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Tag Archives: Research

(Do not) Beat ideas half to death

This is short post/note to self – to see if the way I think about science today will change in couple of years. Its enigmatic title comes from Stu Jenks, one of my favourite photographers. He wrote in the introduction to his works:

I’ve been doing a series of spirals. You know how it is with us artists. We take one idea, and then beat it half to death.

If we substitute “artists” with “scientists” it still sounds true. This is efficient (in modern terms of scientific productivity) way of doing research, but probably not always the best one. While I know that many breakthrough discoveries in science were results of years of hard work, not all of them required fifteen years to establish a procedure only. So, the question is if rapid switching between fields (every few years or so) is a good idea? It probably depends. Ask me in a few years how it works in my case.

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Posted by on February 17, 2009 in Comments

 

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Thinking about RaaS: Research-as-a-Service

The research li...

Image by Getty Images via Daylife

Instead of disclaimer: this is a bunch of loose thoughts on an element of a possible future of research. I’m only touching some issues here and still I don’t have coherent vision of the commercial side of research. So, feel free to show me I’m very wrong – you’ll save me lots of time of coming to your conclusions :).

According to Wikipedia, Everything as a Service is a:

concept of being able to call up re-usable, fine-grained software components across a network.

While the most common example is SaaS – Software as a Service, this concept can be applied to other functions such as communication, infrastructure or data (the last one sounds very interesting). It recently occurred to me, that investments (or maybe I should call these partnerships) of biotech and pharma companies in academic research institutions are good examples of RaaS, Research as a Service. I think every situation where the research is done after the agreement (buying or licensing patented innovation doesn’t qualify) can be called RaaS.

Why

To a company, there are obvious advantages of hiring scientists to get the research done, but I think there also would be plenty of good sides of such arrangement for us (of course I have no experience yet). Probably the biggest plus would be money and ability to get them in somehow predictable manner. I think it’s also important to be stretched intellectually from time to time (I assume that easy things aren’t worth outsourcing).

Many flavors of RaaS

Paying to an academic institution to come up with a new drug candidate is only one of many types of RaaS. There’s researching a given problem (something Innocentive or Nine Sigma are coordinating), coming up with an innovation (drug candidate example), providing expertise (consulting) or innovating and delivering (designing, building and implementing new machine, workflow or pipeline). We could find examples of all types happening everyday, but probably not in all scientific fields. Delivering something in biology is usually quite expensive and time consuming, while consulting gigs in quantum physics don’t appear all that often.

The point is that all these RaaS flavors can and are applied to academic institutions. In other words, many researchers provide commercial services using time and equipment paid from taxpayers money. And I think it’s not an issue – even more: it should be finally admitted and accepted (so we could get rid of the artificial division of researches into academic and all others; but that’s another story), and organized, so we could provide such services easier and more often.

Resources all over the place

The Health Commons project aims at building a framework that could help in sharing and organising research process aiming at developing new drugs. We seem to have lots of elements of such environment in place – we have many (or even too many 😉 ) scientists, some service providers, data centers and some work done on standards of operations and information exchange. If we forget about drug development, not much actually changes. We have workforce, some services aimed at researchers and lots of tools that help in communication in both directions.

Here’s example of research scenario: if I were to market a genetic test that identifies mutations resulting in oversensitivity or resistance to a drug (something which I believe will be the next hit after screening for disease markers), the whole research part wouldn’t require any significant involvement from my side. CRO (contract research organization) would take care of identifying patients with specific conditions, sequencing company would get me their genomes (currently $5000 each, but the price is dropping very fast) and as far as I know bioinformatics community, finding people to analyze the data wouldn’t be an issue at all. While such scenario is a bit too optimistic (I skipped lawyers in the process), we already have resources to make it happen.

Where is it going?

I imagine future RaaS provider as a small company (I’m not yet sure if a non-profit organization is a better fit for people interested in doing research; also, I don’t know how fast the issue of academic-commercial blur can be solved) made by a few scientists from different but closely related fields. The reason I see it small, is about mobility. And I don’t mean here physical mobility (which BTW may be required on some occasions) but mobility of focus – the main advantage of small organizations.

I imagine such company would be able to do consulting (and data analysis, maybe on the RedMonk model) and innovate at a software level. It would be able to do the work on site (small group again) and deliver the results quick (“bursty work”).

Pieces of this vision come from old Deepak’s posts and many FriendFeed discussions. I actually think about putting it into practice. What do you think I am missing here (other than marketing 😉 )?

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Posted by on November 3, 2008 in Comments, Research

 

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Open Access Day

Today is the world’s first Open Access Day . It aims at broadening awareness and understanding of OA. The approach is to make as many people as possible to blog today on the topic, possibly answering the following questions:

  • Why does Open Access matter to you?

In my case, where pretty soon I’ll have no support from a large institution, Open Access means ability to do research. OA is a vital help to small or underfunded research groups.

  • How did you first become aware of it?

Internal policy of my former employer required that all results should be published in OA journals. BTW, it didn’t change since then.

  • Why should scientific and medical research be an open-access resource for the world?

Ability to do research and to innovate shouldn’t be inhibited by access to knowledge and data produced by publicly funded research institutions.

  • What do you do to support Open Access, and what can others do?

I do publish in OA journals (four out of five publications I have so far are OA).

See more OA Day entries at FriendFeed Open Access Day room.

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Posted by on October 14, 2008 in Community, Research

 

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Many Eyes and literature summary

I’m not the first one to come up with this idea – Ntino posted about it before. However, I didn’t really understand before how powerful it could be. Using Many Eyes visualization capabilities I’ve created a quick browsable summary of abstracts related to a particular protein. I took all abstracts PubMed returned for a particular query (in this case it was “YadA Yersinia”; YadA is a prominent adhesin and important pathogenicity factor in Yersiniae) and uploaded them as text into Many Eyes. I chose “Word Tree” representation and searched for “yada”, which gave a nice graph of the most prominent phases related to this protein/gene name. Maybe it’s not a breakthrough, but compared to the classification/semantification provided by GoPubMed, such approach works much better for entities that aren’t well described in biological ontologies.

Given that the whole concept is pretty straightforward, it would be nice if one of alternative PubMed search engines provided a similar method of summarizing user’s query, don’t you think?

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Posted by on October 4, 2008 in Papers, Research, Visualization

 

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One year of blogging – plans for ten years

Ethos Roundtable at Bob Doyle's Home - July 18...Image by Pathfinder Linden via Flickr

Following BioBarCamp I missed one year anniversary of this blog. With sixty something posts I cannot say I’m very productive blogger, but I didn’t aim at being one, as probably all other science-types. My goal was to be engaged in the conversation and I have reached it much faster than I expected. I got lots of help and encouragement from people I wouldn’t even dear to email a year ago. I know much more than I did on things outside of my research area. While it sounds all pathetic, advantages of being part of this community are hard to overestimate – I wrote about it couple of times already (and Neils did a great job summarizing why you should have a web presence).

Where is “Freelancing science” heading? That’s a question I asked myself pretty often during last 12 months. At first, I just blogged about interesting stuff around bioinformatics. Then I made a jump into freelancing as scientists (and this experiment goes pretty well). Statistics on keywords people are using to find this blog clearly show that there’s some interest within bioinformatics community in following this path. But the idea for this blog I have right now is not about freelancing anymore. Or rather it’s about freelancing on the next level, because today I think about starting a non-profit institute.

I believe that small research groups formed as a non-profit organizations will have enourmous impact on science within next ten, twenty years (more about it in upcoming post about the future of scientists). In spirit of freelancing they will jump from one project to another (see Deepak’s post about bursty work and follow-ups), developing solutions and making discoveries much faster (or cheaper) than it is possible in beaurocratic environment. We do have tools for effective collaboration online, we have new generation scientists that do not feel attached to academic system and we have science which starts to evolve about undestanding data, not performing experiments. Is it time to try such approach?

So, watch this space to see how the idea develops. I’m also interested in your opinions and experiences with starting and cooperating with non-profits if you have any.

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Posted by on August 11, 2008 in Career, Community, Research

 

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Semi-automated workflows – Taverna Interaction Service

I was still thinking about recent Neil’s wondering about possibility of automating every scientific workflow, when I saw this (Bioinformatics Advance Access abstract):

The Taverna Interaction Service: enabling manual interaction in workflows by Anders Lanzén and Tom Oinn

Taverna is an application that eases the integration of tools and databases for life science research by the construction of workflows. The Taverna Interaction Service extends the functionality of Taverna by defining human interaction within a workflow and acting as a mediation layer between the automated workflow engine and one or more users.

I have not tried it yet but this Taverna plugin is very likely an answer to doubts I often have when automation of bioinformatics workflows is discussed: we shouldn’t always remove ourselves from the workflow, as interaction with software can be often critical in making a discovery. For example conscious decision about which sequences should go in during PSI-BLAST search can dramatically influence quality of resulting profile. So I agree with Neil that not every workflow can be automated, but more importantly not every workflow should be. Possibility of wrapping one’s mind around a problem is gone when there’s no feedback loop on the process.

 
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Posted by on March 12, 2008 in bioinformatics, Papers, PubMed

 

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Outsiders and great scientists

Last weeks brought another worth reading pieces on being a scientist: one in PLoS Computational Biology (found via The Evilutionary Biologist) and one over at Adaptative Complexity blog (found via Genome Technology). I would add a third one, albeit not strictly about scientists. This is “The power of the marginal” by Paul Graham. Graham in general writes about start-ups, but in this particular essay he put an advice, that I keep repeating myself over and over again:

If most of your ideas aren’t stupid, you’re probably being too conservative. You’re not bracketing the problem.

When I look back over the ideas I had, they could be categorized into four main groups: the ones that were published couple of years before I found them, the ones that were published just before, the ones that were published just after I started to work on them and finally the ideas I’m still working on because they were not published yet. In this light, Graham’s advice seems to me a pretty good way to escape this schema.

 
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Posted by on February 25, 2008 in Career, Research skills

 

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“Startup weekends” in science

News about yet another “startup-weekend-like” event keep hitting me more and more often. They do not always are about creating a company or a product. Sometimes it’s about collaborative coding a game or writing a novel – all in very short time. In many cases it works amazingly well – being so tight on time forces people to be ultra-productive and to be focused only on important parts of the project. I envy people attending such meetings, not necessarily because of possible outcomes, but because of the energetic atmosphere that is present there.

Deepak wrote some time ago about “Bursty work” – idea, that work can be done by distributed teams focused around high value projects, instead of teams gathered around company/startup. That actually made me think if we can join these two ideas in science: to have ultra-productive and distributed team working on time-constrained project.

Lets assume that the average publication in the field of bioinformatics/computational biology takes six months of work of one scientist. It doesn’t really matter if it’s new server, database or protein family annotation. So a team of four people should do the same work in six weeks or faster (why faster? knowledge and skills are not distributed evenly, so someone else may code the necessary script faster than I would do it). If we would increase even further the number of people involved, create a distraction-free environment and prepare enough coffee for everyone, the whole process could be done in a week. Even if the assumptions here are not really correct, I’m pretty sure that quite a number of valuable papers could be done this way in a week.

So what do you think? What about creating a platform that allows for:

  • creating a project that has a clear and appealing outcome (for example publication, or at least manuscript in Nature Precedings)
  • creating a project workspace with all necessary tools (wiki, chat, svn, etc. plus small computational backend for testing)
  • creating a number of roles, that need to be filled by people with certain skills
  • joining the project if the skills match requirements
  • setting an clear deadline (for example, a countdown clock that will forbid to commit changes to the project after certain amount of time, leaving the workspace read-only)

I agree that science takes time, especially the quality science. But on the other hand, I have a feeling that we waste a lot of time learning things by ourselves, instead of learning form others, we waste this time because the outcome is not well defined, and finally we waste time solving everything ourselves instead of bouncing the idea against other people (this is what collaboration is all about). So what about creating an artificial environment that forbids wasting time?

Utopian? Maybe. Naive? Most likely. Worth considering? I hope so. Let me know.

 
 

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Ten simple rules for doing your best research – according to Richard Hamming

There’s an editorial in PLoS Computational Biology presenting condensed thoughts on “first-class research” of mathematician Richard Hamming. It is based on a transcript of a brilliant talk given by Hamming in 1986 at the Bell Communications Research Colloquium Seminar. Definitely a must-read.

clipped from compbiol.plosjournals.org
Hamming’s 1986 talk was remarkable. In “You and Your Research,” he addressed the question: How can scientists do great research, i.e., Nobel-Prize-type work? His insights were based on more than forty years of research as a pioneer of computer science and telecommunications who had the privilege of interacting with such luminaries as the physicists Richard Feynman, Enrico Fermi, Edward Teller, Robert Oppenheimer, Hans Bethe, and Walter Brattain, with Claude Shannon, “the father of information theory,” and with the statistician John Tukey.

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Posted by on November 6, 2007 in Clipped, Research skills

 

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Publishers, please provide images in the journal’s feed

Currently almost all scientific journals provide a RSS feed of their content. I am very grateful for that, as many other scientists. However, I see a large disproportion between what I would like to scan through and what I’m actually able to. Abstracts, which are usually provided in these feeds, look almost exactly the same, and after thirty or fifty I’m not really sure if I understand what I read (most likely even Robert Scoble would have the same problem, although at a different level). Biochemistry journal found a solution (see below) – providing images instead of abstracts in the feed (in fact, they used this approach on their homepage long before RSS feeds became a standard). It’s simple, very effective and I have no idea at all why it’s not more popular. So here I’m asking – publishers of scientific journals: please give me images in the journal’s feed. I don’t mind having also the abstracts, but visual summary would be much more useful. In return I promise read these feeds instead of relying on Pubmed searches or my colleagues recommendations and GR shared items.

Feed of Biochemistry journal

 
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Posted by on October 23, 2007 in Papers, PubMed, Research skills

 

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