Q&A with Dr. Sarah Teichmann
The full feature profile for Sarah can be found here
1. Have the fields of computer science and bioinformatics changed significantly since you started your career? If so, in what ways, and what do you think are the most dramatic changes in the last few years?
Yes, my impression is that there are many more diverse types of scientists that you see roaming the labs and offices these days as compared to when I started my PhD in 1996. I feel the most dramatic and obvious change is the number of women active at all levels. A caveat is that I have not seen numbers on this for the UK or worldwide so it is just my impression that this is the case.
2. Has the gender balance in the general field of bioinformatics, and your particular fields of gene expression and protein interactions changed since you joined the field? If so, how have they changed?
Again, I haven’t seen a precise survey of the split of scientists active in bioinformatics and specifically structural and gene expression bioinformatics, but my impression is that the gender balance has indeed become more even over the past 25 years. This is not to say that we are done by any stretch of the imagination, but I do feel that there has been significant improvement in the gender balance. There have also been improvements at a policy level, with changes in parental leave, careers leave, flexibility in career structures etc.
3. Would you say there are particular assets or challenges to being a woman in bioinformatics?
It is perhaps not fair to generalise, but I’ll do it anyway: my impression is that on average, women are able to collaborate, communicate and work as part of a team in a more natural and effective way overall. This is a huge asset, as is the ability to empathise with others. These skills can be innate to men as well of course but perhaps less ubiquitously.
Challenges that continue to this day include the tendency to be underestimated by others, which is shared to some extent with minorities. Note that women aren’t a minority - we are actually the majority of people!
Another challenge that is biologically given is the physical challenge of pregnancy, giving birth, breastfeeding (for women or transgender men), which is not shared with people who don’t do this, even if they carry out childcare. This is typically currently not recognised at the level of e.g. contract extensions, tenure clock extensions etc.
4. Having co-founded initiatives such as the Human Cell Atlas, and being the head of Cellular Genetics at the Sanger Institute, what are the greatest challenges you have face leading and co-ordinating such large groups and initiatives?
Some of the challenges are scientific, some challenges are more to do with human psychology and leadership, and some challenges are simply lack of time when there is so much to do. What is common to building the Human Cell Atlas community and the Cellular Genetics programme at Sanger is that once structures are in place, things become much easier and run more smoothly. This can take years, but I feel that in both organisations (HCA and CellGen) we are now getting there.
5. Did you ever find it difficult beginning and establishing a research career in bioinformatics? Do you feel like it was more difficult as a woman and if so were there particular challenges you remember having to face?
My greatest challenge was actually after I had established my career and was a tenured MRC Programme Leader, and that was the period of maternity leave with my first daughter. I felt that there was no accommodation for this huge life-changing event and I had to continue to supervise my substantial-sized group, carry out administrative tasks, travel globally to conferences etc. Partly this was due to my own lack of confidence to say no to commitments, but partly this was because the research culture at the time (2008) simply wasn’t accommodating to parental leave (and paid paternity leave of a lengthy period didn’t exist at that time). Luckily things are changing even in this domain, but I would like progress to be faster.
6. Do you have any advice for young women/womxn starting out in academic research careers, especially in computer science, bioinformatics, and STEM?
GO FOR IT! It is a lot of fun and very rewarding. My advice is that everyone who is doing their best to do a good job deserves respect, so don’t hesitate to assert yourself immediately if you feel that colleagues in the workplace aren’t behaving in a respectful way, or in a way that doesn’t accommodate needs that you have (eg pregnancy, childbirth etc). In addition, if you witness someone else being treated in a way that you perceive as being unfair or incorrect, I encourage you to speak up in a polite but firm way. This will change the research culture one small step at a time.
If you want to make a difference in the long term, then working on initiatives that gather together people in order to support each other and propose solutions in the form of policy changes is a great way forwards. This obviously takes time and will not be everyone’s cup of tea. An example of this is the recently formed network of “Black Women in Computational Biology” which provides a forum to unite these scientists across the globe: https://www.blackwomencompbio.org/ [eur01.safelinks.protection.outlook.com]
7. What recent developments in bioinformatics and computer science are you most impressive to you? What future areas and avenues of research are you most excited about?
The computational advancements in interpreting single cell genomics data have been driven by machine learning/deep learning methods over the past five years or so, and this has been exciting to be part of. Future areas and avenues of research that are most exciting to me are multi-modal data integration methods in cell atlas technologies: single cell multi-omics, spatial transcriptomics and highly multiplex imaging modalities. Computationally integrating such diverse data in order to build whole-genome three-dimensionally resolved models of tissues is an exciting challenge for the field. These will enable the HCA, and help to transform our knowledge of biology and medicine.