Applications of Peptide Retention Time in Proteomic Data Analysis

2014 ◽  
pp. 67-75 ◽  
Author(s):  
Chen Shao
Keyword(s):  
Data Analysis ◽  
Retention Time ◽  
Proteomic Data

Proteomic data analysis of glioma cancer stem-cell lines based on novel nonlinear dimensional data reduction techniques

2016 ◽  
Author(s):  
Sylvain Lespinats ◽  
Katja Pinker-Domenig ◽  
Georg Wengert ◽  
Ivo Houben ◽  
Marc Lobbes ◽  
...  
Keyword(s):  
Stem Cell ◽  
Data Analysis ◽  
Cancer Stem Cell ◽  
Cell Lines ◽  
Data Reduction ◽  
Proteomic Data ◽  
Reduction Techniques ◽  
Stem Cell Lines

Proteomic Data Analysis Workflow for Discovery of Candidate Biomarker Peaks Predictive of Clinical Outcome for Patients with Acute Myeloid Leukemia†

2008 ◽  
Vol 7 (6) ◽  
pp. 2332-2341 ◽  
Author(s):  
Jenny Forshed ◽  
Maria Pernemalm ◽  
Chuen Seng Tan ◽  
Marita Lindberg ◽  
Lena Kanter ◽  
...  
Keyword(s):  
Acute Myeloid Leukemia ◽  
Data Analysis ◽  
Clinical Outcome ◽  
Myeloid Leukemia ◽  
Proteomic Data ◽  
Analysis Workflow ◽  
Acute Myeloid

scholarly journals Biomarker Discovery for Arsenic Exposure Using Functional Data. Analysis and Feature Learning of Mass Spectrometry Proteomic Data

2008 ◽  
Vol 7 (1) ◽  
pp. 217-224 ◽  
Author(s):  
Jaroslaw Harezlak ◽  
Michael C. Wu ◽  
Mike Wang ◽  
Armin Schwartzman ◽  
David C. Christiani ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Data Analysis ◽  
Functional Data Analysis ◽  
Functional Data ◽  
Biomarker Discovery ◽  
Arsenic Exposure ◽  
Feature Learning ◽  
Proteomic Data

scholarly journals An automated proteomic data analysis workflow for mass spectrometry

2009 ◽  
Vol 10 (Suppl 11) ◽  
pp. S17 ◽  
Author(s):  
Ken Pendarvis ◽  
Ranjit Kumar ◽  
Shane C Burgess ◽  
Bindu Nanduri
Keyword(s):  
Mass Spectrometry ◽  
Data Analysis ◽  
Proteomic Data ◽  
Analysis Workflow

Applying Random Graphs for Proteomic Data Analysis of RCC Patients

2010 ◽  
Vol 150 ◽  
pp. 435-436
Author(s):  
M. Antoniotti ◽  
M. Borsani ◽  
E. Gianazza ◽  
F. Magni ◽  
G. Mauri ◽  
...  
Keyword(s):  
Data Analysis ◽  
Random Graphs ◽  
Proteomic Data

scholarly journals The Effect of Using an Inappropriate Protein Database for Proteomic Data Analysis

PLoS ONE ◽  
2011 ◽  
Vol 6 (6) ◽  
pp. e20873 ◽  
Author(s):  
Giselle M. Knudsen ◽  
Robert J. Chalkley
Keyword(s):  
Data Analysis ◽  
Protein Database ◽  
Proteomic Data

scholarly journals Blackwater Purification Using Sand Filter

2018 ◽  
Vol 1 (1) ◽  
pp. 35
Author(s):  
Lies Kurniawati Wulandari ◽  
Munasih Munasih
Keyword(s):  
Regression Analysis ◽  
Data Analysis ◽  
Linear Regression ◽  
Residence Time ◽  
Water Purification ◽  
Retention Time ◽  
Linear Regression Analysis ◽  
Sand Filter

This study aimed to determine the effect of the thickness of the sand filter and the best residence time for water purification. The type of sand used in this study was concrete sand, and the observation was focused on turbidity (NTU) parameter. Measurements of turbidity were performed before treatment, as well as at each retention time from 1 to 9 days. The method of data analysis was Linear Regression analysis on SPSS 21 program. Blackwater was collected in the morning and afternoon, and the turbidity of each sample was 1000 and 800 NTU, respectively. Wastewater turbidity was continued to decreased along with the longer retention time. The best results were obtained from the treatment 3 (sand filter 20 cm) with 9 days retention time, in which the turbidity levels decreased to 90 NTU (morning sample), and 105 NTU (afternoon sample).

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