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141.
The computational prediction of gene and protein function is rapidly gaining ground as a central undertaking in computational biology. Making sense of the flood of genomic data requires fast and reliable annotation. Many ingenious algorithms have been devised to infer a protein's function from its amino acid sequence, 3D structure and chromosomal location of the encoding genes. However, there are significant challenges in assessing how well these programs perform. In this article we explore those challenges and review our own attempt at assessing the performance of those programs. We conclude that the task is far from complete and that a critical assessment of the performance of function prediction programs is necessary to make true progress in computational function prediction. 相似文献
142.
In this paper, we assess the predictive content of latent economic policy uncertainty and data surprise factors for forecasting and nowcasting gross domestic product (GDP) using factor-type econometric models. Our analysis focuses on five emerging market economies: Brazil, Indonesia, Mexico, South Africa, and Turkey; and we carry out a forecasting horse race in which predictions from various different models are compared. These models may (or may not) contain latent uncertainty and surprise factors constructed using both local and global economic datasets. The set of models that we examine in our experiments includes both simple benchmark linear econometric models as well as dynamic factor models that are estimated using a variety of frequentist and Bayesian data shrinkage methods based on the least absolute shrinkage operator (LASSO). We find that the inclusion of our new uncertainty and surprise factors leads to superior predictions of GDP growth, particularly when these latent factors are constructed using Bayesian variants of the LASSO. Overall, our findings point to the importance of spillover effects from global uncertainty and data surprises, when predicting GDP growth in emerging market economies. 相似文献
143.
Dmitri B. Papkovsky Ruslan I. Dmitriev 《Cellular and molecular life sciences : CMLS》2018,75(16):2963-2980
Molecular oxygen (O2) is a key player in cell mitochondrial function, redox balance and oxidative stress, normal tissue function and many common disease states. Various chemical, physical and biological methods have been proposed for measurement, real-time monitoring and imaging of O2 concentration, state of decreased O2 (hypoxia) and related parameters in cells and tissue. Here, we review the established and emerging optical microscopy techniques allowing to visualize O2 levels in cells and tissue samples, mostly under in vitro and ex vivo, but also under in vivo settings. Particular examples include fluorescent hypoxia stains, fluorescent protein reporter systems, phosphorescent probes and nanosensors of different types. These techniques allow high-resolution mapping of O2 gradients in live or post-mortem tissue, in 2D or 3D, qualitatively or quantitatively. They enable control and monitoring of oxygenation conditions and their correlation with other biomarkers of cell and tissue function. Comparison of these techniques and corresponding imaging setups, their analytical capabilities and typical applications are given. 相似文献
144.
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146.
Yang J Ferreira T Morris AP Medland SE;Genetic Investigation of ANthropometric Traits 《Nature genetics》2012,44(4):369-75, S1-3
We present an approximate conditional and joint association analysis that can use summary-level statistics from a meta-analysis of genome-wide association studies (GWAS) and estimated linkage disequilibrium (LD) from a reference sample with individual-level genotype data. Using this method, we analyzed meta-analysis summary data from the GIANT Consortium for height and body mass index (BMI), with the LD structure estimated from genotype data in two independent cohorts. We identified 36 loci with multiple associated variants for height (38 leading and 49 additional SNPs, 87 in total) via a genome-wide SNP selection procedure. The 49 new SNPs explain approximately 1.3% of variance, nearly doubling the heritability explained at the 36 loci. We did not find any locus showing multiple associated SNPs for BMI. The method we present is computationally fast and is also applicable to case-control data, which we demonstrate in an example from meta-analysis of type 2 diabetes by the DIAGRAM Consortium. 相似文献
147.
Extremely low-coverage sequencing and imputation increases power for genome-wide association studies 总被引:1,自引:0,他引:1
Pasaniuc B Rohland N McLaren PJ Garimella K Zaitlen N Li H Gupta N Neale BM Daly MJ Sklar P Sullivan PF Bergen S Moran JL Hultman CM Lichtenstein P Magnusson P Purcell SM Haas DW Liang L Sunyaev S Patterson N de Bakker PI Reich D Price AL 《Nature genetics》2012,44(6):631-635
Genome-wide association studies (GWAS) have proven to be a powerful method to identify common genetic variants contributing to susceptibility to common diseases. Here, we show that extremely low-coverage sequencing (0.1-0.5×) captures almost as much of the common (>5%) and low-frequency (1-5%) variation across the genome as SNP arrays. As an empirical demonstration, we show that genome-wide SNP genotypes can be inferred at a mean r(2) of 0.71 using off-target data (0.24× average coverage) in a whole-exome study of 909 samples. Using both simulated and real exome-sequencing data sets, we show that association statistics obtained using extremely low-coverage sequencing data attain similar P values at known associated variants as data from genotyping arrays, without an excess of false positives. Within the context of reductions in sample preparation and sequencing costs, funds invested in extremely low-coverage sequencing can yield several times the effective sample size of GWAS based on SNP array data and a commensurate increase in statistical power. 相似文献
148.
S Peña-Llopis S Vega-Rubín-de-Celis A Liao N Leng A Pavía-Jiménez S Wang T Yamasaki L Zhrebker S Sivanand P Spence L Kinch T Hambuch S Jain Y Lotan V Margulis AI Sagalowsky PB Summerour W Kabbani SW Wong N Grishin M Laurent XJ Xie CD Haudenschild MT Ross DR Bentley P Kapur J Brugarolas 《Nature genetics》2012,44(9):1072
149.
RK Koenekoop H Wang J Majewski X Wang I Lopez H Ren Y Chen Y Li GA Fishman M Genead J Schwartzentruber N Solanki EI Traboulsi J Cheng CV Logan M McKibbin BE Hayward DA Parry CA Johnson M Nageeb;Finding of Rare Disease Genes 《Nature genetics》2012,44(9):1035-1039
Leber congenital amaurosis (LCA) is a blinding retinal disease that presents within the first year after birth. Using exome sequencing, we identified mutations in the nicotinamide adenine dinucleotide (NAD) synthase gene NMNAT1 encoding nicotinamide mononucleotide adenylyltransferase 1 in eight families with LCA, including the family in which LCA was originally linked to the LCA9 locus. Notably, all individuals with NMNAT1 mutations also have macular colobomas, which are severe degenerative entities of the central retina (fovea) devoid of tissue and photoreceptors. Functional assays of the proteins encoded by the mutant alleles identified in our study showed that the mutations reduce the enzymatic activity of NMNAT1 in NAD biosynthesis and affect protein folding. Of note, recent characterization of the slow Wallerian degeneration (Wld(s)) mouse model, in which prolonged axonal survival after injury is observed, identified NMNAT1 as a neuroprotective protein when ectopically expressed. Our findings identify a new disease mechanism underlying LCA and provide the first link between endogenous NMNAT1 dysfunction and a human nervous system disorder. 相似文献
150.