The Molecular Oncology Almanac attempts to capture the current body of knowledge on how genetic alterations affect clinical actionability. As the field of precision medicine grows, the quantity of research on how specific alterations affect therapeutic response and patient prognosis expands at an increasing rate. The Molecular Oncology Almanac seeks to curate this information from the literature, increasing the abilities of clinicians and researchers alike to rapidly assess the importance of an alteration.
The contents of the Molecular Oncology Almanac may be downloaded here.
Each feature represented in the almanac (e.g., "somatic variant," "knockdown," etc.) is represented in a separate tab-separated value (TSV) file.
The collection of TSV files representing the entire Almanac database is provided in a single ZIP file. The knowledge base can also be programmatically interfaced
with through our API endpoints.
Please consider suggesting relationships through our web form or our Google Chrome extension.
The Molecular Oncology Almanac categorizes each curated assertion by the strength of evidence asserting the relationship between a given molecular feature and clinical action. The levels used are:
|FDA-Approved||The Food and Drug Association (FDA) recognizes an association between the alteration and recommended clinical action.|
|Guideline||This relationship is catalogued as a guideline for standard of care treatment.|
|Clinical trial||The alteration is or has been used as an eligibility criterion for a clinical trial.|
|Clinical evidence||The relationship is reported in a clinical study that did not directly involve a clinical trial.|
|Preclinical evidence||This relationship is reported in a study involving mice, cell lines, or patient derived models.|
|Inferential evidence||The relationship is inferred as a result of mathematical modeling or an association between molecular features.|
The Molecular Oncology Almanac draws primarily from primary research articles, review articles, and the NCCN guidelines. Data is curated through both expert review and using a Natural Language Processing (NLP) approach to select potentially informative articles from PubMed.
The Molecular Oncology Almanac is co-developed with the PHIAL (Precision Heuristics for Interpreting the Alteration Landscape) algorithm, which draws from Molecular Oncology Almanac and other alterations databases to classify patient tumor data.
The Molecular Oncology Almanac is made available under the Open Database License (ODbL). A "plain-language" summary of the ODbL is available here.
You are free to share and modify the contents of The Molecular Oncology Almanac under the following restrictions:
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