Update cl.md to include CELLxGENE in applications (#2644)

* Update cl.md to include CELLxGENE in applications

* Update CZ CELLxGENE name

* Add CELLxGEN as a user in CL

* Fix bugs 

Colon wrongly placed and missing apostrophes

* Remove trailing spaces

* Include example

An example to a Cell Guide entry has been added, which provides information of all CL terms used by CELLxGENE and connects them.

---------

Co-authored-by: Deepak <deepakunni3@users.noreply.github.com>

ontology/cl.md

@@ -84,6 +84,15 @@ usages:
     title: 'The human body at cellular resolution: the NIH Human Biomolecular Atlas Program.'
   type: annotation
   user: https://hubmapconsortium.org/
+- description: The single-cell transcriptomics platform CZ CELLxGENE uses CL to annotate all cell types. All datasets on CellXGene are annotated according to a standard schema that specifies the use of CL to record Cell Type.
+  examples:
+  - description: A CELLxGENE Cell Guide entry for 'luminal adaptive secretory precursor cell of mammary gland', which includes the CL ID (CL:4033057), CL definition and a visualizer of CL hierarchy
+    url: https://cellxgene.cziscience.com/cellguide/CL:4033057
+  publications:
+  - id: https://doi.org/10.1101/2021.04.05.438318
+    title: 'CELLxGENE: a performant, scalable exploration platform for high dimensional sparse matrices'
+  type: annotation
+  user: https://cellxgene.cziscience.com/
 - description: The Human Cell Atlas (HCA) is an international group of researchers using a combination of these new technologies to create cellular reference maps. The HCA use CL to annotate cells in their reference maps.
   examples:
   - description: HCA collection studies that are related B cell (CL:0000236) that is filtered through CL annotation
@@ -149,6 +158,10 @@ Uberon and various phenotype ontologies.
 
 The following are some applications of the cell ontology along with their publications: 
 
+**CZ CELLxGENE**
+
+CZI Single-Cell Biology Program, Shibla Abdulla, Brian Aevermann, Pedro Assis, Seve Badajoz, Sidney M. Bell, Emanuele Bezzi, et al. 2023. “CZ CELL×GENE Discover: A Single-Cell Data Platform for Scalable Exploration, Analysis and Modeling of Aggregated Data.” bioRxiv. [doi:10.1101/2023.10.30.563174](https://doi.org/10.1101/2023.10.30.563174).
+
 **HuBMAP**
 
 HuBMAP Consortium (2019) The human body at cellular resolution: the NIH Human Biomolecular Atlas Program. Nature, 574, 187–192