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Update README.md

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@@ -31,6 +31,7 @@ size_categories:
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  - "n>1M"
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  ---
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  # PISCES-CulledPDB database as of January 2026
 
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  The **PISCES dataset** provides curated sets of protein sequences from the Protein Data Bank (PDB) based on sequence identity and structural quality criteria. PISCES yields **non-redundant subsets of protein chains** by applying filters such as sequence identity, experimental resolution, R-factor, chain length, and experimental method (e.g., X-ray, NMR, cryo-EM). The goal is to maximize structural reliability while minimizing sequence redundancy. Unlike culling tools that rely on BLAST or global alignments, PISCES uses **PSI-BLAST** for position-specific scoring matrices, improving detection of homologs below 40% sequence identity.
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@@ -99,7 +100,7 @@ from huggingface_hub import hf_hub_download
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  import pandas as pd
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  path = hf_hub_download(
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- repo_id="PRMegathon26/PISCES-CulledPDB",
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  filename="curated_csv/cullpdb_combined_chains.csv",
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  repo_type="dataset"
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  )
 
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  - "n>1M"
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  ---
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  # PISCES-CulledPDB database as of January 2026
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+ Recurated on Hugging Face March 5th 2026
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  The **PISCES dataset** provides curated sets of protein sequences from the Protein Data Bank (PDB) based on sequence identity and structural quality criteria. PISCES yields **non-redundant subsets of protein chains** by applying filters such as sequence identity, experimental resolution, R-factor, chain length, and experimental method (e.g., X-ray, NMR, cryo-EM). The goal is to maximize structural reliability while minimizing sequence redundancy. Unlike culling tools that rely on BLAST or global alignments, PISCES uses **PSI-BLAST** for position-specific scoring matrices, improving detection of homologs below 40% sequence identity.
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  import pandas as pd
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  path = hf_hub_download(
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+ repo_id="RosettaCommons/PISCES-CulledPDB",
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  filename="curated_csv/cullpdb_combined_chains.csv",
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  repo_type="dataset"
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  )