LEADER 01187nam0 22002771i 450 001 UON00077226 005 20231205102415.756 100 $a20020107d1926 |0itac50 ba 101 $aeng 102 $aGB 105 $a|||| ||||| 200 1 $aPeople of the veil$eBeing an account of the habits, organisation and history of the wandering Tuareg tribes which inhabit the mountains of air or Asben in the Central Sahara$fby Francis Rennell Rodd 210 $aLondon$cMacmillan and co.$d1926 215 $axv, 504 p., c. di tav.$cill.$d26 cm 316 $adata inesatta$5IT-UONSI B Afr4/0210 606 $aTUAREG$3UONC018257$2FI 620 $aGB$dLondon$3UONL003044 676 $a306.089933$cETNOLOGIA - Tuareg$v21 700 1$aRODD$bFrancis Rennell$3UONV050650$0660444 712 $aMacmillan & Co.$3UONV247335$4650 801 $aIT$bSOL$c20240220$gRICA 899 $aSIBA - SISTEMA BIBLIOTECARIO DI ATENEO$2UONSI 912 $aUON00077226 950 $aSIBA - SISTEMA BIBLIOTECARIO DI ATENEO$dSI B Afr 4 0210 $eSI MR 132 7 0210 data inesatta 996 $aPeople of the veil$91299792 997 $aUNIOR LEADER 03774nam 22006615 450 001 9910299775603321 005 20200704120952.0 010 $a3-319-16065-6 024 7 $a10.1007/978-3-319-16065-8 035 $a(CKB)3710000000434400 035 $a(EBL)2096172 035 $a(SSID)ssj0001524817 035 $a(PQKBManifestationID)11869177 035 $a(PQKBTitleCode)TC0001524817 035 $a(PQKBWorkID)11484924 035 $a(PQKB)10067254 035 $a(DE-He213)978-3-319-16065-8 035 $a(MiAaPQ)EBC2096172 035 $a(PPN)186399030 035 $a(EXLCZ)993710000000434400 100 $a20150620d2015 u| 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 10$aBranching Process Models of Cancer /$fby Richard Durrett 205 $a1st ed. 2015. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2015. 215 $a1 online resource (73 p.) 225 1 $aStochastics in Biological Systems,$x2364-2297 ;$v1.1 300 $aDescription based upon print version of record. 311 $a3-319-16064-8 320 $aIncludes bibliographical references. 327 $aMultistage Theory of Cancer -- Mathematical Overview -- Branching Process Results -- Time for Z_0 to Reach Size M -- Time Until the First Type 1 -- Mutation Before Detection? -- Accumulation of Neutral Mutations -- Properties of the Gamma Function -- Growth of Z_1(t) -- Movements of Z_1(t) -- Luria-Delbruck Distributions -- Number of Type 1's at Time T_M -- Gwoth of Z_k(t) -- Transitions Between Waves -- Time to the First Type \tau_k, k \ge 2 -- Application: Metastasis -- Application: Ovarian Cancer -- Application: Intratumor Heterogeneity. 330 $aThis volume develops results on continuous time branching processes and applies them to study rate of tumor growth, extending classic work on the Luria-Delbruck distribution. As a consequence, the authors calculate the probability that mutations that confer resistance to treatment are present at detection and quantify the extent of tumor heterogeneity. As applications, the authors evaluate ovarian cancer screening strategies and give rigorous proofs for results of Heano and Michor concerning tumor metastasis. These notes should be accessible to students who are familiar with Poisson processes and continuous time. Richard Durrett is mathematics professor at Duke University, USA. He is the author of 8 books, over 200 journal articles, and has supervised more than 40 Ph.D. students. Most of his current research concerns the applications of probability to biology: ecology, genetics, and most recently cancer. 410 0$aStochastics in Biological Systems,$x2364-2297 ;$v1.1 606 $aProbabilities 606 $aBiomathematics 606 $aCancer$xResearch 606 $aProbability Theory and Stochastic Processes$3https://scigraph.springernature.com/ontologies/product-market-codes/M27004 606 $aMathematical and Computational Biology$3https://scigraph.springernature.com/ontologies/product-market-codes/M31000 606 $aCancer Research$3https://scigraph.springernature.com/ontologies/product-market-codes/B11001 615 0$aProbabilities. 615 0$aBiomathematics. 615 0$aCancer$xResearch. 615 14$aProbability Theory and Stochastic Processes. 615 24$aMathematical and Computational Biology. 615 24$aCancer Research. 676 $a614.5999 700 $aDurrett$b Richard$4aut$4http://id.loc.gov/vocabulary/relators/aut$055577 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910299775603321 996 $aBranching process models of cancer$91522586 997 $aUNINA