8 papers · ranked by Valyu relevance
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…
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…
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…
Wesley E. Robertson, Fabian B. H. Rehm, Martin Spinck, Raffael L. Schumann + 12 more
The near-universal genetic code of living organisms uses 64 codons to encode the 20 canonical amino acids in protein synthesis. Here we design and generate a variant of Escherichia coli with a 4 Mb synthetic genome in which we replace every known occurrence of six sense codons and a stop codon with synonymous codons.…
Akos Nyerges, Anush Chiappino-Pepe, Bogdan Budnik, Maximilien Baas-Thomas + 26 more
Engineering the genetic code of an organism provides the basis for (i) making any organism safely resistant to natural viruses and (ii) preventing genetic information flow into and out of genetically modified organisms while (iii) allowing the biosynthesis of genetically encoded unnatural polymers^1–4^. Achieving these…
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…
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…
Yunran Chen, Jennifer M Groh, Surya T Tokdar
Understanding how neurons encode multiple simultaneous stimuli is a fundamental question in neuroscience. We have previously introduced a novel theory of stochastic encoding patterns wherein a neuron’s spiking activity dynamically switches among its constituent single-stimulus activity patterns when presented with…