LEADER 01033nam0-2200349---450- 001 990008706910403321 005 20090121124356.0 010 $a88-430-1452-8 035 $a000870691 035 $aFED01000870691 035 $a(Aleph)000870691FED01 035 $a000870691 100 $a20080910d2000----km-y0itay50------ba 101 0 $aita 102 $aIT 105 $af-------001yy 200 1 $aSociologia delle forme religiose$eorganizzazioni e culture dalle teorie classiche alle ricerche contemporanee$fRoberto Marchisio 205 $a1. ed. 210 $aRoma$cCarocci$d©2000 215 $a171 p.$ctav.$d21 cm 225 1 $aBiblioteca di testi e studi$v110 320 $aContiene biblio. 610 0 $aReligione$aAspetti sociali 676 $a306.6$v21$zita 700 1$aMarchisio,$bRoberto$079424 801 0$aIT$bUNINA$gRICA$2UNIMARC 901 $aBK 912 $a990008706910403321 952 $a306.6 MAR 2$b3903$fBFS 959 $aBFS 996 $aSociologia delle forme religiose$9718310 997 $aUNINA LEADER 01091nam a2200253 a 4500 001 991003819119707536 008 020 $a9788820403485 035 $ab14392616-39ule_inst 040 $aDip.to di Storia, Societą e Studi sull'Uomo$bita 082 04$a371.2 100 1 $aMossi, Piergiorgio$0552321 245 13$aLa soddisfazione dell'utenza scolastica :$bQUASUS : uno strumento per la sua rilevazione /$cPiergiorgio Mossi, Sergio Salvatore 260 $aMilano :$bAngeli,c2012 300 $a269 p. ;$c23 cm 490 0 $aPsicologia ;$v378 650 4$aScuole$xValutazione [da parte dei] Genitori$zItalia$xIndagini statistiche 700 1 $aSalvatore, Sergio$eauthor$4http://id.loc.gov/vocabulary/relators/aut$0157495 907 $a.b14392616$b02-09-20$c17-06-20 912 $a991003819119707536 945 $aLE023 371.2 MOS 1 1$g1$i2023000186619$lle023$op$pE34.00$q-$rl$s- $t0$u0$v0$w0$x0$y.i15929437$z17-06-20 996 $aSoddisfazione dell'utenza scolastica$91755301 997 $aUNISALENTO 998 $ale023$b17-06-20$cm$da $e-$fita$git $h3$i0 LEADER 03552nam 22007215 450 001 9910502664103321 005 20251107172921.0 010 $a981-16-5351-8 024 7 $a10.1007/978-981-16-5351-3 035 $a(CKB)4100000012025947 035 $a(MiAaPQ)EBC6725067 035 $a(Au-PeEL)EBL6725067 035 $a(OCoLC)1268205818 035 $a(PPN)258058536 035 $a(DE-He213)978-981-16-5351-3 035 $a(EXLCZ)994100000012025947 100 $a20210911d2021 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aChemical Master Equation for Large Biological Networks $eState-space Expansion Methods Using AI /$fby Don Kulasiri, Rahul Kosarwal 205 $a1st ed. 2021. 210 1$aSingapore :$cSpringer Nature Singapore :$cImprint: Springer,$d2021. 215 $a1 online resource (231 pages) 225 1 $aPhysics and Astronomy Series 311 08$a981-16-5350-X 327 $a1. Introduction -- 2. A Review and Challenges in Chemical Master Equation -- 3. Visualizing Markov Process through Graphs and Trees -- 4. Intelligent State Projection -- 5. Comparative Study And Analysis of Methods and Models -- 6. A Large Model Case Study: Solving CME for G1/S Checkpoint Involving the DNA-damage Signal Transduction Pathway -- 7. An Integrated Large Model Case Study: Solving CME for Oxidative Stress Adaptation in the Fungal Pathogen Candida Albicans. 330 $aThis book highlights the theory and practical applications of the chemical master equation (CME) approach for very large biochemical networks, which provides a powerful general framework for model building in a variety of biological networks. The aim of the book is to not only highlight advanced numerical solution methods for the CME, but also reveal their potential by means of practical examples. The case studies presented are mainly from biology; however, the applications from novel methods are discussed comprehensively, underlining the interdisciplinary approach in simulation and the potential of the chemical master equation approach for modelling bionetworks. The book is a valuable guide for researchers, graduate students, and professionals alike. 410 0$aPhysics and Astronomy Series 606 $aMathematical physics 606 $aComputer simulation 606 $aBioinformatics 606 $aBiomathematics 606 $aComputational intelligence 606 $aArtificial intelligence 606 $aComputational Physics and Simulations 606 $aComputational and Systems Biology 606 $aMathematical and Computational Biology 606 $aComputational Intelligence 606 $aArtificial Intelligence 615 0$aMathematical physics. 615 0$aComputer simulation. 615 0$aBioinformatics. 615 0$aBiomathematics. 615 0$aComputational intelligence. 615 0$aArtificial intelligence. 615 14$aComputational Physics and Simulations. 615 24$aComputational and Systems Biology. 615 24$aMathematical and Computational Biology. 615 24$aComputational Intelligence. 615 24$aArtificial Intelligence. 676 $a574.192 700 $aKulasiri$b Don$01065159 702 $aKosarwal$b Rahul 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910502664103321 996 $aChemical Master Equation for Large Biological Networks$92557668 997 $aUNINA