首页 | 本学科首页   官方微博 | 高级检索  
文章检索
  按 检索   检索词:      
出版年份:   被引次数:   他引次数: 提示:输入*表示无穷大
  收费全文   15431篇
  免费   1452篇
  国内免费   2302篇
  19185篇
  2024年   64篇
  2023年   274篇
  2022年   674篇
  2021年   989篇
  2020年   756篇
  2019年   886篇
  2018年   767篇
  2017年   589篇
  2016年   761篇
  2015年   1106篇
  2014年   1357篇
  2013年   1352篇
  2012年   1636篇
  2011年   1579篇
  2010年   955篇
  2009年   827篇
  2008年   898篇
  2007年   744篇
  2006年   626篇
  2005年   476篇
  2004年   346篇
  2003年   319篇
  2002年   242篇
  2001年   119篇
  2000年   121篇
  1999年   129篇
  1998年   88篇
  1997年   68篇
  1996年   59篇
  1995年   52篇
  1994年   43篇
  1993年   33篇
  1992年   42篇
  1991年   39篇
  1990年   28篇
  1989年   23篇
  1988年   16篇
  1987年   14篇
  1986年   11篇
  1985年   26篇
  1984年   7篇
  1983年   5篇
  1982年   4篇
  1981年   4篇
  1978年   3篇
  1977年   3篇
  1975年   5篇
  1973年   4篇
  1969年   2篇
  1964年   2篇
排序方式: 共有10000条查询结果,搜索用时 15 毫秒
1.
Plant Molecular Biology -  相似文献   
2.
3.
Using cytochemical method,microspectrophotometry and image analysis,effects of va-soactive intestinal peptide(VIP)on activities of succinic dehydrogenase(SDH)and alkalinephosphatase(ALP)in rat hepatoma cells were studied in vitro.The results showed that thehepatoma cell expressed potent positive reactions of SDH and ALP,the positive positionswere located at the cell membranes and/or cytoplasm.Having been treated with VIP,ALPdecreased obviously in activity(P<0. 01,compared with hepatoma cells untreated by VIP).The sites of ALP activty were chiefly located at the cell membranes,particularly at the cell-cell contacts.Cultured rat hepatoma cells had intensive SDH activity in their cytoplasm.Compared with untreated eclls,there was no marked difference in the intensity of SDH activ-ity in VIP-treated hepatoma cells(P>0.05).  相似文献   
4.
5.
用基因定点诱变技术,删除了pO_1α ANF表达质粒中的33对碱基,使人α型心钠素结构基因直接与大肠杆菌分泌型表达质粒pIN-Ⅲ-OmPA中的信号肽酶切位点编码区相连,构成天然人α型心钠素的表达质粒pANF,在IPTG诱导下表达28肽的天然人α型心钠素。纯化后的表达产物具有天然心钠素的放免活性和很强的舒张血管的生物活性。  相似文献   
6.
7.
Sophora japonica is a medium-size deciduous tree belonging to Leguminosae family and famous for its high ecological, economic and medicinal value. Here, we reveal a draft genome of S. japonica, which was ∼511.49 Mb long (contig N50 size of 17.34 Mb) based on Illumina, Nanopore and Hi-C data. We reliably assembled 110 contigs into 14 chromosomes, representing 91.62% of the total genome, with an improved N50 size of 31.32 Mb based on Hi-C data. Further investigation identified 271.76 Mb (53.13%) of repetitive sequences and 31,000 protein-coding genes, of which 30,721 (99.1%) were functionally annotated. Phylogenetic analysis indicates that S. japonica separated from Arabidopsis thaliana and Glycine max ∼107.53 and 61.24 million years ago, respectively. We detected evidence of species-specific and common-legume whole-genome duplication events in S. japonica. We further found that multiple TF families (e.g. BBX and PAL) have expanded in S. japonica, which might have led to its enhanced tolerance to abiotic stress. In addition, S. japonica harbours more genes involved in the lignin and cellulose biosynthesis pathways than the other two species. Finally, population genomic analyses revealed no obvious differentiation among geographical groups and the effective population size continuously declined since 2 Ma. Our genomic data provide a powerful comparative framework to study the adaptation, evolution and active ingredients biosynthesis in S. japonica. More importantly, our high-quality S. japonica genome is important for elucidating the biosynthesis of its main bioactive components, and improving its production and/or processing.  相似文献   
8.
Drug-target interactions provide insight into the drug-side effects and drug repositioning. However, wet-lab biochemical experiments are time-consuming and labor-intensive, and are insufficient to meet the pressing demand for drug research and development. With the rapid advancement of deep learning, computational methods are increasingly applied to screen drug-target interactions. Many methods consider this problem as a binary classification task (binding or not), but ignore the quantitative binding affinity. In this paper, we propose a new end-to-end deep learning method called DeepMHADTA, which uses the multi-head self-attention mechanism in a deep residual network to predict drug-target binding affinity. On two benchmark datasets, our method outperformed several current state-of-the-art methods in terms of multiple performance measures, including mean square error (MSE), consistency index (CI), rm2, and PR curve area (AUPR). The results demonstrated that our method achieved better performance in predicting the drug–target binding affinity.  相似文献   
9.
Nitric oxide (NO) is a key player in numerous physiological processes. Excessive NO induces DNA damage, but how plants respond to this damage remains unclear. We screened and identified an Arabidopsis NO hypersensitive mutant and found it to be allelic to TEBICHI/POLQ, encoding DNA polymerase θ. The teb mutant plants were preferentially sensitive to NO- and its derivative peroxynitrite-induced DNA damage and subsequent double-strand breaks (DSBs). Inactivation of TEB caused the accumulation of spontaneous DSBs largely attributed to endogenous NO and was synergistic to DSB repair pathway mutations with respect to growth. These effects were manifested in the presence of NO-inducing agents and relieved by NO scavengers. NO induced G2/M cell cycle arrest in the teb mutant, indicative of stalled replication forks. Genetic analyses indicate that Polθ is required for translesion DNA synthesis across NO-induced lesions, but not oxidation-induced lesions. Whole-genome sequencing revealed that Polθ bypasses NO-induced base adducts in an error-free manner and generates mutations characteristic of Polθ-mediated end joining. Our experimental data collectively suggests that Polθ plays dual roles in protecting plants from NO-induced DNA damage. Since Polθ is conserved in higher eukaryotes, mammalian Polθ may also be required for balancing NO physiological signaling and genotoxicity.  相似文献   
10.
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号