metadata
language:
- en
license: cc-by-4.0
task_categories:
- text-generation
- token-classification
- question-answering
tags:
- biology
- kluyveromyces-marxianus
- yeast
- genomics
- proteomics
- bioinformatics
size_categories:
- 10K<n<100K
dataset_info:
features:
- name: id
dtype: string
- name: source
dtype: string
- name: category
dtype: string
- name: gene_id
dtype: string
- name: gene_name
dtype: string
- name: gene_symbol
dtype: string
- name: protein_id
dtype: string
- name: protein_name
dtype: string
- name: sequence
dtype: string
- name: title
dtype: string
- name: abstract
dtype: string
- name: full_text
dtype: string
- name: pmid
dtype: string
- name: doi
dtype: string
- name: authors
dtype: string
- name: journal
dtype: string
- name: year
dtype: string
- name: timestamp
dtype: string
splits:
- name: validation
num_bytes: 50247
num_examples: 50
- name: test
num_bytes: 26233
num_examples: 25
- name: train
num_bytes: 181691
num_examples: 98
download_size: 778393
dataset_size: 258171
configs:
- config_name: default
data_files:
- split: train
path: cell3_semantic/train-*
- split: validation
path: cell2_splits/validation-*
- split: test
path: cell2_splits/test-*
𧬠Kluyveromyces marxianus Quantum Dataset v10.0.0
Overview
Comprehensive multi-omics dataset for Kluyveromyces marxianus collected using quantum-grade async streaming pipeline, fully integrated with Cell 0's structured directory system.
Statistics
| Metric | Value |
|---|---|
| Total Collected | 3,836 |
| Total Local Saved | 3,836 |
| Version | v10.0.0 |
| Collection Date | 2025-11-10 |
Data Categories & Local Storage
- Literature: 1,417 records (local: 1,417)
- Proteins: 1,001 records (local: 1,001)
- PMC Full-Text: 1,000 records (local: 1,000)
- SRA Sequencing: 352 records (local: 352)
- GEO Expression: 48 records (local: 48)
- Nucleotide Sequences: 18 records (local: 18)
Cell 0 Integration
This dataset strictly respects Cell 0's directory structure. Only folders actively used by collectors:
km_dataset/
βββ genomic/ # Genes, nucleotide sequences
βββ protein/ # Protein sequences
βββ literature/ # PubMed, PMC articles
βββ expression/ # GEO, SRA sequencing data
βββ checkpoints/
βββ cell1_quantum/ # Collection checkpoints
Note: Cell 0 also creates pathway/, interaction/, structure/, repository/ folders, but current collectors don't produce data for these categories yet.
HuggingFace Organization
Data is organized by phase using data_dir to prevent overwrites:
cell1_genes- Gene datacell1_proteins- Protein sequencescell1_literature- PubMed articlescell1_pmc- PMC full-text articlescell1_sequences- Nucleotide sequencescell1_geo- GEO expression datacell1_sra- SRA sequencing datacell1_splits- Train/validation/test splits
Usage
Load All Data
from datasets import load_dataset, concatenate_datasets
# Load all phases (FIXED: correct data_dir names)
all_data = []
for phase in ['cell1_genes', 'cell1_proteins', 'cell1_literature',
'cell1_pmc', 'cell1_sequences', 'cell1_geo', 'cell1_sra']:
try:
ds = load_dataset("Milad96/Kluyveromyces-marxianus", split='train', data_dir=phase)
all_data.append(ds)
except:
pass
combined = concatenate_datasets(all_data)
Load Specific Phase
# Load only genes
genes = load_dataset("Milad96/Kluyveromyces-marxianus", split='train', data_dir='cell1_genes')
# Load only literature
literature = load_dataset("Milad96/Kluyveromyces-marxianus", split='train', data_dir='cell1_literature')
Load Splits
dataset = load_dataset("Milad96/Kluyveromyces-marxianus", data_dir='cell1_splits')
train = dataset['train']
val = dataset.get('validation')
test = dataset.get('test')
Citation
@dataset{km_quantum_v10_0_0,
title={Kluyveromyces marxianus Quantum Dataset},
version={v10.0.0},
year={2025},
url={https://huggingface.co/datasets/Milad96/Kluyveromyces-marxianus}
}
Status: β Production Ready Quality: π Quantum Grade Pipeline: Async Streaming v10.0 + Cell 0 Full Integration Local Storage: β All records saved in structured folders Overwrite Protection: β Phase-specific data_dirs