Yi Chen

Bio: Yi Chen is an academic researcher from Chinese Academy of Sciences. The author has contributed to research in topics: Large Hadron Collider & Medicine. The author has an hindex of 217, co-authored 4342 publications receiving 293080 citations. Previous affiliations of Yi Chen include Rochester Institute of Technology & National Institutes of Health.

Search for gravitational waves from galactic and extra-galactic binary neutron stars

Abstract: We use 373 hours (≈15 days) of data from the second science run of the LIGO gravitational-wave detectors to search for signals from binary neutron star coalescences within a maximum distance of about 1.5 Mpc, a volume of space which includes the Andromeda Galaxy and other galaxies of the Local Group of galaxies. This analysis requires a signal to be found in data from detectors at the two LIGO sites, according to a set of coincidence criteria. The background (accidental coincidence rate) is determined from the data and is used to judge the significance of event candidates. No inspiral gravitational-wave events were identified in our search. Using a population model which includes the Local Group, we establish an upper limit of less than 47 inspiral events per year per Milky Way equivalent galaxy with 90% confidence for nonspinning binary neutron star systems with component masses between 1 and 3M⊙.

Search for narrow resonances using the dijet mass spectrum in pp collisions at √s=8 TeV

Abstract: Results are presented of a search for the production of new particles decaying to pairs of partons (quarks, antiquarks, or gluons), in the dijet mass spectrum in proton-proton collisions at sqrt(s) = 8 TeV. The data sample corresponds to an integrated luminosity of 4.0 inverse femtobarns, collected with the CMS detector at the LHC in 2012. No significant evidence for narrow resonance production is observed. Upper limits are set at the 95% confidence level on the production cross section of hypothetical new particles decaying to quark-quark, quark-gluon, or gluon-gluon final states. These limits are then translated into lower limits on the masses of new resonances in specific scenarios of physics beyond the standard model. The limits reach up to 4.8 TeV, depending on the model, and extend previous exclusions from similar searches performed at lower collision energies. For the first time mass limits are set for the Randall-Sundrum graviton model in the dijet channel.

Synthesis and c-Met Kinase Inhibition of 3,5-Disubstituted and 3,5,7-Trisubstituted Quinolines: Identification of 3-(4-Acetylpiperazin-1-yl)-5-(3-nitrobenzylamino)-7- (trifluoromethyl)quinoline as a Novel Anticancer Agent

Abstract: By use of an improved synthetic strategy, a series of 3,5-disubstituted and 3,5,7-trisubstituted quinolines were readily prepared. 3,5,7-Trisubstituted quinolines 21a−c, 21l, and 27a−c were identified as the most potent c-Met inhibitors with IC50 of less than 1.0 nM. Compound 21b showed the most promising overall PK profile and has high potency and extraordinary selectivity to c-Met against c-Met family member Ron and 12 other tyrosine kinases. It produced constitutive inhibition of c-Met phosphorylation in c-Met dependent cell lines. At doses of 100 mg/kg, compound 21b showed statistically significant tumor growth inhibition (68−69%) in both NIH-3T3-TPR-Met and U-87 MG human gliobastoma xenograft models. These results clearly indicated that compound 21b is a potent and highly selective c-Met inhibitor. Its favorable in vitro and in vivo profiles warrant further investigation.

Strong feature sets from small samples.

Abstract: For small samples, classifier design algorithms typically suffer from overfitting. Given a set of features, a classifier must be designed and its error estimated. For small samples, an error estimator may be unbiased but, owing to a large variance, often give very optimistic estimates. This paper proposes mitigating the small-sample problem by designing classifiers from a probability distribution resulting from spreading the mass of the sample points to make classification more difficult, while maintaining sample geometry. The algorithm is parameterized by the variance of the spreading distribution. By increasing the spread, the algorithm finds gene sets whose classification accuracy remains strong relative to greater spreading of the sample. The error gives a measure of the strength of the feature set as a function of the spread. The algorithm yields feature sets that can distinguish the two classes, not only for the sample data, but for distributions spread beyond the sample data. For linear classifiers...

I and i

Abstract: There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality. Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

KEGG: Kyoto Encyclopedia of Genes and Genomes

Abstract: Kyoto Encyclopedia of Genes and Genomes (KEGG) is a knowledge base for systematic analysis of gene functions in terms of the networks of genes and molecules. The major component of KEGG is the PATHWAY database that consists of graphical diagrams of biochemical pathways including most of the known metabolic pathways and some of the known regulatory pathways. The pathway information is also represented by the ortholog group tables summarizing orthologous and paralogous gene groups among different organisms. KEGG maintains the GENES database for the gene catalogs of all organisms with complete genomes and selected organisms with partial genomes, which are continuously re-annotated, as well as the LIGAND database for chemical compounds and enzymes. Each gene catalog is associated with the graphical genome map for chromosomal locations that is represented by Java applet. In addition to the data collection efforts, KEGG develops and provides various computational tools, such as for reconstructing biochemical pathways from the complete genome sequence and for predicting gene regulatory networks from the gene expression profiles. The KEGG databases are daily updated and made freely available (http://www.genome.ad.jp/kegg/).

limma powers differential expression analyses for RNA-sequencing and microarray studies

Abstract: limma is an R/Bioconductor software package that provides an integrated solution for analysing data from gene expression experiments. It contains rich features for handling complex experimental designs and for information borrowing to overcome the problem of small sample sizes. Over the past decade, limma has been a popular choice for gene discovery through differential expression analyses of microarray and high-throughput PCR data. The package contains particularly strong facilities for reading, normalizing and exploring such data. Recently, the capabilities of limma have been significantly expanded in two important directions. First, the package can now perform both differential expression and differential splicing analyses of RNA sequencing (RNA-seq) data. All the downstream analysis tools previously restricted to microarray data are now available for RNA-seq as well. These capabilities allow users to analyse both RNA-seq and microarray data with very similar pipelines. Second, the package is now able to go past the traditional gene-wise expression analyses in a variety of ways, analysing expression profiles in terms of co-regulated sets of genes or in terms of higher-order expression signatures. This provides enhanced possibilities for biological interpretation of gene expression differences. This article reviews the philosophy and design of the limma package, summarizing both new and historical features, with an emphasis on recent enhancements and features that have not been previously described.

Atherosclerosis — An Inflammatory Disease

Abstract: Atherosclerosis is an inflammatory disease. Because high plasma concentrations of cholesterol, in particular those of low-density lipoprotein (LDL) cholesterol, are one of the principal risk factors for atherosclerosis,1 the process of atherogenesis has been considered by many to consist largely of the accumulation of lipids within the artery wall; however, it is much more than that. Despite changes in lifestyle and the use of new pharmacologic approaches to lower plasma cholesterol concentrations,2,3 cardiovascular disease continues to be the principal cause of death in the United States, Europe, and much of Asia.4,5 In fact, the lesions of atherosclerosis represent . . .