adding some tools

pages/tool_assembly/transmed_assembly.md

@@ -43,5 +43,5 @@ TransMed projects usually require different data types from different cohorts to
 
 ### Data stewardship
 
-To facilitate the findability of data the TransMed assembly provides a {% tool "data-catalog" %} tool that supports the indexing search and discovery of studies, data sets and samples accumulated in the context of projects from different sites and cohorts. The catalog implements a controlled-access model by integration with {% tool "rems" %}. Audit trailing of data access is achieved by integration of the {% tool "daisy" %} in the access process. The catalog tool can be integrated with various identity management systems such as {%tool "keycloak" %}, {% tool "life-science-login" %} or {% tool "free-ipa" %}. 
+To facilitate the findability of data the TransMed assembly provides a {% tool "data-catalog" %} tool that supports the indexing search and discovery of studies, data sets and samples accumulated in the context of projects from different sites and cohorts. The catalog implements a controlled-access model by integration with {% tool "rems" %}. Audit trailing of data access is achieved by integration of the {% tool "daisy" %} in the access process. The catalog tool can be integrated with various identity management systems such as {% tool "keycloak" %}, {% tool "life-science-login" %} or {% tool "free-ipa" %}. 
 

pages/your_tasks/identifiers.md

@@ -41,7 +41,7 @@ If the research institute or group has a centralised and structured system (such
 * Local identifiers can be applied not only for individual records or observations in a tabular dataset but also for each variable or even value ([columns and cells in a tabular dataset](https://datacarpentry.org/spreadsheet-ecology-lesson/01-format-data/index.html), respectively).
 * Identifiers for an individual record, variable and value in a dataset can be assigned by using ontology terms (see [metadata page](metadata_management#how-do-you-find-appropriate-vocabularies-or-ontologies)) or accession numbers provided by public databases such as, [EBI](https://www.ebi.ac.uk/services/all) and {% tool "national-center-for-biotechnology-information" %} repositories. Here there are few examples for tabular (meta)data, but the same type of identifiers can be applied independently of the (meta)data structure and format.
   * The patient ID is in its own row, a column header is the variable “[disease](http://www.ebi.ac.uk/efo/EFO_0000408)” from the EFO ontology (ID EFO:0000408), and the value in the cell is the child term “[chronic fatigue syndrome](http://www.ebi.ac.uk/efo/EFO_0004540)” (ID EFO:0004540) of “disease”.
-  * The specimen ID is in its own row, a column header is the variable “Ensembl gene ID” from the Ensembl genome browser and the value in the cell is the identifier for [BRCA1](https://www.ensembl.org/Homo_sapiens/Gene/Summary?g=ENSG00000012048;r=17:43044295-43170245) gene ENSG00000012048.
+  * The specimen ID is in its own row, a column header is the variable “Ensembl gene ID” from the {% tool "ensembl" %} genome browser and the value in the cell is the identifier for [BRCA1](https://www.ensembl.org/Homo_sapiens/Gene/Summary?g=ENSG00000012048;r=17:43044295-43170245) gene ENSG00000012048.
 
 ### Solutions
 

pages/your_tasks/machine_actionability.md

@@ -99,7 +99,7 @@ The advantages of having machine-actionable data and metadata are numerous for a
 
 By providing structured metadata and data to a database that follows standards (metadata schemas, ontologies, file formats, programmatic access, etc.), at the level of each recorded value or observation, researchers:
 * Could more easily query and filter (meta)data based on specific variables, experimental conditions, biological sources and many other parameters, based on the capabilities of the used ELN or data management software.
-* Can more easily find and reproduce experiments performed in the past by others in  literature or in databases e.g. by using [Europe PMC](https://europepmc.org/) and [EBI Search](https://www.ebi.ac.uk/ebisearch/overview.ebi/about).
+* Can more easily find and reproduce experiments performed in the past by others in  literature or in databases e.g. by using {% tool "europe-pmc" %} and [EBI Search](https://www.ebi.ac.uk/ebisearch/overview.ebi/about).
 * Can easily integrate data from multiple datasets and studies, sharing the same experimental conditions or variables. Datasets integration and manipulation are easier to achieve, more reproducible and can be automated by using common programmes/software such as R and {% tool "openrefine" %}.
 * Can make use of visualization and exploration tools, provided by some repositories, to browse and explore the data of multiple datasets at once. For instance, you can use {% tool "expression-atlas" %} to easily make a query about the expression of a gene in specific conditions, even without knowledge of any data analysis software. As another example, {% tool "gisaid" %} allows you to visualise the spreading of viral variants. See the pages in the [Your Domain](https://rdmkit.elixir-europe.org/your_domain) section to find domain-specific databases, atlas or portals.
 * Can import, export and exchange (meta)data between tools/systems/platforms without data loss. Exchanging and integrating (meta)data between two software or platforms is possible only if the format in which the information is contained can be read and interpreted by both. For instance, (meta)data from both {% tool "uniprot" %} and {% tool "pdbe-kb" %}  can be accessed in {% tool "3dbionotes" %} to enrich the structural analysis with sequence features.