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Faculty of Science and Technology

Our Faculty has 3 300 full-time students, 1 000 employees, and a strong research. The eleven departments of the faculty comprises research and education within architecture, biology, chemistry, computing science, industrial design, mathematics, physics, educational science, and technology.

Latest news

Porträttbild på en man med glasögon. Brevid en bild på en lövkrans.
Spectroscopy expert appointed honorary doctor

Professor Kevin K. Lehmann from the University of Virginia: "I have always followed my curiosity."

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One single rule helps explain life on Earth

The discovery will help to understand why species are spread the way they are across the planet.

Doktorand vid Institutionen för datavetenskap
New AI research secures privacy

Sonakshi Garg shows that privacy is not a barrier to progress.

Umeå Plant Science Centre, växtforskning Jian-Feng Mao
Long non-coding RNAs, called lncRNAs, are transcribed from DNA as other RNAs but they do not carry instructions for proteins. Instead, they help controlling genes, guide plant development and are involved in plant responses to stress like drought or heat. Identifying these lncRNAs has been difficult because their genetic sequences vary a lot between different plant species. The team around Jian-Feng Mao tackled the problem using machine learning, a type of artificial intelligence that is trained on large amounts of data to find patterns. They analysed over 1,600 different features of lncRNAs and identified just three key features that could effectively distinguish lncRNAs from RNAs containing the code for a protein. Identification of sequence patterns using mathematical parameters What makes PlantLncBoost particularly innovative is its use of mathematical parameters to capture intrinsic sequence properties beyond traditional biological features. The research team used so called Fourier transformation-based approaches. That allowed them to detect patterns in the RNA sequences that are consistent across diverse plant species despite of the high variability in the genetic sequences. “Through systematic evaluation of multiple machine learning algorithms and rigorous parameter optimization, we have developed a tool that achieves both high accuracy and strong generalization capabilities,” explains Jian-Feng Mao, Associate professor at Umeå University who established his lab at the Umeå Plant Science Centre in 2023. To make sure their new tool worked, the team tested PlantLncBoost on datasets from 20 different plant species. It correctly identified lncRNAs with over 96% accuracy, significantly outperforming existing tools. The tool even recognised nearly all 358 long lncRNAs that had been experimentally validated before, including those from twelve species that were not included in the training set used to develop the tool. New possibilities to analyse long non-coding RNAs across species “Developing PlantLncBoost was an exciting opportunity to apply machine learning to solve a complex biological problem,” says first author Xue-Chan Tian, who completed this work as part of her PhD thesis at Beijing Forestry University. “My doctoral programme focused on combining advanced computational methods with plant genomics to extract meaningful biological insights from complex sequence data.” The project brought together experts in genomics, bioinformatics and computer science from around the world, including researchers from Sweden, China and Brazil. The tool is now freely available to the scientific community and has been integrated in a larger analysis workflow that was developed earlier by Jian-Feng Mao’s group. It allows not only to identify but also to characterise lncRNAs in plants. By implementing PlantLncBoost in this workflow, researchers can now identify long non-coding RNAs from different plant species much more accurate, making it easier to compare and analyse them.

Better identification of plant-specific long non-coding RNAs allows comparisons across species.

Porträttbild på Frank Drewes, professor vid Institutionen för datavetenskap
Record number of doctoral theses at the department of computing science

"A remarkable evidence of our thriving research environment", says Frank Drewes, Head of the Department.

En rad solpaneler som sitter bredvid varandra.
Advanced coatings boost the competitiveness of solar thermal energy

Solar thermal collectors are taking on fossil energy sources – thanks to a new type of coating.

Latest features

Mats G LarsonProfessor vid Institutionen för matematik och matematisk statistik
Mathematics that can change the world

Mats G Larson’s research is shaping the future of cars, cities and robots through models and simulations.

Christiane Funk
Fascinated by the superpower of microalgae

Christiane Funk is passionate about small organisms with great potential for a more sustainable future.

Václava Hazuková, cellting water samples from an Arctic lake.
Peering through the ice to uncover the secrets of Arctic lakes

Václava Hazuková, KBC-Kempe postdoc, researches carbon storage in Arctic lakes.

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Science outreach events

Umeå University researchers disseminate their research outside the University through various events.

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