Update README.md

README.md

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-Dataset Summary
-The EpicNet dataset is a curated integration of peptide and protein epitope records extracted from the Immune Epitope Database (IEDB) and related immunoinformatics resources. It standardizes linear peptide epitope representations, cross-links source molecules, organisms, and taxonomy references, and unifies metadata under consistent ontological mappings.
-It supports bioinformatics, machine learning on epitope prediction, and immunotherapy research by providing aligned, structured representations of epitopes, their parent proteins, and associated immune contexts.
-
-Supported Tasks and Use Cases
-Epitope–Protein Mapping — link and analyze how antigenic peptides relate to their source proteins and organisms.
-
-Sequence-Based Epitope Prediction — train models to predict immunogenic peptide segments.
-
-Antigen Similarity & Cross-reactivity Studies — compare epitopes across species for vaccine development.
-
-Knowledge Graph Integration — generate RDF/OWL graphs for ontology-powered immunoinformatics.
-
-Embedding Generation and Representation Learning using transformers or peptide encoders (e.g., ESM, ProtBERT).
-
-Dataset Structure
-Data Fields
-Field	Description
-IEDB IRI	Canonical IEDB reference for the epitope entry.
-Object Type	Epitope structure classification (e.g., Linear peptide, Fragment, Analog).
-Name	Peptide sequence string (8–35 amino acids typical length).
-Modified Residue(s)	List of modified amino acids, if any.
-Modifications	Type of modification (e.g., phosphorylation, main-chain modification).
-Starting Position / Ending Position	Residue range within the source molecule sequence.
-Source Molecule	Protein name or precursor from which the epitope originates.
-Source Molecule IRI	Accession to protein database such as UniProt or NCBI Protein.
-Molecule Parent	Parent macromolecule, if hierarchically defined (e.g., domain‑level annotation).
-Source Organism / Source Organism IRI	Organism name and taxonomy reference (NCBI Taxon).
-Species / Species IRI	Species-level classification.
-Epitope Relation	Functional or structural relation type (e.g., analog, fragment of natural sequence).
-Record Count
-2,308,224 rows representing peptide–protein associations
-
-Average peptide length: 8–35 amino acids
-
-Approximate dataset size: 85.8 MB (raw TSV) / 156 MB (Parquet)
-
-Data Sources and Provenance
-Primary sources include:
-
-IEDB (Immune Epitope Database) — canonical epitope and antigen relationships
-
-UniProt / NCBI Protein — sequence-level references
-
-NCBI Taxonomy — standardized organism identifiers
-Each entry maps identifiers to IEDB IRIs, providing internationally traceable cross‑links.
-
-Languages and Data Format
-Sequence representation: Amino acid single-letter codes (A–Y)
-
-Metadata fields: English-language labels and ontology-class terms
-
-Format: TSV / Parquet (CSV-compatible with structured metadata)
-
-Intended Uses
-EpicNet is designed for use in:
-
-Computational immunology pipelines (e.g., T-cell / B-cell epitope classifier fine-tuning)
-
-Graph-based representation of immune networks
-
-Comparative peptide analytics across pathogens and hosts
-
-Foundation datasets for large-scale protein–epitope pretraining
-
-Limitations and Ethical Considerations
-Dataset reflects experimentally or computationally curated peptide sequences; not all records are experimentally verified.
-
-Certain peptide segments appear across species due to homologs or predicted analogs.
-
-Users must verify NCBI Taxonomy and UniProt IDs for clinical or diagnostic applications.
-
-Dataset does not contain personally identifiable data or clinical metadata.
-
-Citation
-If you use this dataset, please cite:
-Gokul Alex (2025). EpicNet – International Epitope Database Peptide Network. Hugging Face Datasets.
-Available at: https://huggingface.co/datasets/gokulalex/EpicNet
-
-License
-Creative Commons Attribution 4.0 International (CC BY‑4.0)
-
-Dataset Creation and Maintenance
-Author: Gokul Alex
-Release Date: October 2025
-Version: v1.0
-Contact: huggingface.co/gokulalex
-
-Example Entry
+# Dataset Summary
+- The EpicNet dataset is a curated integration of peptide and protein epitope records extracted from the Immune Epitope Database (IEDB) and related immunoinformatics resources. It standardizes linear peptide epitope representations, cross-links source molecules, organisms, and taxonomy references, and unifies metadata under consistent ontological mappings.
+- It supports bioinformatics, machine learning on epitope prediction, and immunotherapy research by providing aligned, structured representations of epitopes, their parent proteins, and associated immune contexts.
+
+# Supported Tasks and Use Cases
+- Epitope–Protein Mapping — link and analyze how antigenic peptides relate to their source proteins and organisms.
+- Sequence-Based Epitope Prediction — train models to predict immunogenic peptide segments.
+- Antigen Similarity & Cross-reactivity Studies — compare epitopes across species for vaccine development.
+- Knowledge Graph Integration — generate RDF/OWL graphs for ontology-powered immunoinformatics.
+- Embedding Generation and Representation Learning using transformers or peptide encoders (e.g., ESM, ProtBERT).
+
+# Dataset Structure
+
+## Record Count
+- 2,308,224 rows representing peptide–protein associations
+- Average peptide length: 8–35 amino acids
+- Approximate dataset size: 85.8 MB (raw TSV) / 156 MB (Parquet)
+
+# Data Sources and Provenance
+- IEDB (Immune Epitope Database) — canonical epitope and antigen relationships
+- UniProt / NCBI Protein — sequence-level references
+- NCBI Taxonomy — standardized organism identifiers
+- Each entry maps identifiers to IEDB IRIs, providing internationally traceable cross‑links.
+
+# Languages and Data Format
+- Sequence representation: Amino acid single-letter codes (A–Y)
+- Metadata fields: English-language labels and ontology-class terms
+- Format: TSV / Parquet (CSV-compatible with structured metadata)
+
+# Intended Uses
+- Computational immunology pipelines (e.g., T-cell / B-cell epitope classifier fine-tuning)
+- Graph-based representation of immune networks
+- Comparative peptide analytics across pathogens and hosts
+- Foundation datasets for large-scale protein–epitope pretraining
+
+# Limitations and Ethical Considerations
+- Dataset reflects experimentally or computationally curated peptide sequences; not all records are experimentally verified.
+- Certain peptide segments appear across species due to homologs or predicted analogs.
+- Users must verify NCBI Taxonomy and UniProt IDs for clinical or diagnostic applications.
+- Dataset does not contain personally identifiable data or clinical metadata.
+
+# Citation
+- If you use this dataset, please cite:
+- Gokul Alex (2025). EpicNet – International Epitope Database Peptide Network. Hugging Face Datasets.
+- Available at: https://huggingface.co/datasets/gokulalex/EpicNet
+
+# License
+- Creative Commons Attribution 4.0 International (CC BY‑4.0)
+
+# Dataset Creation and Maintenance
+- Author: Gokul Alex
+- Release Date: October 2025
+- Version: v1.0
+- Contact: huggingface.co/gokulalex
+
+# Example Entry
 json
 {
   "IEDB IRI": "http://www.iedb.org/epitope/1",
@@ -101,6 +68,6 @@ json
   "Source Organism": "Streptococcus pyogenes",
   "Species": "Streptococcus pyogenes serotype M3 D58"
 }
-Acknowledgments
-Data derived from the IEDB Consortium, NCBI, and UniProt KB.
-Compilation, integration, and ontology alignment under the EpicNet Data Initiative.
+# Acknowledgments
+- Data derived from the IEDB Consortium, NCBI, and UniProt KB.
+- Compilation, integration, and ontology alignment under the EpicNet Data Initiative.