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Institution

Agilent Technologies

CompanySanta 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
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Journal ArticleDOI
14 Feb 2013-Cell
TL;DR: The ability to rapidly generate mammalian GI maps provides a potentially transformative tool for defining gene function and designing combination therapies based on synergistic pairs.

347 citations

Journal ArticleDOI
TL;DR: Microfluidic integration of the nano-LC components enabled separations with subfemtomole detection sensitivity, minimal carryover, and robust and stable electrospray throughout the LC solvent gradient.
Abstract: Current nano-LC/MS systems require the use of an enrichment column, a separation column, a nanospray tip, and the fittings needed to connect these parts together. In this paper, we present a microfabricated approach to nano-LC, which integrates these components on a single LC chip, eliminating the need for conventional LC connections. The chip was fabricated by laminating polyimide films with laser-ablated channels, ports, and frit structures. The enrichment and separation columns were packed using conventional reversed-phase chromatography particles. A face-seal rotary valve provided a means for switching between sample loading and separation configurations with minimum dead and delay volumes while allowing high-pressure operation. The LC chip and valve assembly were mounted within a custom electrospray source on an ion-trap mass spectrometer. The overall system performance was demonstrated through reversed-phase gradient separations of tryptic protein digests at flow rates between 100 and 400 nL/min. Microfluidic integration of the nano-LC components enabled separations with subfemtomole detection sensitivity, minimal carryover, and robust and stable electrospray throughout the LC solvent gradient.

347 citations

Journal ArticleDOI
TL;DR: The External RNA Controls Consortium (ERCC) is developing commonly agreed-upon and tested controls for use in expression assays, a true industry-wide standard control.
Abstract: Standard controls and best practice guidelines advance acceptance of data from research, preclinical and clinical laboratories by providing a means for evaluating data quality. The External RNA Controls Consortium (ERCC) is developing commonly agreed-upon and tested controls for use in expression assays, a true industry-wide standard control.

337 citations

Journal ArticleDOI
TL;DR: Analysis of the same infected-tissue RNAs with rice oligoarrays identified putative effector-induced rice susceptibility genes, which are highly enriched for sensor-transduction components rather than typically identified defense response genes.
Abstract: Biotrophic invasive hyphae (IH) of the blast fungus Magnaporthe oryzae secrete effectors to alter host defenses and cellular processes as they successively invade living rice (Oryza sativa) cells. However, few blast effectors have been identified. Indeed, understanding fungal and rice genes contributing to biotrophic invasion has been difficult because so few plant cells have encountered IH at the earliest infection stages. We developed a robust procedure for isolating infected-rice sheath RNAs in which ∼20% of the RNA originated from IH in first-invaded cells. We analyzed these IH RNAs relative to control mycelial RNAs using M. oryzae oligoarrays. With a 10-fold differential expression threshold, we identified known effector PWL2 and 58 candidate effectors. Four of these candidates were confirmed to be fungal biotrophy-associated secreted (BAS) proteins. Fluorescently labeled BAS proteins were secreted into rice cells in distinct patterns in compatible, but not in incompatible, interactions. BAS1 and BAS2 proteins preferentially accumulated in biotrophic interfacial complexes along with known avirulence effectors, BAS3 showed additional localization near cell wall crossing points, and BAS4 uniformly outlined growing IH. Analysis of the same infected-tissue RNAs with rice oligoarrays identified putative effector-induced rice susceptibility genes, which are highly enriched for sensor-transduction components rather than typically identified defense response genes.

336 citations

Journal ArticleDOI
TL;DR: PRC1 physically constrains developmental transcription factor genes and their enhancers in a silenced but poised spatial network and it is proposed that the selective release of genes from this spatial network underlies cell fate specification during early embryonic development.
Abstract: The Polycomb repressive complexes PRC1 and PRC2 maintain embryonic stem cell (ESC) pluripotency by silencing lineage-specifying developmental regulator genes. Emerging evidence suggests that Polycomb complexes act through controlling spatial genome organization. We show that PRC1 functions as a master regulator of mouse ESC genome architecture by organizing genes in three-dimensional interaction networks. The strongest spatial network is composed of the four Hox gene clusters and early developmental transcription factor genes, the majority of which contact poised enhancers. Removal of Polycomb repression leads to disruption of promoter-promoter contacts in the Hox gene network. In contrast, promoter-enhancer contacts are maintained in the absence of Polycomb repression, with accompanying widespread acquisition of active chromatin signatures at network enhancers and pronounced transcriptional upregulation of network genes. Thus, PRC1 physically constrains developmental transcription factor genes and their enhancers in a silenced but poised spatial network. We propose that the selective release of genes from this spatial network underlies cell fate specification during early embryonic development.

334 citations


Authors

Showing all 7402 results

NameH-indexPapersCitations
Hongjie Dai197570182579
Zhuang Liu14953587662
Jie Liu131153168891
Thomas Quertermous10340552437
John E. Bowers102176749290
Roy G. Gordon8944931058
Masaru Tomita7667740415
Stuart Lindsay7434722224
Ron Shamir7431923670
W. Richard McCombie7114464155
Tomoyoshi Soga7139221209
Michael R. Krames6532118448
Shabaz Mohammed6418817254
Geert Leus6260919492
Giuseppe Gigli6154115159
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
20231
20228
2021142
2020157
2019168
2018164