In Silico PCR is a computational technique used to predict PCR outcomes, improve primer specificity, and optimize experimental conditions prior to conducting laboratory work. Numerous web-based tools with pre-loaded genome templates have been developed for conducting In Silico PCR simulations. However, there is an increasing demand for a flexible, user-friendly package that allows users to upload or define their own custom template sequences and operates offline, ensuring data privacy and security during In Silico PCR simulations and primer verification. This paper introduces PyPCRtool, a Python package designed to perform In Silico PCR simulations and verify primer specificity. The tool aims to offer a flexible, user-friendly solution that handles data locally, facilitating the prediction of DNA fragment amplification and the visualization of PCR product bands through gel electrophoresis simulations. PyPCRtool allows users to input and specify template DNA sequence files, forward and reverse primer sequences and customize mismatch tolerances. An example scenario demonstrates PyPCRtool's functionality, showcasing its ability to predict PCR product formation and visualize gel electrophoresis results. The tool provides detailed outputs, including PCR product sequences, sizes, and binding site information, assisting in experimental planning and analysis. PyPCRtool offers a robust and versatile solution for In Silico PCR and primer verification. By integrating flexible Python-based operations with local data handling for privacy, it serves as an invaluable resource for students and researchers in molecular biology and biotechnology, enhancing the accuracy and efficiency of PCR experimental planning and result interpretation.
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