https://ioannis-mouratidis.github.io/tags/Python/PythonHugo Blox Builder (https://hugoblox.com)en-usWed, 01 Jan 2025 00:00:00 +0000https://ioannis-mouratidis.github.io/media/icon_hu_899445b689d8f445.pnghttps://ioannis-mouratidis.github.io/tags/Python/https://ioannis-mouratidis.github.io/projects/compression-tool/Wed, 01 Jan 2025 00:00:00 +0000https://ioannis-mouratidis.github.io/projects/compression-tool/<h2 id="overview">Overview</h2> <p>A novel compression tool developed in C++ and Python specifically optimized for multiple genomic file formats. This tool significantly reduces storage requirements while dramatically improving compression speed compared to existing solutions.</p> <h2 id="performance">Performance</h2> <ul> <li><strong>10-20% smaller file sizes</strong> compared to standard genomic compression tools</li> <li><strong>50-70% faster compression times</strong> enabling real-time analysis</li> <li><strong>Multiple format support</strong>: Handles various genomic data formats</li> <li><strong>Lossless compression</strong>: Maintains data integrity for scientific applications</li> </ul> <h2 id="technical-approach">Technical Approach</h2> <p>The tool leverages domain-specific knowledge about genomic data structure to achieve superior compression ratios and speeds. Implementation in C++ provides low-level performance optimization while Python bindings enable easy integration into bioinformatics pipelines.</p> <h2 id="impact">Impact</h2> <p>This compression tool enables:</p> <ul> <li>Reduced storage costs for large-scale genomic projects</li> <li>Faster data transfer and backup operations</li> <li>Real-time compression for sequencing pipelines</li> <li>More efficient cloud-based genomic analysis</li> </ul> <h2 id="applications">Applications</h2> <ul> <li>Large-scale sequencing projects</li> <li>Genomic data archiving</li> <li>Cloud-based bioinformatics platforms</li> <li>Real-time sequencing data processing</li> </ul>https://ioannis-mouratidis.github.io/projects/zseeker/Wed, 01 Jan 2025 00:00:00 +0000https://ioannis-mouratidis.github.io/projects/zseeker/<h2 id="overview">Overview</h2> <p>Zseeker is an open-source Python tool designed for optimized detection of Z-DNA forming sequences in large genomic datasets. Z-DNA is an alternative left-handed DNA structure implicated in gene regulation, genome instability, and various biological processes.</p> <h2 id="features">Features</h2> <ul> <li><strong>High Performance</strong>: Optimized algorithms enable analysis of entire genomes</li> <li><strong>Accuracy</strong>: Improved detection accuracy compared to previous methods</li> <li><strong>Scalability</strong>: Designed to handle large-scale genomic datasets</li> <li><strong>Easy to Use</strong>: Simple Python interface with clear documentation</li> <li><strong>Open Source</strong>: Freely available for academic and commercial use</li> </ul> <h2 id="technical-details">Technical Details</h2> <p>Zseeker implements advanced algorithms for identifying sequences capable of forming Z-DNA structures based on sequence composition and thermodynamic properties. The tool is optimized for both speed and accuracy, making it suitable for genome-wide analyses.</p> <h2 id="use-cases">Use Cases</h2> <ul> <li>Genome-wide Z-DNA mapping</li> <li>Regulatory element identification</li> <li>Genome stability studies</li> <li>Comparative genomics of non-B DNA structures</li> <li>Disease-associated variant analysis</li> </ul> <h2 id="publications">Publications</h2> <p>Wang, G., Mouratidis, I., Provatas, K., et al. (2025). ZSeeker: an optimized algorithm for Z-DNA detection in genomic sequences. <em>Briefings in Bioinformatics, 26</em>(3).</p>