K. C. Kent Lloyd

The paper analyzes citation practices for biological resources over 10 years, showing improved findability and adherence to NIH rigor criteria after adopting RRID citations.

The paper analyzes 3,313 genetically engineered mouse lines to identify gene essentiality as the main factor affecting Cas9-based genome editing success.

The paper analyzes whole-genome sequencing data from Cas9-edited mice to assess off-target mutagenesis, finding minimal off-target activity across 163 guide RNAs.

The paper identifies novel Mendelian genes by analyzing mouse embryo lethality and linking them to human disease phenotypes and genetic variants.

The paper introduces the GA4GH Phenopacket schema to standardize the exchange of phenotypic data for precision medicine applications.

The paper evaluates druggable genes in mice and finds that many understudied ones have significant phenotypes similar to human diseases, suggesting therapeutic potential.

This study shows that Arap1 in retinal pigment epithelium (RPE) is essential for photoreceptor survival through its role in phagocytosis, as Arap1 deficiency leads to photoreceptor degeneration.

This paper develops and evaluates [11C]26, a PET probe for imaging PDE7 in the brain, showing promising in vitro performance and moderate specific binding in nonhuman primates.

This study shows that deleting TAD boundaries in mice often causes molecular or developmental phenotypes, highlighting their importance for genome function.

The paper reports the generation of over 5,000 new mouse mutant strains for targeted genes, significantly expanding the available genetic resources for biomedical research.

The paper integrates gene essentiality data from human and mouse screens to classify genes into FUSIL categories, identifying developmental lethal genes associated with rare diseases.

The paper introduces a method called soft windowing to improve analysis of high-throughput phenotyping data by reducing false positives and increasing significant results.

The paper provides a metabolomics dataset from 30 mouse gene knockouts and wildtypes, identifying 832 metabolites across multiple analytical methods.