Franklin applies advanced Natural Language Processing (NLP) algorithms that scan the entire web for evidence found in scientific papers, and "read" through the entire text, not only the abstracts.

All the articles are displayed under the "Publications" tab which shows the article title, scope (for SNP interpretation), authors, journal, and publication year. Clicking on the article tile shows the full abstract.

Note that, when searching for a single nucleotide variant, articles highlighted with a star are articles that mention your specific variant.

Below the article abstract, Franklin displays tags with the curated evidence from the article. On the left, there are genes and variants mentioned in the text, and on the right phenotypes, conditions, and drugs (if applicable). Blue tags highlight pieces of evidence that are relevant to the curated variant and case phenotypes. Hovering over any tag will highlight the relevant text in the abstract, so you can locate it easily.

When working on the interpretation of an SNP, the list can be filtered by scope to show only articles mentioning the specific variant, amino acid, domain, or the entire gene. In the case of CNVs and other structural variants, users are able to filter by one or multiple genes. Another option is to filter by date.

The list default sort is by relevance, showing first the articles in the narrow variant scope that are also related to the case phenotypes.

As mentioned above, Franklin community members are encouraged to link additional articles to Franklin's database.

In order to link a new article, simply click on the button in the variant community feed on the right, type the PMID and add your insights, The article will immediately be added to the list and displayed in the feed along with your comment.

If you wish to look for further findings on your own, click on the Google Scholar button. This will run a complex query for more papers via the Google academic search engine, covering all the possible nomenclatures for the variant and the genes associated with it. In the event you found something we missed, we encourage you to simply add it to the platform and contribute to the Franklin Community to improve genetic diagnosis worldwide.