This year half of the Nobel prize in Physiology or Medicine was awarded to May-Britt Moser and Edvard Moser, who happen to be both a personal and professional couple. Interestingly, they are not the first but rather the fourth couple to win the prize jointly: In 1903 Marie Curie and Pierre Curie shared the Nobel prize in physics, in 1935 Frederic Joiliot and Irene Joliot-Curie shared the Nobel prize in chemistry and in 1947 Carl Cori and Gerty Cori also shared the Nobel prize in physiology or medicine. It seems working on science with a spouse or partner can be a formula for success. Why then, when partners apply together for academic jobs, do universities refer to them as “two body problems“?

The “two-body problem” is a question in physics about the motions of pairs of celestial bodies that interact with each other gravitationally. It is a special case of the difficult “N-body problem” but simple enough that is (completely) solved; in fact it was solved by Johann Bernoulli a few centuries ago. The use of the term in the context of academic job searches has always bothered me- it suggests that hiring in academia is an exercise in mathematical physics (it is certainly not!) and even if one presumes that it is, the term is an oxymoron because in physics the problem is solved whereas in academia it is used in a way that implies it is unsolvable. There are countless times I have heard my colleagues sigh “so and so would be great but there is a two body problem”. Semantics aside, the allusion to high brow physics problems in the process of academic hiring belies a complete lack of understanding of the basic mathematical notion of epistasis relevant in the consideration of joint applications, not to mention an undercurrent of sexism that plagues science and engineering departments everywhere.  The results are poor hiring decisions, great harm to the academic prospects of partners and couples, and imposition of stress and anxiety that harms the careers of those who are lucky enough to be hired by the flawed system.

I believe it was Aristotle who first noted used the phrase “the whole is greater than the sum of its parts”. The old adage remains true today: owning a pair of matching socks is more than twice as good as having just one sock. This is called positive epistasis, or synergy. Of course the opposite may be true as well: a pair of individuals trying to squeeze through a narrow doorway together will take more than twice as long than if they would just go through one at a time. This would be negative epistasis. There is a beautiful algebra and geometry associated to positive/negative epistasis this is useful to understand, because its generalizations reveal a complexity to epistasis that is very much at play in academia.

Formally, thinking of two “parts”, we can represent them as two bit strings: 01 for one part and 10 for the other. The string 00 represents the situation of having neither part, and 11 having both parts. A “fitness function” f:[0,1]^2 \rightarrow \mathbb{R}_+ assigns to each string a value. Epistasis is defined to be the sign of the linear form


That is, u>0 is positive epistasis, u<0 is negative epistasis and u=0 is no epistasis. In the case where f(00)=0, “the whole is greater than the sum of its parts” means that f(11)>f(10)+f(01) and “the whole is less than the sum of its parts” means f(11)<f(10)+f(01). There is an accompanying geometry that consists of drawing a square in the x-y plane whose corners are labeled by 00,01,10 and 11. At each corner,  the function f can be represented by a point on the z axis, as shown in the example below:


The black line dividing the square into two triangles comes about by imagining that there are poles at the corners of the square, of height equal to the fitness value, and then that a tablecloth is draped over the poles and stretched taught. The picture above then correspond to the leftmost panel below:


The crease is the resulting of projecting down onto the square the “fold” in the tablecloth (assuming there is a fold). In other words, positive and negative epistasis can be thought of as corresponding to one of the two triangulations of the square. This is the geometry of two parts but what about n parts? We can similarly represent them by bit strings 100 \cdots 0, 010 \cdots 0, 001 \cdots 0, \ldots, 000 \cdots 1 with the “whole” corresponding to 111 \cdots 1. Assuming that the parts can only be added up all together, the geometry now works out to be that of triangulations of the hyperbipyramid; the case n=3 is shown below:



“The whole is greater than the sum of its parts”: the superior-inferior slice.


“The whole is less than the sum of its parts”: the transverse slice.

With multiple parts epistasis can become more complicated if one allows for arbitrary combining of parts. In a paper written jointly with Niko Beerenwinkel and Bernd Sturmfels titled “Epistasis and shapes of fitness landscapes“, we developed the mathematics for the general case and showed that epistasis among objects allowed to combine in all possible ways corresponds to the different triangulations of a hypercube. For example, in the case of three objects, the square is replaced by the cube with eight corners corresponding to the eight bit strings of length 3. There are 74 triangulations of the cube, falling into 6 symmetry classes. The complete classification is shown below (for details on the meaning of the GKZ vectors and out-edges see the paper):



There is a beautiful geometry describing how the different epistatic shapes (or triangulations) are related, which is known as the secondary polytope. Its vertices correspond to the triangulations and two are connected by an edge when they are the same except for the “flip” of one pair of neighboring tetrahedra. The case of the cube is shown below:


The point of the geometry, and its connection to academic epistasis that I want to highlight in this post, is made clear when considering the case of n=4. In that case the number of different types of epistatic interactions is given by the number of triangulations of the 4-cube. There are 87,959,448 triangulations and 235,277 symmetry types! In other words, the intuition from two parts that “interaction” can be positive, negative or neutral is difficult to generalize without math, and the point is there are a myriad of ways a faculty in a large department can be interacting both to the benefit and the detriment of their overall scientific output.

In many searches I’ve been involved in the stated principle for hiring is “let’s hire the best person”. Sometimes the search may be restricted to a field, but it is not uncommon that the search is open. Such a hiring policy deliberately ignores epistasis, and I think it’s crazy, not to mention sexist, because the policy affects and hurts women applicants far more than it does men. Not because women are less likely to be “the best” in their field, in fact quite the opposite. It is very common for women in academia to be partnered with men who are also in academia, and inevitably they suffer for that fact because departments have a hard time reconciling that both could be “the best”. There are also many reasons for departments to think epistaticially that go beyond basic fairness principles. For example, in the case of partners that are applying together to a university, even if they are not working together on research, it is likely that each one will be far more productive if the other has a stable job at the same institution. It is difficult to manage a family if one partner needs to commute hours, or in some cases days, to work. I know of a number of couples in academia that have jobs in different states.

In the last few years there are a few couples that have been bold enough to openly declare themselves “positively epistatic”. What I mean is that they apply jointly as a single applicant, or “joint lab” in the case of biology. For example, there is the case of the Altschuler-Wu lab that has recently relocated to UCSF or the Eddy-Rivas lab that is relocating to Harvard. Still, such cases are far and few between, and for the most part hiring is inefficient, clumsy and unfair (it is also worth noting that there are many other epistatic factors that can and should be considered, for example the field someone is working in, collaborators, etc.)

Epistasis has been carefully studied for a long time in population and statistical genetics, where it is fundamental in understanding the effects of genotype on phenotype. The geometry described above can be derived for diploid genomes and this was done by Ingileif Hallgrímsdóttir and Debbie Yuster in the paper “A complete classification of epistatic two-locus models” from 2008. In the paper they examine a previous classification of epistasis among 30 pairs of loci in a QTL analysis of growth traits in chicken (Carlborg et al., Genome Research 2003). The (re)-classification is shown in the figure below:


If we can classify epistasis for chickens in order to understand them, we can certainly assess the epistasis outlook for our potential colleagues, and we should hire accordingly.

It’s time that the two body problem be recognized as the two body opportunity.