How to make Mathematics Biology's next and better microscope

Abstract

An essay published in 2004 has the perceptive heading: “Mathematics Is Biology's Next Microscope, Only Better; Biology Is Mathematics’ Next Physics, Only Better” [1]. This title neatly summarises the developmental path taken by biology over the past 30 years or so. It emphasises both the exciting role that mathematics and statistics are adopting in the identification and quantification of wholly unimagined and entirely new realms within biology as well as the repercussions biology is precipitating in the prompting of new developments in mathematics and statistics. The title also underlines the intensifying interlinking of numerous disciplines: the complexity of biological and clinical phenomena requires increasingly sophisticated, specialised and discipline-transcending expertise to complete a technical workflow comprising experimental design, generation and analysis of data, interpretation of results and subsequent transparent reporting (Fig. 1)

A glance at the applications of Singular Spectrum Analysis in gene expression data

“…Nowadays there exists a large amount of datasets in the field of genetics and expression measurement and there are many different methods and techniques for analysing these datasets [1] , [2] , [3] . However, it has been widely accepted that the major difficulties in working with such data no longer is the validity of expression measurements, but the reliability of inferences from the data as the achieved data is difficult to understand without the use of proper analytical tools [4] and if research result is obtained from an inappropriate model it can never be translated into a valid scientific context [5] .…”