000108640 001__ 108640
000108640 005__ 20211216104750.0
000108640 037__ $$aTAZ-TFM-2021-625
000108640 041__ $$aeng
000108640 1001_ $$aLuna Cerralbo, David
000108640 24200 $$aApplication of a statistical inference model to the prediction of antibody affinity from sequence analisys.
000108640 24500 $$aAplicación de un modelo de inferencia estadística para la predicción de la afinidad de anticuerpos a partir del análisis de secuencias.
000108640 260__ $$aZaragoza$$bUniversidad de Zaragoza$$c2021
000108640 506__ $$aby-nc-sa$$bCreative Commons$$c3.0$$uhttp://creativecommons.org/licenses/by-nc-sa/3.0/
000108640 520__ $$aIn this project, the aim is to improve the scoring function described in Asti L et al (2016) by taking a more realistic a priori distribution and reinterpreting the germline and the hypermutated clusters as clusters linked by a temporal evolution, instead of as independent ones. This evolution will be modeled following an Ornstein-Uhlenbeck process, from which we extract the links between the two clusters and the attractors of the dynamic process. <br /><br />
000108640 521__ $$aMáster Universitario en Biotecnología Cuantitativa
000108640 540__ $$aDerechos regulados por licencia Creative Commons
000108640 700__ $$aBruscolini, Pierpaolo$$edir.
000108640 700__ $$aPérez Gaviro, Sergio$$edir.
000108640 7102_ $$aUniversidad de Zaragoza$$bFísica Teórica$$cFísica Teórica
000108640 8560_ $$f736195@unizar.es
000108640 8564_ $$s1573517$$uhttps://zaguan.unizar.es/record/108640/files/TAZ-TFM-2021-625.pdf$$yMemoria (eng)
000108640 8564_ $$s262977$$uhttps://zaguan.unizar.es/record/108640/files/TAZ-TFM-2021-625_ANE.pdf$$yAnexos (eng)
000108640 909CO $$ooai:zaguan.unizar.es:108640$$pdriver$$ptrabajos-fin-master
000108640 950__ $$a
000108640 951__ $$adeposita:2021-12-16
000108640 980__ $$aTAZ$$bTFM$$cCIEN
000108640 999__ $$a20210628231611.CREATION_DATE