LDR | | 02147nmm uu200421 4500 |
001 | | 000000332059 |
005 | | 20240805165933 |
008 | | 190108s2018 |||||||||||||||||c||eng d |
020 | |
▼a 9780438254879 |
035 | |
▼a (MiAaPQ)AAI10844695 |
035 | |
▼a (MiAaPQ)wisc:15565 |
040 | |
▼a MiAaPQ
▼c MiAaPQ
▼d 248032 |
082 | 0 |
▼a 310 |
100 | 1 |
▼a Zhang, Huikun. |
245 | 10 |
▼a Statistical Tools in Early-Stage Drug Discovery. |
260 | |
▼a [S.l.] :
▼b The University of Wisconsin - Madison.,
▼c 2018 |
260 | 1 |
▼a Ann Arbor :
▼b ProQuest Dissertations & Theses,
▼c 2018 |
300 | |
▼a 91 p. |
500 | |
▼a Source: Dissertation Abstracts International, Volume: 79-12(E), Section: B. |
500 | |
▼a Adviser: Michael A. Newton. |
502 | 1 |
▼a Thesis (Ph.D.)--The University of Wisconsin - Madison, 2018. |
520 | |
▼a In biomedical research, drug discovery is usually done through studying the interaction between drug-like compounds and protein targets. The challenge is that it is inefficient to screen millions of compounds. Computational tools have been deployed to save the screening effort. |
520 | |
▼a In this collaborated research with UW Small Molecule Screening Facility, two projects are focused: Consensus Docking: statistical models are developed using computational docking data to predict compound-target interactions; Informer compound set generation and prediction: prediction on compound-target interaction is made through using experimental assay data. |
520 | |
▼a Statistical considerations include mixture modeling, ranking and regression. In both study, improved drug discovery performance has been achieved through applying developed statistical models. |
590 | |
▼a School code: 0262. |
650 | 4 |
▼a Statistics. |
650 | 4 |
▼a Biochemistry. |
690 | |
▼a 0463 |
690 | |
▼a 0487 |
710 | 20 |
▼a The University of Wisconsin - Madison.
▼b Statistics. |
773 | 0 |
▼t Dissertation Abstracts International
▼g 79-12B(E). |
773 | |
▼t Dissertation Abstract International |
790 | |
▼a 0262 |
791 | |
▼a Ph.D. |
792 | |
▼a 2018 |
793 | |
▼a English |
856 | 40 |
▼u http://www.riss.kr/pdu/ddodLink.do?id=T15013681
▼n KERIS |
980 | |
▼a 201812
▼f 2019 |
990 | |
▼a 관리자 |