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Manolis Kellis (Kamvysselis) is a professor of Computer Science at the Massachusetts Institute of Technology (MIT) in the area of Computational Biology and a member of the Broad Institute of MIT and Harvard[3]. He is the head of the Computational Biology Group at MIT[4] and he is a Principal Investigator in the Computer Science and Artificial Intelligence Lab (CSAIL) at MIT[5]. His research interests are in the area of computational biology, genomics, epigenomics, gene regulation, and genome evolution[6].
Manolis Kellis | |
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Born | |
Alma mater | Massachusetts Institute of Technology |
Awards | US Presidential Early Career Award in Science and Engineering (PECASE), 2010
National Science Foundation CAREER Awards, 2007 Faculty Research Innovation Fellowships, 2015 [1] Alfred P. Sloan Fellowship [2] Karl Van Tassel chair, MIT EECS, 2007 Distinguished Alumnus 1964 chair, MIT EECS, 2005 Ruth and Joel Spira Teaching Award in EECS Athens Information Technology (AIT) Niki Award for Science and Engineering, 2011 Technology Review TR35 Top Young Innovators, 2006 MIT Sprowls Award for Best PhD Thesis in Computer Science, 2003 |
Scientific career | |
Institutions | Broad Institute of MIT and Harvard Massachusetts Institute of Technology Harvard Medical School |
Thesis | Computational Comparative Genomics: Genes, Regulation, Evolution. (2003) |
Doctoral advisor | Eric Lander, Bonnie Berger |
He is known for his contributions to genomics, including leading an National Institutes of Health effort to create a map of the human epigenome, which constitute the most comprehensive view of the human epigenome to date[7][8]. A major focus of his work is understanding the effects of genetic variations on human disease[9] with contributions to obesity[10][11][12], diabetes[13], Alzheimer's Disease[14][15][16], Schizophrenia[17] and cancer[18].
Manolis Kellis was born in Greece, moved with his family to France when he was 12, and came to the U.S. in 1993[19]. He obtained his Ph.D. from MIT, where he received the Sprowls award for the best doctorate thesis in Computer Science[20], and the first Paris Kanellakis graduate fellowship[21]. Prior to computational biology, he worked on artificial intelligence, sketch and image recognition, robotics, and computational geometry, at MIT and at the Xerox Palo Alto Research Center[22].
Manolis Kellis started comparing the genomes of yeast species as an MIT graduate student working with Eric Lander, founding director of the Broad and Bonnie Berger, professor at MIT[22]. As part of this work, which was published in Nature in 2003[23], he developed computational methods to pinpoint patterns of similarity and difference. The goal was to develop methods for understanding genomes with a view to apply them to the human genome. He turned from yeast to flies and ultimately to mammals, comparing multiple species to explore genes, their control and their dysfunction in the human genome[24].
As of July 2018, he has authored 187 journal publications[25] that have been cited 68,380 times[26]. He has helped direct several large-scale genomics projects, including the Roadmap Epigenomics project[27][8], the Encyclopedia of DNA Elements (ENCODE) project[28], the Genotype Tissue-Expression (GTEx) project[9], and comparative genomics projects in humans[24], mammals[29], flies[30] and yeast[31].
He led the NIH government-funded project to catalogue the epigenome. He told during an interview with the MIT Technology Review[24] “If the genome is the book of life, the epigenome is the complete set of annotations and bookmarks”[24]. He now uses the map to further the understanding of fundamental processes and disease in humans.
Following the publication of the Epigenome Roadmap, he and his colleagues used epigenomic data to investigate the process of dissipating energy as heat[10].They showed that this mechanism operates in the fat cells of both humans and mice and detailed how changes within the relevant genomic regions cause shifts in the dissipating energy[12]. A full understanding of the phenomenon might lead to treatments for people whose so-called slow metabolisms cause them to gain excessive weight[11].
In another paper published in 2015, Kellis, Li-Huei Tsai, and others at MIT used epigenomic markings in human and mouse brains to study the mechanisms leading to Alzheimer’s disease[14]. They showed that immune cell activation and inflammation, which have long been associated with the condition, are not simply the result of neurodegeneration, as some researchers have argued. Rather, in mice engineered to develop Alzheimer’s-like symptoms, they found that immune cells start to change even before neural changes are observed[15].
He is leading the MIT team in the new phase of the Genotype-Tissue Expression (GTEx) project to elucidate basis of disease predisposition. It is an NIH-sponsored work to characterize genetic variation in human tissues with roles in diabetes, heart disease, and cancer[9].
To date, his lab has developed specific domain expertise in obesity[11], diabetes[13], Alzheimer's Disease[14], Schizophrenia[17] and cancer[18].
In addition to his research, he has for several years co-taught MIT's required undergraduate introductory algorithm course 6.006: Introduction to Algorithms and 6.046: Design and Analysis of Algorithms[32]. He is also teaching a computational biology course at MIT, titled "Computational Biology: Genomes, Networks, Evolution"[33]. The course (6.047/6.878) is geared towards advanced undergraduate and early graduate students, seeking to learn the algorithmic and machine learning foundations of computational biology, and also be exposed to current frontiers of research in order to become active practitioners of the field[34]. He started 6.881: Computational Personal Genomics: Making sense of complete genomes[35]. This course is aimed at exploring the computational challenges associated with interpreting how sequence differences between individuals lead to phenotypic differences such as gene expression, disease predisposition, or response to treatment[36].
He received the US Presidential Early Career Award for Scientists and Engineers (PECASE)[37], the National Science Foundation CAREER award[38], the Alfred P. Sloan Foundation Award[39], the Athens Information Technology (AIT) Niki Award for Science and Engineering[40], the Ruth and Joel Spira Teaching award[41], and the George M. Sprowls Award for the best Ph.D. thesis in Computer Science at MIT[20]. He was named as one of Technology Review's Top 35 Innovators Under 35 for his research in comparative genomics[42].
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