Editing Computational biology (section)

===Pharmacology===
{{main|Pharmacology}}

Computational pharmacology is "the study of the effects of genomic data to find links between specific [[genotype]]s and diseases and then [[drug discovery|screening drug data]]".<ref>{{cite journal |last1=Price |first1=Michael |title=Computational Biologists: The Next Pharma Scientists? |journal=Science |date=13 April 2012 |doi=10.1126/science.caredit.a1200041 }}</ref> The [[pharmaceutical industry]] requires a shift in methods to analyze drug data. Pharmacologists were able to use [[Microsoft Excel]] to compare chemical and genomic data related to the effectiveness of drugs. However, the industry has reached what is referred to as the Excel barricade. This arises from the limited number of cells accessible on a [[spreadsheet]]. This development led to the need for computational pharmacology. Scientists and researchers develop computational methods to analyze these massive [[data set]]s. This allows for an efficient comparison between the notable data points and allows for more accurate drugs to be developed.<ref name="Walter">{{cite web|last=Jessen|first=Walter|title=Pharma's shifting strategy means more jobs for computational biologists|url=http://medcitynews.com/2012/04/pharmas-shifting-strategy-means-more-jobs-for-computational-biologists/|date=2012-04-15}}</ref>

Analysts project that if major medications fail due to patents, that computational biology will be necessary to replace current drugs on the market. Doctoral students in computational biology are being encouraged to pursue careers in industry rather than take Post-Doctoral positions. This is a direct result of major pharmaceutical companies needing more qualified analysts of the large data sets required for producing new drugs.<ref name="Walter"/>