diff --git a/R/lap.R b/R/lap.R
index 7fefc23a..6182ed63 100644
--- a/R/lap.R
+++ b/R/lap.R
@@ -41,6 +41,16 @@
 #'                     3, 6, 2, 2, 9), 4, 5, byrow = TRUE)
 #'
 #' LAPJV(problem)
+#' @seealso 
+#' Implementations of the Hungarian algorithm exist in \pkg{adagio},
+#' \pkg{RcppHungarian}, and \pkg{clue} and \pkg{lpSolve}; for larger matrices,
+#' these are substantially slower. (See discussion at [Stack Overflow](
+#' https://stackoverflow.com/questions/72806265/).)
+#' 
+#' The JV algorithm is implemented for square matrices in the Bioconductor
+#' package [`GraphAlignment::LinearAssignment()`](
+#' https://www.bioconductor.org/packages/release/bioc/html/GraphAlignment.html).
+#' 
 #' @export
 LAPJV <- function(x) {
   dims <- dim(x)
diff --git a/man/LAPJV.Rd b/man/LAPJV.Rd
index a6e8d29e..561d0032 100644
--- a/man/LAPJV.Rd
+++ b/man/LAPJV.Rd
@@ -47,6 +47,14 @@ LAPJV(problem)
 \references{
 \insertAllCited{}
 }
+\seealso{
+Implementations of the Hungarian algorithm exist in \pkg{adagio},
+\pkg{RcppHungarian}, and \pkg{clue} and \pkg{lpSolve}; for larger matrices,
+these are substantially slower. (See discussion at \href{https://stackoverflow.com/questions/72806265/}{Stack Overflow}.)
+
+The JV algorithm is implemented for square matrices in the Bioconductor
+package \href{https://www.bioconductor.org/packages/release/bioc/html/GraphAlignment.html}{\code{GraphAlignment::LinearAssignment()}}.
+}
 \author{
 \href{https://github.com/yongyanghz/LAPJV-algorithm-c/blob/master/LAPJV/lap.cpp}{C++ code}
 by Roy Jonker, MagicLogic Optimization Inc. \href{mailto:roy_jonker@magiclogic.com}{roy_jonker@magiclogic.com},