Webinar: Modelling gene regulatory networks via high performance computing

New Zealand eScience Infrastructure(NeSI) designs, builds, and operates a shared national platform of advanced computing resources and data services. All researchers in Aotearoa New Zealand have access to NeSI’s platforms. Through NeSI, researchers can access high-capacity CPUs, GPUs and high memory nodes; tailored software environments; expertise in research software and data science engineering; and skills training in computational  tools and approaches. NeSI enables researchers to investigate large, unique, or complex projects more easily, quickly, and accurately.  To learn more, get in touch: info@nesi.org.nz.

New Zealand eScience Infrastructure (NeSI)

Olivia Angelin-Bonnet discusses what regulatory networks are and why/how they are reconstructed from biological data

<p><a href="https://www.nesi.org.nz/" target="_blank" data-msys-clicktrack="0" rel="nofollow noopener noreferrer">NeSI’s</a> next research spotlight webinar comes from Massey University PhD student Olivia Angelin-Bonnet.  Olivia researches how to decipher genotype-phenotype interactions through regulatory networks using multi-omics data, and will speak about simulating gene regulatory networks, using R and Julia, to assess the performance of network inference reconstruction methods.  Specifically, Olivia will explain to attendees:</p><ul><li>What regulatory networks are and why/how they are reconstructed from biological data,</li><li>why simulations are valuable in systems biology,</li><li>how to link R and Julia, and</li><li>how using NeSI platforms and services was necessary for Olivia to take her research to the next level</li></ul><h2>About the speaker </h2><p>I studied for my master degree in France (at INSA de Lyon), where I discovered the fields of bioinformatics and biostatistics. My formation was very multidisciplinary, at the interface between biology, statistics, modelling and programming. I became passionate about Systems Biology, mathematical modelling and the study of biological networks from a statistical and computational perspective. I am currently working on unravelling genotype-to-phenotype relationships from multi-omics data using causality inference methods, with a focus on polyploid organisms. I turned to NeSI to scale up my work with simulations.</p><h2>Who is this webinar for?</h2><p>This webinar is for researchers from all domains.  You do not need to know molecular biology or mathematical modelling to attend this webinar and we encourage non-computational scientists to listen in.  This webinar is a great introduction to how modelling and simulations can help answer important biological questions, and why high performance computing is essential for scaling up simulation-based projects.</p><h2>Prerequisites</h2><p>No prerequisites required. </p><h2>More Information</h2><p>If you have any questions or would like more information about this session, please email training@nesi.org.nz</p><p>Additionally, consider <a href="http://eepurl.com/grV9if" target="_blank" data-msys-clicktrack="0" rel="nofollow noopener noreferrer">subscribing to the NeSI training mailing list</a> to stay updated about future training opportunities.</p>

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Webinar: Modelling gene regulatory networks via high performance computing

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Webinar: Modelling gene regulatory networks via high performance computing

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