Computational prediction of gene structure is crucial for interpreting genomic sequences. But how do the algorithms involved work and how accurate are they? Expression-based systems that use only ...

Probabilistic models, such as hidden Markov models or Bayesian networks, are commonly used to model biological data. Much of their popularity can be attributed to the existence of efficient and ...

Led by Dr. Jedrzej Jakub Szymanski, the international research team trained interpretable deep learning models, a subset of AI algorithms, on a vast dataset of genomic information from various ...

As DNA methylation is a key marker of gene expression ... that would also be observed in other tissues. By training an algorithm on methylation data from living species, the team achieved up ...

The diabetes prediction system is designed to predict the risk of diabetes utilizing clinical and genetic information through deep learning artificial intelligence algorithms. The number of type 2 ...