Samuel Lampa

Samuel Lampa
Uppsala University | UU · Department of Pharmaceutical Biosciences



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Newly graduated PhD alumnus from the Pharmaceutical Bioinformatics group ( at Dept. of Pharmaceutical Biosciences, Uppsala University, where I have been researching the handling of large and complex data and processing in pharmaceutical biosciences using approaches such as scientific workflow management systems, HPC and cloud computing, as well as semantic technologies, especially for querying and data integration.
Additional affiliations
July 2014 - September 2018
Uppsala University
  • PhD Student
  • Information about and link to thesis:
September 2004 - May 2010
Uppsala University
Field of study
  • Molecular Biotechnology Engineering


Questions (3)
I'm wondering whether, in the central dogma of DNA-[transcription]->RNA-[translation]->Protein process in Biology, whether it happens in such a way, in any organism, that the translation to a protein of a specific mRNA strand starts before its transcription is finished?
That is, that the mRNA strand is simultaneously connected to the trasncription, and the translation machinery (on each side of the nucleus wall, I assume)?
I was wondering if anyone is using the Java based library for doing molecular biology simulations, and if so, what are your experiences with it? E.g, what is its strengths / weaknesses compared to other simulations techniques?
What is a suitable ABM framework for learning? That is, something where you can quickly get up to speed and play around with it, to get a feel for how ABM works.
It has to be suited for biological simulations, since that is what I would like to use it for in the end.
I have seen about Flame, Breve, Spade, MASON, Swarm etc, but it is hard to know in beforehand what it is like to work in the respective tools, what is the learning curve etc.


Cited By


Projects (3)
Archived project
Archived project
Enabling full import of RDF datasets consisting of plain triples (not requiring any ontologies). This is supposed to enable full round-trip between Semantic MediaWiki and the wider Semantic Web, thus enabling to leverage the powerful and flexible data authoring, curation and visualization abilities in Semantic MediaWiki, also for RDF datasets in general.
The goal is to enable agile workflow design, by being able to build up a component library of re-usable analysis components that can be connected together ad-hoc into workflows that support dynamic scheduling, to enable highly complex machine learning workflows in Drug Discovery.