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1.
发酵水产食品风味形成机制复杂,制备和发酵过程中的原料、所用发酵剂以及设备和加工工艺中的多种微生物相互作用,导致形成的风味成分种类多样,从单一层面对不同发酵水产食品风味成分解析较为困难。近年来,通过利用对不同层面准确解析的组学技术,研究基因表达调控、蛋白质转录翻译及相互作用,并对代谢物进行定性及定量分析,可用于明确特征风味成分,揭示风味形成机制。因此,多组学技术可以用于动态检测发酵过程中水产品风味成分变化并解析风味形成机制、构建风味化合物代谢网络,探究风味相关微生物及酶作用关系。本文综述水产品发酵中风味形成的主要代谢途径、多组学技术应用于解析水产品发酵过程中风味形成的研究进展,以及多组学技术在发酵水产品风味研究中的重要作用。  相似文献   
2.
藻类具有复杂多样的进化历史和生物学特征,不仅在生态系统中扮演着重要角色,而且具有许多独特的基因和生物过程。随着后基因时代的到来,组学技术受到各界学者的高度重视,近年来在藻类研究中也得到了应用。高通量技术在藻类研究领域中的应用,也大大促进了藻类蛋白质组学的发展。本文综述了蛋白质组学技术在藻类品质差异鉴定、养殖胁迫作用、生理机制方面的研究进展,并对其发展方向和应用前景进行了展望,为从事藻类组学的研究者提供参考。  相似文献   
3.
With more than 25 million people affected, heart failure (HF) is a global threat. As energy production pathways are known to play a pivotal role in HF, we sought here to identify key metabolic changes in ischemic- and non-ischemic HF by using a multi-OMICS approach. Serum metabolites and mRNAseq and epigenetic DNA methylation profiles were analyzed from blood and left ventricular heart biopsy specimens of the same individuals. In total we collected serum from n = 82 patients with Dilated Cardiomyopathy (DCM) and n = 51 controls in the screening stage. We identified several metabolites involved in glycolysis and citric acid cycle to be elevated up to 5.7-fold in DCM (p = 1.7 × 10−6). Interestingly, cardiac mRNA and epigenetic changes of genes encoding rate-limiting enzymes of these pathways could also be found and validated in our second stage of metabolite assessment in n = 52 DCM, n = 39 ischemic HF and n = 57 controls. In conclusion, we identified a new set of metabolomic biomarkers for HF. We were able to identify underlying biological cascades that potentially represent suitable intervention targets.  相似文献   
4.
Systemic Acquired Resistance (SAR) improves immunity of plant systemic tissue after local exposure to a pathogen. Guard cells that form stomatal pores on leaf surfaces recognize bacterial pathogens via pattern recognition receptors, such as Flagellin Sensitive 2 (FLS2). However, how SAR affects stomatal immunity is not known. In this study, we aim to reveal molecular mechanisms underlying the guard cell response to SAR using multi-omics of proteins, metabolites and lipids. Arabidopsis plants previously exposed to pathogenic bacteria Pseudomonas syringae pv. tomato DC3000 (Pst) exhibit an altered stomatal response compared to control plants when they are later exposed to the bacteria. Reduced stomatal apertures of SAR primed plants lead to decreased number of bacteria in leaves. Multi-omics has revealed molecular components of SAR response specific to guard cells functions, including potential roles of reactive oxygen species (ROS) and fatty acid signaling. Our results show an increase in palmitic acid and its derivative in the primed guard cells. Palmitic acid may play a role as an activator of FLS2, which initiates stomatal immune response. Improved understanding of how SAR signals affect stomatal immunity can aid biotechnology and marker-based breeding of crops for enhanced disease resistance.  相似文献   
5.
随着组学新测序技术的不断涌现和推广,产生了大量的组学数据,这些数据对人们深入研究和揭示生命奥秘有着极重要的意义。利用多组学数据整合技术分析生命科学问题可获得更丰富更全面的生命系统相关信息,已成为研究者探索生命机制的新方向。介绍了多组学数据整合分析的研究背景和研究意义,综述了近年来多组学数据整合分析的方法和相关领域的应用研究,探讨了多组学数据整合分析方法当前所存在的问题以及未来展望。  相似文献   
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7.
Cancer biomarkers identification based on multi-omics data is of great significance for the study of molecular mechanisms of cancer, while most of the current work is based on protein-protein interaction data. Therefore, a new method based on the gene regulatory network and multi-omic data is proposed to analyze cancer molecular mechanisms and predict cancer biomarkers. Taking stomach adenocarcinoma (STAD) and esophageal carcinoma (ESCA) for example, first we integrate multi-omics data to construct cancer-specific networks for STAD and ESCA respectively. Then, analysis of weighted co-expression gene networks is carried out on the two networks, and hierarchical clustering modules are used to calculate the relationship between the first principal component of the module and all known cancer biomarkers. Furthermore, cancer-specific modules are screened out. Finally, disease-specific biological pathways are extracted, and potential cancer biomarkers are prioritized using similarity assessment methods. Experimental results show that the specific module predicted has functional characteristics, and that the Pearson correlation coefficient method is more accurate.  相似文献   
8.
A systematic method was proposed to infer differential gene regulatory networks (GRNs) among lung adenocarcinoma (LUAD) samples at different stages by integrating multi-omics data to uncover significant network features and to identify tumor progression (TP) biomarker genes. The mRNA expressions, copy number variations, and DNA methylations of two independent LUAD cohorts (TCGA and SPORE) at stages I, II, and III were used, respectively. As results, the transition from normal to early onset was showed to be critical to reveal the pathogenesis of LUAD; 61 genes were identified as TP-related biomarkers, including two types of microRNAs of ABLIM2 and ZFAS1. These identified biomarkers may set light on the underlying mechanism of LUAD TP and may serve as potential drug targets for new treatments. Moreover, our study provides a general framework for TP biomarker identification for other types of cancer, which may improve the mechanism research for cancer development.  相似文献   
9.
转基因组学分析技术研究进展   总被引:1,自引:0,他引:1  
王晨光  许文涛  朱鹏宇  付伟 《食品科学》2015,36(17):288-295
转基因技术备受世人关注,且转基因作物关乎人体健康和生态环境,因此对转基因作物的安全评价地位极其重要,各种评价方法也在不断前进与发展。组学分析技术成为安全评价工作的新思路。本文主要论述了转基因组学分析技术的必要性,组学分析技术的发展,世界主要转基因作物组学评价发展情况及未来转基因组学分析技术的发展趋势,以期对转基因安全评价工作提供新的思路和方向。  相似文献   
10.
在癌症研究中,随着高通量测序技术发展已经产生了海量的复杂数据。尽管有了一些利用深度学习和统计学方法进行多组学数据整合的研究,但目前仍缺乏较为有效率的整合方法。因此提出一种基于深度自编码器的多组学数据整合方法(deep autoencoder for multi-omics integration,DAEMI)。它利用自编码器中的瓶颈层,学习多组学数据的特征表示。与先前利用深度学习整合的研究相比,DAEMI可以发现明显生存差异的癌症亚型。同时因为不需要生存数据来选择特征,DAEMI可以使用更多特征进行[K]均值聚类,进而完成癌症分型任务。将DAEMI应用于模拟数据集与四个癌症数据集实验,通过与高阶路径相似度网络的融合模型(HOPES)、相似性网络融合(SNF)、iClusterPlus和moCluster进行比较,结合模拟数据集测试结果与真实癌症数据集测试结果来看,DAEMI要优于其他方法。相应的生物功能分析揭示,神经退行性疾病与线粒体功能障碍可能与癌症共享某些生物学通路。  相似文献   
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