Mark Reimers

Virginia Institute for Psychiatric and Behavioral Genetics (cross-appointed to the Dept. of Biostatistics and the Center for the Study of Biological Complexity), at Virginia Commonwealth University

Today’s sophisticated biotechnologies and electronics enable researchers to gather data in quantities unimagined ten years ago. These data acquisition technologies are changing the nature of research in biology and are poised to revolutionize medical diagnosis and treatment. At the same time the infrastructure of knowledge is changing: a great deal of relevant information is stored in online databases, which may aid interpretation of experimental and clinical data.

Statisticians and mathematicians must accept the challenge of analyzing and integrating these new data sets. The first challenge is to extract a clear signal from the technologies; there are many confounding factors, such as technical or physiological artifacts, which distort the signals. Then we may test hypotheses about biological organization or mechanisms against the data. Usually we are testing hypotheses of a common form for many specific items, such as genes or brain regions; these may be simple hypotheses (e.g. which gene expressions are changed) or more complex (e.g. which measures are correlated). Finally we must take advantage of previous efforts, usually in the form of databases, to constrain and aid our analysis.

Recently new technologies such as fMRI, calcium imaging, and voltage-sensitive dyes have enabled collection of broad swathes of neural activity over time. This is the domain of multivariate analysis but only recently have a few statisticians begun to develop multivariate methods specific for such data.

We who analyze such data are like the prisoners in Plato’s Cave: with our measures we perceive only a shadow of the reality, and we must infer the reality from the data using our imagination and logic. In my opinion the best analytic approaches combine statistical subtility with knowledge of the processes under study.

Current Research


See my Opinionated Guide to Microarray Data Analysis

My Collaborators

Selected Publications

Readings for the 'Enlightened Brain' course

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