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991.
Background
Longitudinal phenotypic data provides a rich potential resource for genetic studies which may allow for greater understanding of variants and their covariates over time. Herein, we review 3 longitudinal analytical approaches from the Genetic Analysis Workshop 19 (GAW19). These contributions investigated both genome-wide association (GWA) and whole genome sequence (WGS) data from odd numbered chromosomes on up to 4 time points for blood pressure–related phenotypes. The statistical models used included generalized estimating equations (GEEs), latent class growth modeling (LCGM), linear mixed-effect (LME), and variance components (VC). The goal of these analyses was to test statistical approaches that use repeat measurements to increase genetic signal for variant identification.Results
Two analytical methods were applied to the GAW19: GWA using real phenotypic data, and one approach to WGS using 200 simulated replicates. The first GWA approach applied a GEE-based model to identify gene-based associations with 4 derived hypertension phenotypes. This GEE model identified 1 significant locus, GRM7, which passed multiple test corrections for 2 hypertension-derived traits. The second GWA approach employed the LME to estimate genetic associations with systolic blood pressure (SBP) change trajectories identified using LCGM. This LCGM method identified 5 SBP trajectories and association analyses identified a genome-wide significant locus, near ATOX1 (p?=?1.0E?8). Finally, a third VC-based model using WGS and simulated SBP phenotypes that constrained the β coefficient for a genetic variant across each time point was calculated and compared to an unconstrained approach. This constrained VC approach demonstrated increased power for WGS variants of moderate effect, but when larger genetic effects were present, averaging across time points was as effective.Conclusion
In this paper, we summarize 3 GAW19 contributions applying novel statistical methods and testing previously proposed techniques under alternative conditions for longitudinal genetic association. We conclude that these approaches when appropriately applied have the potential to: (a) increase statistical power; (b) decrease trait heterogeneity and standard error; (c) decrease computational burden in WGS; and (d) have the potential to identify genetic variants influencing subphenotypes important for understanding disease progression.992.
Background
There has been paid more and more attention to supervised classification models in the area of predicting drug-target interactions (DTIs). However, in terms of classification, unavoidable missing DTIs in data would cause three issues which have not yet been addressed appropriately by former approaches. Directly labeled as negatives (non-DTIs), missing DTIs increase the confusion of positives (DTIs) and negatives, aggravate the imbalance between few positives and many negatives, and are usually discriminated as highly-scored false positives, which influence the existing measures sharply.Results
Under the framework of local classification model (LCM), this work focuses on the scenario of predicting how possibly a new drug interacts with known targets. To address the first two issues, two strategies, Spy and Super-target, are introduced accordingly and further integrated to form a two-layer LCM. In the bottom layer, Spy-based local classifiers for protein targets are built by positives, as well as reliable negatives identified among unlabeled drug-target pairs. In the top layer, regular local classifiers specific to super-targets are built with more positives generated by grouping similar targets and their interactions. Furthermore, to handle the third issue, an additional performance measure, Coverage, is presented for assessing DTI prediction. The experiments based on benchmark datasets are finally performed under five-fold cross validation of drugs to evaluate this approach. The main findings are concluded as follows. (1) Both two individual strategies and their combination are effective to missing DTIs, and the combination wins the best. (2) Having the advantages of less confusing decision boundary at the bottom layer and less biased decision boundary at the top layer, our two-layer LCM outperforms two former approaches. (3) Coverage is more robust to missing interactions than other measures and is able to evaluate how far one needs to go down the list of targets to cover all the proper targets of a drug.Conclusions
Proposing two strategies and one performance measure, this work has addressed the issues derived from missing interactions, which cause confusing and biased decision boundaries in classifiers, as well as the inappropriate measure of predicting performance, in the scenario of predicting interactions between new drugs and known targets.993.
Alexey A. Dmitriev Anna V. Kudryavtseva George S. Krasnov Nadezhda V. Koroban Anna S. Speranskaya Anastasia A. Krinitsina Maxim S. Belenikin Anastasiya V. Snezhkina Asiya F. Sadritdinova Natalya V. Kishlyan Tatiana A. Rozhmina Olga Yu. Yurkevich Olga V. Muravenko Nadezhda L. Bolsheva Nataliya V. Melnikova 《BMC plant biology》2016,16(3):237
994.
Background
During inflammation, leukocytes are captured by the selectin family of adhesion receptors lining blood vessels to facilitate exit from the bloodstream. E-selectin is upregulated on stimulated endothelial cells and binds to several ligands on the surface of leukocytes. Selectin:ligand interactions are mediated in part by the interaction between the lectin domain and Sialyl-Lewis x (sLex), a tetrasaccharide common to selectin ligands. There is a high degree of homology between selectins of various species: about 72 and 60 % in the lectin and EGF domains, respectively. In this study, molecular dynamics, docking, and steered molecular dynamics simulations were used to compare the binding and dissociation mechanisms of sLex with mouse and human E-selectin. First, a mouse E-selectin homology model was generated using the human E-selectin crystal structure as a template.Results
Mouse E-selectin was found to have a greater interdomain angle, which has been previously shown to correlate with stronger binding among selectins. sLex was docked onto human and mouse E-selectin, and the mouse complex was found to have a higher free energy of binding and a lower dissociation constant, suggesting stronger binding. The mouse complex had higher flexibility in a few key residues. Finally, steered molecular dynamics was used to dissociate the complexes at force loading rates of 2000–5000 pm/ps2. The mouse complex took longer to dissociate at every force loading rate and the difference was statistically significant at 3000 pm/ps2. When sLex-coated microspheres were perfused through microtubes coated with human or mouse E-selectin, the particles rolled more slowly on mouse E-selectin.Conclusions
Both molecular dynamics simulations and microsphere adhesion experiments show that mouse E-selectin protein binds more strongly to sialyl Lewis x ligand than human E-selectin. This difference was explained by a greater interdomain angle for mouse E-selectin, and greater flexibility in key residues. Future work could introduce similar amino acid substitutions into the human E-selectin sequence to further modulate adhesion behavior.995.
Sunita M. C. De Sousa Liam C. McIntyre Chan-Eng Chong Hamish S. Scott 《BMC endocrine disorders》2016,16(1):58
Background
The 46,XY female is characterised by a male karyotype and female phenotype arising due to any interruption in the sexual development pathways in utero. The cause is usually genetic and various genes are implicated.Case presentation
Herein we describe a 46,XY woman who was first diagnosed with androgen insensitivity syndrome (testicular feminisation) at 18 years; however, this was later questioned due to the presence of intact Müllerian structures. The clinical phenotype suggested several susceptibility genes including SRY, DHH, NR5A1, NR0B1, AR, AMH, and AMHR2. To study candidate genes simultaneously, we performed whole genome sequencing. This revealed a novel and likely pathogenic missense variant (p.Arg130Pro, c.389G>C) in SRY, one of the major genes implicated in complete gonadal dysgenesis, hence securing this condition over androgen insensitivity syndrome as the cause of the patient’s disorder of sexual development.Conclusion
This case highlights the emerging clinical utility of whole genome sequencing as a tool in differentiating disorders of sexual development.996.
M. A. Bottelier A. Schrantee G. van Wingen H. G. Ruhé M. B. de Ruiter L. Reneman 《生物学前沿》2016,11(3):256-259
Treatment of adolescents with antidepressants may induce an increased risk for suicidality in this population. The activity of the amygdala during processing of emotional faces with functional Magnetic Resonance Imaging (fMRI) is a well-known measure of emotional dysregulation. Based upon data of our prematurely ended randomized clinical trial with fluoxetine (NTR3103) in anxious and or depressed girls (12–14 years of age) we calculated that with the found effect size of r = 0.66, compared to placebo, only 8 subjects are needed to demonstrate increased amygdala activity following 16 weeks of treatment with fluoxetine. 相似文献
997.
998.
Fatemeh Norozi Javad Mohammadi-asl Tina Vosoughi Mohammad Ali Jalali Far Amal Saki Malehi Najmaldin Saki 《生物学前沿》2016,11(5):404-411
Objectives
Targeted therapy of Philadelphia-positive ALL and CML patients using imatinib (IM) has caused significant changes in treatment course and has increased the survival of patients. A small group of patients show resistance to IM. Acquired mutations in tyrosine kinase domain of BCR-ABL protein are a mechanism for development of resistance. T315I is one of the most common acquired mutations in this domain, which occurs in ATP binding site and inhibits the formation of hydrogen bond with IM. The aim of this study was to evaluate the prevalence of this mutation in BCR/ABL-positive CML and ALL patients.Methods
To conduct this study, 60 BCR-ABL-positive patients (including 50 CML and 10 ALL patients) who were subject to treatment with IM were selected. After taking the samples, presence of T315I mutation was assessed using ARMS-PCR on cDNA and its polymorphism was evaluated by sequencing.Results
The results showed that among 60 patients, only three patients had T315I mutation, which was detected using ARMS technique. The three patients bearing mutation were afflicted with CML and no significant association was found between blood parameters with duration of treatment in presence of mutation.Conclusions
The mutation was found in three CML patients, which indicated lower likelihood and diagnostic value of this mutation in ALL patients. Given the negative direct sequencing results in T315I patients, it can be concluded that ARMS-PCR is a more sensitive technique when the number of cancer cells is low in patients during treatment.999.
1000.
Grace C. Lee Ronald G. Hall Natalie K. Boyd Steven D. Dallas Liem C. Du Lucina B. Treviño Sylvia B. Treviño Chad Retzloff Kenneth A. Lawson James Wilson Randall J. Olsen Yufeng Wang Christopher R. Frei 《Annals of clinical microbiology and antimicrobials》2016,15(1):58