Update README.md

README.md

@@ -993,49 +993,155 @@ size_categories:
 # PISCES-CulledPDB
 
 Curated protein chain tables from PISCES/CullPDB: one row per chain with sequence and metadata.
+Use the **subset dropdown** in the Hugging Face Data Viewer to switch between the main table and 242 curation subsets.
 
-**Dataset:** [PRMegathon26/PISCES-CulledPDB](https://huggingface.co/datasets/PRMegathon26/PISCES-CulledPDB)
 
-Use the **subset dropdown** in the Hugging Face Data Viewer to switch between the main table and 242 curation subsets.
+```
+---
+license: apache-2.0
+task_categories:
+- protein-structure-prediction
+- bioinformatics
+language:
+- en
+pretty_name: PISCES Culled Protein Chains
+size_categories:
+- 100K<n<1M
+---
 
-## Summary
+# Dataset Card for PISCES Protein Sequence Cull Sets
 
-| Item | Description |
-|------|-------------|
-| **Main CSV** | `curated_csv/cullpdb_combined_chains.csv` — full chain table |
-| **Subsets** | `curated_csv/subsets/*.csv` — 242 files (same columns) |
-| **Index** | `curated_csv/cullpdb_list_fasta_index.csv` |
+## Dataset Details
+
+### Dataset Description
+
+The **PISCES dataset** provides curated sets of protein sequences from the Protein Data Bank (PDB) based on user-defined sequence identity and structural quality criteria.
+
+PISCES enables users to obtain **non-redundant subsets of protein chains** by applying filters such as:
+
+- Sequence identity
+- Experimental resolution
+- R-factor
+- Chain length
+- Experimental method (e.g., X-ray, NMR, cryo-EM)
+
+The goal of PISCES is to **maximize structural reliability while minimizing sequence redundancy**.
+
+Unlike other culling tools that rely on BLAST or global alignments, PISCES uses **PSI-BLAST** to generate position-specific scoring matrices. This enables more accurate detection of homologous relationships, particularly **below 40% sequence identity**.
+
+---
+
+## Dataset Sources
+
+**Original Server:**  
+PISCES
+
+**Primary Reference:**  
+Wang, G., & Dunbrack, R. L., Jr. (2003). *Bioinformatics*, 19(12), 1589–1591.
+
+**Availability:**  
+https://dunbrack.fccc.edu/pisces/
+
+**Contact:**  
+rldunbrack@fccc.edu
+
+---
 
-Full list of subset paths: `curated_csv/dataset_metadata.json` (keys `data_paths`, `subset_paths`).
+## Citation
 
-## Columns (chain CSVs)
+```bibtex
+@article{wang2003pisces,
+  title={PISCES: a protein sequence culling server},
+  author={Wang, Guoying and Dunbrack, Roland L. Jr.},
+  journal={Bioinformatics},
+  volume={19},
+  number={12},
+  pages={1589--1591},
+  year={2003},
+  publisher={Oxford University Press}
+}
+dditional Attribution
 
-| Column | Description |
-|--------|-------------|
-| **pdb_chain** | PDB chain ID (e.g. 1ABC_A) |
-| **pdb** | PDB ID (first 4 chars) |
-| **chain** | Chain ID |
-| **sequence** | Amino acid sequence (one-letter) |
-| **len** | Sequence length |
-| **method** | Experimental method (e.g. XRAY, NMR) |
-| **resolution** | Resolution in Å (per structure) |
-| **rfac** | R-factor |
-| **freerfac** | Free R-factor |
-| **pc** | Sequence identity cutoff % used for this subset |
-| **no_breaks** | Whether chain has no breaks (yes/no) |
-| **R** | R-factor cutoff used for this subset |
-| **source_list** | Subset list basename (identifies curation parameters) |
+Recurated in Hugging Face by: Akshaya Narayanasamy (akshayanarayanasamy[at]gmail.com)
 
-## Usage
+License: Apache-2.0
 
-```python
+Primary Domain: Structural Bioinformatics / Computational Biology
+
+Uses
+
+This dataset can be used for:
+
+Generating non-redundant protein chain datasets for machine learning and statistical analysis
+
+Benchmarking protein structure prediction or homology modeling algorithms
+
+Studying evolutionary relationships using sequence identity thresholds
+
+Designing high-quality training datasets filtered by structural resolution and reliability
+
+Building structure-based machine learning datasets for protein modeling
+
+Dataset Structure
+
+Each record corresponds to one protein chain.
+| Field       | Description                                         |
+| ----------- | --------------------------------------------------- |
+| PDB         | Protein Data Bank identifier                        |
+| Chain       | Chain identifier within the PDB structure           |
+| Sequence    | Amino acid sequence of the chain                    |
+| Len         | Sequence length                                     |
+| Method      | Experimental method used to determine the structure |
+| Rfac        | Crystallographic R-factor                           |
+| Freerfac    | Free R-factor                                       |
+| Pc          | Maximum pairwise sequence identity threshold        |
+| Break       | Indicates whether the chain contains breaks         |
+| R           | Resolution of the structure                         |
+| Source_list | Original PISCES list source                         |
+
+Sequences are sorted by structural quality metrics such as resolution and R-factor and then culled based on mutual sequence identity thresholds to ensure non-redundancy.
+| Item         | Description                                                  |
+| ------------ | ------------------------------------------------------------ |
+| **Main CSV** | `curated_csv/cullpdb_combined_chains.csv` — full chain table |
+| **Subsets**  | `curated_csv/subsets/*.csv` — 242 files (same columns)       |
+| **Index**    | `curated_csv/cullpdb_list_fasta_index.csv`                   |
+Full list of subset paths:
+curated_csv/dataset_metadata.json (keys data_paths, subset_paths).
 from huggingface_hub import hf_hub_download
 import pandas as pd
 
-path = hf_hub_download(repo_id="PRMegathon26/PISCES-CulledPDB", filename="curated_csv/cullpdb_combined_chains.csv", repo_type="dataset")
+path = hf_hub_download(
+    repo_id="PRMegathon26/PISCES-CulledPDB",
+    filename="curated_csv/cullpdb_combined_chains.csv",
+    repo_type="dataset"
+)
+
 df = pd.read_csv(path)
-```
+File Naming Convention
+
+Each dataset file follows the naming pattern:
+cullpdb_pc{pc}_res{res_min}-{res_max}[_noBrks]_len40-10000_R{R}_{methods}_d2026_01_26_chains{N}
+Parameters
+
+pc – Percent sequence identity cutoff
+Examples: 15, 20, 25, …, 95
+
+res – Resolution range (Å)
+Examples: 0.0-1.0, 0.0-2.5, 0.0-5.0
+
+noBrks – Optional flag indicating chains with breaks are excluded
+
+R – R-factor cutoff
+Possible values: 0.2, 0.25, 0.3, 1.0
+
+methods – Experimental structure determination methods
+
+Possible values:
+
+Xray
+
+Xray+EM
 
-## License
+Xray+Nmr+EM
 
-cc-by-4.0
+N – Total number of chains in the list