Last updated: May 15, 2020

Book cover

Into the Sciences

To laymen ‘science’ and ‘research’ seem amorphous things, mysterious activities by lab-coated acolytes that somehow yield knowledge of our world. This book breaks them down into a clear model of the activities involved, then uses that model to explain why science is separated into disciplines, how those disciplines are shaped by their different subject matter, and finally how researchers choose what they do.


Diagnostic Questionnaires
The goal of this column is to help working clinicians understand the statistical calculations involved in interpreting the results of diagnostic questionnaires. Using the Patient Health Questionnaire-9 as an example, the author explains how to determine the most appropriate cutoffs to choose, depending on the population involved, the probabilities of error (αand β), and the expected losses associated with each kind of error in the context in which the test is being administered. (Journal of Psychiatric Practice. 2011;17:57–60)
Hypothesis tests and p-values
The goal of this column is to help working clinicians understand p-values and the machinery of hypothesis testing underlying them, using a fictional study of an anti-insomnia drug. The author discusses what p-values really mean and common misconceptions concerning them. (Journal of Psychiatric Practice 2011;17:288–291)
The four aspects of statistics
Statistics resembles the apocryphal elephant being examined by blind men. Each person uses, and often only knows, a particular set of statistical tools, and, when passing on their knowledge, does not have a picture to impart of the general structure of statistics. Yet that structure consists of only four pieces.


Koch’s postulates
How do we know that Mycobacterium tuberculosis actually causes tuberculosis? More generally, how do you prove that a given organism is the cause of a given disease?
The Lockless-Ranganathan formalism
Are all monomers of a polypeptide chain equally important? Are some merely incidental—does something needs to be there, but it doesn’t matter what? Lockless and Ranganathan developed a way of answering this in the context of thermodynamic mutant cycles, and found that only sparse pairs of amino acids appear to be important.
Intrinsic and extrinsic noise in gene expression
The question of noise in gene expression has been more and more important recently, both as an interesting question in its own right, and as a necessary piece of information for constructing random processes to describe other aspects of biology. There is a problem with measuring noise, however: how much of it is actually noise associated with the components of a pathway operating in a thermal bath, and how much is cell to cell variation, the local density of a necessary enzymes, and other things that are extraneous to the pathway?
A clean calculation of the Luria-Delbruck mathematics
All biology students are made to read Luria and Delbruck’s paper “Mutations of bacteria from virus sensitivity to virus resistance,” which begins with a series of ad hoc probability calculations. When the paper was written in 1943, they represented the best tools available in probability. Today they are quaint to the point of being incomprehensible. Here is the whole calculation from the paper in modern form.

A farewell to bioinformatics

This rant is the most widely read thing I have ever written. It gets reviled, quoted, assigned in graduate bioinformatics courses around the world, and people still email me about it. The response to it was extreme enough that I felt it necessary to comment on it.

I’ve considered just removing it, there are a lot of people who quote a passage and say, “I wouldn’t be this extreme, but there’s a kernel of truth in this,” so it’s serving as an object of discourse where someone can let me utter an uncomfortable truth, then other me but expand on that truth. It’s serving a purpose.