TY - Generic T1 - Computing the Tree of Life: Leveraging the Power of Desktop and Service Grids T2 - Parallel and Distributed Processing Workshops and Phd Forum (IPDPSW), 2011 IEEE International Symposium on Y1 - 2011 A1 - Adam L. Bazinet A1 - Michael P. Cummings KW - (artificial KW - (mathematics) KW - analysis KW - BOINC KW - COMPUTATION KW - computational KW - computing KW - data KW - Estimation KW - evolutionary KW - GARLI KW - genetic KW - Grid KW - GRIDS KW - handling KW - heterogeneous KW - History KW - HPC KW - information KW - intelligence) KW - interface KW - interfaces KW - Internet KW - jobs KW - lattice KW - learning KW - life KW - likelihood KW - load KW - machine KW - maximum KW - method KW - model KW - molecular KW - phylogenetic KW - portal KW - Portals KW - power KW - project KW - resource KW - Science KW - sequence KW - service KW - services KW - sets KW - software KW - substantial KW - system KW - systematics KW - tree KW - TREES KW - user KW - Web AB - The trend in life sciences research, particularly in molecular evolutionary systematics, is toward larger data sets and ever-more detailed evolutionary models, which can generate substantial computational loads. Over the past several years we have developed a grid computing system aimed at providing researchers the computational power needed to complete such analyses in a timely manner. Our grid system, known as The Lattice Project, was the first to combine two models of grid computing - the service model, which mainly federates large institutional HPC resources, and the desktop model, which harnesses the power of PCs volunteered by the general public. Recently we have developed a "science portal" style web interface that makes it easier than ever for phylogenetic analyses to be completed using GARLI, a popular program that uses a maximum likelihood method to infer the evolutionary history of organisms on the basis of genetic sequence data. This paper describes our approach to scheduling thousands of GARLI jobs with diverse requirements to heterogeneous grid resources, which include volunteer computers running BOINC software. A key component of this system provides a priori GARLI runtime estimates using machine learning with random forests. JA - Parallel and Distributed Processing Workshops and Phd Forum (IPDPSW), 2011 IEEE International Symposium on ER - TY - JOUR T1 - Genetic consequences of ecological reserve design guidelines: An empirical investigation JF - Conserv GenetConserv Genet Y1 - 2003 A1 - Neel, M. C. A1 - Michael P. Cummings KW - albens KW - Astragulus KW - Bernardino KW - conservation KW - design KW - diversity KW - Erigeron KW - Eriogonum KW - genetic KW - Genetics KW - goodmaniana KW - Mountains KW - ovalifolium KW - Oxytheca KW - parishii KW - plant KW - reserve KW - San KW - var. KW - vineum AB - We assessed the genetic diversity consequences of applying ecological reserve design guidelines to four federally-listed globally-rare plant species. Consequences were measured using two metrics: proportion of all alleles and of common alleles included in reserves. Common alleles were defined as those alleles having a frequency of greater than or equal to0.05 in at least one population. Four conservation professionals applied ecological reserve guidelines to choose specific populations of each species for inclusion in reserves of size 1 to N - 1, where N is the total number of populations of each species. Information regarding genetic diversity was not used in selecting populations. The resulting reserve designs were compared to random designs, and the agreement among experts was assessed using Kendall's coefficient of concordance. Application of ecological reserve design guidelines proved mostly ineffective in capturing more genetic diversity than is captured selecting populations randomly. Meeting established targets for genetic diversity, such as one advocated by the Center for Plant Conservation, required larger numbers of populations than are suggested to be sufficient. Relative performance of expert designs differed among species and was dependent on whether the proportion of all alleles or of common alleles was used as a measure of diversity. Furthermore there was no significant concordance among experts in order in which populations were incorporated into reserves as experts differed in priority they placed on individual guidelines. VL - 4 ER - TY - JOUR T1 - DNA sequence variation in the ribosomal internal transcribed spacer region of freshwater ıt Cladophora species (Chlorophyta) JF - J PhycolJ Phycol Y1 - 1996 A1 - Marks, J. C. A1 - Michael P. Cummings KW - algae KW - Chlorophyta KW - Cladophora KW - diversity KW - freshwater KW - genetic KW - internal KW - spacer KW - transcribed AB - Freshwater species of Cladophora (Chlorophyta) are globally distributed and occupy an unusually wide range of ecological habitats. Delineating species is difficult because most easily observed morphological traits are highly variable and because sexual reproduction has not been clearly documented. Synthesizing ecological data on freshwater Cladophora species is problematic because it is unclear whether freshwater Cladophora species comprise many genetically distinct species or a few ecologically and morphologically variable and / or plastic species. We determined nucleotide sequences of the internal transcribed spacer (ITS) region of the nuclear ribosomal cistron of freshwater Cladophora species from a wide range of habitats and geographic locations. We compared these sequences to those derived from culture collections of C. fracta and C. glomerata, the two most commonly reported freshwater Cladophora species. Cladophora fracta and C. glomerata had very similar ITS sequences (95.3%). All other sequences were identical to those from the C. fracta or C. glomerata culture collections with the exception of one California sample that was similar to both C. fracta (95.6%) and C. glomerata (92.4%). ITS genotypes did not correlate with morphology or geography. This analysis shows that common freshwater Cladophora species comprise very few (possibly one) ecologically and morphologically variable species. VL - 32 ER -