12 research outputs found
MODELING OF POLLUTANT ADSORPTION ON NOVEL MODIFIED BIOMASS AS A MEANS OF SEAWATER DECONTAMINATION
Electronic system of the RPC Muon Trigger in CMS experiment at LHC accelerator (Elektroniczny system trygera mionowego RPC w eksperymencie CMS akceleratora LHC
This paper presents implementation of distributed, multichannel electronic measurement system for RPC - based Muon Trigger in the CMS experiment at LHC. The introduction shortly describes the research aims of LHC and shows the metrological requirements for CMS - good spatial and time resolution, and possibility to estimate multiple physical parameters from registered collisions of particles. Further the paper describes RPC Muon Trigger consisting of 200 000 independent channels for position measurement. The first part of the paper presents the functional structure of the system in the context of requirements put by the CMS experiment, like global triggering system and data acquisition. The second part describes the hardware solutions used in particular parts of the RPC detector measuremnt system and shows some test results. The paper has a digest and overview nature
In silico structural study of random amino acid sequence proteins not present in nature
The three-dimensional structures of a set of 'never born proteins' (NBP, random amino acid sequence proteins with no significant homology with known proteins) were predicted using two methods: Rosetta and the one based on the 'fuzzy-oil-drop' (FOD) model. More than 3000 different random amino acid sequences have been generated, filtered against the non redundant protein sequence data base, to remove sequences with significant homology with known proteins, and subjected to three-dimensional structure prediction. Comparison between Rosetta and FOD predictions allowed to select the ten top (highest structural similarity) and the ten bottom (the lowest structural similarity) structures from the ranking list organized according to the RMS-D value. The selected structures were taken for detailed analysis to define the scale of structural accordance and discrepancy between the two methods. The structural similarity measurements revealed discrepancies between structures generated on the basis of the two methods. Their potential biological function appeared to be quite different as well. The ten bottom structures appeared to be 'unfoldable' for the FOD model. Some aspects of the general characteristics of the NBPs are also discussed. The calculations were performed on the EUChinaGRID grid platform to test the performance of this infrastructure for massive protein structure predictions. © 2009 Verlag Helvetica Chimica Acta AG.
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In silico structural study of random amino acid sequence proteins not present in nature
none13The three-dimensional structures of a set of 'never born proteins' (NBP, random amino acid sequence proteins with no significant homology with known proteins) were predicted using two methods: Rosetta and the one based on the 'fuzzy-oil-drop' (FOD) model. More than 3000 different random amino acid sequences have been generated, filtered against the non redundant protein sequence data base, to remove sequences with significant homology with known proteins, and subjected to three-dimensional structure prediction. Comparison between Rosetta and FOD predictions allowed to select the ten top (highest structural similarity) and the ten bottom (the lowest structural similarity) structures from the ranking list organized according to the RMS-D value. The selected structures were taken for detailed analysis to define the scale of structural accordance and discrepancy between the two methods. The structural similarity measurements revealed discrepancies between structures generated on the basis of the two methods. Their potential biological function appeared to be quite different as well. The ten bottom structures appeared to be 'unfoldable' for the FOD model. Some aspects of the general characteristics of the NBPs are also discussed. The calculations were performed on the EUChinaGRID grid platform to test the performance of this infrastructure for massive protein structure predictions. © 2009 Verlag Helvetica Chimica Acta AG.nonePrymula K.; Piwowar M.; Kochanczyk M.; Flis L.; Malawski M.; Szepieniec T.; Evangelista G.; Minervini G.; Polticelli F.; Wisniowski Z.; Salapa K.; Matczynska E.; Roterman I.Prymula, K.; Piwowar, M.; Kochanczyk, M.; Flis, L.; Malawski, M.; Szepieniec, T.; Evangelista, G.; Minervini, G.; Polticelli, F.; Wisniowski, Z.; Salapa, K.; Matczynska, E.; Roterman, I