Institution
Agilent Technologies
Company•Santa Clara, California, United States•
About: Agilent Technologies is a company organization based out in Santa Clara, California, United States. It is known for research contribution in the topics: Signal & Mass spectrometry. The organization has 7398 authors who have published 11518 publications receiving 262410 citations. The organization is also known as: Agilent Technologies, Inc..
Papers published on a yearly basis
Papers
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07 Sep 2001TL;DR: In this paper, the authors propose a method of facilitating data transfers through a communication network, which includes forwarding a first data set received from a first interconnect device to a processor.
Abstract: A method of facilitating data transfers through a communication network. The method includes forwarding a first data set received from a first interconnect device to a processor. The first data set has transfer instructions and routing instructions associated therewith. The routing instructions specify a destination for the first data set. The method further includes extracting the transfer instructions at the processor and generating a first routing request for the first data set according to the transfer instructions to transfer the first data set to a second interconnect device. The second interconnect device is capable of routing the first data set to the destination. The first routing request has no association to the routing instructions.
57 citations
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TL;DR: The MEC method has been applied to three different atomic spectrometric techniques and the results were comparable with, and in several cases more accurate than, values obtained using the traditional external calibration, internal standardization, and standard additions methods.
57 citations
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TL;DR: This work evaluated the feasibility of using in-solution hybridization-based target capture on pooled DNA samples to enable cost-efficient population sequencing studies and identified single nucleotide variants with a low false discovery rate and accurately detect short insertion/deletion variants.
Abstract: High-throughput sequencing of targeted genomic loci in large populations is an effective approach for evaluating the contribution of rare variants to disease risk. We evaluated the feasibility of using in-solution hybridization-based target capture on pooled DNA samples to enable cost-efficient population sequencing studies. For this, we performed pooled sequencing of 100 HapMap samples across ∼ 600 kb of DNA sequence using the Illumina GAIIx. Using our accurate variant calling method for pooled sequence data, we were able to not only identify single nucleotide variants with a low false discovery rate ( = 0.995).
57 citations
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03 Apr 2001TL;DR: In this article, a polyphase, noise-shaping, fractional-N frequency synthesizer utilizes multiple, parallel fractional N divider channels to decorrelate noise and improve spectral purity.
Abstract: A polyphase, noise-shaping, fractional-N frequency synthesizer utilizes multiple, parallel fractional-N divider channels to deliberately decorrelate noise and improve spectral purity. The synthesizer comprises a voltage controlled oscillator (VCO), a reference signal source to produce a plurality of different reference signals, a loop integrator, a plurality of desynchronized divider channels and a signal summer. Each divider channel comprises a frequency divider, a fractional-N control logic and a phase detector. Each divider channel divides an output signal from the VCO by a variable division factor and compares the divided signal to a different reference signal to produce an error signal. The signal summer combines the error signals from the desynchronized divider channels into a combined error signal. The loop integrator integrates the combined error signal to produce a control voltage that is applied to the VCO. The divider channels are desynchronized with respect to one another using time and/or phase shifting techniques.
57 citations
Authors
Showing all 7402 results
Name | H-index | Papers | Citations |
---|---|---|---|
Hongjie Dai | 197 | 570 | 182579 |
Zhuang Liu | 149 | 535 | 87662 |
Jie Liu | 131 | 1531 | 68891 |
Thomas Quertermous | 103 | 405 | 52437 |
John E. Bowers | 102 | 1767 | 49290 |
Roy G. Gordon | 89 | 449 | 31058 |
Masaru Tomita | 76 | 677 | 40415 |
Stuart Lindsay | 74 | 347 | 22224 |
Ron Shamir | 74 | 319 | 23670 |
W. Richard McCombie | 71 | 144 | 64155 |
Tomoyoshi Soga | 71 | 392 | 21209 |
Michael R. Krames | 65 | 321 | 18448 |
Shabaz Mohammed | 64 | 188 | 17254 |
Geert Leus | 62 | 609 | 19492 |
Giuseppe Gigli | 61 | 541 | 15159 |