% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/data.R
\docType{data}
\name{data_enc}
\alias{data_enc}
\title{Angle-Encoding Dataset for 3-Qubit Quantum State Preparation}
\format{
A data frame with 12 rows and 6 variables:
\describe{
\item{CD14}{Expression level of CD14 (innate immune receptor; phi2 angle).}
\item{HADH}{Expression level of HADH (beta-oxidation marker; theta3 angle).}
\item{IDO1}{Expression level of IDO1 (tryptophan metabolism; phi1 angle).}
\item{IL6}{Expression level of IL6 (inflammatory signaling; theta1 angle).}
\item{LDHB}{Expression level of LDHB (glycolytic flux; phi3 angle).}
\item{TDO2}{Expression level of TDO2 (systemic metabolic repression; theta2 angle).}
}
}
\usage{
data(data_enc)
}
\description{
A numeric data frame containing patient-level biomarker expression values
used for angle encoding into a 3-qubit quantum state. Each row corresponds
to a sample (patient), and each column corresponds to a biomarker mapped
to a rotation angle in the quantum circuit.
}
\details{
The encoding follows a 3-qubit angle encoding scheme:

\deqn{
|\psi_j\rangle = \bigotimes_{i=1}^3 R_y(\theta_{j,i}) R_z(\phi_{j,i}) |0\rangle
}

where each qubit is parameterized by two biomarkers:

\itemize{
\item \strong{Qubit 1:} \code{IL6} (\eqn{\theta_1}), \code{IDO1} (\eqn{\phi_1})
\item \strong{Qubit 2:} \code{TDO2} (\eqn{\theta_2}), \code{CD14} (\eqn{\phi_2})
\item \strong{Qubit 3:} \code{HADH} (\eqn{\theta_3}), \code{LDHB} (\eqn{\phi_3})
}

These biomarkers capture key immunometabolic axes, including inflammation,
tryptophan metabolism, innate immune sensing, and metabolic reprogramming.

Prior to encoding, values are typically normalized to angular ranges
(e.g., \eqn{[0, 2\pi]}) using dataset-specific min–max scaling.
}
\examples{
data(data_enc)
str(data_enc)

}
\references{
Brown, A. J., et al. (2024). Metabolic reprogramming of human macrophages during Mycobacterium tuberculosis infection under HIV exposure. Gene Expression Omnibus (GEO), accession GSE314344.
Baluku, J. B., et al. (2023). DNA methylation profiling of people living with HIV stratified by tuberculosis status. Gene Expression Omnibus (GEO), accession GSE304107.
}
\keyword{datasets}
