Fix dead and moved web links

R/panther.R

@@ -916,14 +916,16 @@ rba_panther_family <- function(id,
 }
 
 #' PANTHER Tree Grafter
+#'
 #' Use this function to retrieve a PANTHER family's tree topology information
 #'   with a node corresponding to your sequence grafted in the best location
 #'   in that tree.
 #'
 #' For more information, see:
-#'   \href{https://academic.oup.com/bioinformatics/article/35/3/518/5056037}{TreeGrafter:
-#'   phylogenetic tree-based annotation of proteins with Gene Ontology terms
-#'   and other annotations}
+#'   Haiming Tang, Robert D Finn, Paul D Thomas, TreeGrafter: phylogenetic
+#'   tree-based annotation of proteins with Gene Ontology terms and other
+#'   annotations, Bioinformatics, Volume 35, Issue 3, February 2019, Pages
+#'   518–520, \doi{10.1093/bioinformatics/bty625}
 #'
 #' @param protein_seq A character string with the protein's sequence. Maximum
 #'   allowed sequence length is 50kb.

R/stringdb.R

@@ -626,7 +626,7 @@ rba_string_interaction_partners <- function(ids,
 #'   protein and it's closets homologous proteins in other species, see
 #'   \code{\link{rba_string_homology_inter}}.
 #'   \cr Similarity matrix is imported -by STRING- from:
-#'   \href{https://cube.univie.ac.at/resources/simap}{Similarity Matrix of
+#'   \href{https://cube.univie.ac.at/research/software-databases/simap/}{Similarity Matrix of
 #'   Proteins (SIMAP)}
 #'
 #' @section Corresponding API Resources:
@@ -736,7 +736,7 @@ rba_string_homology_intra <- function(ids,
 #'   species. to retrieve similarity scores of different proteins within the
 #'   same species see \code{\link{rba_string_homology_intra}}.
 #'   \cr Similarity matrix is imported -by STRING- from:
-#'   \href{https://cube.univie.ac.at/resources/simap}{Similarity Matrix of
+#'   \href{https://cube.univie.ac.at/research/software-databases/simap/}{Similarity Matrix of
 #'   Proteins (SIMAP)}
 #'
 #' @section Corresponding API Resources:

vignettes/rbioapi_do_enrich.Rmd

@@ -258,7 +258,7 @@ if (is.data.frame(panther_sets)) {
 }
 ```
 
-Note that you should enter the "id" of the datasets, not its label. For example, entering "biological_process" is incorrect, you should rather use "GO:0008150".
+Note that you should enter the "id" of the datasets, not its label. For example, entering `"biological_process"` is incorrect, you should rather use `"GO:0008150"`.
 
 Here, we demonstrate the enrichment analysis using the Biological Process annotations. The Gene Ontology (GO) project is one of the pinnacles of scientists' collective effort in bioinformatics. The GO Consortium provides a comprehensive model of biological systems. In short, GO curates a thoroughly designed directed acyclic graph (DAG) of ontologies. You may think of it as a tree of terms, where as it branches out, the terms become more specific). Each protein may be annotated with one or more terms. The terms are organized in three domains: "Molecular Function," "Biological Process," and "Cellular Component". GO slim datasets refer to subsets which are a cut-down version of GO terms. If you are not familiar with GO, I strongly encourage you to see this page and follow the links it provides: [About the GO resource](https://geneontology.org/docs/introduction-to-go-resource/ "About the GO resource").
 
@@ -319,7 +319,7 @@ In addition to proteins interaction data, STRING also curates proteins/genes ann
 
     1.  [Gene Ontology](https://geneontology.org/ "Gene Ontology Resource - Unifying Biology") domains: Molecular Function, Biological Process, and Cellular Component
 
-    2.  [COMPARTMENTS](https://academic.oup.com/database/article/doi/10.1093/database/bau012/2633793 "Subcellular localization database")
+    2.  [COMPARTMENTS](https://doi.org/10.1093/database/bau012 "Subcellular localization database")
 
     3.  [Human Disease Ontology](https://disease-ontology.org/ "Disease Ontology")
 

vignettes/rbioapi_string.Rmd

@@ -181,7 +181,7 @@ if (is.array(graph_2)) {
 
 # Enrichment using STRING {#enrichment-using-string}
 
-STRING let you perform two types of enrichments. See [STRING's paper](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3531103/ "STRING v9.1: protein-protein interaction networks, with increased coverage and integration") for more information.
+STRING let you perform two types of enrichments. See [STRING's paper](https://doi.org/10.1093/nar/gks1094 "STRING v9.1: protein-protein interaction networks, with increased coverage and integration") for more information.
 
 ## Functional enrichment {#functional-enrichment}
 
@@ -239,7 +239,7 @@ if (is.array(graph_3)) {
 
 ## Protein-protein interaction enrichment {#protein-protein-interaction-enrichment}
 
-Even without incorporating annotation data, STRING can calculate if your proteins are functionally related. Briefly, STRING accomplishes this by comparing the interactions' distribution in your protein-set to the interactions' distribution in the proteome. Read [STRING's paper](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3531103/#__sec4title "STRING v9.1: protein-protein interaction networks, with increased coverage and integration") for more information.
+Even without incorporating annotation data, STRING can calculate if your proteins are functionally related. Briefly, STRING accomplishes this by comparing the interactions' distribution in your protein-set to the interactions' distribution in the proteome. Read [STRING's paper](https://doi.org/10.1093/nar/gks1094 "STRING v9.1: protein-protein interaction networks, with increased coverage and integration") for more information.
 
 ```{r rba_string_enrichment_ppi}
 rba_string_enrichment_ppi(ids = proteins_mapped,