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Adding a short description of the team
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index.md

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<img src="{{ site.baseurl }}/public/assets/datascience_graph.png" style="width:100%">
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Our research spans biology and data science, tackling complex planetary and human health challenges. We focus on **Multimodal Data**, processing and analyzing diverse types such as mass spectrometry (proteomics, metabolomics) and metaomics (metagenomics, metatranscriptomics, metaproteomics), tackling complex biological problems.
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A key component is developing **High-quality Knowledge Graphs** that connect data, allowing integration and interpretation of these data and we use **Graph Machine Learning** to extract insights, revealing patterns and generating predictions from graph structures.
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We apply these technologies to explore and understand **Microbial Communities** and their environments, unraveling assembly, interaction, adaptation, and impact, spanning ecology to biotech.
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Further, we're strong advocates of **Open Science**, adhering to open principles for our generated data, training, and software, aiming to reduce inequality and promote accessibility by democratizing data science.
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<a class="prev" onclick="plusSlides(-1)">❮</a>
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<a class="next" onclick="plusSlides(1)">❯</a>
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Our research spans biology and data science, tackling complex planetary and human health challenges. We focus on **Multimodal Data**, processing and analyzing diverse types such as mass spectrometry (proteomics, metabolomics) and metaomics (metagenomics, metatranscriptomics, metaproteomics), tackling complex biological problems.
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A key component is developing **High-quality Knowledge Graphs** that connect data, allowing integration and interpretation of these data and we use **Graph Machine Learning** to extract insights, revealing patterns and generating predictions from graph structures.
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We apply these technologies to explore and understand **Microbial Communities** and their environments, unraveling assembly, interaction, adaptation, and impact, spanning ecology to biotech.
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Further, we're strong advocates of **Open Science**, adhering to open principles for our generated data, training, and software, aiming to reduce inequality and promote accessibility by democratizing data science.

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