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
Improved Identification and Analysis of Small Open Reading Frame Encoded Polypeptides
Jiao Ma,Jiao Ma,Jolene K. Diedrich,Jolene K. Diedrich,Irwin Jungreis,Irwin Jungreis,Cynthia J. Donaldson,Joan Vaughan,Manolis Kellis,Manolis Kellis,John R. Yates,John R. Yates,Alan Saghatelian +12 more
TL;DR: Several steps in the SEP discovery workflow are optimized to improve SEP isolation and identification, leading to the detection of several new human SEPs (novel human genes), improved confidence in theSEP assignments, and enabled quantification of SEPs under different cellular conditions.
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Discovery and validation of sub-threshold genome-wide association study loci using epigenomic signatures.
Xinchen Wang,Xinchen Wang,Nathan R. Tucker,Gizem Rizki,Robert W. Mills,Peter H.L. Krijger,Elzo de Wit,Vidya Subramanian,Eric Bartell,Xinh Xinh Nguyen,Jiangchuan Ye,Jordan Leyton-Mange,Elena Dolmatova,Pim van der Harst,Wouter de Laat,Patrick T. Ellinor,Patrick T. Ellinor,Christopher Newton-Cheh,Christopher Newton-Cheh,David J. Milan,Manolis Kellis,Manolis Kellis,Laurie A. Boyer +22 more
TL;DR: It is shown that enhancers significantly overlap known loci associated with the cardiac QT interval and QRS duration, and it is demonstrated that these 'sub-threshold' signals represent novel loci, and that epigenomic maps are effective at discriminating true biological signals from noise.
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PhyloCSF: a comparative genomics method to distinguish protein-coding and non-coding regions
TL;DR: PhyloCSF as mentioned in this paper is a comparative genomics method that analyzes a multi-species nucleotide sequence alignment to determine whether it is likely to represent a conserved protein-coding region, based on a formal statistical comparison of phylogenetic codon models.
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Linking DNA Methyltransferases to Epigenetic Marks and Nucleosome Structure Genome-wide in Human Tumor Cells
Bilian Jin,Jason Ernst,Jason Ernst,Rochelle L. Tiedemann,Hongyan Xu,Suhas Sureshchandra,Manolis Kellis,Manolis Kellis,Stephen Dalton,Chen Liu,Jeong Hyeon Choi,Keith D. Robertson +11 more
TL;DR: A comparison of the epigenomes of normal and cancerous stem cells, and pluripotent and differentiated states shows that the presence of at least two DNMTs is strongly associated with loci targeted for DNA hypermethylation, and shed important light on the determinants of DNA methylation and how it may become disrupted in cancer cells.
Journal ArticleDOI
Integrative pathway enrichment analysis of multivariate omics data
Marta Paczkowska,Jonathan Barenboim,N Sintupisut,Natalie S. Fox,Helen He Zhu,Diala Abd-Rabbo,Miles W Mee,Paul C. Boutros,Federico Abascal,Samirkumar B. Amin,Gary D. Bader,Rameen Beroukhim,Johanna Bertl,Keith A. Boroevich,Søren Brunak,Peter J. Campbell,Joana Carlevaro-Fita,Dimple Chakravarty,Calvin Wing Yiu Chan,Ken Chen,Jung Kyoon Choi,Jordi Deu-Pons,Priyanka Dhingra,Klev Diamanti,Lars Feuerbach,J Fink,Nuno A. Fonseca,Joan Frigola,C Gambacorti Passerini,Dale W. Garsed,Mark Gerstein,Gad Getz,Abel Gonzalez-Perez,Qianyun Guo,Ivo Gut,David Haan,Mark P. Hamilton,Nicholas J. Haradhvala,Arif Harmanci,Mohamed Helmy,Carl Herrmann,Julian M. Hess,Asger Hobolth,Ermin Hodzic,Chen Hong,Henrik Hornshøj,Keren Isaev,Jose M. G. Izarzugaza,Rory Johnson,Toby Johnson,Malene Juul,Randi Istrup Juul,André Kahles,Abdullah Kahraman,Manolis Kellis,Ekta Khurana,Jong Kyoung Kim,Young-Wook Kim,Jan Komorowski,Jan O. Korbel,Swathi Ashok Kumar,Andrés Lanzós,Mitchell G. Lawrence,Darlene Lee,Kjong-Van Lehmann,Shantao Li,Xiaotong Li,Z Lin,Eric Minwei Liu,Lucas Lochovsky,Shaoke Lou,Tobias Madsen,Kathleen Marchal,Inigo Martincorena,Alexander Martinez-Fundichely,Yosef E. Maruvka,Patrick McGillivray,William Meyerson,Ferran Muiños,Loris Mularoni,Hidewaki Nakagawa,Morten Nielsen,Kiejung Park,Jakob Skou Pedersen,Oriol Pich,Tirso Pons,Sergio Pulido-Tamayo,Benjamin J. Raphael,I Reyes-Salazar,Matthew A. Reyna,Ester Rheinbay,Mark A. Rubin,Carlota Rubio-Perez,Radhakrishnan Sabarinathan,Suleyman Cenk Sahinalp,Gordon Saksena,Leonidas Salichos,Cindy Sander,Steve Schumacher,Mark Shackleton,Ofer Shapira,Ciyue Shen,Raunak Shrestha,Shimin Shuai,Nikos Sidiropoulos,Lina Sieverling,Nicholas A Sinnott-Armstrong,Lincoln Stein,Joshua M. Stuart,David Tamborero,Grace Tiao,Tatsuhiko Tsunoda,Husen M. Umer,Liis Uusküla-Reimand,Alfonso Valencia,Miguel Vazquez,Lieven Verbeke,Claes Wadelius,Lina Wadi,Jian Wang,Jonathan Warrell,Sebastian M. Waszak,Joachim Weischenfeldt,D Wheeler,Guanming Wu,Jun Yu,Jiashan Zhang,Xiuqing Zhang,Yan Zhang,Zhongming Zhao,Lihua Zou,C. Von Mering,Jüri Reimand +132 more
TL;DR: The authors develop ActivePathways method, which uses data fusion techniques for integrative pathway analysis of multi-omics data and candidate gene discovery that discovers significantly enriched pathways across multiple datasets using statistical data fusion.