--- dataset_info: features: - name: pmid dtype: string - name: sentence dtype: string - name: cancer_type dtype: string - name: gene struct: - name: name dtype: string - name: pos sequence: int64 - name: cancer struct: - name: name dtype: string - name: pos sequence: int64 - name: CGE dtype: string - name: CCS dtype: string - name: PT dtype: string - name: IGE dtype: string - name: expression_change_keyword_1 struct: - name: name dtype: string - name: pos sequence: int64 - name: type dtype: string - name: expression_change_keyword_2 struct: - name: name dtype: string - name: pos sequence: int64 - name: type dtype: string splits: - name: train num_bytes: 361666 num_examples: 821 download_size: 99496 dataset_size: 361666 configs: - config_name: default data_files: - split: train path: data/train-* license: cc-by-2.0 task_categories: - text-classification language: - en tags: - biology - cancer - gene - medical pretty_name: CoMAGC size_categories: - n<1K --- # Dataset Card for CoMAGC ## Dataset Description - **Website:** http://biopathway.org/CoMAGC/ - **Paper:** [CoMAGC: a corpus with multi-faceted annotations of gene-cancer relations](https://bmcbioinformatics.biomedcentral.com/articles/10.1186/1471-2105-14-323) #### Dataset Summary **CoMAGC Dataset Summary:** CoMAGC is a corpus with multi-faceted annotations of gene-cancer relations. CoMAGC consists of 821 sentences collected from MEDLINE abstracts, and the sentences are about three different types of cancers, or prostate, breast and ovarian cancers. In CoMAGC, a piece of annotation is composed of four semantically orthogonal concepts that together express 1) how a gene changes, 2) how a cancer changes and 3) the causality between the gene and the cancer. The four concepts that constitute the multi-faceted annotation scheme are Change in Gene Expression (CGE), Change in Cell State (CCS), Proposition Type (PT) and Initial Gene Expression level (IGE). - CGE captures whether the expression level of a gene is `increased` or `decreased` in a cell - CCS captures the way how the cell changes together with a gene expression level change - `normalTOnormal`: The cell or tissue remains as normal after the change in the gene’s expression level. - `normalTOcancer`: The cell or tissue acquires cancerous properties as the gene expression level changes; some cancerous properties are strengthened. - `cancerTOcancer`: There's no change in the cancerous properties of the cell or tissue despite the change in the expression level of the gene. - `cancerTOnormal`: The cell or tissue loses some cancerous properties as the gene expression level changes; some cancerous properties are weakened. - `unidentifiable`: The information about whether or not the gene expression level change accompanies cell or tissue state change is not provided. - PT captures whether the causality between the gene expression change and the cell property change - `observation`: Cell or tissue change accompanied by the gene expression level change is reported as observed but the causality between the two is not claimed. | - `causality`: The causality between the gene expression level change and the cell or tissue change is claimed. - IGE captures the initial expression level of a gene before the change in its expression level - `up-regulated`: The initial gene expression level is higher than the expression level of the gene in the normal state. - `down-regulated`: The initial gene expression level is lower than the expression level of the gene in the normal state. - `unchanged`: The initial gene expression level is comparable to the expression level of the gene in the normal state. - `unidentifiable`: The information about the initial gene expression level is not provided. | The original dataset in XML format is available here: http://biopathway.org/CoMAGC/ We converted the dataset to a JSONL format before pushing the data to the hub. ### Languages The language in the dataset is English. ## Dataset Structure ### Dataset Instances An example of 'train' looks as follows: ```json { "pmid": "11722842.s0", "sentence": "Isolation and characterization of the major form of human MUC18 cDNA gene and correlation of MUC18 over-expression in prostate cancer cell lines and tissues with malignant progression.", "cancer_type": "prostate", "gene": { "name": "MUC18", "pos": [93, 97] }, "cancer": { "name": "prostate cancer", "pos": [118, 132] }, "CGE": "increased", "CCS": "normalTOcancer", "PT": "observation", "IGE": "unchanged", "expression_change_keyword_1": { "name": "over-expression", "pos": [99, 113], "type": "Gene_expression" }, "expression_change_keyword_2": { "name": "over-expression", "pos": [99, 113], "type": "Positive_regulation" } } ``` ### Data Fields - `pmid`: the id of this sentence, a `string` feature. - `sentence`: the text of this sentence, a `string` feature. - `cancer_type`: the type of cancer in this sentence, a `string` feature. - `gene`: gene entity - `pos`: character offsets of the gene entity, a list of `int32` features. - `name`: gene entity text, a `string` feature. - `cancer`: cancer entity - `pos`: character offsets of the cancer entity, a list of `int32` features. - `name`: cancer entity text, a `string` feature. - `CGE`: change in gene expression, a `string` feature. - `CCS`: change in cell state, a `string` feature. - `PT`: proposition type, a `string` feature. - `IGE`: initial gene expression, a `string` feature. - `expression_change_keyword_1`: a `dict` - `name`: keyword text, a `string` feature. - `pos`: character offsets of the keyword, a list of `int32` features. - `type`: type of the expression change keyword, a `string` feature. - `expression_change_keyword_2`: a `dict` - `name`: keyword text, a `string` feature. - `pos`: character offsets of the keyword, a list of `int32` features. - `type`: type of the expression change keyword, a `string` feature. ## Citation **BibTeX:** ``` @article{lee2013comagc, title={CoMAGC: a corpus with multi-faceted annotations of gene-cancer relations}, author={Lee, Hee-Jin and Shim, Sang-Hyung and Song, Mi-Ryoung and Lee, Hyunju and Park, Jong C}, journal={BMC bioinformatics}, volume={14}, pages={1--17}, year={2013}, publisher={Springer} } ``` **APA:** - Lee, H. J., Shim, S. H., Song, M. R., Lee, H., & Park, J. C. (2013). CoMAGC: a corpus with multi-faceted annotations of gene-cancer relations. BMC bioinformatics, 14, 1-17. ## Dataset Card Authors [@phucdev](https://github.com/phucdev)