| LDR | | 02000nmm uu200397 4500 |
| 001 | | 000000331261 |
| 005 | | 20240805164031 |
| 008 | | 181129s2018 |||||||||||||||||c||eng d |
| 020 | |
▼a 9780438353534 |
| 035 | |
▼a (MiAaPQ)AAI10840589 |
| 035 | |
▼a (MiAaPQ)umn:19465 |
| 040 | |
▼a MiAaPQ
▼c MiAaPQ
▼d 248032 |
| 082 | 0 |
▼a 519 |
| 100 | 1 |
▼a Lindsay, Danika Gray. |
| 245 | 10 |
▼a Applications of Evolutionary Modeling to the Study of Drug Resistance in Cancer. |
| 260 | |
▼a [S.l.] :
▼b University of Minnesota.,
▼c 2018 |
| 260 | 1 |
▼a Ann Arbor :
▼b ProQuest Dissertations & Theses,
▼c 2018 |
| 300 | |
▼a 140 p. |
| 500 | |
▼a Source: Dissertation Abstracts International, Volume: 80-01(E), Section: B. |
| 500 | |
▼a Adviser: Jasmine Foo. |
| 502 | 1 |
▼a Thesis (Ph.D.)--University of Minnesota, 2018. |
| 520 | |
▼a The evolution of resistance to therapy remains a significant challenge to the clinical treatment of cancer. As a tumor evolves, new genetic variants possessing a fitness advantage over normal cancer cells may be produced, thus leading to the dev |
| 520 | |
▼a In the first project, we develop a stochastic model of a non-small cell lung tumor undergoing treatment with a combination of two drugs. One drug is the current standard therapy used in the clinic to treat this disease, which has proven to be in |
| 520 | |
▼a The goal of the second project is to understand the impact of different resistance mechanisms on tumor recurrence. We define two separate branching process models to compare the case in which resistance arises via a single gene mutation with the |
| 590 | |
▼a School code: 0130. |
| 650 | 4 |
▼a Applied mathematics. |
| 690 | |
▼a 0364 |
| 710 | 20 |
▼a University of Minnesota.
▼b Mathematics. |
| 773 | 0 |
▼t Dissertation Abstracts International
▼g 80-01B(E). |
| 773 | |
▼t Dissertation Abstract International |
| 790 | |
▼a 0130 |
| 791 | |
▼a Ph.D. |
| 792 | |
▼a 2018 |
| 793 | |
▼a English |
| 856 | 40 |
▼u http://www.riss.kr/pdu/ddodLink.do?id=T14999739
▼n KERIS |
| 980 | |
▼a 201812
▼f 2019 |
| 990 | |
▼a 관리자 |