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| 1 | 肿瘤异质性:精准医学需破解的难题显示文摘肿瘤异质性是恶性肿瘤的重要特征,表现为同一种恶性肿瘤不同患者个体之间或者同一患者体内不同部位肿瘤细胞间从基因型到表型上存在的差异.这种差异可表现为不同的遗传背景、不同的病理类型、不同的分化状态、不同的基因突变谱和转录组、蛋白质组表达谱等,体现了恶性肿瘤在演进过程中的高度复杂性和多样性.肿瘤异质性给肿瘤的治疗带来极大的困难,一直是肿瘤发生发展机制研究领域重要的科学问题.本文综述了肿瘤异质性的生物学特征及其可能的形成机制,并对'精准医学'时代如何针对肿瘤异质性设计更为有效的个性化治疗方案进行了思考. | 涂超峰 綦鹏 李夏雨 莫勇真 李小玲 熊炜 曾朝阳 李桂源 | 2015 | 生物化学与生物物理进展2015，42，10： | 15 |
| 2 | Sequencing XMET genes to promote genotype-guided risk assessment and precision medicine显示文摘High-throughput next generation sequencing (NGS) is a shotgun approach applied in a parallel fashion by which the genome is fragmented and sequenced through small pieces and then analyzed either by aligning to a known reference genome or by de novo assembly without reference genome.This technology has led researchers to conduct an explosion of sequencing related projects in multidisciplinary fields of science.However,due to the limitations of sequencing-based chemistry,length of sequencing reads and the complexity of genes,it is difficult to determine the sequences of some portions of the human genome,leaving gaps in genomic data that frustrate further analysis.Particularly,some complex genes are difficult to be accurately sequenced or mapped because they contain high GC-content and/or low complexity regions,and complicated pseudogenes,such as the genes encoding xenobiotic metabolizing enzymes and transporters (XMETs).The genetic variants in XMET genes are critical to predicate interindividual variability in drug efficacy,drug safety and susceptibility to environmental toxicity.We summarized and discussed challenges,wet-lab methods,and bioinformatics algorithms in sequencing 'complex' XMET genes,which may provide insightful information in the application of NGS technology for implementation in toxicogenomics and pharmacogenomics. | Yaqiong Jin Geng Chen Wenming Xiao Huixiao Hong Joshua Xu Yongli Guo Wenzhong Xiao Tieliu Shi Leming Shi Weida Tong Baitang Ning | 2019 | Science China(Life Sciences)2019，62，7： | 1 |
| 3 | 下一代测序在孟德尔型运动障碍中的应用(英文)显示文摘在过去10年中,下一代测序技术(next generation sequencing,NGS)得到了十分迅速的发展。与传统测序相比,NGS具有高通量和高灵敏性等优点。孟德尔型运动障碍是一类常见的神经疾病。由于样本较少等原因,通过连锁分析等传统方法寻找新的孟德尔型运动障碍尤其是罕见疾病的致病基因已经变得越来越困难,而NGS则可作为发现新的致病基因的理想手段。目前NGS已被应用于多种孟德尔型运动障碍的研究。本文将从基因组和转录组的角度对NGS在孟德尔型运动障碍中的最新应用进行综述,并展望NGS在罕见孟德尔型疾病中的应用。 | 王裕民 潘序雅 薛丹 李雨薇 张雪莹 邝彪 郑嘉博 邓昊 李小玲 熊炜 曾朝阳 李桂源 | 2016 | 中南大学学报(医学版)2016，41，2： | 0 |
| 4 | Opportunities for Computational Techniques for Multi-Omics Integrated Personalized Medicine显示文摘Personalized medicine is defined as 'a model of healthcare that is predictive, personalized, preventive,and participator' and has very broad content. With the rapid development of high-throughput technologies, an explosive accumulation of biological information is collected from multiple layers of biological processes, including genomics, transcriptomics, proteomics, metabonomics, and interactomics(omics). Implementing integrative analysis of these multiple omics data is the best way of deriving systematical and comprehensive views of living organisms, achieving better understanding of disease mechanisms, and finding operable personalized health treatments. With the help of computational methods, research in the field of biology and biomedicine has gained tremendous benefits over the past few decades. In the new era of personalized medicine, we will rely more on the assistance of computational analysis. In this paper, we briefly review the generation of multiple omics and their basic characteristics. And then the challenges and opportunities for computational analysis are discussed and some state-of-art analysis methods that were recently proposed by peers for integrative analysis of multiple omics data are reviewed. We foresee that further integrated omics data platform and computational tools would help to translate the biological knowledge to clinical usage and accelerate development of personalized medicine. | Yuan Zhang Yue Cheng Kebin Jia Aidong Zhang | 2014 | Tsinghua Science and Technology2014，19，6： | 0 |
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