Scientists don't just want to find insights within their data - they want to tell a story with it.
Learning more about a gene feels like searching for a needle in a haystack. Fragmented information lives across various resources, leaving it to the scientist to put all of the pieces together. The process of finding gene information and connecting it back to a research hypothesis is time consuming.
What scientists care about is how their gene of interest is relevant in the context of their own data. And yet, these resources live independently of their data, thus making it difficult for them to find insights.
Instead of manually visiting each resource to find information about a gene, what if we could consolidate them into a singular interface so that scientists could easily access this information? Better yet, what if we could integrate their data directly with gene information, enabling them to discover direct relationships between their gene of interest and their own datasets?
With the Knowledge Engine, you can accomplish both.
In the Knowledge Engine, you can retrieve a plethora of information about your gene of interest all in one place without having to open up multiple tabs in your browser.
Receive a high-level overview of your searched gene, including a gene description, gene ID, transcript isoforms and protein.
Explore consolidated public consortiums that tie back to your gene of interest.
Retrieve papers relevant to your searched gene and filter by publication type & date.
Explore papers that have a gene reference into function.
Explore how your gene of interest interacts with other genes. Dynamically change the confidence threshold to observe gene relationships.
Explore how your gene of interest is correlated or causal to specific diseases.
This is where you'll get the most value out of the Knowledge Engine. Beyond consolidating all of this gene information for you, we integrate these insights directly with your data. In the observation tab, you'll be able to see how your gene of interest operates in any of the datasets you've uploaded to your organization in the BioBox Platform.
For example, let's say you've uploaded 8 RNA samples and their respective datasets. In the Knowledge Engine, you will be able to see how a gene operates across all 8 of your datasets, enabling you to build a comprehensive story with your research.
It is common for software and tools to analyze data on a sample-by-sample basis. However the onus is on the scientist to manually find relationships between their samples. We want to provide the tools for scientists to analyze multi-samples in a singular interface and help them build a holistic view of their research.