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Institution

University of California, Irvine

EducationIrvine, California, United States
About: University of California, Irvine is a education organization based out in Irvine, California, United States. It is known for research contribution in the topics: Population & Galaxy. The organization has 47031 authors who have published 113602 publications receiving 5521832 citations. The organization is also known as: UC Irvine & UCI.
Topics: Population, Galaxy, Poison control, Cancer, Gene


Papers
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Journal ArticleDOI
TL;DR: In this article, the authors discuss the needs and benefits for a system that would monitor and predict the Earth's terrestrial water, energy, and biogeochemical cycles, and they call upon the international hydrologic community and the hydrological science support infrastructure to endorse the effort.
Abstract: Monitoring Earth's terrestrial water conditions is critically important to many hydrological applications such as global food production; assessing water resources sustainability; and flood, drought, and climate change prediction. These needs have motivated the development of pilot monitoring and prediction systems for terrestrial hydrologic and vegetative states, but to date only at the rather coarse spatial resolutions (∼10–100 km) over continental to global domains. Adequately addressing critical water cycle science questions and applications requires systems that are implemented globally at much higher resolutions, on the order of 1 km, resolutions referred to as hyperresolution in the context of global land surface models. This opinion paper sets forth the needs and benefits for a system that would monitor and predict the Earth's terrestrial water, energy, and biogeochemical cycles. We discuss six major challenges in developing a system: improved representation of surface-subsurface interactions due to fine-scale topography and vegetation; improved representation of land-atmospheric interactions and resulting spatial information on soil moisture and evapotranspiration; inclusion of water quality as part of the biogeochemical cycle; representation of human impacts from water management; utilizing massively parallel computer systems and recent computational advances in solving hyperresolution models that will have up to 109 unknowns; and developing the required in situ and remote sensing global data sets. We deem the development of a global hyperresolution model for monitoring the terrestrial water, energy, and biogeochemical cycles a “grand challenge” to the community, and we call upon the international hydrologic community and the hydrological science support infrastructure to endorse the effort.

704 citations

Proceedings ArticleDOI
01 Apr 1998
TL;DR: An architecture-based approach to runtime software evolution is presented and the role of software connectors in supporting runtime change is highlighted and an initial implementation of a tool suite for supporting the runtime modification of software architectures is presented.
Abstract: Continuous availability is a critical requirement for an important class of software systems. For these systems, runtime system evolution can mitigate the costs and risks associated with shutting down and restarting the system for an update. We present an architecture-based approach to runtime software evolution and highlight the role of software connectors in supporting runtime change. An initial implementation of a tool suite for supporting the runtime modification of software architectures, called ArchStudio, is presented.

704 citations

Journal ArticleDOI
TL;DR: Afatinib was active in non-small-cell lung cancer tumours that harboured certain types of uncommon EGFR mutations, especially Gly719Xaa, Leu861Gln, and Ser768Ile, but less active in other mutations types.
Abstract: Summary Background Most patients with non-small-cell lung cancer tumours that have EGFR mutations have deletion mutations in exon 19 or the Leu858Arg point mutation in exon 21, or both (ie, common mutations). However, a subset of patients (10%) with mutations in EGFR have tumours that harbour uncommon mutations. There is a paucity of data regarding the sensitivity of these tumours to EGFR inhibitors. Here we present data for the activity of afatinib in patients with advanced non-small-cell lung cancer that have tumours harbouring uncommon EGFR mutations. Methods In this post-hoc analysis, we used prospectively collected data from tyrosine kinase inhibitor-naive patients with EGFR mutation-positive advanced (stage IIIb–IV) lung adenocarcinomas who were given afatinib in a single group phase 2 trial (LUX-Lung 2), and randomised phase 3 trials (LUX-Lung 3 and LUX-Lung 6). Analyses were done in the intention-to-treat population, including all randomly assigned patients with uncommon EGFR mutations. The type of EGFR mutation (exon 19 deletion [del19], Leu858Arg point mutation in exon 21, or other) and ethnic origin (LUX-Lung 3 only; Asian vs non-Asian) were pre-specified stratification factors in the randomised trials. We categorised all uncommon mutations as: point mutations or duplications in exons 18–21 (group 1); de-novo Thr790Met mutations in exon 20 alone or in combination with other mutations (group 2); or exon 20 insertions (group 3). We also assessed outcomes in patients with the most frequent uncommon mutations, Gly719Xaa, Leu861Gln, and Ser768Ile, alone or in combination with other mutations. Response was established by independent radiological review. These trials are registered with ClinicalTrials.gov, numbers NCT00525148, NCT00949650, and NCT01121393. Findings Of 600 patients given afatinib across the three trials, 75 (12%) patients had uncommon EGFR mutations (38 in group 1, 14 in group 2, 23 in group 3). 27 (71·1%, 95% CI 54·1–84·6) patients in group 1 had objective responses, as did two (14·3%, 1·8–42·8) in group 2 and two (8·7%, 1·1–28·0) in group 3. Median progression-free survival was 10·7 months (95% CI 5·6–14·7) in group 1, 2·9 months (1·2–8·3) in group 2; and 2·7 months (1·8–4·2) in group 3. Median overall survival was 19·4 months (95% CI 16·4–26·9) in group 1, 14·9 months (8·1–24·9) in group 2, and 9·2 months (4·1–14·2) in group 3. For the most frequent uncommon mutations, 14 (77·8%, 95% CI 52·4–93·6) patients with Gly719Xaa had an objective response, as did nine (56·3%, 29·9–80·2) with Leu861Gln, and eight (100·0%, 63·1–100·0) with Ser768Ile. Interpretation Afatinib was active in non-small-cell lung cancer tumours that harboured certain types of uncommon EGFR mutations, especially Gly719Xaa, Leu861Gln, and Ser768Ile, but less active in other mutations types. Clinical benefit was lower in patients with de-novo Thr790Met and exon 20 insertion mutations. These data could help inform clinical decisions for patients with non-small-cell lung cancer harbouring uncommon EGFR mutations. Funding Boehringer Ingelheim.

704 citations

Journal ArticleDOI
TL;DR: The current state of development of HDAC therapeutics and their application for the treatment of human brain disorders such as Rubinstein–Taybi syndrome, Rett syndrome, Friedreich's ataxia, Huntington's disease and multiple sclerosis are summarized.
Abstract: Histone deacetylases (HDACs)--enzymes that affect the acetylation status of histones and other important cellular proteins--have been recognized as potentially useful therapeutic targets for a broad range of human disorders. Pharmacological manipulations using small-molecule HDAC inhibitors--which may restore transcriptional balance to neurons, modulate cytoskeletal function, affect immune responses and enhance protein degradation pathways--have been beneficial in various experimental models of brain diseases. Although mounting data predict a therapeutic benefit for HDAC-based therapy, drug discovery and development of clinical candidates face significant challenges. Here, we summarize the current state of development of HDAC therapeutics and their application for the treatment of human brain disorders such as Rubinstein-Taybi syndrome, Rett syndrome, Friedreich's ataxia, Huntington's disease and multiple sclerosis.

703 citations

Journal ArticleDOI
01 May 2002-Proteins
TL;DR: This paper used ensembles of bidirectional recurrent neural network architectures, PSI-BLAST-derived profiles, and a large non-redundant training set to derive two new predictors: SSpro and SSpro8.
Abstract: Secondary structure predictions are increasingly becoming the workhorse for several methods aiming at predicting protein structure and function. Here we use ensembles of bidirectional recurrent neural network architectures, PSI-BLAST-derived profiles, and a large nonredundant training set to derive two new predictors: (a) the second version of the SSpro program for secondary structure classification into three categories and (b) the first version of the SSpro8 program for secondary structure classification into the eight classes produced by the DSSP program. We describe the results of three different test sets on which SSpro achieved a sustained performance of about 78% correct prediction. We report confusion matrices, compare PSI-BLAST to BLAST-derived profiles, and assess the corresponding performance improvements. SSpro and SSpro8 are implemented as web servers, available together with other structural feature predictors at: http://promoter.ics.uci.edu/BRNN-PRED/. Proteins 2002;47:228–235. © 2002 Wiley-Liss, Inc.

702 citations


Authors

Showing all 47751 results

NameH-indexPapersCitations
Daniel Levy212933194778
Rob Knight2011061253207
Lewis C. Cantley196748169037
Dennis W. Dickson1911243148488
Terrie E. Moffitt182594150609
Joseph Biederman1791012117440
John R. Yates1771036129029
John A. Rogers1771341127390
Avshalom Caspi170524113583
Yang Gao1682047146301
Carl W. Cotman165809105323
John H. Seinfeld165921114911
Gregg C. Fonarow1611676126516
Jerome I. Rotter1561071116296
David Cella1561258106402
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
20242
2023252
20221,224
20216,518
20206,348
20195,610