Mika Gustafsson and David Martínez hope that AI-based models could eventually be used in precision medicine to develop treatments and preventive strategies tailored to the individual. Artificial intelligence, AI, which finds patterns in complex biological data could eventually contribute to the development of individually tailored healthcare. Researchers at LiU have developed an AI-based method applicable to various medical and biological issues. Their models can, for instance, estimate people's chronological age and determine whether they have been smokers or not. Genes play an important role in health, but so do environmental and behavioural factors, such as diet and level of physical activity.

The applicant should have a Ph.D. degree in a relevant area, such as bioinformatics, statistics or computer science. The Ph.D. degree should normally not be obtained more than three years before the application. Previous experience with machine learning and/or artificial intelligence and genomics is meritorious. The applicant should also be experienced in programming (Python/R or equivalent languages) and used to working with big data computing solutions. Strong communicative skills and fluency in written and spoken English are a requirement.

It's common when using social media that the platform suggests people whom you may want to add as friends. The suggestion is based on you and the other person having common contacts, which indicates that you may know each other. In a similar manner, scientists are creating maps of biological networks based on how different proteins or genes interact with each other. The researchers behind a new study have used artificial intelligence, AI, to investigate whether it is possible to discover biological networks using deep learning, in which entities known as "artificial neural networks" are trained by experimental data. Since artificial neural networks are excellent at learning how to find patterns in enormous amounts of complex data, they are used in applications such as image recognition.

Researchers have developed an artificial neural network using deep learning to identify genes that are related to disease. An artificial neural network has revealed patterns in huge amounts of gene expression data and discovered groups of disease-related genes. The developers, from Linköping University, Sweden, hope that the method can eventually be applied within precision medicine and individualised treatment. The scientists created maps of biological systems based on how different proteins or genes interact with each other. Using artificial intelligence (AI), they investigated whether it is possible to discover biological networks with deep learning, in which entities known as artificial neural networks are trained by experimental data.

An artificial neural network can reveal patterns in huge amounts of gene expression data and discover groups of disease-related genes. This has been shown by a new study led by researchers at Linköping University, published in Nature Communications. The scientists hope that the method can eventually be applied within precision medicine and individualized treatment. It's common when using social media that the platform suggests people whom you may want to add as friends. The suggestion is based on you and the other person having common contacts, which indicates that you may know each other.