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Beyond Words: The Expanding Role of Language Models in Biology
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Executive summary
Omar KantidzeNovember 27th, 2023

It's a characteristic of human nature to find new ways to use recently discovered tools, especially when scientists adapt them to address practical problems that spark their curiosity.

Transformer-based pre-trained language models (PLMs) such as Bidirectional Encoder Representations from Transformers (BERTand Generative Pre-Trained Transformers (GPT) have greatly changed the contemporary landscape of artificial intelligence (AI), and the real-world applications of such PLMs are continually expanding. Although originally designed for working with natural languages, these models have proven equally effective in handling languages of nature, such as nucleotide and amino acid sequences.

In this brief article, we aim to illustrate how these language models are reshaping the domains of biomedical text mining, functional genomics*, and protein engineering**, thus opening up fresh avenues for research and the development of innovative biologics-based therapies.

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About the author
Omar Kantidze Quantori
Omar Kantidze
Principal Scientist​

Omar Kantidze is an experienced team leader and scientist with a PhD in Molecular Biology, extensive knowledge, and a proven 15-year track record of accomplishment in functional genomics and molecular cell biology.

At Quantori, Omar plays a key role in developing internal scientific research, establishing collaborations with academic partners, and consulting on complex life science-related projects. His vast academic background makes Omar an integral part of Quantori's scientific achievements and reputation.

Previously, Omar served as the Head of the Cellular Genomics Department at the academic research organization and as a Scientific Director at the major medical research center.

Omar received his PhD and Dr.Sc. Degrees from the Institute of Gene Biology and a Master's degree from the Lomonosov State University.

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