Introduction Ab-Initio Modelling Obtaining Models Postprocessing Models DAMMIF Update Get the latest version of DAMMIF together with the latest release of ATSAS! ATSAS 2.5.0 will be available soon! http://www.embl-hamburg.de/biosaxs/download.html Daniel Franke — Ab-Initio Modelling 1/35
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Ab initio modelling: DAMMIN and DAMMIF - EMBL Hamburg
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Acts as a placeholder for, but does not resemble, areal atomOccupies a known position in spaceHas a known scattering patternMay either contribute to the solvent or the particle
An estimate on the problem’s size.The Universe is not enough
A search volume of 2000 dummy atoms has
22000 ≈ 10600
possible conformations, i.e. scattering curves.
On 40.000.000 conformations per hour per CPU, 1000CPUs, 24 hours a day, 365 days a year one would spendthe next couple of universes’ time on enumerating allscattering curves!
A valid conformation is ...connected: particle beads must beinterconnectedtightly packed: particle beads shallbe tightly packed, avoid loosestrandscentered: assemble the particlewithin the search volume, avoidboundary contactin right shape: oblate or prolateshapes can be enforced
Step Step numberT Temperature, artificalp/a Number of particle beads of all beadsSucc Number of successfull iterations at current TEval Accumulated number of iterationsCPU Accumulated runtime
Rf Goodness of Fit, data onlyLos Contribution of Looseness PenaltyDis Contribution of Disconnectivity PenaltyPer Contribution of Periphal PenaltyAni Contribution of Anisometry PenaltyFit Goodness of Fit, data and penalties
Please contact your system administrator for details ofyour cluster and how to submit jobs.
Important: as processes are being run in parallel, multiplemay be started at the same time – with the same randomseed – resulting in exactly the same model.
Make sure to redefine the random seed for each run!
With multiple models:find those that are most similar(uniqueness of reconstruction is not guaranteed) ORgroup models into clusterssuperimpose and average the selectionrestart fitting process using the averaged model
SUPCOMB: superimpose any two models(principle axis alignment, gradient minimization, localgrid search)DAMSUP: superimpose multiple models on areference using SUPCOMB.
DAMAVER: Creates a bead probability density mapwithin the search volume.DAMFILT: Generates the averaged model, using auser-defined probability threshold. Will give a validmodel, violating the threshold if necessary.
take the model(s) that have the least NSD to allothers – this fits the datatake the filtered model(s) – but this will not fit the datause averaged model(s) and restart DAMMIN to fit theexperimental data (via DAMSTART)
take the model(s) that have the least NSD to allothers – this fits the datatake the filtered model(s) – but this will not fit the datause averaged model(s) and restart DAMMIN to fit theexperimental data (via DAMSTART)
take the model(s) that have the least NSD to allothers – this fits the datatake the filtered model(s) – but this will not fit the datause averaged model(s) and restart DAMMIN to fit theexperimental data (via DAMSTART)