Gustavo Henrique Ferreira Cruz
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Update README.md
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README.md
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---
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license: cc-by-4.0
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configs:
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- config_name: default
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data_files:
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- split: train
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path: data/train-*
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dataset_info:
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features:
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- name: accession
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dtype: string
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- name: sequence
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- name: introns
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list:
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list:
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dtype: int64
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- name: proteins
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list:
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dtype: int64
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dtype: string
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dtype: int64
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splits:
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- name: train
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num_bytes: 11536678696
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num_examples: 1677609
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download_size: 5448417115
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dataset_size: 11536678696
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---
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license: cc-by-4.0
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+
configs:
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- config_name: default
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data_files:
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- split: train
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path: data/train-*
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+
dataset_info:
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features:
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- name: accession
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dtype: string
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- name: organism
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dtype: string
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- name: sequence
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dtype: string
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- name: introns
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list:
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- name: after
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dtype: string
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- name: before
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dtype: string
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- name: end
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dtype: int64
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- name: gene
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dtype: string
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- name: sequence
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dtype: string
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- name: start
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dtype: int64
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- name: exons
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list:
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- name: after
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dtype: string
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- name: before
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dtype: string
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- name: end
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dtype: int64
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- name: gene
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dtype: string
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- name: sequence
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dtype: string
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- name: start
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dtype: int64
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- name: proteins
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list:
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- name: end
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dtype: int64
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- name: gene
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dtype: string
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- name: sequence
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dtype: string
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- name: start
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dtype: int64
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+
splits:
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- name: train
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| 56 |
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num_bytes: 11536678696
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| 57 |
+
num_examples: 1677609
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| 58 |
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download_size: 5448417115
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dataset_size: 11536678696
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task_categories:
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- text-classification
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- token-classification
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- translation
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tags:
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- Exons
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- Introns
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- Proteins
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- DNA
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pretty_name: DNA Coding Regions
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size_categories:
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- 1M<n<10M
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---
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# DNA Coding Regions Dataset
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This is a curated collection of genomic sequences extracted directly from **NCBI GenBank**, designed to support research in **, **DNA-to-protein translation**, **gene structure analysis**, and **biological sequence modeling** with deep learning architectures.
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---
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## Source and Extraction Pipeline
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All records were extracted from **GenBank** using [Biopython](https://biopython.org/).
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The dataset construction followed a reproducible data processing pipeline written in Python, which:
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- Downloads and parses GenBank records.
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- Extracts **genomic DNA sequences**, their associated **exons**, **introns**, and **coding sequences (CDS)**.
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- Processes the `strand` orientation to produce normalized sequences.
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- Removes duplicate entries based on `(sequence, organism)` pairs.
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- Assembles each record into a structured JSONL format suitable for machine learning models.
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The GenBank **search query** used for data collection was:
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```
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"genomic DNA"[Filter]
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AND ("exon"[Feature Key] OR "intron"[Feature Key])
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AND "CDS"[Feature Key]
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AND ("3"[SLEN] : "16384"[SLEN])
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````
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You can find more information about the pipeline in the GitHub from the [DNA Coding Regions](https://github.com/GustavoHCruz/CodingDNATransformers) repository.
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---
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## Dataset Structure
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Each entry in the dataset corresponds to a **unique DNA sequence**, identified by its **GenBank accession**.
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The dataset is serialized in JSON Lines (`.jsonl`) format and can be loaded with the Hugging Face `datasets` library.
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### Example record
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```json
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{
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"accession": "NC_045512.2",
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"organism": "Homo sapiens",
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"sequence": "ATTAAAGGTTTATACCTTCCCAGGTAACAAACCAACCAACTTTCGAT...",
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"introns": [
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{
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"sequence": "TTGTAGACCAGTGCAGTA...",
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"start": 1450,
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"end": 1783,
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"gene": "ORF1ab",
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"before": "ATGCCDG",
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"after": "TAACAFG"
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}
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],
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"exons": [
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{
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"sequence": "ATGGACACAAGTCAGG...",
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"start": 1,
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"end": 1449,
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"gene": "ORF1ab",
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"before": null,
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"after": "GT"
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}
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],
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"proteins": [
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{
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"sequence": "MESLVPGFNEKTHVQLSLPVLQVRDVLVRGFGDSVEEVL...",
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"start": 1,
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"end": 4405,
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"gene": "ORF1ab"
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}
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]
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}
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````
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---
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## Field Descriptions
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| Field | Type | Description |
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| ------------- | ------ | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
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| **accession** | `str` | GenBank accession number for the DNA sequence. |
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| **organism** | `str` | Name of the organism from which the sequence was derived. |
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| **sequence** | `str` | The full genomic DNA sequence (processed strand). |
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| **introns** | `list` | List of intronic regions associated with this DNA sequence. Each item contains: <ul><li>`sequence`: only the nucleotide sequence of the intron</li><li>`start`, `end`: coordinates relative to the DNA sequence</li><li>`gene`: gene name when annotated</li><li>`before`, `after`: short flanking sequences</li></ul> |
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| **exons** | `list` | List of exonic regions associated with this DNA sequence. Same structure as `introns`. |
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| **proteins** | `list` | List of coding sequences (CDS) translated to amino acid sequences, with: <ul><li>`sequence`: protein sequence</li><li>`start`, `end`: coordinates in the DNA sequence</li><li>`gene`: gene name</li></ul> |
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---
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## Applications
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This dataset can be directly used for:
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* **DNA to protein translation modeling**
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* **Exon and Introns classification**
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* **Splicing prediction**
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* **Genomic representation learning**
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* **Bioinformatics-focused LLM pretraining (DAPT)**
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---
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## Loading Example
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```python
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from datasets import load_dataset
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dataset = load_dataset("gu-dudi/DNA_coding_regions")
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print(dataset)
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print(dataset["train"][0])
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```
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---
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## Dataset Metadata
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* **Source:** NCBI GenBank
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* **Processed with:** Biopython, Pandas, tqdm
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* **Maintainer:** [Gustavo Henrique Ferreira Cruz](https://huggingface.co/gu-dudi)
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* **License:** Open for research and educational use
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* **Format:** JSON Lines (UTF-8)
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---
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### Citation
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If you use this dataset in your research, please cite:
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> Cruz, G. H. F. (2025). *DNA Coding Regions Dataset: Genomic Sequences with Introns, Exons, and Protein Mappings Extracted from GenBank.*
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---
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### Version and Integrity
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* **Version:** 1.0
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* **Total entries:** 1,677,609
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* **Deduplication:** duplicates removed based on `(sequence, organism)` pair
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* **Strand normalization:** handled during extraction
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---
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### Notes
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* Coordinates (`start`, `end`) are **relative to the parent DNA sequence**.
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* `sequence` inside each **intron/exon** corresponds *only to that region* (not the full DNA).
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* Protein sequences are already **translated amino acid chains**, not nucleotide fragments.
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---
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*Developed as part of the Master’s research project on DNA sequence understanding and translation using deep learning models.*
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