Quantitative skills in biology

Scientific research relies heavily on quantification – math and statistics. Identifying those genes that affect any particular characteristic - be it plant height, yield, disease resistance, etc. - requires a large amount of carefully measured data, both genotype data (such as DNA sequence variation) and phenotype data (the observed characteristics that are the result of gene expression). Phenotypic, or morphological, data can include measuring plant height, counting maize kernels, assessing how healthy or diseased the plant is, and a large number of other measurements. Laboratory tests can be done to measure the chemical composition, e.g. carotenoid content. Advances in technology have made this quantification process easier and less prone to human error. For example, aerial photographs of the field or bar coding systems can be used to measure traits such as height and ear number via computer or bar code scanner. Laboratory Information Management Systems (LIMS) are often used to help keep track of samples and data, including giving each plant in the field a barcode.

This phenotype data is combined with the genotypic data then cutting edge statistical analyses are then conducted to look for correlations to try to identify which genes are involved with the specific traits. The statistical tests employed run from the fairly standard - such as t-tests, ANOVA, and regression - to much more complex and customized methods too novel to be covered here. Given the large amounts of data involved, these analyses are almost always performed on a computer with specific and/or customized software programs. Scientists that work specifically in the area of analyzing large amounts of biological data include bioinformaticists, biometricians, and statistical geneticists. If you have a particular talent for mathematics, there are most certainly career opportunities for you in biology and genetics that will take full advantage of your quantitative skills!

See also Careers in science