> For the complete documentation index, see [llms.txt](https://docs.mithrl.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.mithrl.com/platform/key-concepts.md). # Key Concepts ## Raw Data (Files) Raw data can be in the form of fastq files, matrix data, or tabular data (csv, tsv, etc). Such files can be outputs from scientific instruments or processed data files from such instruments or other bioinformatic sources. These files may be derivatives of image files (ex. processed matrix data from spatial images, cell paintings, etc), proteomics platforms (ex. high throughput mass spectrometry, antibody protein arrays, etc.), or gene expression platforms (ex.microarray). ## Datasets Mithrl datasets form the foundation of the Mithrl Scientific Decision Engine. A Mithrl dataset is in the MFF format (Mithrl Friendly Format) and is the result of cleaning raw data files via nomenclature standardization, normalization, and harmonization. Once the dataset is created it is then ready for any agentic processing to allow acalable, and flexible tertiary analysis and hypothesis generation. This data clean up process also allows for ready true cross-dataset and cross-omics analysis. ## Analysis An analysis is the series of natural-language queries (questions) a user asks of one or more datasets. For example, a user might take the results of a one-time single-cell experiment then ask for a volcano plot followed by a list of the top DEGs, followed by a list of the enriched pathways, followed by predicted targets. That entire thread would be an analysis. ## Projects Projects are an aggregation of Mithrl datasets that are related to a specific research goal. Projects may include multiple analysis threads, multiple datasets and across multiple modalities. {% hint style="info" %} Still have questions? We have answers. Contact us at {% endhint %} --- # Agent Instructions This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com. ## Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter, and the optional `goal` query parameter: ``` GET https://docs.mithrl.com/platform/key-concepts.md?ask=&goal= ``` `ask` is the immediate question: it should be specific, self-contained, and written in natural language. `goal` is optional and describes the broader end goal you are ultimately trying to accomplish on behalf of the user. GitBook uses it to tailor the answer towards what is most useful for that goal. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.