scispace - formally typeset
Search or ask a question
Institution

University of Colorado Boulder

EducationBoulder, Colorado, United States
About: University of Colorado Boulder is a education organization based out in Boulder, Colorado, United States. It is known for research contribution in the topics: Population & Galaxy. The organization has 48794 authors who have published 115151 publications receiving 5387328 citations. The organization is also known as: CU Boulder & UCB.
Topics: Population, Galaxy, Poison control, Solar wind, Stars


Papers
More filters
Journal ArticleDOI
TL;DR: A roadmap of the most widely used and ecologically relevant approaches for analysis through a series of mission statements is provided, distinguishing two types of β diversity: directional turnover along a gradient vs. non-directional variation.
Abstract: A recent increase in studies of β diversity has yielded a confusing array of concepts, measures and methods. Here, we provide a roadmap of the most widely used and ecologically relevant approaches for analysis through a series of mission statements. We distinguish two types of β diversity: directional turnover along a gradient vs. non-directional variation. Different measures emphasize different properties of ecological data. Such properties include the degree of emphasis on presence/absence vs. relative abundance information and the inclusion vs. exclusion of joint absences. Judicious use of multiple measures in concert can uncover the underlying nature of patterns in β diversity for a given dataset. A case study of Indonesian coral assemblages shows the utility of a multi-faceted approach. We advocate careful consideration of relevant questions, matched by appropriate analyses. The rigorous application of null models will also help to reveal potential processes driving observed patterns in β diversity.

1,995 citations

Journal ArticleDOI
TL;DR: This paper shows that the essential condition for distribution-free learnability is finiteness of the Vapnik-Chervonenkis dimension, a simple combinatorial parameter of the class of concepts to be learned.
Abstract: Valiant's learnability model is extended to learning classes of concepts defined by regions in Euclidean space En. The methods in this paper lead to a unified treatment of some of Valiant's results, along with previous results on distribution-free convergence of certain pattern recognition algorithms. It is shown that the essential condition for distribution-free learnability is finiteness of the Vapnik-Chervonenkis dimension, a simple combinatorial parameter of the class of concepts to be learned. Using this parameter, the complexity and closure properties of learnable classes are analyzed, and the necessary and sufficient conditions are provided for feasible learnability.

1,967 citations

Journal ArticleDOI
TL;DR: Astropy as mentioned in this paper provides core astronomy-related functionality to the community, including support for domain-specific file formats such as Flexible Image Transport System (FITS) files, Virtual Observatory (VO) tables, and common ASCII table formats, unit and physical quantity conversions, physical constants specific to astronomy, celestial coordinate and time transformations, world coordinate system (WCS) support, generalized containers for representing gridded as well as tabular data, and a framework for cosmological transformations and conversions.
Abstract: We present the first public version (v0.2) of the open-source and community-developed Python package, Astropy. This package provides core astronomy-related functionality to the community, including support for domain-specific file formats such as Flexible Image Transport System (FITS) files, Virtual Observatory (VO) tables, and common ASCII table formats, unit and physical quantity conversions, physical constants specific to astronomy, celestial coordinate and time transformations, world coordinate system (WCS) support, generalized containers for representing gridded as well as tabular data, and a framework for cosmological transformations and conversions. Significant functionality is under active development, such as a model fitting framework, VO client and server tools, and aperture and point spread function (PSF) photometry tools. The core development team is actively making additions and enhancements to the current code base, and we encourage anyone interested to participate in the development of future Astropy versions.

1,944 citations

Journal ArticleDOI
TL;DR: In this article, the authors presented cosmological constraints from a joint analysis of type Ia supernova (SN Ia) observations obtained by the SDSS-II and SNLS collaborations.
Abstract: Aims. We present cosmological constraints from a joint analysis of type Ia supernova (SN Ia) observations obtained by the SDSS-II and SNLS collaborations. The dataset includes several low-redshift samples (z< 0.1), all three seasons from the SDSS-II (0.05

1,939 citations

Journal ArticleDOI
TL;DR: It is shown that applying qualitative and quantitative measures to the same data set can lead to dramatically different conclusions about the main factors that structure microbial diversity and can provide insight into the nature of community differences.
Abstract: The assessment of microbial diversity and distribution is a major concern in environmental microbiology. There are two general approaches for measuring community diversity: quantitative measures, which use the abundance of each taxon, and qualitative measures, which use only the presence/absence of data. Quantitative measures are ideally suited to revealing community differences that are due to changes in relative taxon abundance (e.g., when a particular set of taxa flourish because a limiting nutrient source becomes abundant). Qualitative measures are most informative when communities differ primarily by what can live in them (e.g., at high temperatures), in part because abundance information can obscure significant patterns of variation in which taxa are present. We illustrate these principles using two 16S rRNA-based surveys of microbial populations and two phylogenetic measures of community β diversity: unweighted UniFrac, a qualitative measure, and weighted UniFrac, a new quantitative measure, which we have added to the UniFrac website (http://bmf.colorado.edu/unifrac). These studies considered the relative influences of mineral chemistry, temperature, and geography on microbial community composition in acidic thermal springs in Yellowstone National Park and the influences of obesity and kinship on microbial community composition in the mouse gut. We show that applying qualitative and quantitative measures to the same data set can lead to dramatically different conclusions about the main factors that structure microbial diversity and can provide insight into the nature of community differences. We also demonstrate that both weighted and unweighted UniFrac measurements are robust to the methods used to build the underlying phylogeny.

1,927 citations


Authors

Showing all 49233 results

NameH-indexPapersCitations
Yi Chen2174342293080
Robert J. Lefkowitz214860147995
Rob Knight2011061253207
Charles A. Dinarello1901058139668
Jie Zhang1784857221720
David Haussler172488224960
Bradley Cox1692150156200
Gang Chen1673372149819
Rodney S. Ruoff164666194902
Menachem Elimelech15754795285
Jay Hauser1552145132683
Robert E. W. Hancock15277588481
Robert Plomin151110488588
Thomas E. Starzl150162591704
Rajesh Kumar1494439140830
Network Information
Related Institutions (5)
University of Washington
305.5K papers, 17.7M citations

97% related

Columbia University
224K papers, 12.8M citations

96% related

University of Michigan
342.3K papers, 17.6M citations

96% related

Stanford University
320.3K papers, 21.8M citations

96% related

University of California, Los Angeles
282.4K papers, 15.7M citations

96% related

Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
2023164
2022779
20216,286
20206,493
20196,063
20185,522