What is the extent of gender bias in bioinformatics? Please help me find out.

I've been drawing up a short-list of people to interview for my 101 questions with a bioinformatician series, and I've realized that this list is skewed towards males (maybe 2:1). This partly reflects my own biases in choosing people that I know through work and from people that I follow on twitter. 

However, it probably also reflect underlying biases in the bioinformatics field as a whole. The existence of gender biases is STEM subjects is hardly a new concept (see here or here for some recent studies into this area) and anyone who follows Jonathan Eisen's blog will know that there is an all-too-common bias towards male speakers at scientific meetings. In a great blog post from last year (The Magnifying Glass Ceiling: The Plight of Women in Science), Jane Hu discusses the topic of gender bias in science. I encourage everyone to read this post, but I'll highlight one sentence here (emphasis mine):

It is true that women are underrepresented…but not because women aren’t interested in it or can’t handle the work.

Although projects like Girls Who Code and App Camp for Girls are doing a great job at increasing female participation in some STEM subjects, these projects will not help remove the discrimination against women that occurs later in their careers. Fortunately, other fantastic projects like Tools for Change: Boosting the retention of women in the STEM pipeline are helping raise awareness about these problems, and are offering solutions (e.g. encouraging more family friendly policies).

So I'm curious as to the extent of gender bias in bioinformatics. Please help me find out more by completing the really short form (below) and feel free to share this form with others (the Google form can be accessed separately via this link). I will report on the results in a future blog post. Also, I will make more effort to address any gender biases in my 101 questions with a bioinformatician series.