Decoding the Chemical Language of Plants with Machine Learning

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27740%2F25%3A10260235" target="_blank" >RIV/61989100:27740/25:10260235 - isvavai.cz</a>

Result on the web

<a href="https://events.it4i.cz/event/345/" target="_blank" >https://events.it4i.cz/event/345/</a>

DOI - Digital Object Identifier

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Result language

angličtina

Original language name

Decoding the Chemical Language of Plants with Machine Learning

Original language description

In this course, students investigated the biosynthetic pathways of non-model plant species, focusing on the identification of specialized metabolites. They addressed the challenges of gene distribution in plant genomes and learned to apply innovative tools such as the EnzymeExplorer pipeline for predicting terpene synthase functions and the DreaMS model for enhancing tandem mass spectrometry analysis. Through hands-on experience, participants connected biosynthetic gene sequences from RNA sequencing to metabolites detected in LC-MS data, ultimately gaining insights into characterizing the chemodiversity and biosynthetic potential of various plant species.

Czech name

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Czech description

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Type

O - Miscellaneous

CEP classification

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OECD FORD branch

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Project

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Continuities

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Publication year

2025

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů