LEADER 00915nam a2200277 i 4500 001 991001507059707536 005 20020502180621.0 008 950105s1985 it ||| | ita 020 $a8840234381 035 $ab10858829-39ule_inst 035 $aLE02370332$9ExL 040 $aDip.to Studi Storici$bita 082 0 $a746.3 100 1 $aGabetti, Margherita$0537379 245 10$aArazzi :$brinascimento e barocco /$cdi Margherita Gabetti 260 $aNovara :$bDe Agostini,$c1985 300 $a80 p. :$bill. ;$c25 cm. 490 0 $aDocumenti d'antiquariato 650 4$aArazzi 650 4$aTessuti d'arte 907 $a.b10858829$b23-02-17$c28-06-02 912 $a991001507059707536 945 $aLE023 746.3 GAB 1 1$g1$i2023000017593$lle023$o-$pE0.00$q-$rl$s- $t0$u1$v0$w1$x0$y.i1096874x$z28-06-02 996 $aArazzi$9918145 997 $aUNISALENTO 998 $ale023$b01-01-95$cm$da $e-$fita$git $h0$i1 LEADER 03696nam 22005895 450 001 9910513590203321 005 20251113192645.0 010 $a3-030-91241-8 024 7 $a10.1007/978-3-030-91241-3 035 $a(MiAaPQ)EBC6825378 035 $a(Au-PeEL)EBL6825378 035 $a(CKB)20120242300041 035 $a(PPN)259384836 035 $a(OCoLC)1289370194 035 $a(DE-He213)978-3-030-91241-3 035 $a(EXLCZ)9920120242300041 100 $a20211211d2021 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aMathematical and Computational Oncology $eThird International Symposium, ISMCO 2021, Virtual Event, October 11?13, 2021, Proceedings /$fedited by George Bebis, Terry Gaasterland, Mamoru Kato, Mohammad Kohandel, Kathleen Wilkie 205 $a1st ed. 2021. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2021. 215 $a1 online resource (91 pages) 225 1 $aLecture Notes in Bioinformatics,$x2366-6331 ;$v13060 311 08$aPrint version: Bebis, George Mathematical and Computational Oncology Cham : Springer International Publishing AG,c2022 9783030912406 327 $aStatistical and Machine Learning Methods for Cancer Research Image Classification of Skin Cancer: Using Deep Learning as a Tool for Skin Self-Examinations -- Predictive Signatures for Lung Adenocarcinoma Prognostic Trajectory by Omics Data Integration and Ensemble Learning -- The Role of Hydrophobicity in Peptide-MHC Binding -- Spatio-temporal tumor modeling and simulation Simulating cytotoxic T-lymphocyte & cancer cells interactions : An LSTM-based approach to surrogate an agent-based model -- General cancer computational biology Strategies to reduce long-term drug resistance by considering effects of differential selective treatments -- Mathematical Modeling for Cancer Research Improved Geometric Configuration for the Bladder Cancer BCG-based Immunotherapy Treatment Model -- Computational methods for anticancer drug development Run for your life ? an integrated virtual tissue platform for incorporating exercise oncology into immunotherapy. 330 $aThis book constitutes the refereed proceedings of the Third International Symposium on Mathematical and Computational Oncology, ISMCO 2021, held in October 2021. Due to COVID-19 pandemic the conference was held virtually. The 3 full papers and 4 short papers presented were carefully reviewed and selected from 20 submissions. The papers are organized in topical sections named: statistical and machine learning methods for cancer research; mathematical modeling for cancer research; spatio-temporal tumor modeling and simulation; general cancer computational biology; mathematical modeling for cancer research; computational methods for anticancer drug development. 410 0$aLecture Notes in Bioinformatics,$x2366-6331 ;$v13060 606 $aComputer vision 606 $aComputer engineering 606 $aComputer networks 606 $aComputer Vision 606 $aComputer Engineering and Networks 606 $aComputer Engineering and Networks 615 0$aComputer vision. 615 0$aComputer engineering. 615 0$aComputer networks. 615 14$aComputer Vision. 615 24$aComputer Engineering and Networks. 615 24$aComputer Engineering and Networks. 676 $a572.80285 702 $aBebis$b George 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910513590203321 996 $aMathematical and computational oncology$92169006 997 $aUNINA