Dataset Card for Dataset Name
Dataset Summary
This dataset contains datas being collected from Genbank. The dataset is organized in a way that it separate all the genes from an DNA , and was classified according to the region and coding type. In that way, people could get more detailed information regarding each DNA sequences. The dataset also contain source, which is the whole DNA sequence, where the user can use it to compare to each segment to see the exact location. The dataset contains 937 files with about 200 million data and 300-400 GB storage space. Therefore user can specify the number of files they are going to use by using the code below according to their own needs. If user want to download all of files, they can enter 937 as second arguement.
datasets.load_dataset('wyxu/Genome_database', num_urls = number of file you want to use)
Supported Tasks and Leaderboards
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Languages
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Dataset Structure
Data Instances
{DNA id: AP013063.1
Organism: Serratia marcescens SM39
year: 2017
region type:coding
specific_class: Protein
Product:thr operon leader peptide
sequence: ATGCGCAACATCAGCCTGAAAACCACAATTATTACCACCACCGATACCACAGGTAACGGGGCGGGCTGA
gc_content:0.52173913
translation code: MRNISLKTTIITTTDTTGNGAG
start_position: 207
end_position: 276}
Data Fields
DNA id: id number for the whole DNA sequence, sequences with same DNA id are from same DNA
Organism: Organism of the DNA
year: the year of the DNA sequence
region type: determine the general type of the sequence. For all the type that is typically classified as coding region, it was named with coding; while others including those that are case dependent were named according to their own type such as regulator, repeat_region,gap, intron,extron, etc.(Note: when classifying coding type, all the CDS, mRNA, tmRNA, tRNA,rRNA and others such as propetide, sig_propetide,mat_propetide was classified as coding. In order to minimize the missing coding part, all the other categories which has associated product was also classified as coding )
specific class: if the sequence is coding sequence, it would be classified according to their production type such as RNA, Protein. The regulators would also be classified by their own class such as terminator, ribosome
Product : if the sequence produce protein, the product name would be listed
sequence: the actual sequence
gc_content: the gc_content of the sequence
translation code: if the sequence produce protein, then the translation code would be provided as a reference
start_position: the start position of the segment
end_position: the end position of the segment
Data Splits
first 80% of files was used as training dataset, while last 20% was used as testing dataset
Dataset Creation
Curation Rationale
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Source Data
The data collected are all from the most recent release of genbank, genbank 255.
Initial Data Collection and Normalization
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Who are the source language producers?
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Annotations
Annotation process
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Who are the annotators?
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Personal and Sensitive Information
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Considerations for Using the Data
Social Impact of Dataset
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Discussion of Biases
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Other Known Limitations
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Additional Information
Dataset Curators
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Licensing Information
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Citation Information
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Contributions
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