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# genome-homomorphic | ||
# Sequence Analysis Security Study | ||
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$∀p \ ∀q \ ∃◊: E(p) ◊ E(q) = E(p + q)$ | ||
## Overview | ||
This repository contains a collection of studies and tools focused on the intersection of sequence analysis and data security. The main goal is to explore how genomic sequence data can be analyzed while preserving confidentiality and ensuring the integrity of sensitive information. The repo includes various proof-of-concept (POC) implementations, scripts, and documentation to support research and development in this domain. | ||
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$∀p \ ∀q \ ∃⋆: E(p) ⋆ E(q) = E(p \cdot q)$ | ||
## Features | ||
- **Genomic Sequence Analysis**: Tools and methods for aligning and analyzing genomic sequences. | ||
- **Security Mechanisms**: Implementation of cryptographic techniques to ensure secure data processing, including homomorphic encryption and secret sharing. | ||
- **Proof of Concepts (POCs)**: Demonstrations of concepts that combine bioinformatics and cryptography to create secure, efficient data analysis pipelines. | ||
- **Variant Calling**: Scripts and algorithms to identify variants from sequencing data. | ||
- **Commitment Schemes**: Implementations for generating commitments and verifying data in secure computations. | ||
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## Objectives | ||
- To develop and test methods for secure sequence analysis. | ||
- To explore the practical applications of homomorphic encryption, secret sharing, and distributed key generation (DKG) in the context of genomic data. | ||
- To bridge the gap between bioinformatics and cryptographic research. |