Datasets:

RosettaCommons
/

PISCES-CulledPDB

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 ---
-license: apache-2.0
 ---
-As of 2026 January
-# Dataset Card for Dataset Name
-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 allows users to obtain non-redundant subsets of protein chains by applying filters such as sequence identity, resolution, R-value, chain length, and experiment type (e.g., X-ray, NMR).
-Unlike other culling tools that rely on BLAST or global alignments, PISCES uses PSI-BLAST to create position-specific scoring matrices for more accurate detection of homologous relationships, especially below 40% sequence identity. The server supports culling of:
-<!-- Provide a quick summary of the dataset. -->
-This dataset card aims to be a base template for new datasets. It has been generated using [this raw template](https://github.com/huggingface/huggingface_hub/blob/main/src/huggingface_hub/templates/datasetcard_template.md?plain=1).
-## Dataset Details
-### Dataset Description
-<!-- Provide a longer summary of what this dataset is. -->
-- **Recurated in Hugging Face by:** Akshaya Narayanasamy
-- **Funded by [optional]:** [More Information Needed]
-- **Shared by [optional]:** [More Information Needed]
-- **Language(s) (NLP):** [More Information Needed]
-- **License:** [More Information Needed]
-### Dataset Sources [optional]
-<!-- Provide the basic links for the dataset. -->
-- **Repository:** [More Information Needed]
-- **Paper [optional]:** [More Information Needed]
-- **Demo [optional]:** [More Information Needed]
-## Uses
-<!-- Address questions around how the dataset is intended to be used. -->
-### Direct Use
-<!-- This section describes suitable use cases for the dataset. -->
-[More Information Needed]
-### Out-of-Scope Use
-<!-- This section addresses misuse, malicious use, and uses that the dataset will not work well for. -->
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-## Dataset Structure
-<!-- This section provides a description of the dataset fields, and additional information about the dataset structure such as criteria used to create the splits, relationships between data points, etc. -->
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-## Dataset Creation
-### Curation Rationale
-<!-- Motivation for the creation of this dataset. -->
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-### Source Data
-<!-- This section describes the source data (e.g. news text and headlines, social media posts, translated sentences, ...). -->
-#### Data Collection and Processing
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-#### Who are the source data producers?
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-### Annotations [optional]
-<!-- If the dataset contains annotations which are not part of the initial data collection, use this section to describe them. -->
-#### Annotation process
-<!-- This section describes the annotation process such as annotation tools used in the process, the amount of data annotated, annotation guidelines provided to the annotators, interannotator statistics, annotation validation, etc. -->
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-#### Who are the annotators?
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-#### Personal and Sensitive Information
-<!-- State whether the dataset contains data that might be considered personal, sensitive, or private (e.g., data that reveals addresses, uniquely identifiable names or aliases, racial or ethnic origins, sexual orientations, religious beliefs, political opinions, financial or health data, etc.). If efforts were made to anonymize the data, describe the anonymization process. -->
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-## Bias, Risks, and Limitations
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-### Recommendations
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-Users should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.
-## Citation [optional]
-<!-- If there is a paper or blog post introducing the dataset, the APA and Bibtex information for that should go in this section. -->
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-## Glossary [optional]
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 ---
+license: cc-by-4.0
+task_categories:
+  - other
+tags:
+  - biology
+  - protein
+  - structure
+  - PDB
+  - PISCES
+  - CullPDB
+  - sequence
+  - curation
+language: en
+size_categories:
+  - n>1M
+dataset_info:
+  config_name: default
+  features:
+    - name: pdb_chain
+      dtype: string
+    - name: pdb
+      dtype: string
+    - name: chain
+      dtype: string
+    - name: sequence
+      dtype: string
+    - name: len
+      dtype: int64
+    - name: method
+      dtype: string
+    - name: resolution
+      dtype: float64
+    - name: rfac
+      dtype: string
+    - name: freerfac
+      dtype: string
+    - name: pc
+      dtype: float64
+    - name: no_breaks
+      dtype: string
+    - name: R
+      dtype: float64
+    - name: source_list
+      dtype: string
+  splits: null
+  num_rows: 4540884
+# Main and index paths; full list of subset paths is in dataset_metadata.json
+data_paths:
+  main_csv: curated_csv/cullpdb_combined_chains.csv
+  index_csv: curated_csv/cullpdb_list_fasta_index.csv
+  full_list_csv: curated_csv/cullpdb_full_compiled_list.csv
+  subsets_dir: curated_csv/subsets
+  metadata: curated_csv/dataset_metadata.json
 ---
+# PISCES-CulledPDB — Curated chain CSVs
+Curated protein chain tables derived from PISCES/CullPDB-style lists and FASTA files. One row per chain with sequence, metadata, and curation parameters.
+**Dataset:** [PRMegathon26/PISCES-CulledPDB](https://huggingface.co/datasets/PRMegathon26/PISCES-CulledPDB)
+## Dataset Summary
+| Item | Description |
+|------|-------------|
+| **Main CSV** | `curated_csv/cullpdb_combined_chains.csv` — single table with **4,540,884** chains (one row per chain). |
+| **Subset CSVs** | `curated_csv/subsets/*.csv` — **242** files, one per curation subset (same columns as main). |
+| **Index** | `curated_csv/cullpdb_list_fasta_index.csv` — **242** rows; maps subset basenames to list/FASTA paths and parameters. |
+## Data paths (metadata)
+**Main and index files:**
+- `curated_csv/cullpdb_combined_chains.csv` — master chain table
+- `curated_csv/cullpdb_list_fasta_index.csv` — subset index
+- `curated_csv/cullpdb_full_compiled_list.csv` — full compiled list
+- `curated_csv/subsets/` — directory containing one CSV per subset (**242** files)
+**Subset paths:** The full list of subset CSV paths is in **`curated_csv/dataset_metadata.json`** (keys `data_paths` and `subset_paths`). Use it for programmatic listing or with `hf_hub_download(..., filename=path)`.
+## Main CSV & Subset CSV — Column definitions
+Each chain row has the following columns:
+| Column | Type | Description |
+|--------|------|-------------|
+| **pdb_chain** | string/number | PDB chain ID (e.g. 1ABC_A) |
+| **pdb** | string/number | PDB ID (first 4 chars) |
+| **chain** | string/number | Chain ID |
+| **sequence** | string/number | Amino acid sequence (one-letter) |
+| **len** | string/number | Sequence length |
+| **method** | string/number | Experimental method (e.g. XRAY, NMR) |
+| **resolution** | string/number | Resolution in Å (per structure) |
+| **rfac** | string/number | R-factor |
+| **freerfac** | string/number | Free R-factor |
+| **pc** | string/number | Sequence identity cutoff % used for this subset |
+| **no_breaks** | string/number | Whether chain has no breaks (yes/no) |
+| **R** | string/number | R-factor cutoff used for this subset |
+| **source_list** | string/number | Subset list basename (identifies curation parameters) |
+Subset CSVs use the same schema; each file corresponds to one row in the index (one set of parameters: pc, resolution range, no_breaks, R, Nmethods).
+## Index CSV — Column definitions
+| Column | Description |
+|--------|-------------|
+| **list_basename** | Subset list basename |
+| **fasta_basename** | Corresponding FASTA basename |
+| **list_path** | Full path to list file |
+| **fasta_path** | Full path to FASTA file |
+| **n_chains** | Number of chains in this subset |
+| **pc** | Sequence identity cutoff % |
+| **resolution** | Resolution range (e.g. 0.0-2.0) |
+| **no_breaks** | yes/no |
+| **R** | R-factor cutoff |
+| **Nmethods** | Experiment types (e.g. Xray, Xray+EM) |
+## Subset naming
+Subset list basenames follow:
+`cullpdb_pc{pc}_res{min}-{max}_[noBrks_]len40-10000_R{R}_{Nmethods}_..._chains{N}`
+- **pc**: sequence identity cutoff (%)
+- **resolution**: Å range (e.g. 0.0–2.0)
+- **noBrks** (optional): no breaks in chain
+- **R**: R-factor cutoff
+- **Nmethods**: Xray, Xray+EM, or Xray+Nmr+EM
+- **N**: number of chains in that subset
+## Usage
+```python
+from huggingface_hub import hf_hub_download
+import pandas as pd
+# Download main CSV (large)
+path = hf_hub_download(repo_id="PRMegathon26/PISCES-CulledPDB", filename="curated_csv/cullpdb_combined_chains.csv", repo_type="dataset")
+df = pd.read_csv(path)
+# Or load a single subset
+path = hf_hub_download(repo_id="PRMegathon26/PISCES-CulledPDB", filename="curated_csv/subsets/cullpdb_pc20.0_res0.0-1.0_len40-10000_R0.2_Xray_d2026_01_26_chains314.csv", repo_type="dataset")
+df = pd.read_csv(path)
+```
+## Curation workflow
+1. **Index**: List/FASTA pairs scanned → `cullpdb_list_fasta_index.csv`
+2. **Build**: For each index row, list and FASTA aligned 1:1 → one chain CSV per subset + combined master CSV
+3. **Filter/visualize**: Optional filtering and summary figures from the master CSV
+## License
+CC BY 4.0 (or as specified in the repo).