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I’d like to invite you to share your thoughts on the future of bioinformatics in NZ over the next few years.

On the 3rd of May be a one-day meeting ’Where will New Zealand Bioinformatics be in 2013?’ will be held at the University of Auckland. As the title suggests, this is to be a future-looking event, discussing what is needed in the (short-term) future.

A wide range of topics are being discussed, including GRID computing, which I (tried to!) open a discussion on.

I have started to write a longer post offering some of my own thoughts, but in the meantime, I would like to invite people to look at the schedule for the meeting, then speak up and share what they see as important for the short-term future of bioinformatics.

For those that won’t be attending the meeting, I will do what I can to present your views. (Bear in mind that as I am not a speaker, my opportunities may be limited.)

A little background

I have only learnt of the meeting fairly recently but I am under the impression that it is, at least in part, linked to the New Zealand Genomics Ltd initiative, perhaps aimed getting some direction to the bioinformatics aspects of this initiative from the wider community.

My own interests in bioinformatics infrastructure – aside from the usual ones of being a worker in the area – in part stem from being involved in an early attempt to establish national bioinformatics priorities under Prof. Diana Hill in 1997.

As part of this effort, I prepared a 49 page briefing ’Bioinformatics: Policy overseas, implementation issues and computational molecular biology’, a survey of bioinformatics initiatives, what other initiatives considered were the key concerns, an introduction to computational molecular biology and my suggestions on developing a national initiative in this area.

In the following few years, I tried to initiate local interest in a bioinformatics initiative. (The lack of interest in creating a setting that supported original bioinformatics in part prompted my setting up independently, leaving the university to found my consultancy as I couldn’t envisage an independent research post or setting being created.)

Things have rapidly evolved in genomics and computational biology since, but much of the over-arching basics remain the same. Getting the organisation right still matters, as it has downstream effects. The basic divisions of labour remain. The broad areas of science are largely the same, albeit with new toys! (My particular interests in genomics are in chromatin structure, epigenetics and the higher-order structure and function of the genome.)

Dividing the field up

It’s a big field to take in one go, so it might help to break it down into large, more-or-less homogenous, chunks. Very broadly we can divide bioinformatics into research and support, underpinned by infrastructure.

By infrastructure I mean computer hardware, networking and the support staff associated with this level, work that is computing where little real knowledge of biology needed.

Support bioinformatics, e.g.. using established techniques and data pipelines to process others’ data in a ’set’ manner.

Research bioinformatics (and computational biology) focused on developing new methods or algorithms, or using techniques in novel ways.

Please note that when I write ‘support’ and ‘research’ I see no reason to limit this to academic settings; it equally applies to commercial settings or independent workers / consultants like myself. Some work straddles research and support, of course.

There are also purely commercial operations, e.g. developing software to sell.

We could also look at bioinformatics through the specific projects, research areas or techniques it interacts with: high-throughput sequencing, expression analysis, structural biology, microscopy, medical diagnostics, and so on.

Questions

Write whatever matters to you. The questions I offer below are intended to seed discussion, not limit it.

Do you feel that particular areas of research have poor bioinformatics support?

What kind of support or collaborations do you want?

Speaking for myself, I’m a little concerned (I’m being understated here) of lack of support for research in bioinformatics in NZ. In terms of particular research areas related to genomics, I am concerned at a need for more attention on the higher-order structure of genomes. (Disclosure: I have been trying to get funding for research in this area to no avail for some time now and am, I think understandably, frustrated!)

Do you think that lack of understanding of opportunities by experimental researchers resulting in fewer requests for funding for computational biology collaborators than there might be?

Are researchers under the impression there are few to collaborate with, or seek support from, and hence are not asking when they might otherwise?

While I realise it may be an unpopular suggestion, it might be useful to encourage (or even enforce) applicants to resolve their bioinformatics needs at the time of application. This is more than a funding issue. To spare a little space here, I invite people to read what I have previously written about this.

What needs do other bioinformatics workers want? (My main wish is for research funding! Not very original I know, but there you are. My wants are modest…)

What do you want to see from New Zealand Genomics Ltd.?

Please offer your thoughts in the comments. I realise this is a very open brief, but that is the intention; I want this to be an open forum, rather than driven by my own interests (I can do that in later posts).

I would particularly like to hear from those from NZ who are not speaking at the meeting or are outside of bioinformatics, and those from overseas who have experience in this area. I will try find time to get my own thoughts in order, but you’re best not to hold your breath!


Other bioinformatics articles on Code for life:

External (bioinformatics) specialists: best on the grant from the onset

Developing bioinformatics methods: by who and how

More on ’What is a computational biologist?’ (and related disciplines)

Retrospective–The mythology of bioinformatics

Bioinformatics — computing with biotechnology and molecular biology data.

Computational biology: Natural history v. explanatory models

Reproducible research and computational biology