Hey Jabbari,
There are a lot of tools you can use both for GO specifically and for other databases.
As a starting point, try navigating here: https://www.wikipathways.org/index.php/Help:Tools_using_WikiPathways. While this is for WikiPathways, a substantial number of these tools enable analysis of GO ontologies too. For example, one of the tools listed is clusterProfiler. In one workflow I used ClusterProfiler::enrichGO() followed by ClusterProfiler::enricher() to generate figures like ![this one:](/media/images/fb25641a-119b-4f2c-8704-231ad565)
In this figure, the coloration of each gene is dependent on the level of differential expression between genes belonging to the pathway illustrated, but you could color it any way you please. Thus, you can not only make figures of GO pathways, you can do it in a data-driven fashion, irrespective of what kind of data you have (for instance, why couldn't the color be number of missense variants in each gene, etc.).
I think the last point I would make is that I'd recommend that you pick a set of tools that enables you to upload not only images, but the pathway data themselves to the internet. Irrespective of whether you are a total beginner or a seasoned data scientist, it is helpful to be able to share the network data itself with your collaborators. A flat image file is nice, but if you give your collaborators the power to sift through the network representations of your data, that's a lot more powerful.
To that end, as suggested by Marco, consider tools like ndexbio, which interfaces with Cytoscape. Hope that helps ..