An update of something I wrote back in 2017.
People love to complain and no one feels properly appreciated. But from talking to bioinformaticians (a job title I once sported) and other colleagues, those of us that work in the divide between the biological and computational have the same stories coming up again and again:
Doing a wide array of highly technical tasks (e.g. genome assembly, biostatistics, integrative biology, data visualisation), yet still being referred to as "the database manager” or “computer guy"
Assigned to poor positions in author lists and sometimes omitted entirely
Career and advancement not being considered important or perhaps openly ignored
As a single person, being expected to handle "all of our bioinformatics" (analytics / data science / etc.) regardless of workload, time available, provision of necessary facilities or whether you possess the necessary technical knowledge
Not being consulted when projects are planned
Being expected to produce results from incomplete, fragmented and statistically tiny samples
Your technical advice and results not being taken seriously or questioned with intense scepticism
Being last in line when resources are allocated
Being expected to work long stressful "scientist / principal contributor" hours, while being treated as a junior or technician
I’ll keep talking about bioinformaticians, but here I mean everyone who does number-y, computer-y things to data from wet, living things: epi-informaticists, health data scientists, genomicists, and so on. How did we get here? Why are bioinformaticians held in such low regard? To cut to the chase, I don't have a single answer here. But I do have several theories.
Theories
No one gets any respect
Proposal: This is science, technology and sometimes academia. It's a zero sum game. Everyone's climbing the same greasy pole and fighting for limited resources. Everyone is under stress, everything is under-resourced. Social niceties are pushed to one side to be replaced with "what have you done for me today?" Why should bioinformatics be any different?
Counterpoint: Popssibly true, but this can't be a complete explanation. Other specialities don't have the job title problem, or get left out of planning discussions. And there should be less of a greasy-pole problem in industry.
It'll take time
Proposal: Bioinformatics is too new and academic culture hasn't yet adapted to or understood it. Non-bioinformatic academics don't yet appreciate the way it works, seeing it as partially magic, partially ill-formed voodoo. Give it time.
Counterpoint: Certainly, this was true once upon a time. Certainly, some parts of the academy are slow to adapt (try employing a "research software engineer" at a university and see what your HR department reacts). But we've had a generation of working bioinformaticians now. Some aspects of science and technology and business has changed radically (GWAS, large models, open access, mega-journals, etc.) and work has adapted to that. Why not bioinformatics?
Bioinformatics looks like IT
Proposal: Bioinformatics is inherently computational, looks and acts a lot like IT and so it gets treated like IT, a fungible support service:
Early practitioners came from the IT side and many still do. Bioinformaticians leaving science will often move into pure IT.
Bioinformaticians look and act like IT workers: largely male, hyper-casual dress, an obsession with technical details, an obscurantist style.
Bioinformaticians are often referred explicitly as "computer guys", with bioinformatics and informatics / IT tasks being functionally interleaved and conflated. A cluster needs to be set-up for an analysis, the lab needs a website or database, someone can't figure why a program isn't working: these are all handed to the lab bioinformatician.
Bioinformatics is treated by outsiders like a black box.
Bioinformatics "skill" is often equated with being the master of an obscure technical stack.
Counterpoint: None. I think this is completely true.
Bioinformatics is blue collar
I can't find who first made this distinction or used these terms but it's an a good observation: tasks can be divided into white collar (creative, high profile, seen as "output", "thinkers" and "doers") and blue collar (essential but seen as services or purely technical, that support white collar workers). Essentially, researchers versus technicians; leaders versus doers; inventors versus implementors. Bioinformatics is blue collar.
Counterpoint: The white-blue collar divide is absolutely real (quoting a colleague of mine, "in academia, you do not want to become known as a 'doer'".) While many bioinformaticians willingly slot themselves into blue collar roles, it's unclear what makes a speciality one or the other. Why is someone that coaxes microbes to grow in culture or chains together a drug molecule a white collar worker? Why is it that scientists doing bioinformatics that is labelled as something else (e.g. evo devo, gene regulation) get treated as white collar? (Dare I say it's because their work is actually about biology not obscure technical shibboleths?)
Although this does perhaps shed light on another question - people have forever been arguing about the distinction between bioinformatics and computational biology. To no avail - often the suggested criteria vary wildly across people and even flip completely. One person’s computational biologist is another’s bioinformatician and vice versa.
But I think there’s a common divider: bioinformaticians and blue collar, computational biologists are white collar. Always.
The work is not tangible
Proposal: bioinformatics is "thought work" with little physical output and so is easy to forget about or discount.
Counterpoint: This is a problem but it's not one with mathematicians or statisticians, at least not to the same extent.
Bioinformatics isn't worthy of respect
Proposal: The bioinformatics literature and community contains a lot of obscure, deck-chair rearranging about obscure technical details as opposed to than scientific conversation.
Counterpoint: You got me. This is not to devalue methodological assessment or establishment of best practices. But the most visible conversations in the bioinformatics or analytics space sound like car enthusiasts barracking for their favourite models and waxing lyrical on how they spent the weekend rebuilding an engine. In a way, this is just another form of the "IT" issue. It doesn't sound like science.
Conclusions
As said, I don't have an answer. And the answer is probably a mix of all of the above. But if I was to boil it all down to a single statement, it might be:
Bioinformatics doesn't look like science. Sometimes it doesn't even look like work.
Before you ask how to fix this, should it be fixed? Bioinformatics is a broad, broad church and trying to fit everyone under one image or label (or one set of expectations) is not going to work. Many people who fill "blue collar" technical posts are happy with that and trying to force everyone to fully commit to being "a scientist" (white collar) incurs a new set of problems. Perhaps what we need more is clarity about roles and responsibilities. If you're supposed to be a scientist, do science, talk about science and ask to be treated like a scientist. If you’re “just” the technical guy, insist on being treated as just a technical guy.
Here's one of my pet peeves:
Bioinformaticians rarely respect each other. A typical bioinformatics paper will have less than half of the number of references of an equivalent wetlab driven one.
I'm not saying that we should be citing irrelevant things, but bioinformatics is certainly one subfield where the threshold for "relevance" is too high. People use tools without citing them all the time (IME, wetlab folks are more assiduous about citing bioinformatics tools than other bioinformaticians!) and rarely cite tools from where they got ideas/inspiration or to contrast choices.
Not to sound like a soap(y) commercial, but if bioinformaticians don't respect each other, why should others respect them? Also, this definitely reduces the average number of citations that bioinformatics papers get, which does definitely lead to less respect in all sorts of ways.