2012 - Fellow of John Simon Guggenheim Memorial Foundation
2009 - Fellow of Alfred P. Sloan Foundation
His primary scientific interests are in Genetics, Genome, Human genome, Comparative genomics and Evolutionary biology. His study ties his expertise on Computational biology together with the subject of Genetics. The subject of his Genome research is within the realm of Gene.
His Comparative genomics study combines topics in areas such as Latimeria and Zoology. His Evolutionary biology research is multidisciplinary, incorporating elements of Gene rearrangement and Whole genome sequencing. As a member of one scientific family, Adam Siepel mostly works in the field of ENCODE, focusing on GENCODE and, on occasion, Systems biology, Functional genomics, DNase-Seq and DNA.
Adam Siepel mainly focuses on Genetics, Genome, Computational biology, Gene and Evolutionary biology. His study in Genome focuses on Human genome, Genomics, Comparative genomics, Whole genome sequencing and Human accelerated regions. His work carried out in the field of Human genome brings together such families of science as Genome evolution and Function.
His research in Computational biology intersects with topics in Genome browser, RNA, Selection, microRNA and Statistical model. As a part of the same scientific family, Adam Siepel mostly works in the field of Evolutionary biology, focusing on Natural selection and, on occasion, Genetic algorithm. His ENCODE study frequently draws connections to other fields, such as GENCODE.
Adam Siepel mostly deals with Gene, Genome, Computational biology, Evolutionary biology and Inference. In the subject of general Genome, his work in Genomics, Negative selection and Gene Annotation is often linked to Pteronotus, thereby combining diverse domains of study. Adam Siepel has researched Genomics in several fields, including Genetic Fitness and Human genome.
The study incorporates disciplines such as RNA, Probabilistic logic, Selection and Statistical model in addition to Computational biology. The Evolutionary biology study which covers Natural selection that intersects with Genetic algorithm and Entropy. In Inference, Adam Siepel works on issues like Computational genomics, which are connected to Field.
His scientific interests lie mostly in Genome, Genetic model, Genomics, Data science and Simulation modeling. He interconnects Evolutionary biology and Genetic Fitness, Selection in the investigation of issues within Genome. The various areas that he examines in his Evolutionary biology study include Human genetic variation, Entropy, Natural selection and Probabilistic logic.
Adam Siepel has included themes like Field, Inference and Computational genomics in his Genetic model study. His research integrates issues of Denisovan, Population genetics and Neanderthal genome project in his study of Genomics. His study connects Systems biology and Data science.
This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.
Identification and analysis of functional elements in 1% of the human genome by the ENCODE pilot project
Ewan Birney;John A. Stamatoyannopoulos;Anindya Dutta;Roderic Guigó.
Evolutionarily conserved elements in vertebrate, insect, worm, and yeast genomes
Adam Siepel;Gill Bejerano;Jakob Skou Pedersen;Angie S Hinrichs.
Genome Research (2005)
The ENCODE (ENCyclopedia of DNA elements) Project
E. A. Feingold;P. J. Good;M. S. Guyer;S. Kamholz.
Sequence and comparative analysis of the chicken genome provide unique perspectives on vertebrate evolution
Ladeana W. Hillier;Webb Miller;Ewan Birney;Wesley Warren.
Detection of nonneutral substitution rates on mammalian phylogenies
Katherine S. Pollard;Melissa J. Hubisz;Kate R. Rosenbloom;Adam Siepel.
Genome Research (2010)
Phylogenetic Hidden Markov Models
Adam Siepel;David Haussler.
Combining phylogenetic and hidden Markov models in biosequence analysis.
Adam C. Siepel;David Haussler.
Journal of Computational Biology (2004)
Evolutionary and biomedical insights from the rhesus macaque genome
Richard A. Gibbs;Jeffrey Rogers.
A high-resolution map of human evolutionary constraint using 29 mammals.
Kerstin Lindblad-Toh;Manuel Garber;Or Zuk;Michael F. Lin;Michael F. Lin.
The UCSC Genome Browser Database: update 2006
A. S. Hinrichs;D. Karolchik;R. Baertsch;G. P. Barber.
Nucleic Acids Research (2006)
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