東華大學圖書館 |

Language: English

Help

回圖書館首頁

手機版館藏查詢

Back

Switch To: Labeled | MARC Mode | ISBD

Fossil viruses, redox paradigms and ...

Heinemann, Joshua Vance.

Linked to FindBook

Google Book

Amazon

博客來

Fossil viruses, redox paradigms and predictive metabolism from a systems biology perspective.

Record Type:	Electronic resources : Monograph/item
Title/Author:	Fossil viruses, redox paradigms and predictive metabolism from a systems biology perspective./
Author:	Heinemann, Joshua Vance.
Description:	162 p.
Notes:	Source: Dissertation Abstracts International, Volume: 75-11(E), Section: B.
Contained By:	Dissertation Abstracts International75-11B(E).
Subject:	Biochemistry. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3630539
ISBN:	9781321085235

Fossil viruses, redox paradigms and predictive metabolism from a systems biology perspective.
Heinemann, Joshua Vance.

Fossil viruses, redox paradigms and predictive metabolism from a systems biology perspective. - 162 p.

Source: Dissertation Abstracts International, Volume: 75-11(E), Section: B.

Thesis (Ph.D.)--Montana State University, 2014.

This item is not available from ProQuest Dissertations & Theses.

One of the goals of systems biology is to develop a model which encapsulates the molecular, structural and temporal complexity of a living organism. While modern omics experiments can deliver a high resolution view of an organism's molecular complexity, methods for correlating the information from multiple biomolecular systems (i.e. genes, proteins and metabolites) and their changes over time remain greatly underdeveloped. Presented in this research are: (1) methods for understanding the inter-relation of multiple biomolecular systems correlating genomics, proteomics and metabolomics experiments; (2) techniques for machine learning based metabolic biomarker selection; (3) robotics technology for real-time measurement of changes in metabolism. The methods for correlating information from multiple biomolecular systems have provided a new perspective of biomolecular adaptation and evolutionary relationships in the thermophilic archaea. The techniques for biomarker selection have provided a method to assess the reliability of biomarkers in experiments where limited samples are available. The new technology has provided an engineered system for automated analysis of metabolic patterns and how they change over time. Together, these results have created a framework for future improvement of our understanding of biology through the use of molecular biology, machine learning and robotics.

ISBN: 9781321085235Subjects--Topical Terms:

518028
Biochemistry.

Fossil viruses, redox paradigms and predictive metabolism from a systems biology perspective.
LDR:02396nmm a2200301 4500 001 2066069
005 20151221141524.5
008 170521s2014 ||||||||||||||||| ||eng d
020 $a 9781321085235
035 $a (MiAaPQ)AAI3630539
035 $a AAI3630539
040 $a MiAaPQ $c MiAaPQ
100 1 $a Heinemann, Joshua Vance. $3 3180833
245 1 0 $a Fossil viruses, redox paradigms and predictive metabolism from a systems biology perspective.
300 $a 162 p.
500 $a Source: Dissertation Abstracts International, Volume: 75-11(E), Section: B.
500 $a Adviser: Brian Bothner.
502 $a Thesis (Ph.D.)--Montana State University, 2014.
506 $a This item is not available from ProQuest Dissertations & Theses.
520 $a One of the goals of systems biology is to develop a model which encapsulates the molecular, structural and temporal complexity of a living organism. While modern omics experiments can deliver a high resolution view of an organism's molecular complexity, methods for correlating the information from multiple biomolecular systems (i.e. genes, proteins and metabolites) and their changes over time remain greatly underdeveloped. Presented in this research are: (1) methods for understanding the inter-relation of multiple biomolecular systems correlating genomics, proteomics and metabolomics experiments; (2) techniques for machine learning based metabolic biomarker selection; (3) robotics technology for real-time measurement of changes in metabolism. The methods for correlating information from multiple biomolecular systems have provided a new perspective of biomolecular adaptation and evolutionary relationships in the thermophilic archaea. The techniques for biomarker selection have provided a method to assess the reliability of biomarkers in experiments where limited samples are available. The new technology has provided an engineered system for automated analysis of metabolic patterns and how they change over time. Together, these results have created a framework for future improvement of our understanding of biology through the use of molecular biology, machine learning and robotics.
590 $a School code: 0137.
650 4 $a Biochemistry. $3 518028
650 4 $a Robotics. $3 519753
650 4 $a Systems science. $3 3168411
690 $a 0487
690 $a 0771
690 $a 0790
710 2 $a Montana State University. $b Chemistry and Biochemistry. $3 2100488
773 0 $t Dissertation Abstracts International $g 75-11B(E).
790 $a 0137
791 $a Ph.D.
792 $a 2014
793 $a English
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3630539