File size: 7,226 Bytes
ce004b5 842ac8b 8e2950b 842ac8b ce004b5 842ac8b 8e2950b 842ac8b |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 |
---
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
<!-- Provide a quick summary of the dataset. -->
**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
<!-- 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. -->
### 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
<!-- If there is a paper or blog post introducing the dataset, the APA and Bibtex information for that should go in this section. -->
**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) |