Possible outline of paper 12-16-2013d1154

2015-01-13

Possible outline of paper 12-16-2013d1154

See Word doc here
"C:\Users\kurtw_000\Documents\kurt\storage\CIM Research Folder\DR\2013\12-16-2013d1158\First AbStat Publication Outline 03-10-2014d1349.docx"
Possible journals:
Maybe "Trends in Immunology", "Journal of Immunological Methods", "BMC Immunology", "Cancer Immunology", "Immunotherapy", "Immunologic Research", "BMC Biotechnology", or "BMC Bioinformatics" would be best

Comparison of journals for abstat paper
-"C:\Users\kurtw_000\Documents\kurt\storage\CIM Research Folder\DR\2013\12-17-2013d0903\comparison of journals for AbStat Paper.xlsx"
-I think "BMC Bioinformatics" would be my top choice, and then "immunological methods" after that.

Outline for paper on AbStat
-Introduction
--Paragraph 1: Introduce AbStat concept and question: Can the information acquired from the peptide intensity distribution resulting from sera antibodies reacting with an array of random sequence peptides be used to distinguish healthy or disease states? Can this information be compressed into a single quantified variable?
```
5
```
Last sentence of 1st paragraph: This research shows that several measures from the peptide intensity distribution can be combined to produce an Antibody Status (AbStat) capable of distinguishing healthy and disease states.
--Measuring humoral immune responses section
---Past antibody detection methods paragraph
---Random peptide microarray paragraph
---Affinity and avidity of antibody repertoire
--Measures that compose AbStat section
---Paragraph: Introduction to the measures and a list of them
---Paragraph: Characterisitics of the measures
--AbStat Applications Section
---Paragraph: Summary of types of datasets the AbStat concept was applied to
---Paragraph: Glimpse at possible future applications

Materials and Methods
-Array platforms section
--Paragraph: Two different 10k platforms
--Paragraph: 330k platform
-Array procedures with samples section
--Paragraph: 10k procedure
--Paragraph: 330k procedure
--Paragraph: extracting intensity value
-Mathematical measures section
--Paragraph: description of measures used in AbStat
-Methods of analysis section
--Paragraph: Description of software and programs used
--Paragraph: machine learning algorithms with Weka
-AbStat Changes with Artificial Antibody Experiments
--Paragraph: spiking antibody into sera
--Paragraph: Monoclonal affinities and AbStat Measures
--Paragraph: Mixing two monoclonal antibodies together
-Human vaccines section(one paragraph)
-Reduction in antibody repertoire complexity with lymphoma section (one paragraph)
-Mouse cancer progression (one paragraph)
-Human disease (one paragraph)
-Organism aging experiments
--paragraph: Mouse age experiments
--paragraph: Human age experiments

Results
-AbStat Changes with artificial antibody experiments
--Paragraph: Spiking antibody into sera (I'll use the experiment from Josh in which sera against the GFOD1 protein was added to normal mouse sera)
```
4
```
Figure: Entropy for increasing antibody concentrations in normal mouse sera
--Paragraph: Monoclonal antibody affinities and AbStat Measures
```
4
```
Figure: Peptide intensity histogram of antibodies with varying Kd values
--Paragraph: Mixing two monoclonal antibodies
--Figure: Peptide intensity histogram of antibody mixtures
-Human vaccines section
--Paragraph: description of results for human vaccines
---Figure: Change in entropy after vaccination (I would show change in entropy for 43 in 2006, 84 in 2009, 43 for one month in 2011, 84 for one month in 2011)
-Reduction in antibody repertoire complexity with lymphoma section
--Paragraph describing "Reduction in antibody repertoire complexity with lymphoma section"
--Figure: Box and dotplot of entropy for normal (N) and lymphosarcoma (LSA) dogs
-Mouse Cancer progression section
--Paragraph describing results of mouse cancer progression
--Figure: entropy timecourse for wild type and transgenic mouse
-Human disease data section
--Paragraph: Description of results for wafer 46 results
--Figure: Box and dotplot of entropy for groups on wafer 46
-Changes with age section
--Paragraph: changes with age in mice
---Figure: box and dotplot of entropy for young and aged mice
--Paragraph: changes with age in humans
---Figure: Box and dotplot of entropy for young and aged humans
-Rank of measures section
--Paragraph: description of rank of measures
-Changes in entropy measure with removal of peptides section
--Paragraph: description of "changes in entropy measure with removal of peptides"
---Figure: P-value vs peptides removed

Discussion
-First paragraph: summary of results in the paper. First sentence: "We have demonstrated that the AbStat measures provide indicators for a wide variety of different immunological situations."
-Paragraph: AbStat changes with artificial antibody experiments
-Paragraph: trend in entropy as antibody concentration increases
-Paragraph: difference in resolution between measures
-Paragraph: assessing theory that trend in entropy reversed due to saturation of target peptides (this would contain Kd calculation and Graphpad Prism One to one binding model results from Chris)
-Paragraph: summary of entropy trend with increasing concentration of antibody
-Paragraph: behavior of Abstat with different affinities
-Paragraph: possible explanation for the behavior
-Paragraph: mixing two monoclonal antibodies
-Paragraph: behavior of solutions more or less like monoclonal antibodies
-Paragraph: using knowledge from artificial antibody experiments to understand the state of human sera
-Paragraph: summary of artificial antibody experiments
-Paragraph: reduction in antibody repertoire complexity with lymphoma
-Paragraph: machine learning results for lymphoma
-Paragraph: paragraph on mouse cancer progression
-Paragraph: human disease data
-Paragraph: emphasizing that specific peptides were not selected to separate the samples
-Paragraph: changes with age
-Paragraph: discussion of machine learning results of changes with age
-Paragraph: Rank of measures (I could also mention typical range of entropy here)
-Paragraph: analysis of most important peptides
-Paragraph: removal of highest intensity peptides
-Paragraph: possible future applications (diagnosis and mitigation)
-Paragraph: Conclusion summarizing everything

Sections in dissertation that will be excluded for a paper

the 4 page "Nature of entropy measure" section in introduction
"Java AbStat Program" section
"Mouse vaccines and infections" section. This data may not be good enough for a paper.
HT330k first chip disease dataset
CIM10k
Alzheimer's disease
"Use and possible future applications" section in dissertation