In World of Bioinformatics QuestTM (WoBQ) having the right character that suits your style is essential. You may think that a hot shot Rubyist is the coolest class to be, but remember that you have to play this character for the next 50 years. In general it's better to be a character that you'll enjoy playing, rather than one that will get you more publications but have less fun with. This page will guide you through all the parts of character generation for WoBQ.
The attributes are the core of your character, they define which class you'll best be able to play, and how you'll level up with that class. Getting the right attributes is therefore critical, and playing to your strength will result in more PapersTM and GrantsTM - the scoring system used in WoBQ.
Code defines the ability to write computer programs. There are many computer languages available in WoBQ, and your coding ability determines how effective your character will be using the language. A high coding ability means that tasks can be quickly achieved, with a small likelyhood of bugs. A low coding ability however means that writing computer code is an arduous activity and won't necessarily end in the expected outcome. A mid range coding ability minimum is import for most career choices as many analyses require a degree of computational automation
The statistics attribute governs the ability to draw quantitative conclusions from numerical data. A lower statistical rating limits the character to using spreadsheets to draw pie charts. A character with a high statistical rating will be at ease with all classical statistics, as well as more difficult tasks such as writing custom clustering algorithms to dissect specific multivariate data sets.
The Presenting/Writing ability controls how well the character is able to articulate their research, whether this is giving a presentation, or writing an article. Well presented and written research is able to reach and attract a wider audience which ultimately results in a higher WoBQ publication score.
This ability determines how well the character is able to focus on the research question and answer it in a context relevant to the current field. A high rating in this results in insightful and timely research, while a low rating lends the character to being distracted by irrelevant details, or starting new research projects before previous ones have been completed.
This determines the ability to work with other researchers on joint projects. A high collaboration rating means that each character will work to their effective skills for the minimum amount of time to produce a focused piece of research. Importantly, a high collaboration rating is useful for influencing co-authors to allow your character first or last authorship.
Once you've selected attributes for your character, you next have to choose their class.
Linux Virtuoso - LV
The Linux virtuoso career path focuses on using open source software and tools, but also taking advantage of the power of the Linux operating system. Using a custom compiled kernel for their 8 core, 4 screen, hardware setup, the LV is running all the latest versions of the biological databases, as well as the latest bleeding edge analysis tools. The LV performs all their research at the command line: vi edited bash scripts chained together using shell pipes.
Early Adopter - EA
Always working on the latest area of research, systems biology, synthetic biology, personal genomics, this hype-wave surfer is riding the momentum of the newest scientific topics. All the EA's scripts are available as web services, which has to be the case since the EA has changed programming language four times in the last three years. As for their data? All available in OWL RDF from their web 2.0 ruby-on-rails blog thingy.
Old School - OS
In some respects, the opposite of the early adopter, the Old School has singled minded determination to ask, then answer important research questions. Blinkered to the change in tools and technologies, the Old School is doing their analysis in Fortran on a Windows 95 Pentium II. Not to be underestimated however, the lack of distraction means that they are totally research focused, which is reflected by a WoBQ publication score multiplier.
Data Miner - DM
The most mysterious of all career paths, the DM is the master of all things numerical and statistical. Their everyday tools are mixed effect regressions, hidden Markov models, and the fearsome growing neural gas algorithm. Able to produce a highly significant trend from a 1000 point random normal-normal distribution, the DM is not short of collaborators. However beware if a DM is in your audience during a talk, lest they curse your findings with heteroscedasticity or non-normality.
Perfect Coder - PC
The perfect coder does exactly as the name implies, produces flawless, bug-free programs. The exemplary use of descriptive variable names, comments, and indentation produces code like poetry, and after a 5 second glance, even your dog knows what the script does. Furthermore, design patterns, third-party libraries, behaviour driven development and logging means that the PC doesn't even know what the word 'bug' means. In short, reading the lisp written by the PC feels like your wedding day and the birth of your first child rolled into one.
Wet lab Bioinformatician - WB
A dry lab scientist, working in wet lab, the WB is the support for all things computational biology in the laboratory. The WB is familiar enough with Perl to create simple scripts, but the real strength of the WB doesn't lay in writing code, but rather in using tools. While most bioinformaticians are familiar, in theory, with how to find a gene of interest, the WB uses these tools day in and day out - the WB puts many to shame on basic bioinformatics. While others have their head in the clouds thinking about theories and algorithms, the WB is getting his hands dirty with real data as it is being produced.
In game character traits
Whilst playing WoBQ, you will find that your character gains traits, all have an effect some good, some bad. Here is a list of the ones you'll encounter early on.
By adopting agile programming techniques, your character improves their ability to write reusable and flexible code, resulting in an increase in their coding ability
This free statistical software language has many useful functions for statistics and data mining, as well as the excellent graphics library. The R proficiency results in an increased statistical attribute.
Nice fonts, and easy to use programs like Keynote and Pages. I'm not on commission, but there's a reason why graphic designers use Apple Macs. Increased presenting/writing attributes for your character.
Having a supervisor for your character that will nurture and guide their talent makes all the difference in their research, resulting in an increased research focus attribute.
Open Notebook Science
Making their research open allows other scientists to get faster access, which in turn spreads your research further. An Open Notebook Scientist has an increased collaboration attribute.
It's difficult to write usable code when your vision is blurry and are nursing a hang over. Eight pints of special brew swiftly followed by a donor kebab results in your character having a decreased coding attribute.
Your character went into biology because they were no good at maths. Now the inability to tell the difference between a Poisson distribution and a wet fish results in a decreased statistics ability.
Why isn't your character writing up their paper? Because they're writing a ridiculous blog post on bioinformatics role playing games - decreased presenting/writing attribute.
Who needs cold, hard ambition when you're off having romantic meals, and kissing at the back of the cinema? Love never got anyone anywhere in science - decreased research focus.
Your character stinks. Worse than that time a skunk died in the air conditioning vent. No one wants to go near them, let alone sit with them and discuss research - penalised collaboration attribute.