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Anand K. Ganesan

Researcher at University of California, Irvine

Publications -  56
Citations -  7660

Anand K. Ganesan is an academic researcher from University of California, Irvine. The author has contributed to research in topics: Medicine & Melanoma. The author has an hindex of 20, co-authored 42 publications receiving 6403 citations. Previous affiliations of Anand K. Ganesan include Medical College of Wisconsin & University of California, Berkeley.

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Journal ArticleDOI

Guidelines for the use and interpretation of assays for monitoring autophagy (3rd edition)

Daniel J. Klionsky, +2522 more
- 21 Jan 2016 - 
TL;DR: In this paper, the authors present a set of guidelines for the selection and interpretation of methods for use by investigators who aim to examine macro-autophagy and related processes, as well as for reviewers who need to provide realistic and reasonable critiques of papers that are focused on these processes.
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Genetic mechanisms of critical illness in Covid-19.

Erola Pairo-Castineira, +1449 more
- 04 Mar 2021 - 
TL;DR: The GenOMICC (Genetics Of Mortality In Critical Care) genome-wide association study in 2244 critically ill Covid-19 patients from 208 UK intensive care units is reported, finding evidence in support of a causal link from low expression of IFNAR2, and high expression of TYK2, to life-threatening disease.
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Genome-Wide siRNA-Based Functional Genomics of Pigmentation Identifies Novel Genes and Pathways That Impact Melanogenesis in Human Cells

TL;DR: The power of RNAi-based functional genomics to identify novel genes, pathways, and pharmacologic agents that impact a biological phenotype and operate outside of preconceived mechanistic relationships is illustrated.
Journal ArticleDOI

Pseudomonas aeruginosa exoenzyme S ADP-ribosylates Ras at multiple sites.

TL;DR: Analysis of in vitro transcribed/translated Ras mutants possessing individual Arg-to-Ala substitutions showed that Arg-41 was the preferred site of ADP-ribosylation, which is the first demonstration that ExoS disrupts a Ras-mediated signal transduction pathway.
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Systems-level cancer gene identification from protein interaction network topology applied to melanogenesis-related functional genomics data

TL;DR: By applying a series of clustering methods to proteins' topological signature similarities, it is demonstrated that the obtained clusters are significantly enriched with cancer genes, and clear evidence is provided that PPI network structure around cancer genes is different from the structure around non-cancer genes.