PMID- 15880604
OWN - NLM
STAT- MEDLINE
DCOM- 20050713
LR  - 20061115
IS  - 1076-5174 (Print)
IS  - 1076-5174 (Linking)
VI  - 40
IP  - 5
DP  - 2005 May
TI  - Statistical design of experiments as a tool in mass spectrometry.
PG  - 565-79
AB  - This Tutorial is an introduction to statistical design of experiments (DOE) with 
      focus on demonstration of how DOE can be useful to the mass spectrometrist. In 
      contrast with the commonly used one factor at a time approach, DOE methods 
      address the issue of interaction of variables and are generally more efficient. 
      The complex problem of optimizing data-dependent acquisition parameters in a 
      bottom-up proteomics LC-MS/MS analysis is used as an example of the power of the 
      technique. Using DOE, a new data-dependent method was developed that improved the 
      quantity of confidently identified peptides from rat serum.
CI  - Copyright 2005 John Wiley & Sons, Ltd.
FAU - Riter, Leah S
AU  - Riter LS
AD  - Lilly Research Laboratories, Eli Lilly and Company, Indianapolis, IN 46285, USA. 
      riter_leah_stacey@lilly.com
FAU - Vitek, Olga
AU  - Vitek O
FAU - Gooding, Karen M
AU  - Gooding KM
FAU - Hodge, Barry D
AU  - Hodge BD
FAU - Julian, Randall K Jr
AU  - Julian RK Jr
LA  - eng
PT  - Journal Article
PL  - England
TA  - J Mass Spectrom
JT  - Journal of mass spectrometry : JMS
JID - 9504818
RN  - 0 (Peptides)
SB  - IM
MH  - Animals
MH  - Mass Spectrometry/*methods
MH  - Models, Statistical
MH  - Peptides/blood
MH  - Proteomics/*methods
MH  - Rats
MH  - *Research Design
MH  - Sensitivity and Specificity
EDAT- 2005/05/10 09:00
MHDA- 2005/07/14 09:00
CRDT- 2005/05/10 09:00
PHST- 2005/05/10 09:00 [pubmed]
PHST- 2005/07/14 09:00 [medline]
PHST- 2005/05/10 09:00 [entrez]
AID - 10.1002/jms.871 [doi]
PST - ppublish
SO  - J Mass Spectrom. 2005 May;40(5):565-79. doi: 10.1002/jms.871.