below. On Jul 12, 2011, at 12:21 PM, Benjamin SCHWARZ wrote:
> Hi Keren, > > and many thanks for such a fast answer. > >> The user does not need to infer connected regions. This is done by the program. > Oops… Seems like I missed something here, I'll dig into it. > And great if the program does it on his own. > >>> b) Interactomics data : I have the feeling no interaction data are considered in the process (I mean informations such as "ARC2 in known to interact with ARP2"). Is that true ? >> At least in the new version all interaction data is definitely being considered. The old version was before interaction data was part of MultiFit. > OK, so It wasn't something I missed here. > >>> c) I don't understand what run_multifit() exactly does. More precisely : >>> 1. it appears a preliminary filter is performed on configurations. By configuration I mean the attribution of each subunit to one and only one region (I think it corresponds to a mapping, in the code). If this is the case, I don't think it is performed based on interactomics data, so what is it based upon ? >>> 2. I have the feeling one and only one solution is output (the best score) per retained configuration. Am I right ? >> run_multifit tests all possible configurations according to the sampled ones. > I am not sure I understand that well… So, just for a confirmation : in the tutorial there are 7 subunits, hence 7!, that is ~5000 possible configurations. > Do you mean all 5000 configurations are tested and the solution with the best score extracted ? > ...Unless a first test is achieved to check for each subunit what regions are populated or deserted by the 30 pre-fitted solutions ? Many configurations are removed initially because there are too many overlaps. This is done better in the new versions using the updated domino code. > >>> d) Am I correct to say the cross correlation computations are only used in scoring (step 3), and not in pre fitting of subunits (step 2) ? Hence, if I am correct, the fft based cross correlation approach has been replaced by the neural/gmm approach for that particular step ? >> FFT based fitting was a new addition following the point based matching used in the version we use. We allow for both options depending on the complexity and resolution of the complex you have. > Just great ! > > --Ben > _______________________________________________ > IMP-users mailing list > IMP-users@salilab.org > https://salilab.org/mailman/listinfo/imp-users