On Thu, Mar 3, 2016 at 6:25 AM, Hernán Morales Durand <hernan.morales@gmail.com> wrote:
Hi Stef,
For bioinformatics research it would be **really** nice to have:
- Tree creation algorithms: UPGMA, WPGMA. - MCMC methods: Metropolis-adjusted Langevin algorithm (MALA and SMMALA), Metropolis-coupled MCMC (MC3) would enable Bayesian inferences and to work with evolution of genes. I cannot tell how important is to have such algorithms implemented in Smalltalk. - Mahalanobis distance for analyzing bacterial plasmids. - Random Forest is used a lot for gene expression, protein-protein interaction predictions, genome-wide association studies, etc . For the argument "let's use FFI for it" please remember many of these methods are extended, like enriched random forest, for research with specialized data.
Can you add enhancement issues in the SciSmalltalk issue tracker : https://github.com/SergeStinckwich/SciSmalltalk/issues in order to keep them in mind ? We are trying to create a pure Smalltalk library, so we try to avoid FFI as much as possible :-)
There are implementations of naive Bayes classifier in NaturalSmalltalk (which could be adapted to SciPharo) http://smalltalkhub.com/#!/~hernan/NaturalSmalltalk
Great, if we can move them to SciSmalltalk.
As a side note I found an interesting history report of SciPy. From the slide 9 onwards:
http://sssslide.com/www.slideshare.net/shoheihido/sci-pyhistory
Presentation shows SciPy history (credited contributors with pictures, very nice!). As you can se they even have a Foundation NumFOCUS for raising money.
For sure, money always help ;-) The only problem at the moment is that the Pharo community is much smaller at the moment than the Python one. Thank you for your help. -- Serge Stinckwich UCBN & UMI UMMISCO 209 (IRD/UPMC) Every DSL ends up being Smalltalk http://www.doesnotunderstand.org/