bioinformatics, genomes, biology etc. "I don't mean to sound angry and cynical, but I am, so that's how it comes across"

You’re not allowed bioinformatics anymore

Ah welcome! Come in, come in!” said the institute director as Professor Smith appeared for their scheduled 2pm meeting. “I want to talk to you about your latest proposal”, the director continued.

“Oh?” replied Smith.

“Yes. Now, let’s see. It’s an amazing, visionary proposal, a great collaboration, and congratulations on pulling it together. I just have one question” said the director “This proposal will generate a huge amount of data – how do you plan to deal with it all?”

“Oh that’s easy!” answered Smith. “It’s all on page 6. We’ve requested funds to employ a bioinformatician for the lifetime of the project. They’ll deal with all of the data” he stated, triumphantly.

The director frowned.

“I see. Do you yourself have any experience of bioinformatics?”

Smith seemed uncertain.

“Well, no…..”

“Then how will you be able to guide the bioinformatician, to ensure they are using appropriate tools? How will you train them?” the director pressed

Smith appeared perplexed by the question.

“We’ll employ someone who has already been trained, with at least a Masters in bioinformatics! They should already know what they’re doing…” Smith trailed off.

The director sighed.

“And what papers will the bioinformatician publish?”

Smith regained some confidence.

“They’ll get co-authorship on all of the papers coming out of the project. The post-docs who do the work will be first author, I will be last author and the bioinformatician will be in the middle”

The director drummed his fingers on his desk.

“What about a data management plan?”

“A what?”

“A data management plan. A plan, to manage the data. Where will it be stored? How will it be backed up? When will it be released?” the director asked

“Same as always, I guess” said Smith. “We’ll release supporting data as supplementary PDFs, and we’ll make sure we get every last publication we possibly can before releasing the full data set”

The director shifted uneasily in his seat. “And data storage?”

“Don’t IT deal with that kind of stuff?” Smith answered.

An awkward silence settled over the office. The director stared at Professor Smith. Finally he broke the silence.

“OK, so you have this bioinformatician, you give them the data, and they analyse it and they give you the results. How will you ensure that they’ve carried out reproducible science?”

“Reproducible what? What the hell are you talking about?” Smith answered angrily.

The director slammed his hand down on the desk.

“At least tell me you have a plan for dealing with the sequence data!”

“Of course!” said Smith “We’ve been doing this for years. We’ll keep the sequences in Word documents….”

an amber light started flashing on the director’s desk

“… annotate genes by highlighting the sequence in blue…”

the flashing light turned red

“… annotate promoters by highlighting the sequence in orange…”

Smith’s sentence was interrupted by a noisy klaxon suddenly going off, accompanied by a bright blue flashing light that had popped up behind the director’s chair.  Smith looked wide-eyed, terrified.

The director pressed a few buttons on his desk and the noisy alarm ceased, the blue light disappeared.

Smith, removing his hands from his ears, asked “What the hell was that?”

The director stood, walked over to the window and sighed heavily. “I’m sorry, Smith. I had a feeling this might happen. Look… this may appear harsh, but… you’re not allowed bioinformatics anymore”


“As I said. You’ve crossed the threshold. You’re not allowed bioinformatics anymore”

Smith’s mouth flapped open and shut as he tried to take in the news.

“You mean no-one will analyse my data?”

The director turned to face Smith.

“Quite the contrary, Smith. Good data will always be welcome, and yours will be treated no differently. It’s just that you won’t be in charge of the storage and analysis of it anymore. You can generate the data, but that will be the end of your involvement. The data will be passed to a bioinformatics group who know what to do with it.”

Smith was furious.

“Are you insane? That’s my data! I can do whatever I like with it! Bioinformaticians won’t know what to do with it anyway!”

“On the contrary” replied the director “It’s not your data. Your research is funded by the government, which is in turn funded by the tax payer. The data belong in the public domain. As for bioinformaticians, they’re scientists too and they’ll be able to analyse your data just as well as you can, probably better”

“I’ve never heard anything so ridiculous! Who decided that I’m not allowed bioinformatics anymore?”

“The Universe.”

“The Universe? Why should the Universe say I’m not allowed bioinformatics anymore?”

“Because you haven’t paid bioinformatics enough attention. It’s not a support service, at your beck and call. It’s a science. Bioinformaticians are scientists too. Young bioinformaticians need support, guidance and training; something you’re clearly not qualified to provide. They also need first-author papers to advance their careers”

“I don’t understand. What do you mean, they’re not support?!” spluttered Smith.

The director continued regardless of the interruption.

“You’ve had the opportunity to learn about bioinformatics. We’ve had a bioinformatics research group at the institute for over ten years, yet you only ever speak to them at the end of a project when you’ve already generated the data and need their help!”

“The bioinformatics group?! They’re just a bunch of computer junkies!”

The director was beginning to get angry.

“Quite the opposite. They publish multiple research papers every year, and consistently bring in funding. More than your group, actually”.

Smith looked stunned.

“But, but, but… how can this be possible? You’ll never get away with this!”

“I’m afraid I can and I will” said the director. “Science has changed, Smith. It’s a brave new world out there. Bioinformatics is key to the success of many major research programmes and bioinformaticians are now driving those programmes. Those researchers who embrace bioinformatics as a new and exciting science will be successful and those that don’t will be left behind.”

The director stared pointedly at Professor Smith. Smith was defeated, but still defiant.

“It doesn’t matter. We have tons of data we haven’t published yet. I’ll be able to work on that for decades! I don’t need new data, I have plenty of existing data”.

A smile flittered at the corners of the director’s mouth.

“Here’s the thing, Smith. As soon as that alarm went off, all of your data were zipped into a .tar.gz archive and uploaded to the cloud. It’s no longer in your possession”.

Smith looked horrified.

“What’s the cloud? How do I access it? What is a .tar.gz file and how do I open it?”

“You know” said the director “keep asking questions like that, and you might get bioinformatics back”

If you are leading a project that creates huge amounts of data, instead of employing a bioinformatician in your own group, why not collaborate with an existing bioinformatics group and fund a post there? The bioinformatician will benefit hugely from being around more knowledgeable computational biologists, and will still be dedicated to your project.

The above was hugely Inspired by “Ballantyne T (2012) If only … Nature 489(7414):170-170”.  I hope Tony doesn’t mind.



  1. great article. very much enjoyed it. It is time to change my biologist colleagues………I certainly have experienced the value of bringing bioinformatics to the heart of the project right from the outset

    • Hi Venu!

      Indeed, you are a perfect example of a researcher who collaborates with bioinformaticians and bioinformatics groups!

      A shining example to everyone else!


  2. I enjoyed your post above, and have a lot of sympathy with the sentiment in it. My worry is that the “bioinformatics community” is as much to blame for the culture as it stands as are “biologists”. Rather than being smugly congratulatory about the fact that they know what a tar.gz file is and some biologists don’t, or that they know better ways of dealing with sequence data than wet-lab experimentalists do, and consequently dismissing biologists as idiots (not that you’re doing that here – but many of the responses to your article on twitter etc are in that vein) perhaps some more effort to meet each other in the middle would be helpful. For example, the sentence: “…they’ll be able to analyse your data just as well as you can, probably better…” implies that you think the analytic process is of more value than understanding the biological question being posed – and that just be knowing how to run the analysis, a scientist can derive as much as or more information than a non-expert analyst who understands the science.
    I know you’re an advocate for truly collaborative work, and that, surely, is the way forward; my concern is that there is a growing sense of animosity between “biologists” and “bioinformaticians” which can only be harmful… No real purpose or focus to this reply, but I felt that some of the chatter following this article was pretty negative.

    • Hi Steve

      Yes, of course, indeed science has to be done in collaboration. I guess there’s a few things to say. Firstly, this is supposed to be satire, and shouldn’t be taken too seriously. Having said that, I am passionate about the plight of the lonely bioinformatician (http://biomickwatson.wordpress.com/2013/04/23/a-guide-for-the-lonely-bioinformatician/) and I believe we must think very carefully about what support is available when we employ bioinformaticians into lab-based groups. Secondly, to a certain extent I think bioinformatics has to “fight back” – we have very high profile biologists (e.g. Dan Graur) publicly mocking high profile bioinformaticians (e.g. Ewan Birney) as nothing more than computer junkies. Finally, it’s generally accepted in our institute that when we employ bioinformaticians, we expect to see “middle author syndrome”. We have to ask whether this is right, and have to think hard about where the credit lies in research projects.

      I’m slightly in danger of becoming a militant bioinformatician, in the same way Dawkins is a militant atheist. I don’t really want to be, but I do think, as a field, we need to stand up for ourselves a little and make sure we get the credit we deserve.


      • One of the challenges we seem to face is getting the biologists to talk to the informaticians to stop us just discussing the methods which might use in a vacuum without any biological context. Part of this problem does seem to stem from the fear that we are just trying to supersede the lab biologists and not work together collaboratively not sure how to get over that problem

    • Personally, as a computational biologist/bioinformatican/whatever, I always get annoyed when people (usually experimentalists) make the distinction between “bioinformatican” and “biologist”. Data analysis is as much biology as generating data. As far as I know, biology is the only science where not being an experimentalist is often viewed as not really being a scientist. If anything, in fields like physics the computational/theoretical people are actually more respected than the experimentalists.

      • Hmm, I am a computational biologist/bioinformatican/whatever too but the distinction made by us as well.

      • So you don’t see yourself as a biologist, jayonmars? Not criticizing, but it’s interesting. Of course computational stuff in biology is done by people with a variety of backgrounds — maybe people with a background mostly in CS or statistics consider themselves primarily computer scientists or statisticians rather than biologists.

    • I feel that the key sentence is this:
      ” implies that you think the analytic process is of more value than understanding the biological question being posed – and that just be knowing how to run the analysis, a scientist can derive as much as or more information than a non-expert analyst who understands the science.”

      And the implicit assumption that the analyst doesn’t understand the science as well as the experimentalist. Computation is just a technique like any other. Many people choose a technique as well as biological question to specialise in. Just because someone is an expert in tissue culture, qPCR, or any other experimental technique, you would think that implied anything about their knowledge of biological systems. Sure for some infomaticians its the computer science of the thing that interests them, but increasingly bioinfomaticians are biologists that have chosen computers as their tool of choice rather than tissue culture or western-blotting.

      I would be reluctant to get involved with any project where I understood nothing about the biology.

  3. Thanks for the reply. I was aware of the satire (and enjoyed it) along with the serious message behind it. I am absolutely behind you in the lonely bioinformatician arena (and have recommended your post to a number of colleagues and friends in the past). The difficult nature of bringing a new skill into an established lab is a very thorny one – and not limited to bioinformatics. Any new post-doc (or RA, tech, whatever) entering an environment as “the guy who can…” is in for a rough ride, be it the “cell culture guy(/gal)”, the “data guy”, the “mouse girl” etc etc if there is no established skill-set to learn from in the lab itself.
    Your advice to seek out the comp bio/bioinformatics group on campus and aim to become a regular at their lab meeting etc is excellent, and works well (in my experience at least) – but ideally there would be individual mentorship, career development and genuine investment in the post-doc by the PI/lab head. In the case of computational biology this works both ways, of course. The CompSci going into biology needs to learn how to think in biological terms, understand feedback (the biological kind), get the fundamentals of cell/gene/protein biology nailed down etc etc before the application of their computational skills can bear fruit, just as someone originally trained as a biologist will need to really focus on their stats, coding, analytic methods etc…
    The problem may come that, as bioinformaticians in leadership roles and with high public profiles become more militant and bunkered in their mentality (fighting back, standing up for ourselves, however you want to put it) the field as a whole may begin to be seen as the “awkward squad”, not team players, hard to work with etc, and as a result, the collaborations will dry up, the opportunities to be at the forefront of cutting edge research will go to bright biologists who are willing to spend time learning the single-use case informatics (rather than career bioinformaticians) and bioinformatics will regress back to being a genuine “support-only” field. Not what we want! As recent international events might indicate, militant and reactionary responses to small acts (in the moral sense at least) of provocation may not have entirely positive outcomes…

    • Hi Steve, I totally agree. The best way is to work together, and I absolutely, 100% agree that bioinformaticians need to be biologists and think scientifically! There is a real responsibility on us (bioinformaticians) to be research scientists.

  4. A former lonely bioinformatician

    22nd July 2014 at 9:35 am

    Reading this blog post, I can’t help but relate it to the situation in my previous job. Fresh out of university with a Masters degree in bioinformatics, I was prepared to take any position that came available. I wound up in a biology lab at a research institute in London where they had recently gained some additional grant money to fund a bioinformatician for a few years. The institute had little computational support and had no group dedicated to bioinformatics. Many consumables were not factored into the grant application, even basics such as a desktop computer! I found the situation to be both positive and negative. On the positive side, it let me learn a lot of techniques and considerably advance my skillset at a pace that suited me. However I had no (face to face) access to experts in the field and had no chance of ever getting a first author paper. I suggested we split a publication into a biological lab paper and a second computational methods paper with the tool released publicly on GitHub (or similar) but this was dismissed completely. At the time I was of the opinion that all bioinformatics roles were like this, until I read your “lonely bioinformatician” article. This gave me the drive to want more and find an opportunity that worked for me, rather than being “the data monkey over there in the corner”. I now work as the lead developer on a new biological database resource at a leading bioinformatics institute. The skills I gained whilst a “lonely bioinformatician” have been invaluable and I’m actually pleased I had the opportunity to sample life as a dry scientist in a wet lab.

    • Pretty much how I learned bioinformatics.
      I started my PhD program in a wet lab, but toward the end I started doing a little bit theoretical physics (applying to biological context), and learned a bit of programming.
      After that, I joined a wet lab as the lone bioinformatician because I had a little bit programming skills. There, I didn’t have any direct interaction with real experts in the field, but I was able to learn some critical skills on my own pace. Three years later, I’m doing serious work for a bioinformatics software company.

  5. I completed B. tech Bioinformatics. I am now working in the area of Machine Learning, Natural Language Processing and Data mining for more than 5 years. I am planning to pursue research in Bioinformatics. But I see a lot of pessimism appears in the community. I spoke to so many people who are not giving a thumps up for a career in Bioinformatics. Not sure what to do. But one thing I can vouch for is a specialized jobs is sometimes advantageous and sometimes very difficult to survive. It is just my perception and need not be right. I wish this field could thrive better. I am looking for safe bet. Lonely confused former Bioinformatician. Good post though 🙂

    • On the contary, bioinfomatics is a great career choice, as long as you are prepared to learn the biology as well as the computation. There are far more jobs out there at the moment for people with computational skills than for other parts of biology. And this isn’t just for data-monkey positions (although there are still plenty of those), but all the way up to group leader positions.

  6. My issue comes from how biologists often respond when people try and do this in reverse. It is quite trivial to purchase many of the biological steps as services – as a ‘damp’ bioinformatician I can type in a sequence and get protein mailed to me, send RNA to a quality service provider and get RNAseq etc. In fact I think outsourcing the biology these days is easier than outsourcing the bioinformatics.
    The trouble is that few who has taken the time to develop bioinfomatics skills have been able to maintain the track record of first author publication and grant funding to pull in new grants based on their own original ideas.
    We need to better value contributions within groups generally – the idea that only two of the people on a 10 or even 200 author paper actually did anything of merit is laughable. When we focus on actual contributions rather than perceptions it makes it easier to have structural groups that support the work rather than support the gaming of scientific careers.

  7. Thanks, really enjoyed this post. We run a few workshops on various bioinformatics topics for “bench scientists”, and I always say that the main benefit of the workshop is not that they will be able to do it all themselves, but they will be able to interact with the bioinformatician in a more useful way.
    In the workshops, it’s been quite nice to see people realise that we don’t ask all these questions about the biology and experimental design because we like the sound of our own voice, but because it’s absolutely essential for a meaningful analysis. Have noticed a big drop in the “just analyse the data and leave the biology to me” attitude. Progress.
    That said, I definitely do love the sound of my own voice.

  8. There is a lot of truth in it, indeed!
    The motivation for me working as a “lonely bioinformatician” is the fact that I am working really close to biology and to have the opportunity to initiate projects based on biological questions. But that’s my personal ideal situation because I am still a biologist at heart 😉 and of course it is only perfect when the boss allows you to have your first-authorship publications beside those in the middle.

  9. very nice article indeed. I still feel it is so hard to start a bioinformatics group. They always ask for biological question, data analysis, visualisation, statistics and method development.. in summary problem solving is’nt this also science. Some confusion but I know Bioinformatics is here for many more years.

  10. Reblogged this on Scientific B-sides and commented:
    Our institute director is a bioinformatician – so this could actually happen. But then again, none of my experimental colleagues would be as stupid as Prof Smith.

  11. For me the crux of the matter is that bioinformatics is not Science. At least in the way jobs are created and filled in, indeed ending up at author positions reserved for lab analysts (first and last positions are reserved for people ‘owning’ the data, rather than the ‘exciting’ analysis), while at the same time bioinformaticians are held fully accountable as scientists. There is a huge discrepancy/gap there. Furthermore, to apply for grants a Scientist-bioinformatician will face a panel of biologists which diminishes the chance of getting funding unless he/she writes it in a way that it is a biology grant. In a way, bioinformatics is mis-sold as a Science: to do the work the grant system in most countries only can fund people willing to work as a Scientist. It may well be that the position of the bioinformatician of the future is equal to that of a lab analyst.
    At BOSC 2014 I asked many bioinformaticians whether they were happy with their jobs and/or had good career prospects. The general response was depressing.
    There are signs that bioinformatics is in a crisis, despite the fact that bioinformatics is more critical to good Science than ever before.

  12. And please ensure you pay your bioinformatics folks properly. I saw a post just the other days for a software developer in a bioinformatics group at our neighbouring university…the salary was laughable! How on earth you they expect to get a good developer at what they were offering, it was 2/3 of what a developer could get in industry. And how are us developers supposed to make a career in this field if there are only entry level wages being offered? That will be one of the continuing issues holding back really robust software from coming out of the field if it’s a continual revolving door of developers jumping ship to industry (and I mean the software industry, not biotech) as they become more senior and their wage needs increase. Just as I’ve seen many many do over my 12 years in the field, countless colleagues heading back to industry because the wage gap is so large, and as I’m considering doing as I’ve hit a ceiling as well.

  13. i will share this, nice, i enjoyed reading it; relative to disciplines in the academy, bioinformatics is *still* one of the new areas of science …

  14. This is virtually identical to another person’s writing from 2012. Problematically so.


    Journalists lose their jobs under plagiarism for stealing single paragraphs; entire books are tainted for lifting a page. This seems to be the same structure and the same narrative entirely.

  15. Speak up! And ask yourself what is your research field of interest. I am a stem cell computational biologist, doing “in-silico” experiments to answer the questions I am interested in (TFs driving cell fates). I am collaborating in an equal relationship with my fellow biologists, designing together the experiments, interpreting together the results and deciding together on follow-up experiments.

  16. Love it Mick – lots of good points squeezed in there. I think things will get better in general, at least on the -omics side for bioinformaticians, as the ease of producing data continues to increase exponentially, and processses become more and more automated, it will be the wet lab scientists that will be struggling to justify their positions on papers in the future.
    However, there are also many types of bioinformaticians (as there are many types of lab scientist), and some will be happier just making sure the machines/scripts run properly, whilst others are more interested in doing serious development, and others who are really interested in finding the best approach to answer the biological question of interest – I guess basically I think “bioinformatician” is too broad a term, and we need to start to define ourselves better. I sit at a computer all day, but I still regard myself as a geneticist first and foremost, though using current vernacular from the filed of biology, I am clearly a “bioinformatician” 🙂
    I have to disagree with Matt a little about the pay – if you are getting 2/3 of industry rate but working with the traditional benefits of being in public sector research i.e. more holidays, more flexible timetables, less pressure exerted from above, a greater variety of interesting opportunities, then I think you are doing OK. If one is really motivated by money, then there is little point in looking for work in the public sector in the first place. I realise that for those reading who reside in the US, these distinctions may not be as clear as they traditionally have been in Europe.

  17. Great post Mick,
    I know it rubs a lot of people the wrong way but it was coming. The way most biologists treat the unassuming lonely bioinformatician is conveniently ignored, even endorsed, has been going on for quite some time. Not all bioinformaticians are CS or statistics people. I shifted from biology to bioinformatics and saw most wet workers assume seniority or knowledge over bioinformatic counterparts. Even shifting from bio to informatics doesn’t count much in their view. We are all the IT people. So, I chose not to collaborate with whoever had that atttude and rather work in isolation on own ideas with public data. Once they see your solo effort, they come along asking for help. I am all for collaboration and have good collaborators too, but generally so-called biologists have changed the perceptions of who is a scientist and who is a technical assistant. This mentality needs a shift. So, kudos for the post.

  18. I’ve only ever worked on projects where the data was collected well in advance and my input was sought after. I’ve only ever been mid-author too. I’m beginning to develop a bit of a nose for crap bioinformatician jobs. Saw this one today and reckon it smells funny:
    Comp Sci dept wants someone to ‘develop and evaluate algorithms’ for a clinical data project that has clearly already been carried out – or at least applied for and money allocated. The Comp Sci dept has presumably been brought in because the biomed department doesn’t know how to analyse the data or can’t produce ‘significant results’. The Comp Sci department does not know that Metabolomics data processing is a well defined concept that does not require ‘developent and evaluation’ i.e they’re completely unqualified to jump into this study but are willing to give it a go anyway because in time, they will be able to do the job.
    The poor bioinformatician that takes that role will have no training or supervision from knowledgable superiors; will waste a large amount of their time either reinventing the wheel or delving into the extensive literature and coming to the same conclusion as everyone else… much, much later than necessary; will probably find that there is a reason that the original bio team can’t analyse the data and that he/she can’t do a decent job on it e.g. massive systemic/analytic variability that masks biological variability; that variation/contamination could be class/group specific meaning you can’t trust results; perhaps too great a stratification of the study so each subgroup has too few observations.
    Of course, none of this will be fully realised until at least 6 months into the 2 year position, which will be followed by 1 year of soul crushing statistical ‘massaging’ that borders on fraud because it’s imperative that you get publications in press before you start looking for the next job. And those publications will have the biomed staff at the front and end, with the bioinformatician’s name in the middle. Possibly 3rd.

  19. Reblogged this on Kurui's blog and commented:
    Awesome Read.

  20. Enjoyed the read, a lot. Don’t forget those who collect data and when they realise they cannot process them, they make a call to the closest bioinf department asking for help at the condition of being first-author of a potential publication.

  21. I know this if off topic but I’m looking into starting my own blog and was wondering what all
    is required to get set up? I’m assuming having a blog like yours would cost a pretty
    penny? I’m not very internet smart so I’m not 100% positive.
    Any tips or advice would be greatly appreciated.

  22. awesome write-up .. and an amazingly funny narrative of this real issue 🙂

  23. Reblogged this on Pythonic Biologist and commented:

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