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A proteomic strategy for gaining insights into protein sumoylation in yeast

MOLECULAR & CELLULAR PROTEOMICS 2005年第3期4卷 246-254页

作者： Denison, C Rudner, AD Gerber, SA Bakalarski, CE Moazed, D Gygi, SP Harvard Univ Sch Med Dept Cell Biol Boston MA 02115 USA Harvard Univ Sch Med Taplin Biol Mass Spectrometry Facil Boston MA 02115 USA

Sumoylation represents a vital post-translational modification that pervades numerous aspects of cell biology, including protein targeting, transcriptional regulation, signal transduction, and cell division. However, despite its broad reaching effects, most biological outcomes of protein sumoylation remain poorly understood. In an effort to provide further insight into this complex process, a proteomics approach was undertaken to identify the targets of sumoylation en mass. Specifically, SUMO-conjugated proteins were isolated by a double-affinity purification procedure from a Saccharomyces cerevisiae strain engineered to express tagged SUMO. The components of the isolated protein mixture were then identified by subsequent LC-MS/MS analysis using an LTQ FT mass spectrometer. In this manner, 159 candidate sumoylated proteins were identified by two or more peptides. Furthermore, the high accuracy of the instrument, combined with stringent search criteria, enabled the identification of an additional 92 putative candidates by only one peptide. The validity of this proteomics approach was confirmed by performing subsequent Western blot experiments for numerous proteins and determining the actual sumoylation sites for several other substrates. These data combine with recent works to further our understanding of the breadth and impact of protein sumoylation in a diverse array of biological processes.

关键词： Protein processing Post-Translational Amino Acid Sequence Chromatography Liquid Molecular Sequence data Proteomics Research Support N.I.H. Extramural Research Support Non-U.S. Gov't Research Support U.S. Gov't P.H.S. Saccharomyces cerevisiae small Ubiquitin-Related Modifier Proteins Spectrum Analysis Mass

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Dual-sided subspace mappings for main-beam multi-target super-resolution in clutter and interference

Dual-sided subspace mappings for main-beam multi-target supe...

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IEEE National conference on Radar

作者： Manuel F. Fernández Kai-Bor Yu Independent Researcher Syracuse NY USA Independent Consultant Lake Forest CA USA

The need for localizing multiple main-beam targets in the presence of interference, clutter and jammers arises in scenarios such as: air defense, where a radar detection may correspond to one or multiple targets (e.g., a missile launched from an airborne platform); ballistic missile defense, where the incoming missile complex involves a large number of objects; cruise missile defense for low angle target tracking in multipath; etc. This paper presents a super-resolution approach for the sub-beamwidth localization of multiple main-beam targets in the presence of clutter and interference, doing so with a single snapshot of sensor array data while placing nulls at specified locations. Such process first maps array data into compact subspaces containing the information of interest (e.g., a cluster of receive beams with imbedded nulls). Super-resolution is then achieved via small-matrix operations on the subspace data. The ensuing result is a mapping of array data into a compressed “information domain,” yielding an effective, practical Sensor-to-Information process that is more accurate, robust and versatile than current super-resolution methods.

关键词： Arrays Clutter signal resolution Noise Vectors Array signal processing

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Bayesian classifier performance for realistically randomized signals 2

Bayesian classifier performance for realistically randomized...

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conference on Artificial Intelligence and Machine Learning for Multi-Domain Operations Applications II Part of SPIE Defense + Commercial Sensing conference

作者： Wilson, D. Keith Pettit, Chris L. Ostashev, Vladimir E. Dunn, Kyle G. US Army Cold Reg Res & Engn Lab 72 Lyme Rd Hanover NH 03755 USA US Naval Acad Aerosp Engn Dept 590 Holloway Rd Annapolis MD 21402 USA

ISBN: (纸本)9781510636040

Acoustic, seismic, radio-frequency, optical, and other types of signals in complex real-world environments are randomized by processes such as multipath reflections from buildings and hills, surface scattering from rough terrain, and volume scattering by turbulence and vegetation. Bayesian classifier methods have the ability to incorporate physically realistic distributions for the random signal variations caused by these processes, and thus enable quantitative assessments of the uncertainty in the target classifications. This paper formulates a Bayesian classifier for problems involving strongly scattered signals with partially correlated features, as would be appropriate for situations involving observations of multiple signal features (e.g., spectral bands) at multiple sensor locations. In this case, the appropriate formulation of the likelihood function is a complex Wishart distribution. We simulate the classifier performance for two- and three-target problems involving multiple spectral signal features, for cases involving moderate and strong correlations between the signal features. The results illustrate the challenges of performing reliable classification based on a small number of samples of a strongly scattered signal, particularly when the target features are similar in strength. When there exist strong correlations between the feature data, full Bayesian classifiers decisively outperform naive classifiers.

关键词： Bayesian classifiers automated target recognition statistical signal processing wave scattering

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One-class differential expression analysis using tensor decomposition-based unsupervised feature extraction applied to integrated analysis of multiple omics data from 26 lung adenocarcinoma cell lines 17

One-class differential expression analysis using tensor deco...

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17th IEEE International conference on Bioinformatics and Bioengineering (BIBE)

作者： Taguchi, Y-h Chuo Univ Dept Phys Bunkyo Ku 1-13-27 Kasuga Tokyo 1128551 Japan

ISBN: (纸本)9781538613245

Because usually there are no normal control cell lines, cancer cell lines can be examined only in a comparison between treatment and no-treatment conditions. Thus, characterization of cancer cell lines by themselves is impossible. To address this problem, one-class differential expression (DE) analysis, which can evaluate samples without a reference, is proposed here using tensor decomposition (TD)-based unsupervised feature extraction (FE) extended from recently proposed principal component analysis -based unsupervised FE. This one-class DE analysis was applied to multi-omics datasets of 26 lung adenocarcinoma cell lines. Enrichment analysis of selected genes identified multiple biological terms or concepts including signal recognition particles and nonsense-mediated decay (Reactome, Gene Ontology [GO] biological process), cadherin, poly(A) RNA binding (GO molecular function), eukaryotic translation initiation factors (Reactome), aberrant histone protein expression (Reactome and Human Protein Atlas [HPA]), and 163 transcription factors including E2F, PAX5, ARNT, AHR, and CREB, all of which are known to be related to non-small cell lung cancer and are expected to function cooperatively in lung adenocarcinoma oncogenesis. These data not only indicate usefulness of one-class DE analysis using TD -based unsupervised FE but also point to new therapeutic targets in lung adenocarcinoma.

关键词： tensor decomposition feature extraction cancer cell line unsupervised differential expression

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Position Monitoring of Multiple Moving targets Based on ZigBee and GPS

Position Monitoring of Multiple Moving Targets Based on ZigB...

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International conference on data Science and Business Analytics (ICDSBA)

作者： Dai Yu Wang Xuan Long Wenjia Yu Peng Ma Junyu Zhixing College of Hubei University Wuhan China

Moving target monitoring is widely used in many fields such as industrial control, military, and security. Traditional moving target monitoring generally uses infrared, ultra-sonic and other technologies, which have the disadvantages of complex implementation technology, high hardware cost and high environmental requirements. This paper proposes a low-cost, easy-to-deploy, and small-scale environment with little environmental impact by collecting GPS monitoring signals of multi-target speed and location and signal transmission and processing methods based on ZigBee wireless ad hoc network. signal acquisition and real-time data storage, transmission and processing methods have high application value and promotion significance.

关键词： Industrial control Zigbee Memory Real-time systems Hardware Trajectory Security

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Automatic target detection in dynamic clutter from incoherent ISAR data

Automatic target detection in dynamic clutter from incoheren...

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International conference on Acoustics, Speech, and signal processing (ICASSP)

作者： M. Soumekh M. Pollock R. Dinger Department of Electrical & Computer Engineering State University of New York University at Buffalo Amherst NY USA RDT&E Division Naval Command Control and Ocean Surveillance Center San Diego CA USA

This paper presents a method for automatic detection of targets with nonlinear motion embedded in dynamic clutter. This is achieved via processing the targets' incoherent ISAR data that are less vulnerable to multiplicative noise (phase errors). It is shown that the incoherent ISAR signature of a target scene may be viewed as its baseband ISAR signature. Thus, the magnitude of an ISAR database that is severely contaminated with phase errors, i.e., incoherent ISAR data, may be used for ISAR detection of moving targets. Incoherent ISAR data in the fast-time and slow-time domain are transformed into another two-dimensional domain. The signature of a target in the transformed domain is shown to be localized based on its mid-point range and speed. This localized statistic is suitable for automatic, i.e., machine-based, detection of stationary as well as moving targets in the scene.< >

关键词： Object detection Clutter Layout Baseband Radar detection Additive noise Embedded computing data engineering Motion detection Phase noise

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An Effective Approach to Ground Moving Target Imaging for Single Channel SAR System

An Effective Approach to Ground Moving Target Imaging for Si...

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IEEE International conference on Radar

作者： Feng Zhou Yachao Li Renbao Ru Mengdao Xing Zheng Bao National Lab. of Radar Signal Processing Xidian University Xi'an China Tianjin Key Lab for Advanced Signal Processing Civil Aviation University of China Tianjin China

Based on the envelopes and the characteristics of Doppler spectrum of returns in single channel synthetic aperture radar (SAR) systems a method is proposed, which adopts two order Keystone transform to adjust the range curvature of echo data, then range walk rates of echoes' envelopes are estimated to make some adjustments of walk and the Doppler parameters of moving targets are obtained through analyzing the Doppler spectrum of the moving targets. At last the images and positions of ground moving targets are gained, which make it possible that the moving targets can be indicated in right locations in SAR image. In addition the key motion parameters of moving targets can be estimated by the relationship between the Doppler parameters and motion parameters of ground moving targets. The results of the measured data show that this method can image ground moving targets and estimate motion parameters effectively

关键词： Parameter estimation Acceleration Radar signal processing Phase estimation Motion estimation Radar detection Motion analysis Chirp Azimuth Layout

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High Thermal Conductivity Mold Compounds for Advanced Packaging Applications 67

High Thermal Conductivity Mold Compounds for Advanced Packag...

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IEEE 67th Electronic Components and Technology conference (ECTC)

作者： Shibuya, M. Nguyen, L. Texas Instruments Inc Hiji Packaging Ctr Oita Japan Texas Instruments Inc Strateg Packaging R&D Santa Clara CA 95052 USA

ISBN: (纸本)9781509063154

Typical mold compounds with silica fillers have thermal conductivities (k) less than 1 W/mK. This paper will discuss one method to enhance k substantially with the addition of a small amount of graphene to batches of mold compounds with alumina fillers at different weight loading. Mixing techniques will be discussed together with characterization of properties (e.g., breakdown voltage, volume resistivity, and thermal conductivity) of the resulting composites. Several types of graphene powder were tested for these formulations of epoxy composites. A mold compound formulation with the highest k reported to date of 8.7 W/mK was obtained with less than 2wt% of graphene. Thermal resistance and MSL data with thermal test dies packaged in 8x8mm QFN will also be shown.

关键词： Estimation Field programmable gate arrays OFDM Modulation Filtration Clocks signal processing algorithms

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A robust motion compensation algorithm for ISAR imaging of sea-surface targets by Airborne Radar

A robust motion compensation algorithm for ISAR imaging of s...

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IEEE International conference on signal processing, Computing and Control (ISPCC)

作者： B. B. Mohapatra Vinod K Jaisaval Suchith Rajagopal Electronics & Radar Development Establishment DRDO Bangalore India

Motion compensation is the most critical part of Inverse Synthetic Aperture Radar (ISAR) processing in Airborne Radars. For an X-band Airborne Radar where resolution requirement is not sub-metric, Range-Doppler algorithm is the preferred choice to generate ISAR images due to small rotation angle requirement. In addition when both the radar platform and target are expected to move at nearly steady course and speed within the image formation interval, the use of highly sophisticated motion compensation algorithms is not desirable. This paper presents a robust and computationally efficient algorithm for translational motion compensation based on batch profile correlation. The algorithm is robust to background noise and target scintillation effects. It removes the problem of error accumulation inherent in peak-tracking method and avoids limitation of range-shift in integer steps. The effectiveness of the approach is verified by applying the algorithm to simulated ISAR data as well as actual ISAR data collected by an X-band airborne radar. The ISAR data simulation and processing are carried out using MATLAB. Different noise levels and target amplitude fluctuation are added to the simulated ISAR data to test the robustness of the algorithm.

关键词： Radar imaging Motion compensation Correlation Airborne radar Robustness Imaging

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Active Beam Tracking Under Stochastic Mobility

Active Beam Tracking Under Stochastic Mobility

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IEEE International conference on Communications (ICC)

作者： Ronquillo, Nancy Javidi, Tara Univ Calif San Diego Dept Elect & Comp Engn La Jolla CA 92093 USA

ISBN: (纸本)9781728171227

In mmWave communications, higher data rate long-range transmission is achieved by using highly directional beams with access to larger bandwidth. An inherent challenge is tracking channel state information (CSI) necessary for mmWave transmission under systems with unpredictable mobility. We propose a novel method of active and sequential beam tracking at mmWave frequencies and above. We focus on the dynamic scenario of UAV to UAV communications where the problem is equivalent to tracking an optimal beamforming vector along the line-of-sight path. In this setting, the resulting receiver beam ideally points in the direction of the angle of arrival with sufficiently high resolution. Existing solutions account for predictable movements or small random movements using known filtering strategies but resort to re-estimation protocols when tracking fails due to unpredictable movements. We propose an algorithm for actively and sequentially selecting beamforming vectors based on a Bayesian posterior with a prediction step to account for the mobility. Numerically, we analyze the normalized beamforming gain achieved by our proposed algorithm and demonstrate significant improvements over existing strategies.

关键词： Sensitivity Protocols Tracking Array signal processing Receivers Predictive models Prediction algorithms

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