Institution
California Institute of Technology
Education•Pasadena, California, United States•
About: California Institute of Technology is a education organization based out in Pasadena, California, United States. It is known for research contribution in the topics: Galaxy & Redshift. The organization has 57649 authors who have published 146691 publications receiving 8620287 citations. The organization is also known as: Caltech & Cal Tech.
Topics: Galaxy, Redshift, Population, Star formation, Stars
Papers published on a yearly basis
Papers
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TL;DR: In this paper, the authors exploit these static quark symmetries to derive model-independent normalizations of some weak hadronic matrix elements involving heavy quarks, as well as many relationships between such matrix elements.
1,322 citations
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TL;DR: An assay for the presence of given DNA sequences has been developed, based on the ability of two oligonucleotides to anneal immediately adjacent to each other on a complementary target DNA molecule, which permits the rapid and standardized identification of single-copy gene sequences in genomic DNA.
Abstract: An assay for the presence of given DNA sequences has been developed, based on the ability of two oligonucleotides to anneal immediately adjacent to each other on a complementary target DNA molecule. The two oligonucleotides are then joined covalently by the action of a DNA ligase, provided that the nucleotides at the junction are correctly base-paired. Thus single nucleotide substitutions can be distinguished. This strategy permits the rapid and standardized identification of single-copy gene sequences in genomic DNA.
1,320 citations
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TL;DR: Within a Bayesian learning framework, objective functions are discussed that measure the expected informativeness of candidate measurements that depend on the assumption that the hypothesis space is correct.
Abstract: Learning can be made more efficient if we can actively select particularly salient data points. Within a Bayesian learning framework, objective functions are discussed that measure the expected informativeness of candidate measurements. Three alternative specifications of what we want to gain information about lead to three different criteria for data selection. All these criteria depend on the assumption that the hypothesis space is correct, which may prove to be their main weakness.
1,316 citations
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TL;DR: A mass-spectrometry-based proteomic analysis of human centrosomes in the interphase of the cell cycle by quantitatively profiling hundreds of proteins across several centrifugation fractions identified and validated 23 novel components and identified 41 likely candidates as well as the vast majority of the known centrosomal proteins in a large background of nonspecific proteins.
Abstract: The centrosome is the major microtubule-organizing centre of animal cells and through its influence on the cytoskeleton is involved in cell shape, polarity and motility. It also has a crucial function in cell division because it determines the poles of the mitotic spindle that segregates duplicated chromosomes between dividing cells. Despite the importance of this organelle to cell biology and more than 100 years of study, many aspects of its function remain enigmatic and its structure and composition are still largely unknown. We performed a mass-spectrometry-based proteomic analysis of human centrosomes in the interphase of the cell cycle by quantitatively profiling hundreds of proteins across several centrifugation fractions. True centrosomal proteins were revealed by both correlation with already known centrosomal proteins and in vivo localization. We identified and validated 23 novel components and identified 41 likely candidates as well as the vast majority of the known centrosomal proteins in a large background of nonspecific proteins. Protein correlation profiling permits the analysis of any multiprotein complex that can be enriched by fractionation but not purified to homogeneity.
1,312 citations
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California Institute of Technology1, Lawrence Berkeley National Laboratory2, University of California, Berkeley3, University of California, Santa Barbara4, Las Cumbres Observatory Global Telescope Network5, Weizmann Institute of Science6, Max Planck Society7, American Museum of Natural History8, University of Oxford9
TL;DR: The Palomar Transient Factory (PTF) as mentioned in this paper is a fully-automated, wide-field survey aimed at a systematic exploration of the optical transient sky.
Abstract: The Palomar Transient Factory (PTF) is a fully-automated, wide-field survey aimed at a systematic exploration of the optical transient sky. The transient survey is performed using a new 8.1 square degree camera installed on the 48 inch Samuel Oschin telescope at Palomar Observatory; colors and light curves for detected transients are obtained with the automated Palomar 60 inch telescope. PTF uses 80% of the 1.2 m and 50% of the 1.5 m telescope time. With an exposure of 60 s the survey reaches a depth of m_(g′) ≈ 21.3 and m_R ≈ 20.6 (5σ, median seeing). Four major experiments are planned for the five-year project: (1) a 5 day cadence supernova search; (2) a rapid transient search with cadences between 90 s and 1 day; (3) a search for eclipsing binaries and transiting planets in Orion; and (4) a 3π sr deep H-alpha survey. PTF provides automatic, real-time transient classification and follow-up, as well as a database including every source detected in each frame. This paper summarizes the PTF project, including several months of on-sky performance tests of the new survey camera, the observing plans, and the data reduction strategy. We conclude by detailing the first 51 PTF optical transient detections, found in commissioning data.
1,312 citations
Authors
Showing all 58155 results
Name | H-index | Papers | Citations |
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Eric S. Lander | 301 | 826 | 525976 |
Donald P. Schneider | 242 | 1622 | 263641 |
George M. Whitesides | 240 | 1739 | 269833 |
Yi Chen | 217 | 4342 | 293080 |
David Baltimore | 203 | 876 | 162955 |
Edward Witten | 202 | 602 | 204199 |
George Efstathiou | 187 | 637 | 156228 |
Michael A. Strauss | 185 | 1688 | 208506 |
Jing Wang | 184 | 4046 | 202769 |
Ruedi Aebersold | 182 | 879 | 141881 |
Douglas Scott | 178 | 1111 | 185229 |
Hyun-Chul Kim | 176 | 4076 | 183227 |
Phillip A. Sharp | 172 | 614 | 117126 |
Timothy M. Heckman | 170 | 754 | 141237 |
Zhenan Bao | 169 | 865 | 106571 |