Update README.md

README.md

@@ -19,11 +19,7 @@ configs:
 
 # AlphaFoldDB Prediction Index
 
-This repository contains the AlphaFold Protein Structure Database bulk-download files mirrored under `LiteFold/AlphaFoldDB`. The added Parquet files make the accession index loadable in the Hugging Face Dataset Viewer and the `datasets` API.
-
-The default dataset table is built from `accession_ids.csv`. Each row represents one AlphaFold DB prediction entry and includes its UniProt accession, AlphaFold DB identifier, residue range, latest model version, derived sequence length, parsed fragment number, and deterministic split bucket.
-
-The raw FASTA file and structure tar archives are preserved in the repository but are not embedded in the default Parquet table.
+AlphaFoldDB is an open database of predicted protein 3D structures with confidence scores, massively expanding structural coverage for known protein sequences.
 
 ## Splits
 
@@ -117,11 +113,18 @@ For large jobs, prefer streaming or process the Parquet files with a columnar en
 | `is_fragmented_prediction` | Whether `fragment_number` is greater than 1. |
 | `split_bucket` | Deterministic bucket from `hash(uniprot_accession) % 10`; bucket 0 is test. |
 
-## Source Files Used
 
-- `accession_ids.csv`
-- `download_metadata.json`
-- `README.txt`
-- `CHANGELOG.txt`
+# Citation
 
-The processed files were generated from the raw files already present in this repository. The preparation script is included at `scripts/prepare_alphafolddb_dataset.py`.
+```
+@article{varadi2022alphafolddb,
+  title   = {{AlphaFold} Protein Structure Database: massively expanding the structural coverage of protein-sequence space with high-accuracy models},
+  author  = {Varadi, Mihaly and Anyango, Stephen and Deshpande, Mandar and others},
+  journal = {Nucleic Acids Research},
+  volume  = {50},
+  number  = {D1},
+  pages   = {D439--D444},
+  year    = {2022},
+  doi     = {10.1093/nar/gkab1061}
+}
+```