Convert the chip ID of GPL2025 <https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GPL2025> 
    to GeneBank Accession and ENTREZID <http://www.ncbi.nlm.nih.gov/gene>.

Implements the most common Gaussian process (GP) models using Laplace and
  expectation propagation (EP) approximations, maximum marginal likelihood
  (or posterior) inference for the hyperparameters, and sparse approximations
  for larger datasets.

Provides functions for estimating a generalized partial
	     linear model, a semiparametric variant of the generalized linear model
	     (GLM) which replaces the linear predictor by the sum of a linear
	     and a nonparametric function.

Various R programming tools for plotting data, including:
  - calculating and plotting locally smoothed summary function as
    ('bandplot', 'wapply'),
  - enhanced versions of standard plots ('barplot2', 'boxplot2',
    'heatmap.2', 'smartlegend'),
  - manipulating colors ('col2hex', 'colorpanel', 'redgreen',
    'greenred', 'bluered', 'redblue', 'rich.colors'),
  - calculating and plotting two-dimensional data summaries ('ci2d',
    'hist2d'),
  - enhanced regression diagnostic plots ('lmplot2', 'residplot'),
  - formula-enabled interface to 'stats::lowess' function ('lowess'),
  - displaying textual data in plots ('textplot', 'sinkplot'),
  - plotting dots whose size reflects the relative magnitude of the
    elements ('balloonplot', 'bubbleplot'),
  - plotting "Venn" diagrams ('venn'),
  - displaying Open-Office style plots ('ooplot'),
  - plotting multiple data on same region, with separate axes
    ('overplot'),
  - plotting means and confidence intervals ('plotCI', 'plotmeans'),
  - spacing points in an x-y plot so they don't overlap ('space').

We provides functions that employ splines to estimate generalized 
             partially linear single index models (GPLSIM), which extend the generalized linear 
             models to include nonlinear effect for some predictors. Please see Y. (2017) at
             <doi:10.1007/s11222-016-9639-0> and Y., and R. (2002) at <doi:10.1198/016214502388618861> for more details.