M
Manolis Kellis
Researcher at Massachusetts Institute of Technology
Publications - 448
Citations - 132627
Manolis Kellis is an academic researcher from Massachusetts Institute of Technology. The author has contributed to research in topics: Gene & Genome. The author has an hindex of 128, co-authored 405 publications receiving 112181 citations. Previous affiliations of Manolis Kellis include Broad Institute & Epigenomics AG.
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Journal ArticleDOI
Conflicting and ambiguous names of overlapping ORFs in the SARS-CoV-2 genome: A homology-based resolution.
Irwin Jungreis,Irwin Jungreis,Chase W. Nelson,Zachary Ardern,Yaara Finkel,Nevan J. Krogan,Kei Sato,John Ziebuhr,Noam Stern-Ginossar,Angelo Pavesi,Andrew E. Firth,Alexander E. Gorbalenya,Manolis Kellis +12 more
TL;DR: This paper proposed standard names for ORFs and their shorter isoforms, developed in consultation with the Coronaviridae Study Group of the International Committee on Taxonomy of Viruses.
Journal ArticleDOI
NEBULA is a fast negative binomial mixed model for differential or co-expression analysis of large-scale multi-subject single-cell data
Liang He,Jose Davila-Velderrain,Tomokazu Sumida,David A. Hafler,Manolis Kellis,Manolis Kellis,Alexander M. Kulminski +6 more
TL;DR: In this paper, the authors proposed an efficient NEgative Binomial mixed model using a large-sample approximation (NEBULA), which analytically solves high-dimensional integrals instead of using the Laplace approximation.
Journal ArticleDOI
Plasma-derived extracellular vesicle analysis and deconvolution enable prediction and tracking of melanoma checkpoint blockade outcome.
Alvin Shi,Alvin Shi,Gyulnara G. Kasumova,William A. Michaud,Jessica Cintolo-Gonzalez,Marta Díaz-Martínez,Jacqueline Ohmura,Arnav Mehta,Isabel Chien,Dennie T. Frederick,Sonia Cohen,Deborah Plana,Douglas B. Johnson,Keith T. Flaherty,Ryan J. Sullivan,Manolis Kellis,Manolis Kellis,Genevieve M. Boland,Genevieve M. Boland +18 more
TL;DR: In this paper, the authors identify and validate biomarkers from extracellular vesicles (EVs), allowing non-invasive monitoring of tumor- intrinsic and host immune status, as well as a prediction of ICI response.
Journal ArticleDOI
Author Correction: Single-cell transcriptomic analysis of Alzheimer's disease.
Hansruedi Mathys,Jose Davila-Velderrain,Zhuyu Peng,Zhuyu Peng,Fan Gao,Fan Gao,Shahin Mohammadi,Shahin Mohammadi,Jennie Z. Young,Jennie Z. Young,Madhvi Menon,Liang He,Liang He,Fatema Abdurrob,Fatema Abdurrob,Xueqiao Jiang,Xueqiao Jiang,Anthony J Martorell,Anthony J Martorell,Richard M. Ransohoff,Brian P. Hafler,David A. Bennett,Manolis Kellis,Manolis Kellis,Li-Huei Tsai,Li-Huei Tsai,Li-Huei Tsai +26 more
TL;DR: In this Article, the Acknowledgements section should have included that the work was supported in part by the Cure Alzheimer’s Fund (CAF), and the final NIH grant acknowledged should have been ‘U01MH119509’ instead of ‘RF1AG054012’.
Posted ContentDOI
High-Throughput 5’ UTR Engineering for Enhanced Protein Production in Non-Viral Gene Therapies
Jicong Cao,Eva Maria Novoa,Zhizhuo Zhang,William C.W. Chen,Dianbo Liu,Gigi C G Choi,Alan S.L. Wong,Claudia Wehrspaun,Manolis Kellis,Timothy K. Lu +9 more
TL;DR: It is demonstrated that high-throughput screening of 5’ UTR libraries with recombinase-mediated integration can identify genetic elements that enhance protein expression, which should have numerous applications for engineered cell and gene therapies.