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README.md
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data_files:
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- split: train
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path: data/train-*
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---
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data_files:
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- split: train
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path: data/train-*
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license: cc-by-2.0
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task_categories:
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- text-classification
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language:
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- en
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tags:
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- biology
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- cancer
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- gene
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pretty_name: CoMAGC
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size_categories:
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- n<1K
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---
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# Dataset Card for CoMAGC
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## Dataset Description
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- **Website:** http://biopathway.org/CoMAGC/
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- **Paper:** [CoMAGC: a corpus with multi-faceted annotations of gene-cancer relations](https://bmcbioinformatics.biomedcentral.com/articles/10.1186/1471-2105-14-323)
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#### Dataset Summary
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<!-- Provide a quick summary of the dataset. -->
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**CoMAGC Dataset Summary:**
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CoMAGC is a corpus with multi-faceted annotations of gene-cancer relations.
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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.
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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.
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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).
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- CGE captures whether the expression level of a gene is `increased` or `decreased` in a cell
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- CCS captures the way how the cell changes together with a gene expression level change
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- `normalTOnormal`: The cell or tissue remains as normal after the change in the gene’s expression level.
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- `normalTOcancer`: The cell or tissue acquires cancerous properties as the gene expression level changes; some cancerous properties are strengthened.
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- `cancerTOcancer`: There's no change in the cancerous properties of the cell or tissue despite the change in the expression level of the gene.
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- `cancerTOnormal`: The cell or tissue loses some cancerous properties as the gene expression level changes; some cancerous properties are weakened.
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- `unidentifiable`: The information about whether or not the gene expression level change accompanies cell or tissue state change is not provided.
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- PT captures whether the causality between the gene expression change and the cell property change
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- `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. |
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- `causality`: The causality between the gene expression level change and the cell or tissue change is claimed.
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- IGE captures the initial expression level of a gene before the change in its expression level
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- `up-regulated`: The initial gene expression level is higher than the expression level of the gene in the normal state.
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- `down-regulated`: The initial gene expression level is lower than the expression level of the gene in the normal state.
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- `unchanged`: The initial gene expression level is comparable to the expression level of the gene in the normal state.
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- `unidentifiable`: The information about the initial gene expression level is not provided. |
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The original dataset in XML format is available here: http://biopathway.org/CoMAGC/
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We converted the dataset to a JSONL format.
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### Languages
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The language in the dataset is English.
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## Dataset Structure
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<!-- This section provides a description of the dataset fields, and additional information about the dataset structure such as criteria used to create the splits, relationships between data points, etc. -->
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### Dataset Instances
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An example of 'train' looks as follows:
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```json
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{
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"pmid": "11722842.s0",
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"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.",
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"cancer_type": "prostate",
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"gene": {
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"name": "MUC18",
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"pos": [93, 97]
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},
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"cancer": {
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"name": "prostate cancer",
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"pos": [118, 132]
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},
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"CGE": "increased",
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"CCS": "normalTOcancer",
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"PT": "observation",
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"IGE": "unchanged",
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"expression_change_keyword_1": {
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"name": "over-expression",
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"pos": [99, 113],
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"type": "Gene_expression"
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},
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"expression_change_keyword_2": {
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"name": "over-expression",
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"pos": [99, 113],
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"type": "Positive_regulation"
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}
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}
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```
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### Data Fields
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- `pmid`: the id of this sentence, a `string` feature.
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- `sentence`: the text of this sentence, a `string` feature.
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- `cancer_type`: the type of cancer in this sentence, a `string` feature.
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- `gene`: gene entity
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- `pos`: character offsets of the gene entity, a list of `int32` features.
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- `name`: gene entity text, a `string` feature.
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- `cancer`: cancer entity
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- `pos`: character offsets of the cancer entity, a list of `int32` features.
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- `name`: cancer entity text, a `string` feature.
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- `CGE`: change in gene expression, a `string` feature.
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- `CCS`: change in cell state, a `string` feature.
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- `PT`: proposition type, a `string` feature.
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- `IGE`: initial gene expression, a `string` feature.
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- `expression_change_keyword_1`: a `dict`
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- `name`: keyword text, a `string` feature.
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- `pos`: character offsets of the keyword, a list of `int32` features.
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- `type`: type of the expression change keyword, a `string` feature.
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- `expression_change_keyword_2`: a `dict`
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- `name`: keyword text, a `string` feature.
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- `pos`: character offsets of the keyword, a list of `int32` features.
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- `type`: type of the expression change keyword, a `string` feature.
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## Citation
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<!-- If there is a paper or blog post introducing the dataset, the APA and Bibtex information for that should go in this section. -->
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**BibTeX:**
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```
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@article{lee2013comagc,
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title={CoMAGC: a corpus with multi-faceted annotations of gene-cancer relations},
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author={Lee, Hee-Jin and Shim, Sang-Hyung and Song, Mi-Ryoung and Lee, Hyunju and Park, Jong C},
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journal={BMC bioinformatics},
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volume={14},
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pages={1--17},
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year={2013},
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publisher={Springer}
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}
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```
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**APA:**
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- 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.
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## Dataset Card Authors
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[@phucdev](https://github.com/phucdev)
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