Target : Biologists, Students, IT lab strategist
- Biologist must :
- know key concepts and “how to” of IT
- develop some skills to:
- act in autonomy at basic et advanced level
- precisely express its needs to a specialist
- Support is essential
Is everyone $\lambda$-Biologist?
Lambda refers to functional programming language based on $\lambda$-calculus. Shortly it’s a mathematical formalization allowing expression of complex functions based on combination of simpler basics functions.
Recursivity and stability are central in this approach.
These two notions are present in Life Sciences and Biologists are used to empirically pratise forms of $\lambda$-process.
Biologist’s toolkit extension
Progress adaptation and innovation integration have to maximized for an optimized research practise.
IT has to be seens as a new technical layer to be handled and to be interfaced with others.
Its integration can be seamlessly realized because the Biologist is used to handle innovation, new tools and concepts developped in neighboring disciplines
Where and what to do?
It’s necessary to acquire knowledge basis of IT ecosystems to better answer needs. Information seeking would be quicker and more efficient.
A good start could follow these suggestions:
|Field of interest||Topics|
|Hardware & Software||Operation logic and interaction
|Communication||Networks standards and fields of application
Principles client-server / API / P2P
Implementation of simple examples
|Development||Simple development environment
Integrated development tools
Versioning and cloud extensions
“Framework” : pros / cons / implementation
In practice ?
Below is a simple list that may ease the path:
Even if Windows tends to be be Unixified / Linuxified with PowerShell and terminal intgration, Linux can be adapted to nearly every tasK if combined with good tools
To start accumulating a basic programming culture, good balance between hardware proximity and abstration
Simplicity, productivity, community and projects around this langage
Best for statistics datasets, ML, graphic representations
To exploit databases : extraction, filtering and handling
Algorithm design (sorting by example), complexity study and improvement attempts to get better performances by testing different strategies
Package admin (+++)
Regular expressions (++)
Can get / handle / clean text information
Graphs theory, trees, datamining, text analysis, semantic ontologies, modelling, image manipulation and analysis…. fields are countless
To be challenged (+++)
Know where to get informed
IT is a dynamic, ever evolving technological compound. Beyond basic knowledge, Biologist must be abble to find qualitative information.
Among all availlable information sources, some can be noticed :
- manufacturers provided documentation
- Reference websites directory
- institutions (guidelines)
- specialized DB often providing high quality ressources
- online services compiling and annoting availlable tools (OmicsTool…)
- Specialized communities :
- technical notes acurately introducing methodologies
A step towards bioinformatics…
Access data, sorting data, computing data according to specific needs, interacting and maybe generating some new data… this is basically the daily mission of the Bioinformatician where Biologist must include its own activities.
Quickly, its missions are involved in skill fields related to :
- x-omics specialities (genomics, transcriptomics, metabolomics, …)
- system biology
Skills to be master could seem very wide.
However a steep learning curve is possible because of yet acquired fundamentals. It’s often just related to extensions, accessible to motivated non-experts.
Getting a coherent use to cope original aims might be more problematic and could require specialized support.