Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Information Preserving Component Analysis: Data Projections for Flow
  Cytometry Analysis   Flow cytometry is often used to characterize the malignant cells in leukemia
and lymphoma patients, traced to the level of the individual cell. Typically,
flow cytometric data analysis is performed through a series of 2-dimensional
projections onto the axes of the data set. Through the years, clinicians have
determined combinations of different fluorescent markers which generate
relatively known expression patterns for specific subtypes of leukemia and
lymphoma -- cancers of the hematopoietic system. By only viewing a series of
2-dimensional projections, the high-dimensional nature of the data is rarely
exploited. In this paper we present a means of determining a low-dimensional
projection which maintains the high-dimensional relationships (i.e.
information) between differing oncological data sets. By using machine learning
techniques, we allow clinicians to visualize data in a low dimension defined by
a linear combination of all of the available markers, rather than just 2 at a
time. This provides an aid in diagnosing similar forms of cancer, as well as a
means for variable selection in exploratory flow cytometric research. We refer
to our method as Information Preserving Component Analysis (IPCA).

36
The categories of this paper are: cmp-lg
3
The categories of this paper are: physics
8
The categories of this paper are: hep-ex
23
The categories of this paper are: solv-int
35
The categories of this paper are: mtrl-th
13
The categories of this paper are: quant-ph
12
The categories of this paper are: nucl-th
32
The categories of this paper are: atom-ph
18
The categories of this paper are: econ
14
The categories of this paper are: math-ph
7
The categories of this paper are: hep-th
15
The categories of this paper are: nucl-ex
4
The categories of this paper are: cond-mat
0
The categories of this paper are: hep-ph
26
The categories of this paper are: bayes-an
33
The categories of this paper are: plasm-ph