What would be a suitable value for the absolute minimum proportion of female speakers at genomics/bioinformatics conferences?

Photo by ViktorCap/iStock / Getty Images
Photo by ViktorCap/iStock / Getty Images


Hopefully, many people reading this will be aware of Jonathan Eisen's valiant efforts to highlight the Yet Another Mostly Male Meeting (YAMMM) problem; these are conferences where the gender bias is disproportionately skewed towards male speakers. You can see all of Jonathan's YAMMM posts on his blog, and in his latest post he highlights a particularly egregious case: a CSHL meeting on the Evolution of Sequencing where only 7.8% of speakers are women.

In my last ACGT post I looked at how this figure (7.8%) compared to the male/female ratio of senior researchers at 10 different genomics/bioinformatics institutes. Nine out of the ten places that I looked at had a much higher proportion of female scientists. I tried making the point that this suggests that conference organizers have no excuses for not doing a better job at recruiting more female speakers.

But it struck me that my analysis was a bit too shallow, especially as the numbers of researchers in each place differed quite a bit (from 10 to almost 60). So I went back and looked at many more academic institutions and kept track of the absolute numbers of men and women in senior research roles.


In total, my updated dataset comprises details from 40 different academic institutes (or centers/departments) that specialize in genomics and/or bioinformatics. The vast majority (33/40) mention 'genome', 'genomics', or 'bioinformatics' in their title (the exceptions to this include the Broad Institute, Cold Spring Harbor Laboratory, and the Wellcome Trust Sanger Institute).

The 40 different institutes represent locations in North America, Europe, Asia, and Australia. In some cases, the named institute represents an umbrella organization connecting researchers in different locations across that country (e.g. the Swiss Institute of Bioinformatics). There is probably an element of selection bias towards research institutes that provided an English-language version of their staff/personnel page (not all non-English websites have translations of every page available).

I think that this dataset contains most of the widely known research institutes that have a dedicated focus on genomics and bioinformatics. The list could probably be further expanded if I targeted more University departments that have a specialization in these fields.

In total I logged the gender of 1,039 people in various 'senior' research roles (e.g. Faculty, 'Group leaders', 'Project leaders', etc.). In many cases I deduced gender from first names, but looked for images of researchers where this was not easy to do so.

I've uploaded the main table of data to Figshare so that others can look at all of the detailed numbers if they so desire.


  1. The most equitable result for any one academic institute with at least 15 senior research scientists was the Duke Department of Biostatistics and Bioinformatics (40.4% female, N=52)
  2. Only two other institutes had figures of 40% or higher: the National Human Genome Research Institute (40% female, N=40) and the Functional Genomics group at the Russian Academy of Medical Sciences (50% female, N=6).
  3. Only 3 out of 40 institutes had a lower proportion of female scientists than at the aforementioned CSHL meeting with 7.8% female speakers.
  4. Discounting the bottom placed institute due to small sample size (0% female, N=4), the next worse place was NBIC, the Netherlands Bioinformatics Center with only one female Faculty member (4.8% female, N=21).
  5. The overall ratio of female scientists in senior research roles is 23.6% (N=1,039).


It is somewhat depressing to see such a systematic gender bias in my field, where female scientists only account for approximately a quarter of senior research positions. This figure is in line with UK data for the proportion of female professors all biological sciences (25.1%). The lack of equal gender representation is presumably due to bias and discrimination (conscious or otherwise). In 2014 I conducted a survey to look at gender bias in bioinformaticians across different career stages. This survey had 370 responses — from undergraduate level right through to Deans of academic schools — and showed that there is essentially no gender bias at all stages prior to the level of Faculty (or equivalent). This suggests that there is no shortage of talented women coming through the system, they just are hitting a barrier when it comes to attaining senior research positions…a situation clearly not helped by further discrimination at conferences.

Based on the figures that I show here, one might argue that the figure of approximately 25% could be seen as a minimum target for female participation at conferences. However, such a target would only be encouraging the current levels of discrimination. Far better would be a target that not only attempts to reduce discrimination, but which also better reflects the equal representation of female scientists in post-doc and graduate student positions.

For these reasons I feel that conference organizers — in the fields of genomics and bioinformatics — should be aiming for at least a third of all speakers to be female. Ideally, we want to be doing better than this which is why I suggest this as an absolute minimum target. Depressingly, even this low target is something which most (all?) of the YAMMM meetings described by Jonathan Eisen fail to meet. Of course, such a target should apply for male speakers too, though I'm doubtful that there has ever been a conference in this field where men accounted for less than a third of all speakers.

I don't attend many conferences, but from now on I won't be attending any if at least 33% of the talks are not by women.

Update 2015-06-30: Added link to data for percentage of female professors in UK biological sciences, and clarified that my suggested target figure should also apply to male speakers. I also added a caveat that my methods of choosing institutes is biased towards websites written in English (or with English translations available).