fix minor - Summary #34

paper/paper.md

@@ -28,7 +28,7 @@ Correlation-like analysis provides an important statistical measure that describ
 
 Additionally, it offers a C++ implementation of the Average Correlation Clustering Algorithm (ACCA) [@bhattacharya:2010], which was originally developed for genetic studies using Pearson correlation as a similarity measure. In general, ACCA is an unsupervised clustering method, as it identifies patterns in the data without requiring predefined labels. Moreover, it requires the K parameter to be defined, similar to k-means. One of its main differences compared to other clustering methods is that it operates based on correlations rather than traditional distance metrics, such as Euclidean or Mahalanobis distance.
 
-In this package, the ACCA algorithm has been extended to work directly with correlation matrices derived from different association methods, depending on the data types and user preferences. Furthermore, the package is designed for parallel processingin R, making it highly efficient for large datasets.
+In this package, the ACCA algorithm has been extended to work directly with correlation matrices derived from different association methods, depending on the data types and user preferences. Furthermore, the package is designed for parallel processing in R, making it highly efficient for large datasets.