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Showing 1–8 of 8 results
Advanced filters: Author: David M. McCandlish Clear advanced filters

  • Gene regulatory network architecture and complex dosage effects from paralogue diversification converge to shape phenotypic space, producing the potential for both strongly buffered phenotypes and sudden bursts of phenotypic change.

    • Sophia G. Zebell
    • Carlos Martí-Gómez
    • Zachary B. Lippman
    ResearchOpen Access
    Nature
    Volume: 644, P: 984-992

  • High-throughput combinatorial mutagenesis assays are useful to screen the function of many different sequences but they are not exhaustive. Here, Zhou and McCandlish develop a method to impute such missing genotype-phenotype data based on inferring the least epistatic sequence-function relationship.

    • Juannan Zhou
    • David M. McCandlish
    ResearchOpen Access
    Nature Communications
    Volume: 11, P: 1-14

  • Two small-molecule drugs, risdiplam and branaplam, have been developed for treating spinal muscular atrophy. Here the authors develop quantitative modeling methods for the sequence-specific and concentration-dependent effects of these and other splice-modifying drugs.

    • Yuma Ishigami
    • Mandy S. Wong
    • Justin B. Kinney
    ResearchOpen Access
    Nature Communications
    Volume: 15, P: 1-13

  • Mutations in a protein active site can alter function in useful ways, but the active site is sensitive to changes. Here the authors present a general strategy to design combinatorial mutation libraries. Applied to GFP, the authors isolate thousands of fluorescent designs that exhibit large and useful changes in spectral properties.

    • Jonathan Yaacov Weinstein
    • Carlos Martí-Gómez
    • Sarel J. Fleishman
    ResearchOpen Access
    Nature Communications
    Volume: 14, P: 1-13

  • Selfish mitochondrial genomes undergo selection at different levels, within and between hosts. Here, the authors combine mathematical modeling and empirical experimentation to determine the strength of selection at these different levels and to predict selfish mtDNA frequency in C. elegans.

    • Bryan L. Gitschlag
    • Claudia V. Pereira
    • Maulik R. Patel
    ResearchOpen Access
    Nature Communications
    Volume: 15, P: 1-14

  • The intersection of genomics and deep learning shows promise for real impact on healthcare and biological research, but the lack of interpretability in terms of biological mechanisms is limiting utility and further development. As a potential solution, Koo et al. present SQUID, an interpretability framework built using domain-specific genomic surrogate models.

    • Evan E. Seitz
    • David M. McCandlish
    • Peter K. Koo
    Research
    Nature Machine Intelligence
    Volume: 6, P: 701-713