diff --git a/anselm.csv b/anselm.csv
index bb23bd983b01a3cd69da029d356b1af76145fe53..303fa0263229b88b904ec4c622fd3338f716bc64 100644
--- a/anselm.csv
+++ b/anselm.csv
@@ -712,10 +712,10 @@ MATIO/1.5.2-intel-2017a,1
 MATLAB/2015b-COM,1
 MATLAB/2015b-EDU,1
 MATLAB/2015b-EDU-test,1
-matlab/R2013a-COM,1
-matlab/R2013a-EDU,1
-matlab/R2014a-COM,1
-matlab/R2014a-EDU,1
+MATLAB/R2013a-COM,1
+MATLAB/R2013a-EDU,1
+MATLAB/R2014a-COM,1
+MATLAB/R2014a-EDU,1
 matplotlib/1.5.1-Python-2.7.13-freetype-2.6.3,1
 matplotlib/2.0.2-Python-2.7.13-base,1
 matplotlib/2.0.2-Python-3.6.1-libpng-1.6.29,1
diff --git a/anselm.md b/anselm.md
index 18cd847ece7cf8f4f01cb5820ac26de65573694a..640a912e134bf11aee5cee903989bf3d942f5ba6 100644
--- a/anselm.md
+++ b/anselm.md
@@ -162,7 +162,6 @@
 | lsprepost | &nbsp; |
 | lux | &nbsp; |
 | marc | &nbsp; |
-| matlab | &nbsp; |
 | maxwell | &nbsp; |
 | modflow-2005 | &nbsp; |
 | modflow-nwt | &nbsp; |
@@ -311,7 +310,7 @@
 | [h5py](https://github.com/jupyter/testpath) | Test utilities for code working with files and commands |
 | [ISL](http://isl.gforge.inria.fr/) | isl is a library for manipulating sets and relations of integer points bounded by linear constraints. |
 | [Keras](https://keras.io/) | Keras is a minimalist, highly modular neural networks library, written in Python and capable of running on top of either TensorFlow or Theano. |
-| [MATLAB](http://www.mathworks.com/products/matlab) | MATLAB is a high-level language and interactive environment that enables you to perform computationally intensive tasks faster than with traditional programming languages such as C, C++, and Fortran. |
+| MATLAB | &nbsp; |
 | METIS | &nbsp; |
 | [MLD2P4](http://www.mld2p4.it) | MLD2P4 (Multi-Level Domain Decomposition Parallel Preconditioners Package based on PSBLAS) is a package of parallel algebraic multi-level preconditioners. It implements various versions of one-level additive and of multi-level additive and hybrid Schwarz algorithms. In the multi-level case, a purely algebraic approach is applied to generate coarse-level corrections, so that no geometric background is needed concerning the matrix to be preconditioned. The matrix is assumed to be square, real or complex, with a symmetric sparsity pattern. |
 | MPFR | &nbsp; |