11 papers · ranked by Valyu relevance
Paweł Błażej, Małgorzata Wnetrzak, Dorota Mackiewicz, Paweł Mackiewicz
Compounds including non-canonical amino acids or other artificially designed molecules can find a lot of applications in medicine, industry and biotechnology. They can be produced thanks to the modification or extension of the standard genetic code (SGC). Such peptides or proteins including the non-canonical amino…
Mason Minot, Sai T. Reddy
Machine learning-guided protein engineering is a rapidly advancing field. Despite major experimental and computational advances however, collecting protein genotype (sequence) and phenotype (function) data remains time and resource intensive. As a result, the quality and quantity of training data is often a limiting…
Yiyang Yu, Shivani Muthukumar, Peter K Koo
Deep neural networks (DNNs) have been widely applied to predict the molecular functions of regulatory regions in the non-coding genome. DNNs are data hungry and thus require many training examples to fit data well. However, functional genomics experiments typically generate limited amounts of data, constrained by the…
Kuba Nowak, Paweł Błażej, Małgorzata Wnetrzak, Dorota Mackiewicz + 1 more
Reprogramming of the standard genetic code in order to include non-canonical amino acids (ncAAs) opens a new perspective in medicine, industry and biotechnology. There are several methods of engineering the code, which allow us for storing new genetic information in DNA sequences and transmitting it into the protein…
Nikita Janakarajan, Mara Graziani, Maria Rodriguez Martinez
Working with transcriptomic data is challenging in deep learning applications due to its high dimensionality and low patient numbers. Deep learning models tend to overfit this data and do not generalize well on out-of-distribution samples and new cohorts. Data augmentation strategies help alleviate this problem by…
Sahil Thapa, Khushali Samderiya, Rohit Menon, Oluwatosin Oluwadare
Accurate splice site prediction is fundamental to understanding gene expression and its associated disorders. However, most existing models are biased toward frequent canonical sites, limiting their ability to detect rare but biologically important non-canonical variants. These models often rely heavily on large…
Andrew G Duncan, Jennifer A Mitchell, Alan M Moses
Supervised deep learning is used to model the complex relationship between genomic sequence and regulatory function. Understanding how these models make predictions can provide biological insight into regulatory functions. Given the complexity of the sequence to regulatory function mapping (the cis-regulatory code), it…
Pawel M. Mordaka, Kitty Clouston, Jing Cui, Andre Holzer + 3 more
Genome scale engineering has enabled codon compression of the universal genetic code of up to three codons in E. coli, providing the means for genetic code expansion. To go much beyond this number, smaller and simpler genetic systems are needed to avoid significant technical challenges. Chloroplast genomes offer…
Balaji Kumar, Supreet Saini
Many theories have been proposed attempting to explain the origin of the genetic code. While strong reasons remain to believe that the genetic code evolved as a frozen accident, at least for the first few amino acids, other theories remain viable. In this work, we test the optimality of the standard genetic code…
James Heuschkel, Laura Kingsley, Noah Pefaur, Andrew Nixon + 1 more
Codon language models offer a promising framework for modeling protein-coding DNA sequences, yet current approaches often conflate codon usage with amino acid semantics, limiting their ability to capture DNA-level biology. We introduce SynCodonLM, a codon language model that enforces a biologically grounded constraint…
Paulina Kieliba, Danielle Clode, Roni O Maimon-Mor, Tamar R. Makin
From hand tools to cyborgs, humans have long been fascinated by the opportunities afforded by augmenting ourselves. Here, we studied how motor augmentation with an extra robotic thumb (the Third Thumb) impacts the biological hand representation in the brains of able-bodied people. Participants were tested on a variety…