Large-scale profiling of microRNAs for The Cancer Genome Atlas

The comprehensive multiplatform genomics data generated by The Cancer Genome Atlas (TCGA) Research Network is an enabling resource for cancer research. It includes an unprecedented amount of microRNA sequence data: ∼11 000 libraries across 33 cancer types. Combined with initiatives like the National Cancer Institute Genomics Cloud Pilots, such data resources will make intensive analysis of large-scale cancer genomics data widely accessible. To support such initiatives, and to enable comparison of TCGA microRNA data to data from other projects, we describe the process that we developed and used to generate the microRNA sequence data, from library construction through to submission of data to repositories. In the context of this process, we describe the computational pipeline that we used to characterize microRNA expression across large patient cohorts.     

NCI Workshop Report: Clinical and Computational Requirements for Correlating Imaging Phenotypes with Genomics Signatures

The National Cancer Institute (NCI) Cancer Imaging Program organized two related workshops on June 26–27, 2013, entitled “Correlating Imaging Phenotypes with Genomics Signatures Research” and “Scalable Computational Resources as Required for Imaging-Genomics Decision Support Systems.” The first workshop focused on clinical and scientific requirements, exploring our knowledge of phenotypic characteristics of cancer biological properties to determine whether the field is sufficiently advanced to correlate with imaging phenotypes that underpin genomics and clinical outcomes, and exploring new scientific methods to extract phenotypic features from medical images and relate them to genomics analyses. The second workshop focused on computational methods that explore informatics and computational requirements to extract phenotypic features from medical images and relate them to genomics analyses and improve the accessibility and speed of dissemination of existing NIH resources. These workshops linked clinical and scientific requirements of currently known phenotypic and genotypic cancer biology characteristics with imaging phenotypes that underpin genomics and clinical outcomes. The group generated a set of recommendations to NCI leadership and the research community that encourage and support development of the emerging radiogenomics research field to address short-and longer-term goals in cancer research.     

Towards discovery-driven translational research in breast cancer

Discovery-driven translational research in breast cancer is moving steadily from the study of cell lines to the analysis of clinically relevant samples that, together with the ever increasing number of novel and powerful technologies available within genomics, proteomics and functional genomics, promise to have a major impact on the way breast cancer will be diagnosed, treated and monitored in the future. Here we present a brief report on long-term ongoing strategies at the Danish Centre for Translational Breast Cancer Research to search for markers for early detection and targets for therapeutic intervention, to identify signalling pathways affected in individual tumours, as well as to integrate multiplatform 'omic' data sets collected from tissue samples obtained from individual patients. The ultimate goal of this initiative is to coalesce knowledge-based complementary procedures into a systems biology approach to fight breast cancer.     

The mouse as a model for human biology: a resource guide for complex trait analysis

The mouse has been a powerful force in elucidating the genetic basis of human physiology and pathophysiology. From its beginnings as the model organism for cancer research and transplantation biology to the present, when dissection of the genetic basis of complex disease is at the forefront of genomics research, an enormous and remarkable mouse resource infrastructure has accumulated. This review summarizes those resources and provides practical guidelines for their use, particularly in the analysis of quantitative traits.     

中华民族永生细胞库在生命科学研究中的支撑作用

人类样品是生物医学研究必需的物质基础。B淋巴母细胞系(LCL)是利用Epstein-Barr(EB)病毒转化人的B细胞获得,制备简便,可以无限繁殖,是非常便捷的保存人类样品的形式。中华民族永生细胞库保藏有中国各个民族群体的LCL。目前,已经有详实的LCL的性质研究以及关于LCL的全基因组数据,因而, LCL已经广泛应用于遗传学、免疫学、药学基因组学、再生医学、癌症发生与免疫治疗、筛选制备全人单克隆中和抗体及EB病毒致病机理等研究领域。本文对LCL的特性以及LCL在上述研究领域中的应用进行了综述,最后对中华民族永生细胞库的保藏内容做了简单介绍,以促进广大科研人员进一步了解该细胞库的科研价值,充分发挥该库保藏资源在基础科学、生物医学研究中的科技支撑作用。     

Cancer and the web

The applications of functional genomics, proteomics and informatics to cancer research have yielded a tremendous amount of information, which is growing all the time. Much of this information is available publicly on the Internet and ranges from general information about different cancers from a patient or clinical viewpoint, through to databases suitable for cancer researchers of all backgrounds, to very specific sites dedicated to individual genes or molecules. A simple search for 'cancer' from a typical Web browser search engine yields more than half a million hits; an even more specific search for 'leukaemia' (>40 000 hits) or 'p53' (>5700 hits) yields far too many hits to allow one to identify particular sites of interest. This review aims to provide a brief guide to some of the resources and databases that can be used as springboards to home in rapidly on information relevant to many fields of cancer research. As such, this article will not focus on a single website but hopes to illustrate some of the ways that postgenomic biology is revolutionizing cancer research. It will cover genomics and proteomics approaches that have been applied to studying global expression patterns in cancers, in addition to providing links ranging from general information about cancer to specific cancer gene mutation databases.     

How science will help us move forward in 2021

In 2021, the genetics and genomics community needs to communicate to policymakers how the field of human genetics and genomics is transforming biomedical research and medicine, including its essential role in combatting COVID-19. This is important for ensuring that policies enable a thriving scientific enterprise and provide resources for research advances.

In 2021, the genetics and genomics community needs to communicate to policymakers how the field of human genetics and genomics is transforming biomedical research and medicine, including its essential role in combatting COVID-19. This is important for ensuring that policies enable a thriving scientific enterprise and provide resources for research advances.     

Generation Challenge Programme (GCP): standards for crop data

The Generation Challenge Programme (GCP) is an international research consortium striving to apply molecular biological advances to crop improvement for developing countries. Central to its activities is the creation of a next generation global crop information platform and network to share genetic resources, genomics, and crop improvement information. This system is being designed based on a comprehensive scientific domain object model and associated shared ontology. This model covers germplasm, genotype, phenotype, functional genomics, and geographical information data types needed in GCP research. This paper provides an overview of this modeling effort.     

基于CART算法的肺癌微阵列数据的分类

基因芯片技术是基因组学中的重要研究工具。而基因芯片数据( 微阵列数据) 往往是高维的,使得降维成为微阵列数据分析中的一个必要步骤。本文对美国哈佛医学院 G. J. Gordon 等人提供的肺癌微阵列数据进行分析。通过 t- test,Wilcoxon 秩和检测分别提取微阵列数据特征属性,后根据 CART( Classification and Regression Tree) 算法,以 Gini 差异性指标作为误差函数,用提取的特征属性广延的构造分类树; 再进行剪枝找到最优规模的树,目的是提高树的泛化性能使得能很好适应新的预测数据。实验证明: 该方法对肺癌微阵列数据分类识别率达到 96% 以上,且很稳定; 并可以得到人们容易理解的分类规则和分类关键基因。     

Web Resources for Pharmacogenomics

Pharmacogenomics is the study of the impact of genetic variations or genotypes of individuals on their drug response or drug metabolism. Compared to traditional genomics research,pharmacogenomic research is more closely related to clinical practice. Pharmacogenomic discoveries may effectively assist clinicians and healthcare providers in determining the right drugs and proper dose for each patient, which can help avoid side effects or adverse reactions, and improve the drug therapy. Currently, pharmacogenomic approaches have proven their utility when it comes to the use of cardiovascular drugs, antineoplastic drugs, aromatase inhibitors, and agents used for infectious diseases. The rapid innovation in sequencing technology and genome-wide association studies has led to the development of numerous data resources and dramatically changed the landscape of pharmacogenomic research. Here we describe some of these web resources along with their names, web links, main contents, and our ratings.     

From cancer big data to treatment: Artificial intelligence in cancer research

In recent years, developing the idea of “cancer big data” has emerged as a result of the significant expansion of various fields such as clinical research, genomics, proteomics and public health records. Advances in omics technologies are making a significant contribution to cancer big data in biomedicine and disease diagnosis. The increasingly availability of extensive cancer big data has set the stage for the development of multimodal artificial intelligence (AI) frameworks. These frameworks aim to analyze high-dimensional multi-omics data, extracting meaningful information that is challenging to obtain manually. Although interpretability and data quality remain critical challenges, these methods hold great promise for advancing our understanding of cancer biology and improving patient care and clinical outcomes. Here, we provide an overview of cancer big data and explore the applications of both traditional machine learning and deep learning approaches in cancer genomic and proteomic studies. We briefly discuss the challenges and potential of AI techniques in the integrated analysis of omics data, as well as the future direction of personalized treatment options in cancer.     

Uniform standards for genome databases in forest and fruit trees

TreeGenes and tree fruit Genome Database Resources serve the international forestry and fruit tree genomics research communities, respectively. These databases hold similar sequence data and provide resources for the submission and recovery of this information in order to enable comparative genomics research. Large-scale genotype and phenotype projects have recently spawned the development of independent tools and interfaces within these repositories to deliver information to both geneticists and breeders. The increase in next generation sequencing projects has increased the amount of data as well as the scale of analysis that can be performed. These two repositories are now working towards a similar goal of archiving the diverse, independent data sets generated from genotype/phenotype experiments. This is achieved through focused development on data input standards (templates), pipelines for the storage and automated curation, and consistent annotation efforts through the application of widely accepted ontologies to improve the extraction and exchange of the data for comparative analysis. Efforts towards standardization are not limited to genotype/phenotype experiments but are also being applied to other data types to improve gene prediction and annotation for de novo sequencing projects. The resources developed towards these goals represent the first large-scale coordinated effort in plant databases to add informatics value to diverse genotype/phenotype experiments.     

Rice functional genomics research in China

Rice functional genomics is a scientific approach that seeks to identify and define the function of rice genes, and uncover when and how genes work together to produce phenotypic traits. Rapid progress in rice genome sequencing has facilitated research in rice functional genomics in China. The Ministry of Science and Technology of China has funded two major rice functional genomics research programmes for building up the infrastructures of the functional genomics study such as developing rice functional genomics tools and resources. The programmes were also aimed at cloning and functional analyses of a number of genes controlling important agronomic traits from rice. National and international collaborations on rice functional genomics study are accelerating rice gene discovery and application.     

How genomics can help biodiversity conservation

The availability of public genomic resources can greatly assist biodiversity assessment, conservation, and restoration efforts by providing evidence for scientifically informed management decisions. Here we survey the main approaches and applications in biodiversity and conservation genomics, considering practical factors, such as cost, time, prerequisite skills, and current shortcomings of applications. Most approaches perform best in combination with reference genomes from the target species or closely related species. We review case studies to illustrate how reference genomes can facilitate biodiversity research and conservation across the tree of life. We conclude that the time is ripe to view reference genomes as fundamental resources and to integrate their use as a best practice in conservation genomics.     

高通量测序技术在动植物研究领域中的应用

高通量测序是核酸测序研究的一次革命性技术创新, 该技术以极低的单碱基测序成本和超高的数据产出量为特征, 为基因组学和后基因组学研究带来了新的科研方法和解决方案. 在动植物研究领域, 高通量测序引领了一次具有里程碑意义的科学研究模式革新, 科研人员可利用该技术在基因组、转录组和表观基因组等领域展开多层次多方面多水平研究. 本文就高通量测序技术应用于动植物基因组学和功能基因组学研究进展进行了系统阐述, 并对当前高通量测序技术的现状和热点及未来的发展趋势作了深入剖析和讨论.     

From genomics to post-genomics in Aspergillus

Genome sequence data has recently become available for certain Aspergillus species. We consider the transition from genomics to a post-genomic era in Aspergillus, describing resources and methodologies available to underpin research efforts. Advances in our understanding of the fundamental biology of the Aspergilli, together with applications within the biotechnology and medical fields, are anticipated.     

Approaches to lipid metabolism gene identification and characterization in the postgenomic era

The availability of genomic resources has already had a tremendous impact on biomedical research. In this review, we describe how whole genome sequence and high-throughput functional genomics projects have facilitated the identification and characterization of important genes in lipid metabolism and disease. We review key approaches and lipid genes identified in the first years of this century and discuss how genomic resources are likely to streamline gene identification and functional characterization in the future.     

INFRAFRONTIER: a European resource for studying the functional basis of human disease

Ageing research and more generally the study of the functional basis of human diseases profit enormously from the large-scale approaches and resources in mouse functional genomics: systematic targeted mutation of the mouse genome, systemic phenotyping in mouse clinics, and the archiving and distribution of the mouse resources in public repositories. INFRAFRONTIER, the European research infrastructure for the development, systemic phenotyping, archiving and distribution of mammalian models, offers access to sustainable mouse resources for biomedical research. INFRAFRONTIER promotes the global sharing of high-quality resources and data and thus contributes to data reproducibility and animal welfare. INFRAFRONTIER puts great effort into international standardisation and quality control and into technology development to improve and expand experimental protocols, reduce the use of animals in research and increase the reproducibility of results. In concert with the research community and the International Mouse Phenotyping Consortium (IMPC), INFRAFRONTIER is currently developing new pilot platforms and services for the research on ageing and age-related diseases.     

Farm animal genomics and informatics: an update

Farm animal genomics is of interest to a wide audience of researchers because of the utility derived from understanding how genomics and proteomics function in various organisms. Applications such as xenotransplantation, increased livestock productivity, bioengineering new materials, products and even fabrics are several reasons for thriving farm animal genome activity. Currently mined in rapidly growing data warehouses, completed genomes of chicken, fish and cows are available but are largely stored in decentralized data repositories. In this paper, we provide an informatics primer on farm animal bioinformatics and genome project resources which drive attention to the most recent advances in the field. We hope to provide individuals in biotechnology and in the farming industry with information on resources and updates concerning farm animal genome projects.