Zobrazeno 1 - 7
of 7
pro vyhledávání: '"Michael D Karcher"'
Publikováno v:
PLoS Computational Biology, Vol 16, Iss 10, p e1007774 (2020)
Coalescent theory combined with statistical modeling allows us to estimate effective population size fluctuations from molecular sequences of individuals sampled from a population of interest. When sequences are sampled serially through time and the
Externí odkaz:
https://doaj.org/article/a12e8166102741dfb75db7e805a95615
Publikováno v:
PLoS Computational Biology, Vol 12, Iss 3, p e1004789 (2016)
Phylodynamics seeks to estimate effective population size fluctuations from molecular sequences of individuals sampled from a population of interest. One way to accomplish this task formulates an observed sequence data likelihood exploiting a coalesc
Externí odkaz:
https://doaj.org/article/9d01366323b64482b46a413698afd00a
Publikováno v:
Monthly Notices of the Royal Astronomical Society. 468:4077-4092
The sources that reionized the universe are still unknown, but likely candidates are faint but numerous galaxies. In this paper we present results from running a high resolution, uniform volume simulation, the Vulcan, to predict the number densities
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::cc6524392520e2520c93cf826100fa91
https://doi.org/10.1093/mnras/stx709
https://doi.org/10.1093/mnras/stx709
Publikováno v:
Bioinformatics (Oxford, England), vol 31, iss 20
Lan, S; Palacios, JA; Karcher, M; Minin, VN; & Shahbaba, B. (2015). An efficient Bayesian inference framework for coalescent-based nonparametric phylodynamics. Bioinformatics, 31(20), 3282-3289. doi: 10.1093/bioinformatics/btv378. UC Irvine: Retrieved from: http://www.escholarship.org/uc/item/6p23s3h0
Lan, S; Palacios, JA; Karcher, M; Minin, VN; & Shahbaba, B. (2015). An efficient Bayesian inference framework for coalescent-based nonparametric phylodynamics. Bioinformatics, 31(20), 3282-3289. doi: 10.1093/bioinformatics/btv378. UC Irvine: Retrieved from: http://www.escholarship.org/uc/item/6p23s3h0
Motivation: The field of phylodynamics focuses on the problem of reconstructing population size dynamics over time using current genetic samples taken from the population of interest. This technique has been extensively used in many areas of biology
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::64978971b2c442c3f1809c45b33f115b
https://doi.org/10.1093/bioinformatics/btv378
https://doi.org/10.1093/bioinformatics/btv378
Publikováno v:
Karcher, MD; Palacios, JA; Lan, S; & Minin, VN. (2017). PHYLODYN: an R package for phylodynamic simulation and inference. MOLECULAR ECOLOGY RESOURCES, 17(1), 96-100. doi: 10.1111/1755-0998.12630. UC Irvine: Retrieved from: http://www.escholarship.org/uc/item/0pm7d4nk
We introduce phylodyn, an R package for phylodynamic analysis based on gene genealogies. The package main functionality is Bayesian nonparametric estimation of effective population size fluctuations over time. Our implementation includes several Mark
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c90194730e511ec650e1270d76421277
http://www.escholarship.org/uc/item/0pm7d4nk
http://www.escholarship.org/uc/item/0pm7d4nk
Autor:
Lauren Anderson, Thomas R. Quinn, Michael D. Karcher, Jillian Bellovary, Marta Volonteri, Michael Tremmel, Fabio Governato, Andrew Pontzen
We present a novel implementation of supermassive black hole (SMBH) formation, dynamics, and accretion in the massively parallel tree+SPH code, ChaNGa. This approach improves the modeling of SMBHs in fully cosmological simulations, allowing for a mor
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::fa877a8c82f1f8cfc534069ffd52cef3
Publikováno v:
PLoS computational biology, vol 12, iss 3
PLoS Computational Biology, Vol 12, Iss 3, p e1004789 (2016)
PLoS Computational Biology
Karcher, MD; Palacios, JA; Bedford, T; Suchard, MA; & Minin, VN. (2016). Quantifying and Mitigating the Effect of Preferential Sampling on Phylodynamic Inference. PLOS COMPUTATIONAL BIOLOGY, 12(3). doi: 10.1371/journal.pcbi.1004789. UC Irvine: Retrieved from: http://www.escholarship.org/uc/item/34c0d0th
PLoS Computational Biology, Vol 12, Iss 3, p e1004789 (2016)
PLoS Computational Biology
Karcher, MD; Palacios, JA; Bedford, T; Suchard, MA; & Minin, VN. (2016). Quantifying and Mitigating the Effect of Preferential Sampling on Phylodynamic Inference. PLOS COMPUTATIONAL BIOLOGY, 12(3). doi: 10.1371/journal.pcbi.1004789. UC Irvine: Retrieved from: http://www.escholarship.org/uc/item/34c0d0th
Phylodynamics seeks to estimate effective population size fluctuations from molecular sequences of individuals sampled from a population of interest. One way to accomplish this task formulates an observed sequence data likelihood exploiting a coalesc
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d20d760f5abf186c4906bf7a68a46a75