A blog to share more or less groundbreaking scientific discoveries, fascinating insights, and intriguing tidbits, aimed at fostering a deeper understanding and appreciation of the ever-evolving world of bioinformatics.

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    Join RostLab's inaugural Winterschool for Toxinologists, exploring the intersection of machine learning and toxinology, from Dec 11-15, 2023 at TUM Campus Garching. Led by Prof. Burkhard Rost, the school will teach you how to integrate ML into toxinological research. Designed for toxinologists eager to understand machine learning basics and integrate it into their workflow. Register today to boost your research and explore the fascinating nexus of toxinology and machine learning.
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    The research team used artificial intelligence to study the evolutionary relationships of proteins, specifically focusing on the vertebrate kallikrein gene family, and found significant correlations between protein embeddings and sequence similarities. Despite testing various dimension reduction techniques, the initial protein embeddings without any reduction provided the most accurate insights into phylogenetic relationships, marking a substantial advancement in understanding life evolution and facilitating better drug development strategies.
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