as a research assistant and as a laboratory assistant to medical students who were studying biochemistry. Alter 2 years, I left the University to work for a milling company in Kansas City in a program that involved enriching flour with vitamins. My j...

Towards Data Integration for Computational Chemistry

Increasingly, understanding complex problems in computational chemistry requires the use of several applications as components of computational workflows. Unfortunately, this process is severely hindered by a lack of data interchange standards. The eCCP and eMinerals UK eScience projects are developing a framework to facilitate the interoperability of such applications. Data sets are serialised...