Sequentia Network: A Blockchain-Based Ecosystem for Decentralized Genomic Data Management, Analysis, and Intellectual Property Protection

Authors: Daniel Uribe (GenoBank.io) | GenoBank Research Team

Date: October 2025

Abstract—The genomic data ecosystem faces critical challenges in data discovery, laboratory verification, intellectual property management, and computational scalability. We present Sequentia Network (Chain ID: 15132025)—a specialized Layer-1 blockchain designed for genomic data federation, bioinformatics computation, and programmable licensing. The network implements four core innovations: (1) BioData Router, a smart contract for DNA fingerprint-based discovery and laboratory identity verification via LabNFTs; (2) BioFS Protocol, a 4-layer architecture for privacy-preserving data federation; (3) Story Protocol Integration, enabling programmable IP licensing for genomic assets; and (4) Partner Chain Ecosystem, connecting specialized bioinformatics services including OpenCRAVAT, AlphaGenome, SOMOS DAO, AlphaFold, and Claude AI. Sequentia Network operates as a Clique Proof-of-Authority chain with master node at 52.90.163.112, providing deterministic transaction finality and GDPR-compliant data management through separation of control plane (blockchain) and data plane (erasable S3 storage). This paper presents the technical architecture, smart contract specifications, partner integrations, and real-world deployment of Sequentia Network as a production genomic data infrastructure.

1. Introduction

1.1 The Genomic Data Problem

The genomic data landscape is characterized by extreme fragmentation. Laboratories generate sequencing data in isolated silos, researchers cannot discover relevant datasets across institutions, and data owners lack mechanisms to enforce licensing terms or receive attribution for derivative works. Three critical gaps exist:

  1. Discovery Problem: No standardized protocol for discovering genomic datasets across laboratories without exposing raw genetic data.
  2. Identity Problem: No immutable registry for laboratory accreditation and data provenance verification.
  3. Licensing Problem: No programmable system for enforcing intellectual property rights on genomic analyses and derivative works.

Traditional approaches—centralized databases, data use agreements, and manual attribution—fail to scale. Sequentia Network addresses these gaps through blockchain-based infrastructure.

1.2 Sequentia Network Overview

Sequentia Network is a specialized Layer-1 blockchain (Chain ID: 15132025) built on Ethereum’s Clique Proof-of-Authority consensus mechanism. The network provides:

1.3 Contributions

This paper makes the following contributions:

  1. BioData Router Specification: Complete smart contract design for genomic file routing via DNA fingerprints
  2. LabNFT Architecture: Immutable laboratory identity verification system
  3. BioFS Protocol: Technical specification for 4-layer genomic data federation
  4. Story Protocol Integration: First implementation of programmable IP licensing for genomic data
  5. Partner Chain Ecosystem: Architecture for connecting specialized bioinformatics services
  6. Production Deployment: Real-world implementation with deployed smart contracts and active nodes

2. Network Architecture

2.1 Blockchain Fundamentals

Sequentia Network operates as an Ethereum-compatible Layer-1 blockchain with the following specifications:

Network ID: 15132025
Consensus: Clique (Proof of Authority)
Block Time: ~15 seconds
Master Node: 52.90.163.112:8545
RPC: http://52.90.163.112:8545
WebSocket: ws://52.90.163.112:8545
Chain Explorer: In development

2.2 Clique Proof-of-Authority

Sequentia uses Clique PoA consensus, where authorized signers validate blocks. This design provides:

The current authorized signer set includes the master node wallet: 0x088ebE307b4200A62dC6190d0Ac52D55bcABac11.

2.3 Smart Contract Platform

Sequentia is fully EVM-compatible, supporting:

3. BioData Router Smart Contract

BioData Router Architecture
Figure 2: BioData Router smart contract for decentralized genomic data discovery

3.1 Design Overview

The BioData Router is the core smart contract of Sequentia Network, deployed at:

0x2ff3FB85c71D6cD7F1217A08Ac9a2d68C02219cd

It implements a routing table for genomic files, indexed by DNA fingerprints and file hashes. The contract maintains three key registries:

  1. Lab Registry: Verified laboratory identities (LabNFTs)
  2. DNA Fingerprint Registry: Cryptographic hashes of variant positions
  3. File Registry: Genomic files with metadata and S3 paths

3.2 DNA Fingerprints

A DNA fingerprint is a SHA-256 hash of variant positions only (not genotypes):

FDNA = H(chr1:pos1 ∥ chr2:pos2 ∥ ⋯ ∥ chrn:posn)

where H is SHA-256, and ∥ denotes concatenation. This preserves privacy because:

Theorem 1. Given FDNA, an adversary cannot recover individual genotypes without brute-forcing the full variant space.
Proof. The SHA-256 hash function is pre-image resistant. Since only positions (not alleles) are hashed, FDNA reveals no information about the actual genetic variants. An adversary must brute-force 2256 possible hashes to find a matching fingerprint. ∎

3.3 Smart Contract Structure

The BioData Router implements the following data structures:

struct LabInfo {
    string name;
    string location;
    string s3Bucket;
    uint256 registeredAt;
    bool active;
}

struct FileRecord {
    address labWallet;
    address userWallet;
    string s3Path;
    bytes32 fileHash;
    bytes32 dnaFingerprint;
    uint256 timestamp;
    bool isLicensed;
    string ipAssetId;      // Story Protocol
    string fileFormat;     // VCF, BAM, FASTQ
}

mapping(address => LabInfo) registeredLabs;
mapping(bytes32 => address) dnaFingerprintToUser;
mapping(bytes32 => FileRecord) files;
mapping(bytes32 => FileRecord[]) fingerprintFiles;
mapping(address => FileRecord[]) userFiles;

3.4 Core Functions

3.4.1 Laboratory Registration

Only the master node can register laboratories:

function registerLab(
    address labWallet,
    string memory name,
    string memory location,
    string memory s3Bucket
) public {
    require(msg.sender == masterNode);
    registeredLabs[labWallet] = LabInfo({
        name: name,
        location: location,
        s3Bucket: s3Bucket,
        registeredAt: block.timestamp,
        active: true
    });
    emit LabRegistered(labWallet, name, ...);
}

3.4.2 File Registration

Laboratories register genomic files with DNA fingerprints:

function registerFile(
    address labWallet,
    address userWallet,
    string memory s3Path,
    bytes32 fileHash,
    bytes32 dnaFingerprint,
    string memory fileFormat,
    bool isLicensed,
    string memory ipAssetId
) public {
    require(registeredLabs[labWallet].active);

    // Check for duplicate genomic sample
    if (dnaFingerprintToUser[dnaFingerprint] != address(0)) {
        emit DuplicateGenomicSample(...);
    } else {
        dnaFingerprintToUser[dnaFingerprint] = userWallet;
        totalGenomicSamples++;
    }

    FileRecord memory record = FileRecord({
        labWallet: labWallet,
        userWallet: userWallet,
        s3Path: s3Path,
        fileHash: fileHash,
        dnaFingerprint: dnaFingerprint,
        timestamp: block.timestamp,
        isLicensed: isLicensed,
        ipAssetId: ipAssetId,
        fileFormat: fileFormat
    });

    files[fileHash] = record;
    fingerprintFiles[dnaFingerprint].push(record);
    userFiles[userWallet].push(record);
    totalFiles++;

    emit FileRegistered(...);
}

3.4.3 Discovery Functions

Users can query files by DNA fingerprint or user wallet:

function getFilesByDNAFingerprint(bytes32 dnaFingerprint)
public view returns (FileRecord[] memory) {
    return fingerprintFiles[dnaFingerprint];
}

function getUserFiles(address userWallet)
public view returns (FileRecord[] memory) {
    return userFiles[userWallet];
}

3.4.4 Identity Verification

The contract implements genomic identity verification:

function verifyGenomicIdentity(
    bytes32 fileHash,
    bytes32 expectedDnaFingerprint
) public view returns (bool) {
    return files[fileHash].dnaFingerprint == expectedDnaFingerprint;
}

This allows third parties to verify that a genomic file matches the claimed DNA fingerprint without accessing the raw data.

4. BioFS Protocol

4.1 Protocol Architecture

BioFS Protocol Stack
Figure 3: BioFS Protocol secure architecture with privacy-preserving layers

BioFS (Biological File System) is a 4-layer protocol for genomic data federation:

  1. Discovery Layer: Query BioData Router by DNA fingerprint
  2. Identity Layer: Verify LabNFT and data provenance
  3. Storage Layer: Retrieve files from S3 using presigned URLs
  4. Network Layer: Handle cross-chain communication

4.2 Discovery Layer

The Discovery Layer enables privacy-preserving file discovery:

# Client generates DNA fingerprint locally
positions = extract_variant_positions(vcf_file)
fingerprint = sha256(positions)

# Query BioData Router
contract = web3.eth.contract(
    address=BIODATA_ROUTER,
    abi=BIODATA_ROUTER_ABI
)
files = contract.functions.getFilesByDNAFingerprint(
    fingerprint
).call()

# Returns: [(labWallet, s3Path, fileHash), ...]

4.3 Identity Layer

The Identity Layer verifies laboratory credentials via LabNFTs. Each LabNFT contains:

4.4 Storage Layer

The Storage Layer maintains GDPR compliance through:

When a user exercises their “right to erasure” (GDPR Article 17):

  1. Genomic files are deleted from S3
  2. Blockchain records remain (showing file existed)
  3. S3 path becomes invalid (404 Not Found)

This ensures legal compliance while maintaining data provenance.

4.5 Network Layer

The Network Layer handles cross-chain communication using:

5. LabNFTs and BioNFTs

5.1 LabNFT Architecture

LabNFTs (ERC-721 tokens) represent immutable laboratory identities. Each LabNFT includes:

{
  "name": "Johns Hopkins Genomics Center",
  "location": "Baltimore, MD, USA",
  "accreditation": ["CLIA", "CAP"],
  "s3Bucket": "jhgc-genomics-vault",
  "registeredAt": 1698451200,
  "masterNode": "0x088ebE...",
  "image": "ipfs://QmXrT..."
}

LabNFTs cannot be transferred (soulbound tokens), ensuring permanent association between laboratory wallet and identity.

5.2 BioNFT Metamorphosis

BioNFTs represent physical biosamples as they transform through the analysis pipeline:

Biosample Activation → Tokenization → Bioassets

5.2.1 Activation Phase

Physical biosample (blood/saliva) is linked to blockchain:

POST /create_biosample_activation
{
  "serial": "GB-001-XYZ",
  "owner_wallet": "0xUser...",
  "lab_wallet": "0xLab...",
  "collection_date": "2025-10-28"
}

5.2.2 Tokenization Phase

Sequencing generates genomic files, registered on Sequentia:

contract.functions.registerFile(
    labWallet="0xLab...",
    userWallet="0xUser...",
    s3Path="s3://vault/user/vcf/sample.vcf",
    fileHash=sha256(file_contents),
    dnaFingerprint=compute_fingerprint(vcf),
    fileFormat="VCF",
    isLicensed=True,
    ipAssetId="0x1234..."  # Story Protocol
).transact()

5.2.3 Bioasset Phase

Analysis results (annotations, predictions) become derivative IP assets:

All derivatives inherit licensing terms from the parent via Story Protocol.

6. Story Protocol Integration

6.1 Programmable IP Licensing

Sequentia integrates Story Protocol for programmable intellectual property licensing. Every genomic file registered on Sequentia can be:

  1. Registered as IP Asset: Immutable on-chain registration
  2. Attached to License Terms: PIL (Programmable IP License)
  3. Minted as License Tokens: Access granted via NFTs

6.2 License Term Structure

Story Protocol supports flexible licensing:

{
  "commercial_use": false,
  "derivatives_allowed": true,
  "attribution_required": true,
  "revenue_share": 0,
  "currency": "IP_TOKEN",
  "chainId": 15132025
}

6.3 Derivative IP Assets

When an analysis creates derivative data:

# Register child IP asset
child_ip = story_protocol.mint_derivative(
    parent_ip_id="0xParentIP...",
    child_nft_address="0xAnalysisNFT...",
    license_id="0xLicense...",
    metadata_uri="ipfs://QmAnalysis..."
)

# Child automatically inherits license terms
# Revenue sharing flows to parent IP owner

This creates an IP lineage tree where all derivative works are traceable and licensed.

6.4 Revenue Distribution

Story Protocol automatically distributes revenue:

  1. User mints license token for analysis result (pays fee)
  2. Fee splits between:
    • Original data owner (VCF creator)
    • Analysis service provider (OpenCRAVAT)
    • Story Protocol treasury

7. Partner Chain Ecosystem

n

Partner Chain Ecosystem
Figure 4: Web3 OpenCRAVAT integration with Sequentia Network partner chain ecosystem

Sequentia Network connects to specialized bioinformatics chains and services:

7.1 OpenCRAVAT Chain

OpenCRAVAT is a decentralized variant annotation network. Instead of a centralized server at cravat.genobank.app, annotation jobs are distributed across nodes:

  1. User uploads VCF to Sequentia
  2. Smart contract triggers OpenCRAVAT job
  3. Annotation runs on distributed nodes
  4. Results registered as derivative IP

Key Features:

7.2 AlphaGenome

AlphaGenome leverages DeepMind’s AlphaMissense model for variant pathogenicity prediction:

POST /api_alphagenome/submit_variant_scoring
{
  "vcf_file": "s3://vault/user.vcf",
  "model": "alphamissense",
  "user_signature": "0x..."
}

# Returns pathogenicity scores (0-1)
# 0.0 = benign, 1.0 = pathogenic

Results are tokenized and linked to parent VCF as derivative IP.

7.3 SOMOS DAO

SOMOS DAO provides ancestry composition analysis:

7.4 Biomni Multi-Omics

Biomni integrates genomics with other -omics data:

7.5 AlphaFold Protein Prediction

AlphaFold integration enables:

  1. Variant → Protein sequence change
  2. AlphaFold → 3D structure prediction
  3. Impact analysis → Structural disruption assessment

7.6 Claude AI Genomic Assistant

Claude AI (Anthropic) provides:

All AI interactions are logged on-chain for auditability.

8. Security and Privacy

8.1 Threat Model

We consider three adversary types:

  1. Curious Server: Honest-but-curious cloud provider (AWS)
  2. Network Adversary: Passive eavesdropper on network traffic
  3. Malicious User: Attempts to claim others’ genomic data

8.2 Security Mechanisms

8.2.1 DNA Fingerprint Privacy

As proven in Theorem 1, DNA fingerprints reveal no genotype information. Even if an adversary intercepts:

dnaFingerprint: 0x7a3f2c1b...

They cannot reverse-engineer the actual genetic variants.

8.2.2 S3 Encryption

All genomic files are encrypted at rest (AES-256) and in transit (TLS 1.3). S3 presigned URLs expire after 15 minutes.

8.2.3 Access Control

File access requires:

  1. Valid user signature (Web3 wallet)
  2. Ownership verified via BioData Router
  3. Active license token (if commercial use)

8.3 GDPR Compliance

Sequentia implements “right to erasure” through dual-plane architecture:

Data TypeStorageErasable?
Genomic files (VCF)S3Yes
DNA fingerprintsBlockchainNo
File metadataBlockchainNo
S3 pathsBlockchainNo (invalidated)

When a user deletes their data:

9. Performance Analysis

9.1 Transaction Throughput

Sequentia Network achieves:

For genomic data (infrequent registrations), this is sufficient.

9.2 Storage Scalability

BioData Router uses efficient storage:

9.3 Query Performance

Smart contract queries are instant:

getFilesByDNAFingerprint(): O(1) lookup
getUserFiles(): O(n) where n = user's files
getLabInfo(): O(1) lookup

10. Deployment and Production Status

10.1 Live Infrastructure

Sequentia Network is currently deployed in production:

10.2 Usage Statistics

As of October 2025:

10.3 Integration Status

ServiceStatus
BioData RouterProduction
LabNFTsProduction
BioNFTsProduction
Story ProtocolProduction
OpenCRAVATProduction
AlphaGenomeProduction
SOMOS DAOProduction
Claude AIProduction
AlphaFoldBeta
BiomniDevelopment

11. Future Work

11.1 Decentralized Compute Network

We are developing a Sequentia Compute Layer for distributed bioinformatics:

  1. Laboratories contribute idle compute to network
  2. Jobs (alignment, variant calling) run on distributed nodes
  3. Rewards paid in SEQT token (native gas token)

11.2 Cross-Chain Bridges

Future work includes bridges to:

11.3 Advanced Privacy

We are exploring:

11.4 AI-Driven Discovery

Integration of:

12.1 Genomic Data Sharing

Existing platforms include:

Sequentia differs through decentralization and programmable licensing.

12.2 Blockchain Genomics

Prior blockchain genomics projects:

Sequentia advances the state-of-the-art through:

  1. Laboratory-focused (not consumer-only)
  2. Production bioinformatics integration
  3. Story Protocol IP management
  4. Real deployment with active users

13. Conclusion

Sequentia Network provides production-grade infrastructure for decentralized genomic data management. Through the BioData Router smart contract, BioFS Protocol, LabNFTs, and Story Protocol integration, we enable privacy-preserving data discovery, immutable laboratory verification, and programmable IP licensing.

The network’s integration with specialized services—OpenCRAVAT, AlphaGenome, SOMOS DAO, AlphaFold, and Claude AI—demonstrates the viability of a blockchain-based bioinformatics ecosystem. With 847 registered genomic files across 12 laboratories, Sequentia Network is actively used in production.

Future work will expand the compute network, implement advanced privacy mechanisms, and bridge to additional blockchains. We invite the genomics community to deploy nodes, register laboratories, and build applications on Sequentia Network.

Acknowledgments

We thank the OpenCRAVAT team (Johns Hopkins), Story Protocol developers, and the Ethereum Clique consensus team. This work was supported by GenoBank.io research grants and the SOMOS DAO community.

References

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  2. Pagel, K. et al., “OpenCRAVAT: Open Custom Ranked Analysis of Variants Toolkit,” Bioinformatics, 2020.

  3. Cheng, J. et al., “Accurate proteome-wide missense variant effect prediction with AlphaMissense,” Science, 2023.

  4. Story Protocol Team, “Programmable IP License (PIL) Framework,” Story Protocol Whitepaper, 2024.

  5. European Union, “General Data Protection Regulation (GDPR),” Regulation (EU) 2016/679, 2016.

  6. Karczewski, K.J. et al., “The mutational constraint spectrum quantified from variation in 141,456 humans,” Nature, 2020.

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