Bio-IT World Asia brings together, life sciences, pharmaceutical, informatics and IT professionals from all over Asia and the rest of the world to one unique location.

The conference is going to showcase the innovative and disruptive technologies in the field of big data processing and analytics, genomics, molecular diagnostics and translational informatics that have a direct or indirect impact on improving the efficiency of clinical research, healthcare delivery and drug discovery.

If you are atteding, you can meet with Madhu to discuss the latest technologies and technieques that we use to process and analyse big data.

Download the event flyer.

About the workshop

A one-day event especially targeted at the bio-based industries and researchers in the plant and food sciences sectors. The key objective is to understand the desired applications and existing barriers for managing, mining and utilising sequence data sets and in particular, from next-generation sequencing (NGS). An improved understanding of the challenges facing these industries will inform bioInformatics service providers on how best to adapt and/or develop new tools to facilitate the profitable exploitation of sequencing information from plants. The workshop sets out to prepare a framework to achieve the goal whilst also capitalising on publicly available resources.

Target Audience

The target audience is industry (plant breeders and processors), academia (plant scientists, biomedical researchers and computational systems biologists), public sector research institutes (plant science/agriculture – e.g. Rothamsted/ John Innes Centre/ John Hutton Institute) and policy/funding sector (BBSRC/TSB).

Networking

The event provides networking opportunities for delegates to make new business and research contacts. Eligible small to medium size business clients will have the chance to sign up and take advantage of the free NIAB Innovation Farm SME business assistance programme. Eagle staff will be on hand to engage with clients requiring bespoke one-to-one bioinformatics consultation services.

Full details are available here or download the event flyer.

The research from Eagle, the specialist in bioinformatics service solutions, and the Pistoia Alliance, a not-for-profit, precompetitive alliance of companies and organisations engaged in lowering the barriers to innovation in life science R&D shows how using a dynamic leaderboard to monitor progress in a competition, actively stimulates participants to strive harder for success.

In 2012, the Pistoia Alliance launched its “Sequence Squeeze” competition to encourage the development of novel and enhanced data compression algorithms to improve the management of the large volumes of gene sequence data coming from NGS machines.

The Pistoia Alliance partnered with Eagle to organise the event, set up the supporting infrastructure, and manage the process of receiving and judging entries.

Nick Lynch from Pistoia Alliance, and co-author of the paper, said:  “The Pistoia Alliance is keen to encourage pre-competitive collaboration to drive innovation and so we were very pleased not only with the output from the Sequence Squeeze competition itself, but also how the leaderboard worked to foster constructive competition between our contributors. We hope that this model can be adopted more widely as this experiment clearly shows the benefits of such an approach.”

Richard Holland, Chief Business Officer of Eagle and first author of the paper, added: “We were very pleased to be involved in the Sequence Squeeze competition. While the life sciences industry has made huge steps in sequencing many new genomes, the sheer amount of data we are now producing has created incredible challenges. However, through initiatives such as this, we can develop effective tools to help manage the flood of data we are now creating.”

The end result of the contest was a set of brand new compression algorithms for next-generation sequencing data, all of which are fully open-source and available for the community to use and build upon with their own ideas. This open-source requirement ensures that everyone may benefit from this open innovation, and the data compression lessons learnt in the process can be shared with everyone.

The paper can be downloaded at http://www.gigasciencejournal.com/content/2/1/5/abstract

Personally I have to wonder what this does for the quality of the science. There is no question about the BGI's ability to perform huge sequencing experiments and churn out new genomes daily with all the requisite papers and analyses, but this is production-line science. Training junior staff to turn the handle and crank out data is relatively straightforward but how much depth is there to their understanding of the results produced or the biological implications of making various decisions about quality cutoffs or parameter configurations? They certainly seem to do pretty well on the standard tasks that a production-line approach like this would enable, but what happens when data fails to conform to expectations or an unusual question is asked?

At times like that, there is no substitute for experience. Only someone who has spent a long time in the field (or an occasional rare genius with unusually perceptive insight) will be able to spot the subtle nuances that are causing an experiment to go not quite the way they were expecting. At the very least you would expect to find a person of this level at the head of each individual research group to give the more junior members guidance and advice, but Jun says that at the BGI they have quite a few project team leaders who are only 26 themselves, some in charge of teams of 100 or more.

The article's author suggests that the BGI model is like that of a startup or dotcom company, where the drive and innovation that stems from young, enthusiastic staff carry the company forward quickly. I would add that an over-abundance of cautious, conservative, battle-hardened, experienced staff can prevent the truly innovative ideas from getting off the ground because of aversion to risk. A balance must exist where the ideas are free to flow and risks allowed to be taken, whilst in parallel sensible decisions are made to ensure that the company continues to be able to pay the rent of those whose ideas it depends on.

Jun appears to support this idea, and he is quoted as saying “In the past, people emphasized too much about experience, but forgot about the creative parts, or the strengths of the young scientists. It is also very dangerous to also focus on the young scientists, and you lose all the competence, experience, and intelligence of the senior ones.” But this quote doesn't really support the demographics of his employees – a balanced well-qualified scientific workforce comprising so many thousands of people would have an average age in their 30s at least, if not 40s, but definitely not as low as 23.

What is BGI doing then, to ensure quality of results and service, if they cannot rely on hard-won practical experience to guide their researchers? They are certainly successful in terms of publications and sheer volume of work produced at present, but I have heard on several occasions vague unofficial rumours and mutterings that the quality of the work may not always have been as good as it could. For longer-term sustainability and a steady increase in the quality of its output, the BGI will need to start upping the average age of its scientists a little, taking on staff who have got things wrong enough times in the past to understand better how to get them right every time in future.

BioTrinity is a premier European biopartnering and investment conference held every year. If you are looking to outsource your bioinformatics, David will be happy to discuss the options and see how we can help aid your research.

If you are registered please feel free to send David an invite to arrange a meeting through the event's partnering system. If you haven`t yet registered, you can do so at the BioTrinity website.

David's LinkedIn profile is available here.

Web-Based Services and Software: Biofortis, for Labmatrix Chameleon 5.5

"Labmatrix Chameleon is a research management software system that can integrate clinical, specimen, genetic and molecular assay data, and the full life-cycle of Next Generation Biobanking sample management."

What does this mean? It means data integration; that old chestnut that keeps on popping its head up more and more frequently now that volumes of data are growing and old-fashioned Excel spreadsheets and even traditional relational databases are beginning to struggle under the load. Now I am no expert on biobanking or clinical specimen management, but I do know that data integration tasks are hard and good solutions are rare as hens teeth, so it is nice to see something as good as this one in the market.

It begs the question though – specialist, or generic? The actual under-the-hood algorithms in this product are unlikely to be significantly different to those found in any similar product, in my opinion (not having seen the source code I can't say for certain though!), as data integration is currently an area with just two solution spaces: divide and distribute, or merge and summarise. What makes the difference between one tool and the next is how good the user interface is, i.e. can the end-user who needs to work with the system on a daily basis find what they need to find and not have to learn some convoluted procedure to get at their own data. This is where the specialist tools have the advantage over generic ones – and Labmatrix Chameleon certainly does well in the UI space.

Informatics Tools and Data: Seven Bridges Genomics, for the IGOR platform

"The IGOR Platform is a cloud based platform run on Amazon Web Services that allows researchers from any technical background to run, customize, and share peer-reviewed pipelines and tools, including sophisticated tools like BWA+GATK for whole genome analysis and TopHat+CuffDiff for RNA-seq analysis."

IGOR has one brilliant feature – its user interface. I have not seen anything before that comes close to IGOR in cleanliness, usability, and functionality. Technical knowledge is still required to be able to take full advantage of the pipeline design tools, but to the end-user biologist IGOR makes it easy to put together basic analysis pipelines and execute pre-defined ones over their datasets. Pipeline platforms are a dime a dozen these days, as was demonstrated by the multitude on display in the Bio-IT exhibition hall, but few can match IGOR for its UI design.

Do we need another pipeline platform? Not sure. Given that so many are on offer now, there need to be real differences between them in order for the market to develop and mature. The ones that are too similar will most likely merge or fade, leaving the niche offerings to expand and become the dominant players. A split between interface and engine would also be nice – at present everyone has to reinvent both, which is a bit of wasted effort. There is also now a huge market for people to develop apps or plugins to run on all these various platforms – so that no matter which platform wins, the app developer stays in business. I suspect therefore that IGOR is a great tool in its own way, but the killer pipeline platform is yet to be seen.

IT Infrastructure and Hardware: Bright Computing, for the Bright Cluster Manager 6.0

"Bright’s cluster manager is a tool for provisioning, scheduling, monitoring and managing servers—either in the cloud or on-premise—and allowing users to move between the two locations dynamically according to need."

The idea of moving servers and data seamlessly from local data centre to a cloud location, and back again, seems magical. It would truly enable burst deployment to cope with peaks in demand, and it would greatly improve migration paths as data centres slowly depreciate and servers are moved into the cloud a rack at a time until eventually the entire system is virtual.

How is it done though? You have to make sure first of all that all the cloud options you have chosen are intercompatible without requiring any software changes. This is not as easy as it sounds – each provider has its own API or standards, hardly any of which are compatible with the competition. Therefore you are likely to need to restrict yourself to planning ahead on just one or two selected cloud providers, and who's to say which ones will be the best choice 5 or 10 years from now when the hype has passed? Bright attempts to handle this by disguising the differences behind their own toolkit, but you still have to implement or reengineer this toolkit into your existing servers and filesystems in order to be able to make them moveable. 

As with many cloud projects, this technology works brilliantly for a blank sheet – where a project is being built from the ground up and can follow the design specs and requirements of the software toolkits and hardware infrastructure being used. It works far less well as a retrofitted product to be applied to existing systems. Now if someone could solve that latter problem then I would be properly impressed.

Clinical Trials: ePharmaSolutions, for PatientLive

"PatientLive is a geo-therapeutic matching algorithm that links patients who disqualify from one study with other studies for which they are better suited. The system then refers prequalified patients to the closest study and remaining patients can register to receive new study alerts. More than 20 major pharmaceutical companies and CROs have agreed to pilot the program and “share” patients."

Clinical trials is not my specialist area, but my naive point of view is that it must be pretty hard to recruit sufficient patients for a trial and mighty frustrating when you fail to gather enough together that present the correct phenotype. If a patient is turned down for a trial they've applied for, I assume this means it is less likely they'll apply for another trial in future because of the 'disappointment' factor (or am I assuming too much here?). Therefore to find a way to rescue the non-selected patients and offer them alternative trials must save the trial organisers a lot of time and hassle by offering a shortcut to at least part of their recruitment, and it makes the volunteers taking part in the trial feel more wanted and more likely to continue volunteering for future trials.

PatientLive seems like a great thing then – it scans through a database of all trial volunteers past and present and matches them up against all current trial requirements. Data protection and privacy requirements permitting they can then be contacted to see if they want to take part, rather than waiting for them to volunteer themselves. The flaw in the plan though, from what my colleagues tell me, is that human psychology just doesn't work this way when it comes to trial participation, and also the way in which existing cohorts have been recruited historically leave the users of a system like this with a very limited self-selecting pool of patients who are not particularly diverse in their phenotypes.

This type of tool will come into its own only when a better way is found to recruit a more diverse base of volunteers in the first place. Until then, I feel it is a great effort but is limited not by its own features but by the very nature of clinical trials as currently practiced!

All in all then, an interesting selection of winners. One thing was very clear this year though and that was the categories themselves need a serious revamp! Web-based software and services are so ubiquitous now that it seems silly to attempt to separate them from the informatics tools and data category, and the IT infrastructure and hardware category sees so little actual hardware activity these days that it might better be repurposed as data centre management tools. It is encouraging that the organisers of Bio-IT already acknowledge this and are actively seeking suggestions for new categories for 2014. I'm sure they'd love to hear from you! (If you'd like to leave your thoughts in the comments below, I'll make sure to pass them on.)

The Open PHACTS consortium's aim is to reduce the barriers to drug discovery in industry, academia and for small businesses by building the Open PHACTS Discovery Platform. This will be freely available, integrating pharmacological data from a variety of information resources and providing tools and services to question this integrated data to support pharmacological research. More info about the Open PHACTS Consortium is available here.

Other speakers will be from F-star, Epigenetics, Nuclear Dynamics, BBT and other Babraham Campus tenants.

Madeleine had telephone interviews with four delegates of the Symposium on their experience at the meeting and their ideas of the future of genome sequencing and bioinformatics, and her podcast makes for fascinating listening. The interviewed delegates were:

• John Wise, Executive Director at Pistoia Alliance
• Alex Gutteridge, Principle Scientist at Pfizer
• Xose Fernandes, Bioinformatics Consultant at Life Technologies
• Richard Holland, CBO Eagle

The podcast is available here.