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Anisha Luthra

Researcher at Memorial Sloan Kettering Cancer Center

Publications -  24
Citations -  449

Anisha Luthra is an academic researcher from Memorial Sloan Kettering Cancer Center. The author has contributed to research in topics: Medicine & Cancer. The author has an hindex of 5, co-authored 9 publications receiving 217 citations. Previous affiliations of Anisha Luthra include Cornell University.

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Reducing resistance allele formation in CRISPR gene drive

TL;DR: An experimental demonstration that multiplexing of guide RNAs can both significantly increase the drive conversion efficiency and reduce germline resistance rates of a CRISPR homing gene drive in Drosophila melanogaster and shows that an autosomal drive can achieve drive conversion in the male germline, with no subsequent formation of resistance alleles in embryos through paternal carryover of Cas9.
Posted ContentDOI

Genomic characterization of metastatic patterns from prospective clinical sequencing of 25,000 patients

TL;DR: The MSK-MET dataset as discussed by the authors is an integrated pan-cancer cohort of tumor genomic and clinical outcome data from more than 25,000 patients to identify associations between tumor genomic alterations and patterns of metastatic dissemination across 50 tumor types.
Journal ArticleDOI

CRISPR Gene Drive Efficiency and Resistance Rate Is Highly Heritable with No Common Genetic Loci of Large Effect

TL;DR: To investigate the effects of natural genetic variation on resistance formation in Drosophila melanogaster, a CRISPR homing gene drive was developed and crossed into the genetically diverse DGRP lines, measuring several performance parameters and finding resistance and conversion rates were not explained by common alleles of large effect.
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Maximum Likelihood Estimation of Fitness Components in Experimental Evolution.

TL;DR: A flexible maximum likelihood framework is developed that can disentangle different components of fitness from genotype frequency data, and estimate them individually in males and females and should be generally applicable to situations where it is important to quantify fitness components of specific genetic variants.