Implements the Enhanced Portfolio Optimization (EPO) method as 
    described in Pedersen, Babu and Levine (2021)
    <doi:10.2139/ssrn.3530390>.

Estimates sparse matrices A or G using fast lasso regression from mRNA transcript levels Y and CNA profiles U. Two models are provided, EPoC A where
      AY + U + R = 0
  and EPoC G where
      Y = GU + E,
  the matrices R and E are so far treated as noise. For
  details see the manual page of 'lassoshooting' and the
  article Rebecka Jörnsten, Tobias Abenius, Teresia Kling, 
  Linnéa Schmidt, Erik Johansson, Torbjörn E M Nordling, 
  Bodil Nordlander, Chris Sander, Peter Gennemark, 
  Keiko Funa, Björn Nilsson, Linda Lindahl, Sven Nelander
  (2011) <doi:10.1038/msb.2011.17>.

Clinical coding and diagnosis of patients with kidney using
    clinical practice guidelines. The guidelines used are the evidence-based
    KDIGO guidelines, see <https://kdigo.org/guidelines/> for more information.
    This package covers acute kidney injury (AKI), anemia, and
    chronic kidney disease (CKD).

Provides a set of functions, which facilitates removing objects from an environment. 
             It allows to delete objects specified with regular expression or with other conditions (e.g. if object is numeric),
             using one function call.

Analysis and visualization of similarities between epilepsy ontologies based on text mining results by comparing ranked lists of co-occurring drug terms in the BioASQ corpus. The ranked result lists of neurological drug terms co-occurring with terms from the epilepsy ontologies EpSO, ESSO, EPILONT, EPISEM and FENICS undergo further analysis. The source data to create the ranked lists of drug names is produced using the text mining workflows described in Mueller, Bernd and Hagelstein, Alexandra (2016) <doi:10.4126/FRL01-006408558>, Mueller, Bernd et al. (2017) <doi:10.1007/978-3-319-58694-6_22>, Mueller, Bernd and Rebholz-Schuhmann, Dietrich (2020) <doi:10.1007/978-3-030-43887-6_52>, and Mueller, Bernd et al. (2022) <doi:10.1186/s13326-021-00258-w>.