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928篇 您的检索式:作者名="Hearn"
    题名 作者 年代 出处 被引量
1Double-stranded DNA in exosomes: a novel biomarker in cancer detection显示文摘Basant Kumar Thakur Haiying Zhang Annette Becker Irina Matei Yujie Huang Bruno Costa-Silva Yan Zheng Ayuko Hoshino Helene Brazier Jenny Xiang Caitlin Williams Ruth Rodriguez-Barrueco Jose M Silva Weijia Zhang Stephen Hearn Olivier Elemento Navid Paknejad Katia Manova-Todorova Karl Welte Jacqueline Bromberg Hector Peinado David Lyden 2014Cell Research2014,24,6:98
2Velocity structure of uppermost mantle beneath China continent from Pn tomography显示文摘汪素云 Thomas Hearn 许忠淮 James Ni 俞言祥 张晓东 2002Science China Earth Sciences2002,45,2:8
3青藏高原东部的Pn波层析成像研究显示文摘利用INDEPTH/ASCENT台阵和其它布设在青藏高原的流动宽频带地震仪数据,反演了青藏高原东部和周边区域的上地幔顶层Pn波速度以及台站延迟.研究区域的平均Pn波速度是8.1km/s,略高于中国大陆的平均Pn波速度.低速区主要分布在羌塘地块的西部和松潘—甘孜地块,高温异常的岩石圈上地幔很可能是导致这一低速区的原因.班公-怒江缝合带东端区域的Pn波速度达到8.35km/s,这一高速区可能与向北俯冲的印度板块(东端)有关.另一Pn波高速区分布在祁连山和昆仑山之间,主要由柴达木盆地和共和盆地及其周边地区,两个并不完全连续的高速异常区组成,它可能对应于特提斯洋闭合时北部增生的克拉通地体;在后来的欧亚板块与印度板块的碰撞中,这一地体有可能阻挡了青藏高原向北的生长.相对密集的台站提供了高分辨率的速度结构横向分布和地壳厚度变化.台站延迟显示青藏高原北部和东部的地壳存在显著的减薄——松潘—甘孜地块东北缘的地壳厚度仅为约50km,而羌塘地块东部唐古拉山地壳最厚,达到75km,这可能是由于印度—欧亚板块碰撞引起的羌塘地块内部变形增厚所致.王海洋 Thomas HEARN 陈永顺 裴顺平 冯永革 岳汉 金戈 周仕勇 王彦宾 盖增喜 宁杰远 Eric Sandvol James NI 2013地球物理学报2013,56,2:6
4三种胰岛素在反相色谱上的保留行为与热力学性质显示文摘以C8 柱为固定相 ,5 4%~ 5 9%甲醇为流动相 ,在一个广泛的温度 10~ 6 5℃范围内 ,研究了人、牛、猪 3种生物的胰岛素在高效反相色谱上的保留行为和热力学性质。研究结果表明 3种胰岛素在结构上的细微差别 ,能在反相色谱行为上明显地显示出来。同时还测定了 3种胰岛素与C8 柱结合时的焓ΔHo 和熵ΔSo 变化情况 ,这些热力学参数 ,对多肽和疏水界面相互作用机制的研究具有重要的参考价值。实验结果证明 ,通过色谱热力学参数的测定 ,将为蛋白质折叠机制以及生物大分子相互作用机制的研究 。郭敏亮 Milton T W Hearn Reinhard I Boysen 2000生物化学与生物物理学报2000,32,3:6
5Dispersal is associated with morphological innovation, but not increased diversification, in Cyphostemma (Vitaceae)显示文摘包括疏开,词法革新,和产地变化的多重过程经常为增加的多样化作为催化剂被引用。我们在类 Cyphostemma (Vitaceae ) 在他们之中调查这些过程和原因的连接,包括在为它生长习惯的差异的 Vitaceae 是唯一的 200 种类的 clade。我们重建 timecalibrated 在在使用五的类的 64 种类之中的进化关系原子并且叶绿体标记并且推断词法的组和 biogeographic 历史。我们测试因为在种形成的变化评估并且评估时间的协会并且用一条蒙特卡罗模拟途径关于疏开,产地变化,和词法进化事件定序。在 Cyphostemma,既不疏开也不词法进化处于种形成率与移动被联系,但是疏开在生长形式与进化移动被联系。特别地,茎多汁的进化与改编被联系到本地人,先存在在 situ 的条件列在后面 longdistance 疏开,不是产地变化。我们建议在疏开,词法革新,和多样化之间的协会的模式可以在学习下面依靠特别人物。与 evolutionarily 易变的人物一起的系例如茎多汁,未必确实遵循壁龛保守主义的观点并且相反表明显著词法改编到本地气候和土壤的条件列在后面疏开。David J. Hearn Margaret Evans Ben Wolf Michael McGinty Jun Wen 2018Journal of Systematics and Evolution2018,56,4:6
6多肽和蛋白质的反相高效液相色谱研究——色谱行为的多样性显示文摘以C8 柱为固定相 ,研究了微管结合蛋白2中两段重要肽段(肽1 ,肽2)和猪胰岛素在反相色谱上的保留行为。当以甲醇溶液为流动相时 ,猪胰岛素保留因子的对数值(lnK′)随流动相有机溶剂体积分数(φ)的变化呈现很好的线性关系。当以乙腈为流动相测定肽1的lnK′随 φ变化关系时 ,所得结果显示lnK′与 φ呈现良好的二次曲线关系。以乙腈为流动相测定肽1和肽2的Van'tHoff曲线(lnK′与1/T的关系图)时 ,发现两种多肽的Van'tHoff曲线分别呈二次和三次方曲线。所有这些结果说明多肽和蛋白质在反相色谱中保留行为的复杂性。郭敏亮 Milton T W HEARN Hooi Hong KEAH 2000分析测试学报2000,19,4:4
7Treatment of gastric varices with partial splenic embolization in a patient with portal vein thrombosis and a myeloproliferative disorder显示文摘Therapeutic options for gastric variceal bleeding in the presence of extensive portal vein thrombosis associated with a myeloproliferative disorder are limited.We report a case of a young woman who presented with gastric variceal bleeding secondary to extensive splanchnic venous thrombosis due to a Janus kinase 2 mutation associated myeloproliferative disorder that was managed effectively with partial splenic embolization.Robert Gianotti Hearns Charles Kenneth Hymes Hersh Chandarana Samuel Sigal 2014World Journal of Gastroenterology2014,20,39:4
8DNNGP, a deep neural network-based method for genomic prediction using multi-omics data in plants显示文摘Genomic prediction is an effective way to accelerate the rate of agronomic trait improvement in plants.Traditional methods typically use linear regression models with clear assumptions;such methods are unable to capture the complex relationships between genotypes and phenotypes.Non-linear models(e.g.,deep neural networks)have been proposed as a superior alternative to linear models because they can capture complex non-additive effects.Here we introduce a deep learning(DL)method,deep neural network genomic prediction(DNNGP),for integration of multi-omics data in plants.We trained DNNGP on four datasets and compared its performance with methods built with five classic models:genomic best linear unbiased prediction(GBLUP);two methods based on a machine learning(ML)framework,light gradient boosting machine(LightGBM)and support vector regression(SVR);and two methods based on a DL framework,deep learning genomic selection(DeepGS)and deep learning genome-wide association study(DLGWAS).DNNGP is novel in five ways.First,it can be applied to a variety of omics data to predict phenotypes.Second,the multilayered hierarchical structure of DNNGP dynamically learns features from raw data,avoiding overfitting and improving the convergence rate using a batch normalization layer and early stopping and rectified linear activation(rectified linear unit)functions.Third,when small datasets were used,DNNGP produced results that are competitive with results from the other five methods,showing greater prediction accuracy than the other methods when large-scale breeding data were used.Fourth,the computation time required by DNNGP was comparable with that of commonly used methods,up to 10 times faster than DeepGS.Fifth,hyperparameters can easily be batch tuned on a local machine.Compared with GBLUP,LightGBM,SVR,DeepGS and DLGWAS,DNNGP is superior to these existing widely used genomic selection(GS)methods.Moreover,DNNGP can generate robust assessments from diverse datasets,including omics data,and quickly incorporate complex and large datasets into usable models,making it a promising and practical approach for straightforward integration into existing GS platforms.Kelin Wang Muhammad Ali Abid Awais Rasheed Jose Crossa Sarah Hearne Huihui Li 2023Molecular Plant2023,16,1:3
9Combination strategies to enhance antitumor ADCC显示文摘Holbrook E Kohrt Roch Houot Auré lien Marabelle Hearn Jay Cho Keren Osman Matthew Goldstein Ronald Levy Joshua Brody 2012Immunotherapy2012,,5:2
10Deep impact: Excavating comet Tempel 1 显示文摘A'Hearn M F Belton M J S Delamere W A 2005Science2005,310,:1
11Linking Physiological and Architectural Models of Cotton 显示文摘Hanan J Hearn A 2003Agricultural Systems2003,,75:1
12Differential neuronal localizations and dynamics of phosphorylated and unphosphorylated type 1 IP3Rs显示文摘 Braj DJ O'Hearn E 2001Neuroscience2001,102,2:1
13An Overview of Polymer Latex Film Formation and Properties 显示文摘STEWARD P A HEARN J WILKINSON M C 2000Advance in Colloid and Interface Science2000,,86:1
14Microsatllites for linkage analysis of genetic traits显示文摘Hearne C M Ghosh S Todd J A 1992Trends in Genetic1992,8,:1
15Cotton nutrition显示文摘Hearn AB 1980Field Crops Abstract1980,,34:1
16Modal analy-sis for damage de-tection in structure显示文摘Hearn G Testa R B 1991Journal of structural Engineer-ing A-SCE1991,117,10:1
17Geological factors influencing reservoir performance of the hartzog draw field, Wyoming显示文摘Hearn C L Ebanks W Jr Ranganath V 1984JPT1984,,8:1
18Geological Fac tors Influencing Reservoir Performance of the Hartzog Draw Field, Wyoming显示文摘Hearn CL Ebanks WJ JR Tye RS 1984Petrol Tech1984,36,:1
19A comparison of double- focusing sector field ICP-MS, ICP-OES and octopole collision cell 1CP-MS for the high-accuracy determination of calcium in human serum 显示文摘Loma A Simpson Ruth Hearn 2005Talanta2005,65,:1
20Geological factors in- fluencing reservoir performance of the Hartzog Draw Field, Wyoming 显示文摘Hearn C J Ebanks W J Ranganath V 1984Journal of Petroloum Technology1984,36,11:1
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