A set of tools to reconstruct ordered ontogenic trajectories from
    single cell RNAseq data.

Minirhizotrons are widely used to observe and explore roots and
    their growth. This package provides the means to stitch images and 
    divide them into depth layers.
    Please note that this R package was developed alongside the following 
    manuscript:
    Stitching root scans and extracting depth layer information -- a workflow 
    and practical examples, S. Kersting, L. Knüver, and M. Fischer.
    The manuscript is currently in preparation and should be citet as soon as 
    it is available.
    This project was supported by the project ArtIGROW, which is a part of the
    WIR!-Alliance ArtIFARM –  Artificial Intelligence in Farming funded by the
    German Federal Ministry of Research, Technology and Space (No. 03WIR4805).

Implementation of Taylor Regression Estimator (TRE), 
   Tulip Extreme Finding Estimator (TEFE), Bell Extreme Finding Estimator (BEFE),
   Integration Extreme Finding Estimator (IEFE) and 
   Integration Root Finding Estimator (IRFE) for roots, extrema and inflections of a curve .     
   Christopoulos, DT (2019) <doi:10.13140/RG.2.2.17158.32324> .
   Christopoulos, DT (2016) <doi:10.2139/ssrn.3043076> .
   Christopoulos, DT (2016) <https://demovtu.veltech.edu.in/wp-content/uploads/2016/04/Paper-04-2016.pdf> .
   Christopoulos, DT (2014) <doi:10.48550/arXiv.1206.5478> .

Routines to find the root of nonlinear functions, and to perform steady-state and equilibrium analysis of ordinary differential equations (ODE). 
  Includes routines that: (1) generate gradient and jacobian matrices (full and banded),
  (2) find roots of non-linear equations by the 'Newton-Raphson' method, 
  (3) estimate steady-state conditions of a system of (differential) equations in full, banded or sparse form, using the 'Newton-Raphson' method, or by dynamically running,
  (4) solve the steady-state conditions for uni-and multicomponent 1-D, 2-D, and 3-D partial differential equations, that have been converted to ordinary differential equations
    by numerical differencing (using the method-of-lines approach).
  Includes fortran code.