University of California, Santa Cruz

About: University of California, Santa Cruz is a education organization based out in Santa Cruz, California, United States. It is known for research contribution in the topics: Galaxy & Population. The organization has 15541 authors who have published 44120 publications receiving 2759983 citations. The organization is also known as: UCSC & UC, Santa Cruz.

International network of cancer genome projects

Abstract: The International Cancer Genome Consortium (ICGC) was launched to coordinate large-scale cancer genome studies in tumours from 50 different cancer types and/or subtypes that are of clinical and societal importance across the globe. Systematic studies of more than 25,000 cancer genomes at the genomic, epigenomic and transcriptomic levels will reveal the repertoire of oncogenic mutations, uncover traces of the mutagenic influences, define clinically relevant subtypes for prognosis and therapeutic management, and enable the development of new cancer therapies.

Why are "natively unfolded" proteins unstructured under physiologic conditions?

Abstract: "Natively unfolded" proteins occupy a unique niche within the protein kingdom in that they lack ordered structure under conditions of neutral pH in vitro. Analysis of amino acid sequences, based on the normalized net charge and mean hydrophobicity, has been applied to two sets of proteins: small globular folded proteins and "natively unfolded" ones. The results show that "natively unfolded" proteins are specifically localized within a unique region of charge-hydrophobicity phase space and indicate that a combination of low overall hydrophobicity and large net charge represent a unique structural feature of "natively unfolded" proteins.

The Complete Light-curve Sample of Spectroscopically Confirmed SNe Ia from Pan-STARRS1 and Cosmological Constraints from the Combined Pantheon Sample

Abstract: Author(s): Scolnic, DM; Jones, DO; Rest, A; Pan, YC; Chornock, R; Foley, RJ; Huber, ME; Kessler, R; Narayan, G; Riess, AG; Rodney, S; Berger, E; Brout, DJ; Challis, PJ; Drout, M; Finkbeiner, D; Lunnan, R; Kirshner, RP; Sanders, NE; Schlafly, E; Smartt, S; Stubbs, CW; Tonry, J; Wood-Vasey, WM; Foley, M; Hand, J; Johnson, E; Burgett, WS; Chambers, KC; Draper, PW; Hodapp, KW; Kaiser, N; Kudritzki, RP; Magnier, EA; Metcalfe, N; Bresolin, F; Gall, E; Kotak, R; McCrum, M; Smith, KW | Abstract: We present optical light curves, redshifts, and classifications for 365 spectroscopically confirmed Type Ia supernovae (SNe Ia) discovered by the Pan-STARRS1 (PS1) Medium Deep Survey. We detail improvements to the PS1 SN photometry, astrometry, and calibration that reduce the systematic uncertainties in the PS1 SN Ia distances. We combine the subset of 279 PS1 SNe Ia (0.03 l z l 0.68) with useful distance estimates of SNe Ia from the Sloan Digital Sky Survey (SDSS), SNLS, and various low-z and Hubble Space Telescope samples to form the largest combined sample of SNe Ia, consisting of a total of 1048 SNe Ia in the range of 0.01 l z l 2.3, which we call the Pantheon Sample. When combining Planck 2015 cosmic microwave background (CMB) measurements with the Pantheon SN sample, we find Wm = 0.307 ± 0.012 and w = -1.026 ± 0.041 for the wCDM model. When the SN and CMB constraints are combined with constraints from BAO and local H0 measurements, the analysis yields the most precise measurement of dark energy to date: w0 = -1.007 ± 0.089 and wa = -0.222 ± 0.407 for the w0waCDM model. Tension with a cosmological constant previously seen in an analysis of PS1 and low-z SNe has diminished after an increase of 2× in the statistics of the PS1 sample, improved calibration and photometry, and stricter light-curve quality cuts. We find that the systematic uncertainties in our measurements of dark energy are almost as large as the statistical uncertainties, primarily due to limitations of modeling the low-redshift sample. This must be addressed for future progress in using SNe Ia to measure dark energy.

A Survey of Software-Defined Networking: Past, Present, and Future of Programmable Networks

Abstract: The idea of programmable networks has recently re-gained considerable momentum due to the emergence of the Software-Defined Networking (SDN) paradigm. SDN, often referred to as a ''radical new idea in networking'', promises to dramatically simplify network management and enable innovation through network programmability. This paper surveys the state-of-the-art in programmable networks with an emphasis on SDN. We provide a historic perspective of programmable networks from early ideas to recent developments. Then we present the SDN architecture and the OpenFlow standard in particular, discuss current alternatives for implementation and testing of SDN-based protocols and services, examine current and future SDN applications, and explore promising research directions based on the SDN paradigm.