File size: 3,737 Bytes
317b3a3 8df8ff8 e9266af 8df8ff8 e9266af 8df8ff8 317b3a3 d464b10 a4f1362 d464b10 a4f1362 d464b10 a4f1362 d464b10 a4f1362 d464b10 a4f1362 d464b10 7905676 d464b10 7905676 d464b10 7905676 d464b10 7905676 d464b10 a4f1362 7905676 d464b10 |
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 |
---
license: cc-by-nc-nd-4.0
dataset_info:
features:
- name: reference_segment_id
dtype: string
- name: masked_segment
dtype: string
- name: position_to_mask
dtype: int64
- name: masked_segment_id
dtype: int64
- name: contig_id
dtype: string
- name: segment_id
dtype: string
- name: strand
dtype: string
- name: seq_start
dtype: int64
- name: seq_end
dtype: int64
- name: segment_start
dtype: int64
- name: segment_end
dtype: int64
- name: class_label
dtype: string
- name: segment_length
dtype: int64
- name: original_segment
dtype: string
splits:
- name: train
num_bytes: 43505486
num_examples: 40000
download_size: 19049179
dataset_size: 43505486
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
# Dataset Description
This dataset was used to evaluate different models on the masking exercise, measuring how well the different models can recover the original character.
## Dataset Overview
The dataset is compiled from the RefSeq database and other sources, focusing on ESKAPE pathogens. The genomic features were sampled randomly, followed by contiguous segmentation. This dataset contains various segments with lengths: [128, 256, 512, 1024]. The segments were randomly selected, and one of the characters was replaced by '*' (masked_segment column) to create a masking task. The reference_segment contains the original, non-replaced nucleotides. We performed 10,000 maskings per set, with a maximum of 2,000 genomic features. Only the genomic features: 'CDS', 'intergenic', 'pseudogene', and 'ncRNA' were considered.
## Data Fields
- `reference_segment_id`: A mapping of segment identifiers to their respective reference IDs in the database.
- `masked_segment`: The DNA sequence of the segment with certain positions masked (marked with '*') for prediction or testing purposes.
- `position_to_mask`: The specific position(s) in the sequence that have been masked, indicated by index numbers.
- `masked_segment_id`: Unique identifiers assigned to the masked segments. (unique only with respect to length)
- `contig_id`: Identifier of the contig to which the segment belongs.
- `segment_id`: Unique identifier for each genomic segment (same as reference segment id).
- `strand`: The DNA strand of the segment, indicated as '+' (positive) or '-' (negative).
- `seq_start`: Starting position of the segment within the contig.
- `seq_end`: Ending position of the segment within the contig.
- `segment_start`: Starting position of the genomic segment in the sequence.
- `segment_end`: Ending position of the genomic segment in the sequence.
- `label`: Category label for the genomic segment (e.g., 'CDS', 'intergenic').
- `segment_length`: The length of the genomic segment.
- `original_segment`: The original genomic sequence without any masking.
## Usage
This dataset is intended for academic and research purposes. Users are encouraged to use this dataset in the development and evaluation of bioinformatics models, especially those related to genomic studies.
## Contact Information
For any questions, feedback, or contributions regarding the datasets or ProkBERT, please feel free to reach out:
- **Name**: Balázs Ligeti
- **Email**: [email protected]
We welcome your input and collaboration to improve our resources and research.
## Citation
```bibtex
@Article{ProkBERT2024,
author = {Ligeti, Balázs et al.},
journal = {Frontiers in Microbiology},
title = {{ProkBERT} family: genomic language models},
year = {2024},
volume = {14},
URL = {https://www.frontiersin.org/articles/10.3389/fmicb.2023.1331233},
DOI = {10.3389/fmicb.2023.1331233}
}
|