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Executive summary

revised: 12-Dec-02
Copyright  © 2001, 2002 BioinfoTools.com

BioinfoTools aims to produce bioinformatics tools with three overall aims:

1. Shift the emphasis of the bioinformatics development from "how" to "what",

2. Provide general-purpose "engines" to aid developing bioinformatics tools,

3. Provide advanced methods for protein sequence & structure analysis.

These three aims are outlined in more detail in the sections that follow. An important element of the first two aims is to assist users to develop their own bioinformatics strategies, allowing them to focus on what they want from bioinformatics rather than being locked into a fixed list of capacities defined by the software. As all these aims are met by the bioinformatics software industry, these are likely to lead to a changing of the "position" of bioinformatics within companies. (This may be explored in an up-coming Ruminations column.)

Dr. Jacobs founded BioinfoTools as a vehicle for independent bioinformatics software development to exploit his more than a decade of experience in bioinformatics to produce the software tools he feels the field badly needs. In addition, Dr. Jacobs is open to requests for contract software development and consulting within his areas of expertise, as discussed in the FAQ on this topic.

 

Shifting the emphasis of the bioinformatics development from "how" to "what"

Bioinformatics in a biological research environment presents something of a contradictory problem. We'd all like to do exactly the bioinformatics science we have in mind. But if we really were to do that we'd likely have to write all of the software ourselves. Writing software in-house is time-consuming and costly, even though we would get a product tailored to our particular needs.

It could be more time- and cost-effective to purchase a software package written by a bioinformatics specialist. However, we immediately become locked into the specific capabilities of their software - what particular list of tasks it can do - and how to persuade it to do what we wish to using that list of tasks. "Ready-made" bioinformatics tools tend to present a fixed suite of generally slightly out of date methods rather than a system which companies can use to build up their own bioinformatics strategy, thus meeting their particular needs and thus strengthening their particular niche.

Every company is different and wishes to differentiate themselves from their competitors. Its hard to differentiate your bioinformatics effort from rivals if you use nothing but "standard" tools.

A two-part solution is to use commercial packages for core, standardized, protocols and specialist bioinformatics development tools like those BioinfoTools is creating to develop your unique in-house methodology.

What makes in-house bioinformatics unique in most cases, is processing in-house-generated data, which is either unique to the company or being applied in a unique way or to a unique problem.

What is required are tools which allow staff to easily manipulate their data, allowing them to focus on what bioinformatics they want done, rather than how to implement the processes or methods needed to do that bioinformatics.

Were they available, tools of this nature would conveniently solve another problem for employers: hiring staff who have expertise in both the company's area of biology and computer science.

Biologists know, at least in outline, what they would like to learn from raw biological data. In the next level "down" experienced bioinformatics scientists know what general strategies should be applied to generate this knowledge from the data. This level requires a knowledge of the design principles of (or theoretical underpinnings if you like) of bioinformatics methods, but not the computer science-based skills to implement them. Ideally, this is the level that companies should be ideally focused on and that as much as is possible they should purchase ready-made tools to cover the actual implementation.

BioinfoTools is using computer science techniques to develop advanced approaches to calculating these core functions and storing biological data. Clients will not need to know the internal methods used to make these functions work, which may be quite complex. Clients need only know how to ask the engine(s) to perform the functions they are interested in.

Using these tools, in-house developers in research institutes will be able to call up pre-built components and processes rather than implement these themselves. This will enable bioinformatics staff to focus more on what they want to happen to their data (ie. the biology), rather than the technical specifics of implementing some clever algorithm.

One can argue that software tools like this will alter the structure of research companies, relieving much of the present strain of recruiting bioinformatics staff by capturing many of the technical aspects of bioinformatics development into pre-made tools. Details of his argument will later be presented as an article in the ruminations column. The essential conclusion of this argument is that as the bioinformatics software development market matures, there will be better bioinformatics software development tools. This, in turn, will reduce the need to hire staff with both strong biological science and computer science skills. Instead, most of the bioinformatics can be done by staff with good biological backgrounds and modest programming skills. Implementation will be left in the hands of specialised companies skilled in this. Idealistically, the development tools will evolve to the extent that little if any programming skill is needed. This should be accompanied by an increase in productivity of the in-house software development staff.

Bioinfotools will develop on top of its own core methods advanced algorithms in specific areas of protein sequence, structure and evolutionary analysis. These areas — based on Dr. Jacobs previous research expertise — are those highlighted on the home page:

In addition to being products in their own right, These "higher-level" products will serve as a means of thoroughly testing the underlying core methods by actively using the bioinformatics development approach developed.



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