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Cancer Bioinformatics for Biomarker ...

University of California, San Francisco.

Cancer Bioinformatics for Biomarker Discovery.

紀錄類型:	書目-語言資料,手稿 : Monograph/item
正題名/作者:	Cancer Bioinformatics for Biomarker Discovery./
作者:	Webber, James Trubek.
面頁冊數:	1 online resource (316 pages)
附註:	Source: Dissertation Abstracts International, Volume: 79-02(E), Section: B.
Contained By:	Dissertation Abstracts International79-02B(E).
標題:	Bioinformatics. -
電子資源:	click for full text (PQDT)
ISBN:	9780355386127

Cancer Bioinformatics for Biomarker Discovery.
Webber, James Trubek.

Cancer Bioinformatics for Biomarker Discovery. - 1 online resource (316 pages)

Source: Dissertation Abstracts International, Volume: 79-02(E), Section: B.

Thesis (Ph.D.)--University of California, San Francisco, 2017.

Includes bibliographical references

Cancer is a complex and multifaceted disease, and a vast amount of time and effort has been spent on characterizing its behaviors, identifying its weaknesses, and discovering effective treatments. Two major obstacles stand in the way of progress toward effective precision treatment for the majority of patients.

Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2018

Mode of access: World Wide Web

ISBN: 9780355386127Subjects--Topical Terms:

583857
Bioinformatics.
Index Terms--Genre/Form:

554714
Electronic books.

Cancer Bioinformatics for Biomarker Discovery.
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035 $a (MiAaPQ)ucsf:11485
035 $a AAI10604636
040 $a MiAaPQ $b eng $c MiAaPQ $d NTU
100 1 $a Webber, James Trubek. $3 1195284
245 1 0 $a Cancer Bioinformatics for Biomarker Discovery.
264 0 $c 2017
300 $a 1 online resource (316 pages)
336 $a text $b txt $2 rdacontent
337 $a computer $b c $2 rdamedia
338 $a online resource $b cr $2 rdacarrier
500 $a Source: Dissertation Abstracts International, Volume: 79-02(E), Section: B.
500 $a Advisers: Sourav Bandyopadhyay; Nevan J. Krogan.
502 $a Thesis (Ph.D.)--University of California, San Francisco, 2017.
504 $a Includes bibliographical references
520 $a Cancer is a complex and multifaceted disease, and a vast amount of time and effort has been spent on characterizing its behaviors, identifying its weaknesses, and discovering effective treatments. Two major obstacles stand in the way of progress toward effective precision treatment for the majority of patients.
520 $a First, cancer's extraordinary heterogeneity---both between and even within patients---means that most patients present with a disease slightly different from every previously recorded case. New methods are necessary to analyze the growing body of patient data so that we can classify each new patient with as much accuracy and precision as possible. In chapter 2 I present a method that integrates data from multiple genomics platforms to identify axes of variation across breast cancer patients, and to connect these gene modules to potential therapeutic options. In this work we find modules describing variation in the tumor microenvironment and activation of different cellular processes. We also illustrate the challenges and pitfalls of translating between model systems and patients, as many gene modules are poorly conserved when moving between datasets.
520 $a A second problem is that cancer cells are constantly evolving, and many treatments inevitably lead to resistance as new mutations arise or compensatory systems are activated. To overcome this we must find rational combinations that will prevent resistant adaptation before it can start. Starting in chapter 3 I present a series of projects in which we used a high-throughput proteomics approach to characterize the activity of a large proportion of protein kinases, ending with the discovery of a promising drug combination for the treatment of breast cancer in chapter 8.
533 $a Electronic reproduction. $b Ann Arbor, Mich. : $c ProQuest, $d 2018
538 $a Mode of access: World Wide Web
650 4 $a Bioinformatics. $3 583857
655 7 $a Electronic books. $2 local $3 554714
690 $a 0715
710 2 $a ProQuest Information and Learning Co. $3 1178819
710 2 $a University of California, San Francisco. $b Biological and Medical Informatics. $3 1193289
773 0 $t Dissertation Abstracts International $g 79-02B(E).
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10604636 $z click for full text (PQDT)

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