Science.gov

Sample records for personal genomics bioinformatics

  1. Surveying Recent Themes in Translational Bioinformatics: Big Data in EHRs, Omics for Drugs, and Personal Genomics

    PubMed Central

    2014-01-01

    Summary Objective To provide a survey of recent progress in the use of large-scale biologic data to impact clinical care, and the impact the reuse of electronic health record data has made in genomic discovery. Method Survey of key themes in translational bioinformatics, primarily from 2012 and 2013. Result This survey focuses on four major themes: the growing use of Electronic Health Records (EHRs) as a source for genomic discovery, adoption of genomics and pharmacogenomics in clinical practice, the possible use of genomic technologies for drug repurposing, and the use of personal genomics to guide care. Conclusion Reuse of abundant clinical data for research is speeding discovery, and implementation of genomic data into clinical medicine is impacting care with new classes of data rarely used previously in medicine. PMID:25123743

  2. Bioinformatics Workflow for Clinical Whole Genome Sequencing at Partners HealthCare Personalized Medicine

    PubMed Central

    Tsai, Ellen A.; Shakbatyan, Rimma; Evans, Jason; Rossetti, Peter; Graham, Chet; Sharma, Himanshu; Lin, Chiao-Feng; Lebo, Matthew S.

    2016-01-01

    Effective implementation of precision medicine will be enhanced by a thorough understanding of each patient’s genetic composition to better treat his or her presenting symptoms or mitigate the onset of disease. This ideally includes the sequence information of a complete genome for each individual. At Partners HealthCare Personalized Medicine, we have developed a clinical process for whole genome sequencing (WGS) with application in both healthy individuals and those with disease. In this manuscript, we will describe our bioinformatics strategy to efficiently process and deliver genomic data to geneticists for clinical interpretation. We describe the handling of data from FASTQ to the final variant list for clinical review for the final report. We will also discuss our methodology for validating this workflow and the cost implications of running WGS. PMID:26927186

  3. Getting personalized cancer genome analysis into the clinic: the challenges in bioinformatics

    PubMed Central

    2012-01-01

    Progress in genomics has raised expectations in many fields, and particularly in personalized cancer research. The new technologies available make it possible to combine information about potential disease markers, altered function and accessible drug targets, which, coupled with pathological and medical information, will help produce more appropriate clinical decisions. The accessibility of such experimental techniques makes it all the more necessary to improve and adapt computational strategies to the new challenges. This review focuses on the critical issues associated with the standard pipeline, which includes: DNA sequencing analysis; analysis of mutations in coding regions; the study of genome rearrangements; extrapolating information on mutations to the functional and signaling level; and predicting the effects of therapies using mouse tumor models. We describe the possibilities, limitations and future challenges of current bioinformatics strategies for each of these issues. Furthermore, we emphasize the need for the collaboration between the bioinformaticians who implement the software and use the data resources, the computational biologists who develop the analytical methods, and the clinicians, the systems' end users and those ultimately responsible for taking medical decisions. Finally, the different steps in cancer genome analysis are illustrated through examples of applications in cancer genome analysis. PMID:22839973

  4. Bioinformatics and genomic medicine.

    PubMed

    Kim, Ju Han

    2002-01-01

    Bioinformatics is a rapidly emerging field of biomedical research. A flood of large-scale genomic and postgenomic data means that many of the challenges in biomedical research are now challenges in computational science. Clinical informatics has long developed methodologies to improve biomedical research and clinical care by integrating experimental and clinical information systems. The informatics revolution in both bioinformatics and clinical informatics will eventually change the current practice of medicine, including diagnostics, therapeutics, and prognostics. Postgenome informatics, powered by high-throughput technologies and genomic-scale databases, is likely to transform our biomedical understanding forever, in much the same way that biochemistry did a generation ago. This paper describes how these technologies will impact biomedical research and clinical care, emphasizing recent advances in biochip-based functional genomics and proteomics. Basic data preprocessing with normalization and filtering, primary pattern analysis, and machine-learning algorithms are discussed. Use of integrative biochip informatics technologies, including multivariate data projection, gene-metabolic pathway mapping, automated biomolecular annotation, text mining of factual and literature databases, and the integrated management of biomolecular databases, are also discussed. PMID:12544491

  5. Genomics, molecular imaging, bioinformatics, and bio-nano-info integration are synergistic components of translational medicine and personalized healthcare research

    PubMed Central

    2008-01-01

    Supported by National Science Foundation (NSF), International Society of Intelligent Biological Medicine (ISIBM), International Journal of Computational Biology and Drug Design and International Journal of Functional Informatics and Personalized Medicine, IEEE 7th Bioinformatics and Bioengineering attracted more than 600 papers and 500 researchers and medical doctors. It was the only synergistic inter/multidisciplinary IEEE conference with 24 Keynote Lectures, 7 Tutorials, 5 Cutting-Edge Research Workshops and 32 Scientific Sessions including 11 Special Research Interest Sessions that were designed dynamically at Harvard in response to the current research trends and advances. The committee was very grateful for the IEEE Plenary Keynote Lectures given by: Dr. A. Keith Dunker (Indiana), Dr. Jun Liu (Harvard), Dr. Brian Athey (Michigan), Dr. Mark Borodovsky (Georgia Tech and President of ISIBM), Dr. Hamid Arabnia (Georgia and Vice-President of ISIBM), Dr. Ruzena Bajcsy (Berkeley and Member of United States National Academy of Engineering and Member of United States Institute of Medicine of the National Academies), Dr. Mary Yang (United States National Institutes of Health and Oak Ridge, DOE), Dr. Chih-Ming Ho (UCLA and Member of United States National Academy of Engineering and Academician of Academia Sinica), Dr. Andy Baxevanis (United States National Institutes of Health), Dr. Arif Ghafoor (Purdue), Dr. John Quackenbush (Harvard), Dr. Eric Jakobsson (UIUC), Dr. Vladimir Uversky (Indiana), Dr. Laura Elnitski (United States National Institutes of Health) and other world-class scientific leaders. The Harvard meeting was a large academic event 100% full-sponsored by IEEE financially and academically. After a rigorous peer-review process, the committee selected 27 high-quality research papers from 600 submissions. The committee is grateful for contributions from keynote speakers Dr. Russ Altman (IEEE BIBM conference keynote lecturer on combining simulation and machine

  6. Bioinformatics Approach in Plant Genomic Research.

    PubMed

    Ong, Quang; Nguyen, Phuc; Thao, Nguyen Phuong; Le, Ly

    2016-08-01

    The advance in genomics technology leads to the dramatic change in plant biology research. Plant biologists now easily access to enormous genomic data to deeply study plant high-density genetic variation at molecular level. Therefore, fully understanding and well manipulating bioinformatics tools to manage and analyze these data are essential in current plant genome research. Many plant genome databases have been established and continued expanding recently. Meanwhile, analytical methods based on bioinformatics are also well developed in many aspects of plant genomic research including comparative genomic analysis, phylogenomics and evolutionary analysis, and genome-wide association study. However, constantly upgrading in computational infrastructures, such as high capacity data storage and high performing analysis software, is the real challenge for plant genome research. This review paper focuses on challenges and opportunities which knowledge and skills in bioinformatics can bring to plant scientists in present plant genomics era as well as future aspects in critical need for effective tools to facilitate the translation of knowledge from new sequencing data to enhancement of plant productivity. PMID:27499685

  7. Personalized medicine: challenges and opportunities for translational bioinformatics

    PubMed Central

    Overby, Casey Lynnette; Tarczy-Hornoch, Peter

    2013-01-01

    Personalized medicine can be defined broadly as a model of healthcare that is predictive, personalized, preventive and participatory. Two US President’s Council of Advisors on Science and Technology reports illustrate challenges in personalized medicine (in a 2008 report) and in use of health information technology (in a 2010 report). Translational bioinformatics is a field that can help address these challenges and is defined by the American Medical Informatics Association as “the development of storage, analytic and interpretive methods to optimize the transformation of increasing voluminous biomedical data into proactive, predictive, preventative and participatory health.” This article discusses barriers to implementing genomics applications and current progress toward overcoming barriers, describes lessons learned from early experiences of institutions engaged in personalized medicine and provides example areas for translational bioinformatics research inquiry. PMID:24039624

  8. Bioinformatics tools for analysing viral genomic data.

    PubMed

    Orton, R J; Gu, Q; Hughes, J; Maabar, M; Modha, S; Vattipally, S B; Wilkie, G S; Davison, A J

    2016-04-01

    The field of viral genomics and bioinformatics is experiencing a strong resurgence due to high-throughput sequencing (HTS) technology, which enables the rapid and cost-effective sequencing and subsequent assembly of large numbers of viral genomes. In addition, the unprecedented power of HTS technologies has enabled the analysis of intra-host viral diversity and quasispecies dynamics in relation to important biological questions on viral transmission, vaccine resistance and host jumping. HTS also enables the rapid identification of both known and potentially new viruses from field and clinical samples, thus adding new tools to the fields of viral discovery and metagenomics. Bioinformatics has been central to the rise of HTS applications because new algorithms and software tools are continually needed to process and analyse the large, complex datasets generated in this rapidly evolving area. In this paper, the authors give a brief overview of the main bioinformatics tools available for viral genomic research, with a particular emphasis on HTS technologies and their main applications. They summarise the major steps in various HTS analyses, starting with quality control of raw reads and encompassing activities ranging from consensus and de novo genome assembly to variant calling and metagenomics, as well as RNA sequencing. PMID:27217183

  9. Translational bioinformatics applications in genome medicine

    PubMed Central

    2009-01-01

    Although investigators using methodologies in bioinformatics have always been useful in genomic experimentation in analytic, engineering, and infrastructure support roles, only recently have bioinformaticians been able to have a primary scientific role in asking and answering questions on human health and disease. Here, I argue that this shift in role towards asking questions in medicine is now the next step needed for the field of bioinformatics. I outline four reasons why bioinformaticians are newly enabled to drive the questions in primary medical discovery: public availability of data, intersection of data across experiments, commoditization of methods, and streamlined validation. I also list four recommendations for bioinformaticians wishing to get more involved in translational research. PMID:19566916

  10. Genomics and Bioinformatics Resources for Crop Improvement

    PubMed Central

    Mochida, Keiichi; Shinozaki, Kazuo

    2010-01-01

    Recent remarkable innovations in platforms for omics-based research and application development provide crucial resources to promote research in model and applied plant species. A combinatorial approach using multiple omics platforms and integration of their outcomes is now an effective strategy for clarifying molecular systems integral to improving plant productivity. Furthermore, promotion of comparative genomics among model and applied plants allows us to grasp the biological properties of each species and to accelerate gene discovery and functional analyses of genes. Bioinformatics platforms and their associated databases are also essential for the effective design of approaches making the best use of genomic resources, including resource integration. We review recent advances in research platforms and resources in plant omics together with related databases and advances in technology. PMID:20208064

  11. Bacterial bioinformatics: pathogenesis and the genome.

    PubMed

    Paine, Kelly; Flower, Darren R

    2002-07-01

    As the number of completed microbial genome sequences continues to grow, there is a pressing need for the exploitation of this wealth of data through a synergistic interaction between the well-established science of bacteriology and the emergent discipline of bioinformatics. Antibiotic resistance and pathogenicity in virulent bacteria has become an increasing problem, with even the strongest drugs useless against some species, such as multi-drug resistant Enterococcus faecium and Mycobacterium tuberculosis. The global spread of Human Immunodeficiency Virus (HIV) and Acquired Immune Deficiency Syndrome (AIDS) has contributed to the re-emergence of tuberculosis and the threat from new and emergent diseases. To address these problems, bacterial pathogenicity requires redefinition as Koch's postulates become obsolete. This review discusses how the use of bacterial genomic information, and the in silico tools available at present, may aid in determining the definition of a current pathogen. The combination of both fields should provide a rapid and efficient way of assisting in the future development of antimicrobial therapies. PMID:12125816

  12. Online Bioinformatics Tutorials | Office of Cancer Genomics

    Cancer.gov

    Bioinformatics is a scientific discipline that applies computer science and information technology to help understand biological processes. The NIH provides a list of free online bioinformatics tutorials, either generated by the NIH Library or other institutes, which includes introductory lectures and "how to" videos on using various tools.

  13. Skate Genome Project: Cyber-Enabled Bioinformatics Collaboration

    PubMed Central

    Vincent, J.

    2011-01-01

    The Skate Genome Project, a pilot project of the North East Cyber infrastructure Consortium, aims to produce a draft genome sequence of Leucoraja erinacea, the Little Skate. The pilot project was designed to also develop expertise in large scale collaborations across the NECC region. An overview of the bioinformatics and infrastructure challenges faced during the first year of the project will be presented. Results to date and lessons learned from the perspective of a bioinformatics core will be highlighted.

  14. Using bioinformatics for drug target identification from the genome.

    PubMed

    Jiang, Zhenran; Zhou, Yanhong

    2005-01-01

    Genomics and proteomics technologies have created a paradigm shift in the drug discovery process, with bioinformatics having a key role in the exploitation of genomic, transcriptomic, and proteomic data to gain insights into the molecular mechanisms that underlie disease and to identify potential drug targets. We discuss the current state of the art for some of the bioinformatic approaches to identifying drug targets, including identifying new members of successful target classes and their functions, predicting disease relevant genes, and constructing gene networks and protein interaction networks. In addition, we introduce drug target discovery using the strategy of systems biology, and discuss some of the data resources for the identification of drug targets. Although bioinformatics tools and resources can be used to identify putative drug targets, validating targets is still a process that requires an understanding of the role of the gene or protein in the disease process and is heavily dependent on laboratory-based work. PMID:16336003

  15. Design and bioinformatics analysis of genome-wide CLIP experiments

    PubMed Central

    Wang, Tao; Xiao, Guanghua; Chu, Yongjun; Zhang, Michael Q.; Corey, David R.; Xie, Yang

    2015-01-01

    The past decades have witnessed a surge of discoveries revealing RNA regulation as a central player in cellular processes. RNAs are regulated by RNA-binding proteins (RBPs) at all post-transcriptional stages, including splicing, transportation, stabilization and translation. Defects in the functions of these RBPs underlie a broad spectrum of human pathologies. Systematic identification of RBP functional targets is among the key biomedical research questions and provides a new direction for drug discovery. The advent of cross-linking immunoprecipitation coupled with high-throughput sequencing (genome-wide CLIP) technology has recently enabled the investigation of genome-wide RBP–RNA binding at single base-pair resolution. This technology has evolved through the development of three distinct versions: HITS-CLIP, PAR-CLIP and iCLIP. Meanwhile, numerous bioinformatics pipelines for handling the genome-wide CLIP data have also been developed. In this review, we discuss the genome-wide CLIP technology and focus on bioinformatics analysis. Specifically, we compare the strengths and weaknesses, as well as the scopes, of various bioinformatics tools. To assist readers in choosing optimal procedures for their analysis, we also review experimental design and procedures that affect bioinformatics analyses. PMID:25958398

  16. The bioinformatics of psychosocial genomics in alternative and complementary medicine.

    PubMed

    Rossi, E

    2003-06-01

    The bioinformatics of alternative and complementary medicine is outlined in 3 hypotheses that extend the molecular-genomic revolution initiated by Watson and Crick 50 years ago to include psychology in the new discipline of psychosocial and cultural genomics. Stress-induced changes in the alternative splicing of genes demonstrate how psychosomatic stress in humans modulates activity-dependent gene expression, protein formation, physiological function, and psychological experience. The molecular messengers generated by stress, injury, and disease can activate immediate early genes within stem cells so that they then signal the target genes required to synthesize the proteins that will transform (differentiate) stem cells into mature well-functioning tissues. Such activity-dependent gene expression and its consequent activity-dependent neurogenesis and stem cell healing is proposed as the molecular-genomic-cellular basis of rehabilitative medicine, physical, and occupational therapy as well as the many alternative and complementary approaches to mind-body healing. The therapeutic replaying of enriching life experiences that evoke the novelty-numinosum-neurogenesis effect during creative moments of art, music, dance, drama, humor, literature, poetry, and spirituality, as well as cultural rituals of life transitions (birth, puberty, marriage, illness, healing, and death) can optimize consciousness, personal relationships, and healing in a manner that has much in common with the psychogenomic foundations of naturalistic and complementary medicine. The entire history of alternative and complementary approaches to healing is consistent with this new neuroscience world view about the role of psychological arousal and fascination in modulating gene expression, neurogenesis, and healing via the psychosocial and cultural rites of human societies. PMID:12853721

  17. Incorporating Genomics and Bioinformatics across the Life Sciences Curriculum

    SciTech Connect

    Ditty, Jayna L.; Kvaal, Christopher A.; Goodner, Brad; Freyermuth, Sharyn K.; Bailey, Cheryl; Britton, Robert A.; Gordon, Stuart G.; Heinhorst, Sabine; Reed, Kelynne; Xu, Zhaohui; Sanders-Lorenz, Erin R.; Axen, Seth; Kim, Edwin; Johns, Mitrick; Scott, Kathleen; Kerfeld, Cheryl A.

    2011-08-01

    Undergraduate life sciences education needs an overhaul, as clearly described in the National Research Council of the National Academies publication BIO 2010: Transforming Undergraduate Education for Future Research Biologists. Among BIO 2010's top recommendations is the need to involve students in working with real data and tools that reflect the nature of life sciences research in the 21st century. Education research studies support the importance of utilizing primary literature, designing and implementing experiments, and analyzing results in the context of a bona fide scientific question in cultivating the analytical skills necessary to become a scientist. Incorporating these basic scientific methodologies in undergraduate education leads to increased undergraduate and post-graduate retention in the sciences. Toward this end, many undergraduate teaching organizations offer training and suggestions for faculty to update and improve their teaching approaches to help students learn as scientists, through design and discovery (e.g., Council of Undergraduate Research [www.cur.org] and Project Kaleidoscope [www.pkal.org]). With the advent of genome sequencing and bioinformatics, many scientists now formulate biological questions and interpret research results in the context of genomic information. Just as the use of bioinformatic tools and databases changed the way scientists investigate problems, it must change how scientists teach to create new opportunities for students to gain experiences reflecting the influence of genomics, proteomics, and bioinformatics on modern life sciences research. Educators have responded by incorporating bioinformatics into diverse life science curricula. While these published exercises in, and guidelines for, bioinformatics curricula are helpful and inspirational, faculty new to the area of bioinformatics inevitably need training in the theoretical underpinnings of the algorithms. Moreover, effectively integrating bioinformatics into

  18. Bioinformatics tools for small genomes, such as hepatitis B virus.

    PubMed

    Bell, Trevor G; Kramvis, Anna

    2015-02-01

    DNA sequence analysis is undertaken in many biological research laboratories. The workflow consists of several steps involving the bioinformatic processing of biological data. We have developed a suite of web-based online bioinformatic tools to assist with processing, analysis and curation of DNA sequence data. Most of these tools are genome-agnostic, with two tools specifically designed for hepatitis B virus sequence data. Tools in the suite are able to process sequence data from Sanger sequencing, ultra-deep amplicon resequencing (pyrosequencing) and chromatograph (trace files), as appropriate. The tools are available online at no cost and are aimed at researchers without specialist technical computer knowledge. The tools can be accessed at http://hvdr.bioinf.wits.ac.za/SmallGenomeTools, and the source code is available online at https://github.com/DrTrevorBell/SmallGenomeTools. PMID:25690798

  19. Making sense of genomes of parasitic worms: Tackling bioinformatic challenges.

    PubMed

    Korhonen, Pasi K; Young, Neil D; Gasser, Robin B

    2016-01-01

    Billions of people and animals are infected with parasitic worms (helminths). Many of these worms cause diseases that have a major socioeconomic impact worldwide, and are challenging to control because existing treatment methods are often inadequate. There is, therefore, a need to work toward developing new intervention methods, built on a sound understanding of parasitic worms at molecular level, the relationships that they have with their animal hosts and/or the diseases that they cause. Decoding the genomes and transcriptomes of these parasites brings us a step closer to this goal. The key focus of this article is to critically review and discuss bioinformatic tools used for the assembly and annotation of these genomes and transcriptomes, as well as various post-genomic analyses of transcription profiles, biological pathways, synteny, phylogeny, biogeography and the prediction and prioritisation of drug target candidates. Bioinformatic pipelines implemented and established recently provide practical and efficient tools for the assembly and annotation of genomes of parasitic worms, and will be applicable to a wide range of other parasites and eukaryotic organisms. Future research will need to assess the utility of long-read sequence data sets for enhanced genomic assemblies, and develop improved algorithms for gene prediction and post-genomic analyses, to enable comprehensive systems biology explorations of parasitic organisms. PMID:26956711

  20. Public Access for Teaching Genomics, Proteomics, and Bioinformatics

    PubMed Central

    Campbell, A. Malcolm

    2003-01-01

    When the human genome project was conceived, its leaders wanted all researchers to have equal access to the data and associated research tools. Their vision of equal access provides an unprecedented teaching opportunity. Teachers and students have free access to the same databases that researchers are using. Furthermore, the recent movement to deliver scientific publications freely has presented a second source of current information for teaching. I have developed a genomics course that incorporates many of the public-domain databases, research tools, and peer-reviewed journals. These online resources provide students with exciting entree into the new fields of genomics, proteomics, and bioinformatics. In this essay, I outline how these fields are especially well suited for inclusion in the undergraduate curriculum. Assessment data indicate that my students were able to utilize online information to achieve the educational goals of the course and that the experience positively influenced their perceptions of how they might contribute to biology. PMID:12888845

  1. MEMOSys: Bioinformatics platform for genome-scale metabolic models

    PubMed Central

    2011-01-01

    Background Recent advances in genomic sequencing have enabled the use of genome sequencing in standard biological and biotechnological research projects. The challenge is how to integrate the large amount of data in order to gain novel biological insights. One way to leverage sequence data is to use genome-scale metabolic models. We have therefore designed and implemented a bioinformatics platform which supports the development of such metabolic models. Results MEMOSys (MEtabolic MOdel research and development System) is a versatile platform for the management, storage, and development of genome-scale metabolic models. It supports the development of new models by providing a built-in version control system which offers access to the complete developmental history. Moreover, the integrated web board, the authorization system, and the definition of user roles allow collaborations across departments and institutions. Research on existing models is facilitated by a search system, references to external databases, and a feature-rich comparison mechanism. MEMOSys provides customizable data exchange mechanisms using the SBML format to enable analysis in external tools. The web application is based on the Java EE framework and offers an intuitive user interface. It currently contains six annotated microbial metabolic models. Conclusions We have developed a web-based system designed to provide researchers a novel application facilitating the management and development of metabolic models. The system is freely available at http://www.icbi.at/MEMOSys. PMID:21276275

  2. Genomics Virtual Laboratory: A Practical Bioinformatics Workbench for the Cloud

    PubMed Central

    Afgan, Enis; Sloggett, Clare; Goonasekera, Nuwan; Makunin, Igor; Benson, Derek; Crowe, Mark; Gladman, Simon; Kowsar, Yousef; Pheasant, Michael; Horst, Ron; Lonie, Andrew

    2015-01-01

    Background Analyzing high throughput genomics data is a complex and compute intensive task, generally requiring numerous software tools and large reference data sets, tied together in successive stages of data transformation and visualisation. A computational platform enabling best practice genomics analysis ideally meets a number of requirements, including: a wide range of analysis and visualisation tools, closely linked to large user and reference data sets; workflow platform(s) enabling accessible, reproducible, portable analyses, through a flexible set of interfaces; highly available, scalable computational resources; and flexibility and versatility in the use of these resources to meet demands and expertise of a variety of users. Access to an appropriate computational platform can be a significant barrier to researchers, as establishing such a platform requires a large upfront investment in hardware, experience, and expertise. Results We designed and implemented the Genomics Virtual Laboratory (GVL) as a middleware layer of machine images, cloud management tools, and online services that enable researchers to build arbitrarily sized compute clusters on demand, pre-populated with fully configured bioinformatics tools, reference datasets and workflow and visualisation options. The platform is flexible in that users can conduct analyses through web-based (Galaxy, RStudio, IPython Notebook) or command-line interfaces, and add/remove compute nodes and data resources as required. Best-practice tutorials and protocols provide a path from introductory training to practice. The GVL is available on the OpenStack-based Australian Research Cloud (http://nectar.org.au) and the Amazon Web Services cloud. The principles, implementation and build process are designed to be cloud-agnostic. Conclusions This paper provides a blueprint for the design and implementation of a cloud-based Genomics Virtual Laboratory. We discuss scope, design considerations and technical and

  3. Bioinformatics challenges for genome-wide association studies

    PubMed Central

    Moore, Jason H.; Asselbergs, Folkert W.; Williams, Scott M.

    2010-01-01

    Motivation: The sequencing of the human genome has made it possible to identify an informative set of >1 million single nucleotide polymorphisms (SNPs) across the genome that can be used to carry out genome-wide association studies (GWASs). The availability of massive amounts of GWAS data has necessitated the development of new biostatistical methods for quality control, imputation and analysis issues including multiple testing. This work has been successful and has enabled the discovery of new associations that have been replicated in multiple studies. However, it is now recognized that most SNPs discovered via GWAS have small effects on disease susceptibility and thus may not be suitable for improving health care through genetic testing. One likely explanation for the mixed results of GWAS is that the current biostatistical analysis paradigm is by design agnostic or unbiased in that it ignores all prior knowledge about disease pathobiology. Further, the linear modeling framework that is employed in GWAS often considers only one SNP at a time thus ignoring their genomic and environmental context. There is now a shift away from the biostatistical approach toward a more holistic approach that recognizes the complexity of the genotype–phenotype relationship that is characterized by significant heterogeneity and gene–gene and gene–environment interaction. We argue here that bioinformatics has an important role to play in addressing the complexity of the underlying genetic basis of common human diseases. The goal of this review is to identify and discuss those GWAS challenges that will require computational methods. Contact: jason.h.moore@dartmouth.edu PMID:20053841

  4. Integrative genomic analysis by interoperation of bioinformatics tools in GenomeSpace.

    PubMed

    Qu, Kun; Garamszegi, Sara; Wu, Felix; Thorvaldsdottir, Helga; Liefeld, Ted; Ocana, Marco; Borges-Rivera, Diego; Pochet, Nathalie; Robinson, James T; Demchak, Barry; Hull, Tim; Ben-Artzi, Gil; Blankenberg, Daniel; Barber, Galt P; Lee, Brian T; Kuhn, Robert M; Nekrutenko, Anton; Segal, Eran; Ideker, Trey; Reich, Michael; Regev, Aviv; Chang, Howard Y; Mesirov, Jill P

    2016-03-01

    Complex biomedical analyses require the use of multiple software tools in concert and remain challenging for much of the biomedical research community. We introduce GenomeSpace (http://www.genomespace.org), a cloud-based, cooperative community resource that currently supports the streamlined interaction of 20 bioinformatics tools and data resources. To facilitate integrative analysis by non-programmers, it offers a growing set of 'recipes', short workflows to guide investigators through high-utility analysis tasks. PMID:26780094

  5. Integrative genomic analysis by interoperation of bioinformatics tools in GenomeSpace

    PubMed Central

    Thorvaldsdottir, Helga; Liefeld, Ted; Ocana, Marco; Borges-Rivera, Diego; Pochet, Nathalie; Robinson, James T.; Demchak, Barry; Hull, Tim; Ben-Artzi, Gil; Blankenberg, Daniel; Barber, Galt P.; Lee, Brian T.; Kuhn, Robert M.; Nekrutenko, Anton; Segal, Eran; Ideker, Trey; Reich, Michael; Regev, Aviv; Chang, Howard Y.; Mesirov, Jill P.

    2015-01-01

    Integrative analysis of multiple data types to address complex biomedical questions requires the use of multiple software tools in concert and remains an enormous challenge for most of the biomedical research community. Here we introduce GenomeSpace (http://www.genomespace.org), a cloud-based, cooperative community resource. Seeded as a collaboration of six of the most popular genomics analysis tools, GenomeSpace now supports the streamlined interaction of 20 bioinformatics tools and data resources. To facilitate the ability of non-programming users’ to leverage GenomeSpace in integrative analysis, it offers a growing set of ‘recipes’, short workflows involving a few tools and steps to guide investigators through high utility analysis tasks. PMID:26780094

  6. Genomics and natural products: role of bioinformatics and recent patents.

    PubMed

    Preuss, Charles; Das, Malay K; Pathak, Yashwant V

    2014-01-01

    The post genomic era has promised major breakthroughs in personalized medicine which will improve a patient's health by selecting treatments including diet based on the patient's unique DNA sequence. The post genomic era is allowing scientists and clinicians to examine an individuals' DNA and then recommend the best diet in order to remain healthy and attenuate disease processes which the individual might be predisposed to because of their genetic make-up, e.g., cardiovascular disease. Nutrigenomics and nutrigenetics are related terms to pharmacogenomics and pharmacogenetics with an emphasis on diet or nutrition. There has been an increasing interest in consumers on natural medicines or Nutraceuticals in order to remain healthy. The post genomic era will allow a patient to visit their physician who will screen the patients DNA on a silicon chip. This will indicate which of the patient's genes have polymorphisms, e.g., a single nucleotide polymorphism (SNP) that might lead the patient to be more susceptible to certain diseases and then the physician could prescribe the appropriate dietary supplements to prevent or diminish these potential diseases. Several recently published patents are discussed in the article covering recent developments in the field. PMID:25185982

  7. Evolutionary genomics of animal personality.

    PubMed

    van Oers, Kees; Mueller, Jakob C

    2010-12-27

    Research on animal personality can be approached from both a phenotypic and a genetic perspective. While using a phenotypic approach one can measure present selection on personality traits and their combinations. However, this approach cannot reconstruct the historical trajectory that was taken by evolution. Therefore, it is essential for our understanding of the causes and consequences of personality diversity to link phenotypic variation in personality traits with polymorphisms in genomic regions that code for this trait variation. Identifying genes or genome regions that underlie personality traits will open exciting possibilities to study natural selection at the molecular level, gene-gene and gene-environment interactions, pleiotropic effects and how gene expression shapes personality phenotypes. In this paper, we will discuss how genome information revealed by already established approaches and some more recent techniques such as high-throughput sequencing of genomic regions in a large number of individuals can be used to infer micro-evolutionary processes, historical selection and finally the maintenance of personality trait variation. We will do this by reviewing recent advances in molecular genetics of animal personality, but will also use advanced human personality studies as case studies of how molecular information may be used in animal personality research in the near future. PMID:21078651

  8. FDA Bioinformatics Tool for Microbial Genomics Research on Molecular Characterization of Bacterial Foodborne Pathogens Using Microarrays

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Background: Advances in microbial genomics and bioinformatics are offering greater insights into the emergence and spread of foodborne pathogens in outbreak scenarios. The Food and Drug Administration (FDA) has developed the genomics tool ArrayTrackTM, which provides extensive functionalities to man...

  9. Computational and Bioinformatics Frameworks for Next-Generation Whole Exome and Genome Sequencing

    PubMed Central

    Dolled-Filhart, Marisa P.; Lee, Michael; Ou-yang, Chih-wen; Haraksingh, Rajini Rani; Lin, Jimmy Cheng-Ho

    2013-01-01

    It has become increasingly apparent that one of the major hurdles in the genomic age will be the bioinformatics challenges of next-generation sequencing. We provide an overview of a general framework of bioinformatics analysis. For each of the three stages of (1) alignment, (2) variant calling, and (3) filtering and annotation, we describe the analysis required and survey the different software packages that are used. Furthermore, we discuss possible future developments as data sources grow and highlight opportunities for new bioinformatics tools to be developed. PMID:23365548

  10. A Critical Analysis of Assessment Quality in Genomics and Bioinformatics Education Research

    ERIC Educational Resources Information Center

    Campbell, Chad E.; Nehm, Ross H.

    2013-01-01

    The growing importance of genomics and bioinformatics methods and paradigms in biology has been accompanied by an explosion of new curricula and pedagogies. An important question to ask about these educational innovations is whether they are having a meaningful impact on students' knowledge, attitudes, or skills. Although assessments are…

  11. The application of genomics and bioinformatics to accelerate crop improvement in a changing climate.

    PubMed

    Batley, Jacqueline; Edwards, David

    2016-04-01

    The changing climate and growing global population will increase pressure on our ability to produce sufficient food. The breeding of novel crops and the adaptation of current crops to the new environment are required to ensure continued food production. Advances in genomics offer the potential to accelerate the genomics based breeding of crop plants. However, relating genomic data to climate related agronomic traits for use in breeding remains a huge challenge, and one which will require coordination of diverse skills and expertise. Bioinformatics, when combined with genomics has the potential to help maintain food security in the face of climate change through the accelerated production of climate ready crops. PMID:26926905

  12. The discrepancies in the results of bioinformatics tools for genomic structural annotation

    NASA Astrophysics Data System (ADS)

    Pawełkowicz, Magdalena; Nowak, Robert; Osipowski, Paweł; Rymuszka, Jacek; Świerkula, Katarzyna; Wojcieszek, Michał; Przybecki, Zbigniew

    2014-11-01

    A major focus of sequencing project is to identify genes in genomes. However it is necessary to define the variety of genes and the criteria for identifying them. In this work we present discrepancies and dependencies from the application of different bioinformatic programs for structural annotation performed on the cucumber data set from Polish Consortium of Cucumber Genome Sequencing. We use Fgenesh, GenScan and GeneMark to automated structural annotation, the results have been compared to reference annotation.

  13. Exploring laccase genes from plant pathogen genomes: a bioinformatic approach.

    PubMed

    Feng, B Z; Li, P Q; Fu, L; Yu, X M

    2015-01-01

    To date, research on laccases has mostly been focused on plant and fungal laccases and their current use in biotechnological applications. In contrast, little is known about laccases from plant pathogens, although recent rapid progress in whole genome sequencing of an increasing number of organisms has facilitated their identification and ascertainment of their origins. In this study, a comparative analysis was performed to elucidate the distribution of laccases among bacteria, fungi, and oomycetes, and, through comparison of their amino acids, to determine the relationships between them. We retrieved the laccase genes for the 20 publicly available plant pathogen genomes. From these, 125 laccase genes were identified in total, including seven in bacterial genomes, 101 in fungal genomes, and 17 in oomycete genomes. Most of the predicted protein models of these genes shared typical fungal laccase characteristics, possessing four conserved domains with one cysteine and ten histidine residues at these domains. Phylogenetic analysis illustrated that laccases from bacteria and oomycetes were grouped into two distinct clades, whereas fungal laccases clustered in three main clades. These results provide the theoretical groundwork regarding the role of laccases in plant pathogens and might be used to guide future research into these enzymes. PMID:26535716

  14. Silicon Era of Carbon-Based Life: Application of Genomics and Bioinformatics in Crop Stress Research

    PubMed Central

    Li, Man-Wah; Qi, Xinpeng; Ni, Meng; Lam, Hon-Ming

    2013-01-01

    Abiotic and biotic stresses lead to massive reprogramming of different life processes and are the major limiting factors hampering crop productivity. Omics-based research platforms allow for a holistic and comprehensive survey on crop stress responses and hence may bring forth better crop improvement strategies. Since high-throughput approaches generate considerable amounts of data, bioinformatics tools will play an essential role in storing, retrieving, sharing, processing, and analyzing them. Genomic and functional genomic studies in crops still lag far behind similar studies in humans and other animals. In this review, we summarize some useful genomics and bioinformatics resources available to crop scientists. In addition, we also discuss the major challenges and advancements in the “-omics” studies, with an emphasis on their possible impacts on crop stress research and crop improvement. PMID:23759993

  15. Public Access for Teaching Genomics, Proteomics, and Bioinformatics

    ERIC Educational Resources Information Center

    Campbell, A. Malcolm

    2003-01-01

    When the human genome project was conceived, its leaders wanted all researchers to have equal access to the data and associated research tools. Their vision of equal access provides an unprecedented teaching opportunity. Teachers and students have free access to the same databases that researchers are using. Furthermore, the recent movement to…

  16. A new set of bioinformatics tools for genome projects.

    PubMed

    Almeida, Luiz G P; Paixão, Roger; Souza, Rangel C; Costa, Gisele C da; Almeida, Darcy F de; Vasconcelos, Ana T R de

    2004-01-01

    A new tool called System for Automated Bacterial Integrated Annotation--SABIA (SABIA being a very well-known bird in Brazil) was developed for the assembly and annotation of bacterial genomes. This system performs automatic tasks of assembly analysis, ORFs identification/analysis, and extragenic region analyses. Genome assembly and contig automatic annotation data are also available in the same working environment. The system integrates several public domains and newly developed software programs capable of dealing with several types of databases, and it is portable to other operational systems. These programs interact with most of the well-known biological database/softwares, such as Glimmer, Genemark, the BLAST family programs, InterPro, COG, Kegg, PSORT, GO, tRNAScan and RBSFinder, and can also be used to identify metabolic pathways. PMID:15100986

  17. Meet me halfway: when genomics meets structural bioinformatics.

    PubMed

    Gong, Sungsam; Worth, Catherine L; Cheng, Tammy M K; Blundell, Tom L

    2011-06-01

    The DNA sequencing technology developed by Frederick Sanger in the 1970s established genomics as the basis of comparative genetics. The recent invention of next-generation sequencing (NGS) platform has added a new dimension to genome research by generating ultra-fast and high-throughput sequencing data in an unprecedented manner. The advent of NGS technology also provides the opportunity to study genetic diseases where sequence variants or mutations are sought to establish a causal relationship with disease phenotypes. However, it is not a trivial task to seek genetic variants responsible for genetic diseases and even harder for complex diseases such as diabetes and cancers. In such polygenic diseases, multiple genes and alleles, which can exist in healthy individuals, come together to contribute to common disease phenotypes in a complex manner. Hence, it is desirable to have an approach that integrates omics data with both knowledge of protein structure and function and an understanding of networks/pathways, i.e. functional genomics and systems biology; in this way, genotype-phenotype relationships can be better understood. In this review, we bring this 'bottom-up' approach alongside the current NGS-driven genetic study of genetic variations and disease aetiology. We describe experimental and computational techniques for assessing genetic variants and their deleterious effects on protein structure and function. PMID:21350909

  18. Tissue Banking, Bioinformatics, and Electronic Medical Records: The Front-End Requirements for Personalized Medicine

    PubMed Central

    Suh, K. Stephen; Sarojini, Sreeja; Youssif, Maher; Nalley, Kip; Milinovikj, Natasha; Elloumi, Fathi; Russell, Steven; Pecora, Andrew; Schecter, Elyssa; Goy, Andre

    2013-01-01

    Personalized medicine promises patient-tailored treatments that enhance patient care and decrease overall treatment costs by focusing on genetics and “-omics” data obtained from patient biospecimens and records to guide therapy choices that generate good clinical outcomes. The approach relies on diagnostic and prognostic use of novel biomarkers discovered through combinations of tissue banking, bioinformatics, and electronic medical records (EMRs). The analytical power of bioinformatic platforms combined with patient clinical data from EMRs can reveal potential biomarkers and clinical phenotypes that allow researchers to develop experimental strategies using selected patient biospecimens stored in tissue banks. For cancer, high-quality biospecimens collected at diagnosis, first relapse, and various treatment stages provide crucial resources for study designs. To enlarge biospecimen collections, patient education regarding the value of specimen donation is vital. One approach for increasing consent is to offer publically available illustrations and game-like engagements demonstrating how wider sample availability facilitates development of novel therapies. The critical value of tissue bank samples, bioinformatics, and EMR in the early stages of the biomarker discovery process for personalized medicine is often overlooked. The data obtained also require cross-disciplinary collaborations to translate experimental results into clinical practice and diagnostic and prognostic use in personalized medicine. PMID:23818899

  19. proBAMsuite, a Bioinformatics Framework for Genome-Based Representation and Analysis of Proteomics Data*

    PubMed Central

    Wang, Xiaojing; Slebos, Robbert J. C.; Chambers, Matthew C.; Tabb, David L.; Liebler, Daniel C.; Zhang, Bing

    2016-01-01

    To facilitate genome-based representation and analysis of proteomics data, we developed a new bioinformatics framework, proBAMsuite, in which a central component is the protein BAM (proBAM) file format for organizing peptide spectrum matches (PSMs)1 within the context of the genome. proBAMsuite also includes two R packages, proBAMr and proBAMtools, for generating and analyzing proBAM files, respectively. Applying proBAMsuite to three recently published proteomics datasets, we demonstrated its utility in facilitating efficient genome-based sharing, interpretation, and integration of proteomics data. First, the interpretation of proteomics data is significantly enhanced with the rich genomic annotation information. Second, PSMs can be easily reannotated using user-specified gene annotation schemes and assembled into both protein and gene identifications. Third, using the genome as a common reference, proBAMsuite facilitates seamless proteomics and proteogenomics data integration. Finally, proBAM files can be readily visualized in genome browsers and thus bring proteomics data analysis to a general audience beyond the proteomics community. Results from this study establish proBAMsuite as a useful bioinformatics framework for proteomics and proteogenomics research. PMID:26657539

  20. VectorBase: improvements to a bioinformatics resource for invertebrate vector genomics.

    PubMed

    Megy, Karine; Emrich, Scott J; Lawson, Daniel; Campbell, David; Dialynas, Emmanuel; Hughes, Daniel S T; Koscielny, Gautier; Louis, Christos; Maccallum, Robert M; Redmond, Seth N; Sheehan, Andrew; Topalis, Pantelis; Wilson, Derek

    2012-01-01

    VectorBase (http://www.vectorbase.org) is a NIAID-supported bioinformatics resource for invertebrate vectors of human pathogens. It hosts data for nine genomes: mosquitoes (three Anopheles gambiae genomes, Aedes aegypti and Culex quinquefasciatus), tick (Ixodes scapularis), body louse (Pediculus humanus), kissing bug (Rhodnius prolixus) and tsetse fly (Glossina morsitans). Hosted data range from genomic features and expression data to population genetics and ontologies. We describe improvements and integration of new data that expand our taxonomic coverage. Releases are bi-monthly and include the delivery of preliminary data for emerging genomes. Frequent updates of the genome browser provide VectorBase users with increasing options for visualizing their own high-throughput data. One major development is a new population biology resource for storing genomic variations, insecticide resistance data and their associated metadata. It takes advantage of improved ontologies and controlled vocabularies. Combined, these new features ensure timely release of multiple types of data in the public domain while helping overcome the bottlenecks of bioinformatics and annotation by engaging with our user community. PMID:22135296

  1. Genome-wide variant analysis of simplex autism families with an integrative clinical-bioinformatics pipeline

    PubMed Central

    Jiménez-Barrón, Laura T.; O'Rawe, Jason A.; Wu, Yiyang; Yoon, Margaret; Fang, Han; Iossifov, Ivan; Lyon, Gholson J.

    2015-01-01

    Autism spectrum disorders (ASDs) are a group of developmental disabilities that affect social interaction and communication and are characterized by repetitive behaviors. There is now a large body of evidence that suggests a complex role of genetics in ASDs, in which many different loci are involved. Although many current population-scale genomic studies have been demonstrably fruitful, these studies generally focus on analyzing a limited part of the genome or use a limited set of bioinformatics tools. These limitations preclude the analysis of genome-wide perturbations that may contribute to the development and severity of ASD-related phenotypes. To overcome these limitations, we have developed and utilized an integrative clinical and bioinformatics pipeline for generating a more complete and reliable set of genomic variants for downstream analyses. Our study focuses on the analysis of three simplex autism families consisting of one affected child, unaffected parents, and one unaffected sibling. All members were clinically evaluated and widely phenotyped. Genotyping arrays and whole-genome sequencing were performed on each member, and the resulting sequencing data were analyzed using a variety of available bioinformatics tools. We searched for rare variants of putative functional impact that were found to be segregating according to de novo, autosomal recessive, X-linked, mitochondrial, and compound heterozygote transmission models. The resulting candidate variants included three small heterozygous copy-number variations (CNVs), a rare heterozygous de novo nonsense mutation in MYBBP1A located within exon 1, and a novel de novo missense variant in LAMB3. Our work demonstrates how more comprehensive analyses that include rich clinical data and whole-genome sequencing data can generate reliable results for use in downstream investigations. PMID:27148569

  2. AphidBase: A centralized bioinformatic resource for annotation of the pea aphid genome

    PubMed Central

    Legeai, Fabrice; Shigenobu, Shuji; Gauthier, Jean-Pierre; Colbourne, John; Rispe, Claude; Collin, Olivier; Richards, Stephen; Wilson, Alex C. C.; Tagu, Denis

    2015-01-01

    AphidBase is a centralized bioinformatic resource that was developed to facilitate community annotation of the pea aphid genome by the International Aphid Genomics Consortium (IAGC). The AphidBase Information System designed to organize and distribute genomic data and annotations for a large international community was constructed using open source software tools from the Generic Model Organism Database (GMOD). The system includes Apollo and GBrowse utilities as well as a wiki, blast search capabilities and a full text search engine. AphidBase strongly supported community cooperation and coordination in the curation of gene models during community annotation of the pea aphid genome. AphidBase can be accessed at http://www.aphidbase.com. PMID:20482635

  3. Integrating genomics, proteomics and bioinformatics in translational studies of molecular medicine.

    PubMed

    Ostrowski, Jerzy; Wyrwicz, Lucjan S

    2009-09-01

    Understanding the molecular mechanisms of disease requires the introduction of molecular diagnostics into medical practice. Current medicine employs only elements of molecular diagnostics, which are usually applied on the scale of single genes. Medicine in the postgenomic era will utilize thousands of disease-associated molecular markers provided by high-throughput sequencing and functional genomic, proteomic and metabolomic studies. Such a spectrum of techniques will link clinical medicine based on molecularly oriented diagnostics with the prediction and prevention of disease. To achieve this task, large-scale and genome-wide biological and medical data must be combined with biostatistical and bioinformatic analyses to model biological systems. Collecting, cataloging and comparing data from molecular studies, and the subsequent development of conclusions, creates the fundamentals of systems biology. This highly complex analytical process reflects a new scientific paradigm known as integrative genomics. PMID:19732006

  4. Widening participation would be key in enhancing bioinformatics and genomics research in Africa

    PubMed Central

    Karikari, Thomas K.; Quansah, Emmanuel; Mohamed, Wael M.Y.

    2015-01-01

    Bioinformatics and genome science (BGS) are gradually gaining roots in Africa, contributing to studies that are leading to improved understanding of health, disease, agriculture and food security. While a few African countries have established foundations for research and training in these areas, BGS appear to be limited to only a few institutions in specific African countries. However, improving the disciplines in Africa will require pragmatic efforts to expand training and research partnerships to scientists in yet-unreached institutions. Here, we discuss the need to expand BGS programmes in Africa, and propose mechanisms to do so. PMID:26767163

  5. Bioinformatics visualization and integration with open standards: the Bluejay genomic browser.

    PubMed

    Turinsky, Andrei L; Ah-Seng, Andrew C; Gordon, Paul M K; Stromer, Julie N; Taschuk, Morgan L; Xu, Emily W; Sensen, Christoph W

    2005-01-01

    We have created a new Java-based integrated computational environment for the exploration of genomic data, called Bluejay. The system is capable of using almost any XML file related to genomic data. Non-XML data sources can be accessed via a proxy server. Bluejay has several features, which are new to Bioinformatics, including an unlimited semantic zoom capability, coupled with Scalable Vector Graphics (SVG) outputs; an implementation of the XLink standard, which features access to MAGPIE Genecards as well as any BioMOBY service accessible over the Internet; and the integration of gene chip analysis tools with the functional assignments. The system can be used as a signed web applet, Web Start, and a local stand-alone application, with or without connection to the Internet. It is available free of charge and as open source via http://bluejay.ucalgary.ca. PMID:15972014

  6. Edge Bioinformatics

    Energy Science and Technology Software Center (ESTSC)

    2015-08-03

    Edge Bioinformatics is a developmental bioinformatics and data management platform which seeks to supply laboratories with bioinformatics pipelines for analyzing data associated with common samples case goals. Edge Bioinformatics enables sequencing as a solution and forward-deployed situations where human-resources, space, bandwidth, and time are limited. The Edge bioinformatics pipeline was designed based on following USE CASES and specific to illumina sequencing reads. 1. Assay performance adjudication (PCR): Analysis of an existing PCR assay in amore » genomic context, and automated design of a new assay to resolve conflicting results; 2. Clinical presentation with extreme symptoms: Characterization of a known pathogen or co-infection with a. Novel emerging disease outbreak or b. Environmental surveillance« less

  7. Edge Bioinformatics

    SciTech Connect

    Lo, Chien-Chi

    2015-08-03

    Edge Bioinformatics is a developmental bioinformatics and data management platform which seeks to supply laboratories with bioinformatics pipelines for analyzing data associated with common samples case goals. Edge Bioinformatics enables sequencing as a solution and forward-deployed situations where human-resources, space, bandwidth, and time are limited. The Edge bioinformatics pipeline was designed based on following USE CASES and specific to illumina sequencing reads. 1. Assay performance adjudication (PCR): Analysis of an existing PCR assay in a genomic context, and automated design of a new assay to resolve conflicting results; 2. Clinical presentation with extreme symptoms: Characterization of a known pathogen or co-infection with a. Novel emerging disease outbreak or b. Environmental surveillance

  8. A critical analysis of assessment quality in genomics and bioinformatics education research.

    PubMed

    Campbell, Chad E; Nehm, Ross H

    2013-01-01

    The growing importance of genomics and bioinformatics methods and paradigms in biology has been accompanied by an explosion of new curricula and pedagogies. An important question to ask about these educational innovations is whether they are having a meaningful impact on students' knowledge, attitudes, or skills. Although assessments are necessary tools for answering this question, their outputs are dependent on their quality. Our study 1) reviews the central importance of reliability and construct validity evidence in the development and evaluation of science assessments and 2) examines the extent to which published assessments in genomics and bioinformatics education (GBE) have been developed using such evidence. We identified 95 GBE articles (out of 226) that contained claims of knowledge increases, affective changes, or skill acquisition. We found that 1) the purpose of most of these studies was to assess summative learning gains associated with curricular change at the undergraduate level, and 2) a minority (<10%) of studies provided any reliability or validity evidence, and only one study out of the 95 sampled mentioned both validity and reliability. Our findings raise concerns about the quality of evidence derived from these instruments. We end with recommendations for improving assessment quality in GBE. PMID:24006400

  9. Neurogenomics: An opportunity to integrate neuroscience, genomics and bioinformatics research in Africa

    PubMed Central

    Karikari, Thomas K.; Aleksic, Jelena

    2015-01-01

    Modern genomic approaches have made enormous contributions to improving our understanding of the function, development and evolution of the nervous system, and the diversity within and between species. However, most of these research advances have been recorded in countries with advanced scientific resources and funding support systems. On the contrary, little is known about, for example, the possible interplay between different genes, non-coding elements and environmental factors in modulating neurological diseases among populations in low-income countries, including many African countries. The unique ancestry of African populations suggests that improved inclusion of these populations in neuroscience-related genomic studies would significantly help to identify novel factors that might shape the future of neuroscience research and neurological healthcare. This perspective is strongly supported by the recent identification that diseased individuals and their kindred from specific sub-Saharan African populations lack common neurological disease-associated genetic mutations. This indicates that there may be population-specific causes of neurological diseases, necessitating further investigations into the contribution of additional, presently-unknown genomic factors. Here, we discuss how the development of neurogenomics research in Africa would help to elucidate disease-related genomic variants, and also provide a good basis to develop more effective therapies. Furthermore, neurogenomics would harness African scientists' expertise in neuroscience, genomics and bioinformatics to extend our understanding of the neural basis of behaviour, development and evolution. PMID:26937352

  10. Basics of Genome Sequence Analysis in Bioinformatics -- its Fundamental Ideas and Problems

    NASA Astrophysics Data System (ADS)

    Suzuki, Tomonori; Miyazaki, Satoru

    2009-02-01

    The genome sequences are one of the most fundamental data among various omics analyses. So far, basic bioinformatics tools have developing to treat genome sequences. First step of genome sequence analysis is to predict or assign "genes" on genome sequences. In the case of Eukaryotes, we can identify genes by use of full length cDNA sequences with local alignment tools such as search, blast and fasta, etc. However, it is difficult to catch mRNAs (transcripts) in Prokaryotes. Therefore, computational prediction for gene identification is first choice to start genome sequence analysis. In this review, we pick up methods for computational gene prediction first. Once genes are predicted, next step is to functions for proteins or RNAs encoded on a gene. Then, how we can define the distance between gene sequences is very important for the further analysis. So, we describe the basics of mathematical concept for gene comparison. And we also introduce our novel concept for biological sequence comparisons for the view point of informational theory. In the post genome era, many researchers are very interested in not only gene functions but also the gene regulations whose information is also on genome sequences. Cis-regulatory elements, however, is too short to find some mathematical rules. Therefore, computationally predicted cis-elements tend to include many false-positives. To reduce the ratio false-positives, we need reliable database of set of cis-regulatory elements called cis-regulatory modules for a gene. So, we are trying to develop the Cis-Regulatory Elements Module Reference Database. In the third section, we introduce you the procedure to construct the Cis-Regulatory Elements Module Reference Database and its user interfaces.

  11. Personal genomes, quantitative dynamic omics and personalized medicine

    PubMed Central

    Mias, George I.; Snyder, Michael

    2015-01-01

    The rapid technological developments following the Human Genome Project have made possible the availability of personalized genomes. As the focus now shifts from characterizing genomes to making personalized disease associations, in combination with the availability of other omics technologies, the next big push will be not only to obtain a personalized genome, but to quantitatively follow other omics. This will include transcriptomes, proteomes, metabolomes, antibodyomes, and new emerging technologies, enabling the profiling of thousands of molecular components in individuals. Furthermore, omics profiling performed longitudinally can probe the temporal patterns associated with both molecular changes and associated physiological health and disease states. Such data necessitates the development of computational methodology to not only handle and descriptively assess such data, but also construct quantitative biological models. Here we describe the availability of personal genomes and developing omics technologies that can be brought together for personalized implementations and how these novel integrated approaches may effectively provide a precise personalized medicine that focuses on not only characterization and treatment but ultimately the prevention of disease. PMID:25798291

  12. Personalized cloud-based bioinformatics services for research and education: use cases and the elasticHPC package

    PubMed Central

    2012-01-01

    Background Bioinformatics services have been traditionally provided in the form of a web-server that is hosted at institutional infrastructure and serves multiple users. This model, however, is not flexible enough to cope with the increasing number of users, increasing data size, and new requirements in terms of speed and availability of service. The advent of cloud computing suggests a new service model that provides an efficient solution to these problems, based on the concepts of "resources-on-demand" and "pay-as-you-go". However, cloud computing has not yet been introduced within bioinformatics servers due to the lack of usage scenarios and software layers that address the requirements of the bioinformatics domain. Results In this paper, we provide different use case scenarios for providing cloud computing based services, considering both the technical and financial aspects of the cloud computing service model. These scenarios are for individual users seeking computational power as well as bioinformatics service providers aiming at provision of personalized bioinformatics services to their users. We also present elasticHPC, a software package and a library that facilitates the use of high performance cloud computing resources in general and the implementation of the suggested bioinformatics scenarios in particular. Concrete examples that demonstrate the suggested use case scenarios with whole bioinformatics servers and major sequence analysis tools like BLAST are presented. Experimental results with large datasets are also included to show the advantages of the cloud model. Conclusions Our use case scenarios and the elasticHPC package are steps towards the provision of cloud based bioinformatics services, which would help in overcoming the data challenge of recent biological research. All resources related to elasticHPC and its web-interface are available at http://www.elasticHPC.org. PMID:23281941

  13. Challenges, Solutions, and Quality Metrics of Personal Genome Assembly in Advancing Precision Medicine.

    PubMed

    Xiao, Wenming; Wu, Leihong; Yavas, Gokhan; Simonyan, Vahan; Ning, Baitang; Hong, Huixiao

    2016-01-01

    drug therapy and detecting tumors. We believe the precision medicine would largely benefit from bioinformatics solutions, particularly for personal genome assembly. PMID:27110816

  14. Challenges, Solutions, and Quality Metrics of Personal Genome Assembly in Advancing Precision Medicine

    PubMed Central

    Xiao, Wenming; Wu, Leihong; Yavas, Gokhan; Simonyan, Vahan; Ning, Baitang; Hong, Huixiao

    2016-01-01

    -response, tailoring drug therapy and detecting tumors. We believe the precision medicine would largely benefit from bioinformatics solutions, particularly for personal genome assembly. PMID:27110816

  15. The Translational Genomics Core at Partners Personalized Medicine: Facilitating the Transition of Research towards Personalized Medicine.

    PubMed

    Blau, Ashley; Brown, Alison; Mahanta, Lisa; Amr, Sami S

    2016-01-01

    The Translational Genomics Core (TGC) at Partners Personalized Medicine (PPM) serves as a fee-for-service core laboratory for Partners Healthcare researchers, providing access to technology platforms and analysis pipelines for genomic, transcriptomic, and epigenomic research projects. The interaction of the TGC with various components of PPM provides it with a unique infrastructure that allows for greater IT and bioinformatics opportunities, such as sample tracking and data analysis. The following article describes some of the unique opportunities available to an academic research core operating within PPM, such the ability to develop analysis pipelines with a dedicated bioinformatics team and maintain a flexible Laboratory Information Management System (LIMS) with the support of an internal IT team, as well as the operational challenges encountered to respond to emerging technologies, diverse investigator needs, and high staff turnover. In addition, the implementation and operational role of the TGC in the Partners Biobank genotyping project of over 25,000 samples is presented as an example of core activities working with other components of PPM. PMID:26927185

  16. The Translational Genomics Core at Partners Personalized Medicine: Facilitating the Transition of Research towards Personalized Medicine

    PubMed Central

    Blau, Ashley; Brown, Alison; Mahanta, Lisa; Amr, Sami S.

    2016-01-01

    The Translational Genomics Core (TGC) at Partners Personalized Medicine (PPM) serves as a fee-for-service core laboratory for Partners Healthcare researchers, providing access to technology platforms and analysis pipelines for genomic, transcriptomic, and epigenomic research projects. The interaction of the TGC with various components of PPM provides it with a unique infrastructure that allows for greater IT and bioinformatics opportunities, such as sample tracking and data analysis. The following article describes some of the unique opportunities available to an academic research core operating within PPM, such the ability to develop analysis pipelines with a dedicated bioinformatics team and maintain a flexible Laboratory Information Management System (LIMS) with the support of an internal IT team, as well as the operational challenges encountered to respond to emerging technologies, diverse investigator needs, and high staff turnover. In addition, the implementation and operational role of the TGC in the Partners Biobank genotyping project of over 25,000 samples is presented as an example of core activities working with other components of PPM. PMID:26927185

  17. In the Spotlight: Bioinformatics

    PubMed Central

    Wang, May Dongmei

    2016-01-01

    During 2012, next generation sequencing (NGS) has attracted great attention in the biomedical research community, especially for personalized medicine. Also, third generation sequencing has become available. Therefore, state-of-art sequencing technology and analysis are reviewed in this Bioinformatics spotlight on 2012. Next-generation sequencing (NGS) is high-throughput nucleic acid sequencing technology with wide dynamic range and single base resolution. The full promise of NGS depends on the optimization of NGS platforms, sequence alignment and assembly algorithms, data analytics, novel algorithms for integrating NGS data with existing genomic, proteomic, or metabolomic data, and quantitative assessment of NGS technology in comparing to more established technologies such as microarrays. NGS technology has been predicated to become a cornerstone of personalized medicine. It is argued that NGS is a promising field for motivated young researchers who are looking for opportunities in bioinformatics. PMID:23192635

  18. Empowered genome community: leveraging a bioinformatics platform as a citizen-scientist collaboration tool.

    PubMed

    Wendelsdorf, Katherine; Shah, Sohela

    2015-09-01

    There is on-going effort in the biomedical research community to leverage Next Generation Sequencing (NGS) technology to identify genetic variants that affect our health. The main challenge facing researchers is getting enough samples from individuals either sick or healthy - to be able to reliably identify the few variants that are causal for a phenotype among all other variants typically seen among individuals. At the same time, more and more individuals are having their genome sequenced either out of curiosity or to identify the cause of an illness. These individuals may benefit from of a way to view and understand their data. QIAGEN's Ingenuity Variant Analysis is an online application that allows users with and without extensive bioinformatics training to incorporate information from published experiments, genetic databases, and a variety of statistical models to identify variants, from a long list of candidates, that are most likely causal for a phenotype as well as annotate variants with what is already known about them in the literature and databases. Ingenuity Variant Analysis is also an information sharing platform where users may exchange samples and analyses. The Empowered Genome Community (EGC) is a new program in which QIAGEN is making this on-line tool freely available to any individual who wishes to analyze their own genetic sequence. EGC members are then able to make their data available to other Ingenuity Variant Analysis users to be used in research. Here we present and describe the Empowered Genome Community in detail. We also present a preliminary, proof-of-concept study that utilizes the 200 genomes currently available through the EGC. The goal of this program is to allow individuals to access and understand their own data as well as facilitate citizen-scientist collaborations that can drive research forward and spur quality scientific dialogue in the general public. PMID:27054071

  19. Personalized medicine: new genomics, old lessons.

    PubMed

    Offit, Kenneth

    2011-07-01

    Personalized medicine uses traditional, as well as emerging concepts of the genetic and environmental basis of disease to individualize prevention, diagnosis and treatment. Personalized genomics plays a vital, but not exclusive role in this evolving model of personalized medicine. The distinctions between genetic and genomic medicine are more quantitative than qualitative. Personalized genomics builds on principles established by the integration of genetics into medical practice. Principles shared by genetic and genomic aspects of medicine, include the use of variants as markers for diagnosis, prognosis, prevention, as well as targets for treatment, the use of clinically validated variants that may not be functionally characterized, the segregation of these variants in non-Mendelian as well as Mendelian patterns, the role of gene--environment interactions, the dependence on evidence for clinical utility, the critical translational role of behavioral science, and common ethical considerations. During the current period of transition from investigation to practice, consumers should be protected from harms of premature translation of research findings, while encouraging the innovative and cost-effective application of those genomic discoveries that improve personalized medical care. PMID:21706342

  20. Evaluating the utility of personal genomic information.

    PubMed

    Foster, Morris W; Mulvihill, John J; Sharp, Richard R

    2009-08-01

    In evaluating the utility of human genome-wide assays, the answer will differ depending on why the question is asked. For purposes of regulating medical tests, a restrictive sense of clinical utility is used, although it may be possible to have clinical utility without changing patient's outcomes and clinical utility may vary between patients. For purposes of using limited third party or public health resources, cost effectiveness should be evaluated in a societal rather than individual context. However, for other health uses of genomic information a broader sense of overall utility should be used. Behavioral changes and increased individual awareness of health-related choices are relevant metrics for evaluating the personal utility of genomic information, even when traditional clinical benefits are not manifested. In taking account of personal utility, cost effectiveness may be calculated on an individual and societal basis. Overall measures of utility (including both restrictive clinical measures and measures of personal utility) may vary significantly between individuals depending on potential changes in lifestyle, health awareness and behaviors, family dynamics, and personal choice and interest as well as the psychological effects of disease risk perception. That interindividual variation suggests that a more expansive overall measure of utility could be used to identify individuals who are more likely to benefit from personal genomic information as well as those for whom the risks of personal information may be greater than any benefits. PMID:19478683

  1. Mi-DISCOVERER: A bioinformatics tool for the detection of mi-RNA in human genome.

    PubMed

    Arshad, Saadia; Mumtaz, Asia; Ahmad, Freed; Liaquat, Sadia; Nadeem, Shahid; Mehboob, Shahid; Afzal, Muhammad

    2010-01-01

    MicroRNAs (miRNAs) are 22 nucleotides non-coding RNAs that play pivotal regulatory roles in diverse organisms including the humans and are difficult to be identified due to lack of either sequence features or robust algorithms to efficiently identify. Therefore, we made a tool that is Mi-Discoverer for the detection of miRNAs in human genome. The tools used for the development of software are Microsoft Office Access 2003, the JDK version 1.6.0, BioJava version 1.0, and the NetBeans IDE version 6.0. All already made miRNAs softwares were web based; so the advantage of our project was to make a desktop facility to the user for sequence alignment search with already identified miRNAs of human genome present in the database. The user can also insert and update the newly discovered human miRNA in the database. Mi-Discoverer, a bioinformatics tool successfully identifies human miRNAs based on multiple sequence alignment searches. It's a non redundant database containing a large collection of publicly available human miRNAs. PMID:21364831

  2. Genome-wide bioinformatic and molecular analysis of introns in Saccharomyces cerevisiae.

    PubMed Central

    Spingola, M; Grate, L; Haussler, D; Ares, M

    1999-01-01

    Introns have typically been discovered in an ad hoc fashion: introns are found as a gene is characterized for other reasons. As complete eukaryotic genome sequences become available, better methods for predicting RNA processing signals in raw sequence will be necessary in order to discover genes and predict their expression. Here we present a catalog of 228 yeast introns, arrived at through a combination of bioinformatic and molecular analysis. Introns annotated in the Saccharomyces Genome Database (SGD) were evaluated, questionable introns were removed after failing a test for splicing in vivo, and known introns absent from the SGD annotation were added. A novel branchpoint sequence, AAUUAAC, was identified within an annotated intron that lacks a six-of-seven match to the highly conserved branchpoint consensus UACUAAC. Analysis of the database corroborates many conclusions about pre-mRNA substrate requirements for splicing derived from experimental studies, but indicates that splicing in yeast may not be as rigidly determined by splice-site conservation as had previously been thought. Using this database and a molecular technique that directly displays the lariat intron products of spliced transcripts (intron display), we suggest that the current set of 228 introns is still not complete, and that additional intron-containing genes remain to be discovered in yeast. The database can be accessed at http://www.cse.ucsc.edu/research/compbi o/yeast_introns.html. PMID:10024174

  3. Using Informatics-, Bioinformatics- and Genomics-Based Approaches for the Molecular Surveillance and Detection of Biothreat Agents

    NASA Astrophysics Data System (ADS)

    Seto, Donald

    The convergence and wealth of informatics, bioinformatics and genomics methods and associated resources allow a comprehensive and rapid approach for the surveillance and detection of bacterial and viral organisms. Coupled with the continuing race for the fastest, most cost-efficient and highest-quality DNA sequencing technology, that is, "next generation sequencing", the detection of biological threat agents by `cheaper and faster' means is possible. With the application of improved bioinformatic tools for the understanding of these genomes and for parsing unique pathogen genome signatures, along with `state-of-the-art' informatics which include faster computational methods, equipment and databases, it is feasible to apply new algorithms to biothreat agent detection. Two such methods are high-throughput DNA sequencing-based and resequencing microarray-based identification. These are illustrated and validated by two examples involving human adenoviruses, both from real-world test beds.

  4. Forward Individualized Medicine from Personal Genomes to Interactomes

    PubMed Central

    Zhang, Xiang; Kuivenhoven, Jan A.; Groen, Albert K.

    2015-01-01

    When considering the variation in the genome, transcriptome, proteome and metabolome, and their interaction with the environment, every individual can be rightfully considered as a unique biological entity. Individualized medicine promises to take this uniqueness into account to optimize disease treatment and thereby improve health benefits for every patient. The success of individualized medicine relies on a precise understanding of the genotype-phenotype relationship. Although omics technologies advance rapidly, there are several challenges that need to be overcome: Next generation sequencing can efficiently decipher genomic sequences, epigenetic changes, and transcriptomic variation in patients, but it does not automatically indicate how or whether the identified variation will cause pathological changes. This is likely due to the inability to account for (1) the consequences of gene-gene and gene-environment interactions, and (2) (post)transcriptional as well as (post)translational processes that eventually determine the concentration of key metabolites. The technologies to accurately measure changes in these latter layers are still under development, and such measurements in humans are also mainly restricted to blood and circulating cells. Despite these challenges, it is already possible to track dynamic changes in the human interactome in healthy and diseased states by using the integration of multi-omics data. In this review, we evaluate the potential value of current major bioinformatics and systems biology-based approaches, including genome wide association studies, epigenetics, gene regulatory and protein-protein interaction networks, and genome-scale metabolic modeling. Moreover, we address the question whether integrative analysis of personal multi-omics data will help understanding of personal genotype-phenotype relationships. PMID:26696898

  5. Genomes, Populations and Diseases: Ethnic Genomics and Personalized Medicine

    PubMed Central

    Stepanov, V.A.

    2010-01-01

    This review discusses the progress of ethnic genetics, the genetics of common diseases, and the concepts of personalized medicine. We show the relationship between the structure of genetic diversity in human populations and the varying frequencies of Mendelian and multifactor diseases. We also examine the population basis of pharmacogenetics and evaluate the effectiveness of pharmacotherapy, along with a review of new achievements and prospects in personalized genomics. PMID:22649660

  6. The Human Genome Project, and recent advances in personalized genomics.

    PubMed

    Wilson, Brenda J; Nicholls, Stuart G

    2015-01-01

    The language of "personalized medicine" and "personal genomics" has now entered the common lexicon. The idea of personalized medicine is the integration of genomic risk assessment alongside other clinical investigations. Consistent with this approach, testing is delivered by health care professionals who are not medical geneticists, and where results represent risks, as opposed to clinical diagnosis of disease, to be interpreted alongside the entirety of a patient's health and medical data. In this review we consider the evidence concerning the application of such personalized genomics within the context of population screening, and potential implications that arise from this. We highlight two general approaches which illustrate potential uses of genomic information in screening. The first is a narrowly targeted approach in which genetic profiling is linked with standard population-based screening for diseases; the second is a broader targeting of variants associated with multiple single gene disorders, performed opportunistically on patients being investigated for unrelated conditions. In doing so we consider the organization and evaluation of tests and services, the challenge of interpretation with less targeted testing, professional confidence, barriers in practice, and education needs. We conclude by discussing several issues pertinent to health policy, namely: avoiding the conflation of genetics with biological determinism, resisting the "technological imperative", due consideration of the organization of screening services, the need for professional education, as well as informed decision making and public understanding. PMID:25733939

  7. Personal genomes in progress: from the Human Genome Project to the Personal Genome Project

    PubMed Central

    Lunshof (Co-first author), Jeantine E.; Bobe (Co-first author), Jason; Aach, John; Angrist, Misha; V. Thakuria, Joseph; Vorhaus, Daniel B.; R. Hoehe (Co-last author), Margret; Church (Co-last author), George M.

    2010-01-01

    The cost of a diploid human genome sequence has dropped from about $70M to $2000 since 2007- even as the standards for redundancy have increased from 7x to 40x in order to improve call rates. Coupled with the low return on investment for common single-nucleotide polymorphisms, this has caused a significant rise in interest in correlating genome sequences with comprehensive environmental and trait data (GET). The cost of electronic health records, imaging, and microbial, immunological, and behavioral data are also dropping quickly. Sharing such integrated GET datasets and their interpretations with a diversity of researchers and research subjects highlights the need for informed-consent models capable of addressing novel privacy and other issues, as well as for flexible data-sharing resources that make materials and data available with minimum restrictions on use. This article examines the Personal Genome Project's effort to develop a GET database as a public genomics resource broadly accessible to both researchers and research participants, while pursuing the highest standards in research ethics. PMID:20373666

  8. Elucidating ANTs in worms using genomic and bioinformatic tools--biotechnological prospects?

    PubMed

    Hu, Min; Zhong, Weiwei; Campbell, Bronwyn E; Sternberg, Paul W; Pellegrino, Mark W; Gasser, Robin B

    2010-01-01

    Adenine nucleotide translocators (ANTs) belong to the mitochondrial carrier family (MCF) of proteins. ATP production and consumption are tightly linked to ANTs, the kinetics of which have been proposed to play a key regulatory role in mitochondrial oxidative phosphorylation. ANTs are also recognized as a central component of the mitochondrial permeability transition pore associated with apoptosis. Although ANTs have been investigated in a range of vertebrates, including human, mouse and cattle, and invertebrates, such as Drosophila melanogaster (vinegar fly), Saccharomyces cerevisiae (yeast) and Caenorhabditis elegans (free-living nematode), there has been a void of information on these molecules for parasitic nematodes of socio-economic importance. Exploring ANTs in nematodes has the potential lead to a better understanding of their fundamental roles in key biological pathways and might provide an avenue for the identification of targets for the rational design of nematocidal drugs. In the present article, we describe the discovery of an ANT from Haemonchus contortus (one of the most economically important parasitic nematodes of sheep and goats), conduct a comparative analysis of key ANTs and their genes (particularly ant-1.1) in nematodes and other organisms, predict the functional roles utilizing a combined genomic-bioinformatic approach and propose ANTs and associated molecules as possible drug targets, with the potential for biotechnological outcomes. PMID:19770033

  9. Clinical genomics: from a truly personal genome viewpoint.

    PubMed

    Lupski, James R

    2016-06-01

    The path to Clinical Genomics is punctuated by our understanding of what types of DNA structural and sequence variation contribute to disease, the many technical challenges to detect such variation genome-wide, and the initial struggles to interpret personal genome variation in the context of disease. This review describes one perspective of the development of clinical genomics; whereas the experimental challenges, and hurdles to overcoming them, might be deemed readily apparent, the non-technical issues for clinical implementation may be less obvious. Some of these latter challenges, including: (1) informed consent, (2) privacy, (3) what constitutes potentially pathogenic variation contributing to disease, (4) disease penetrance in populations, and (5) the genetic architecture of disease, and the struggles sometimes faced for solutions, are highlighted using illustrative examples. PMID:27221143

  10. The Human Genome Project, and recent advances in personalized genomics

    PubMed Central

    Wilson, Brenda J; Nicholls, Stuart G

    2015-01-01

    The language of “personalized medicine” and “personal genomics” has now entered the common lexicon. The idea of personalized medicine is the integration of genomic risk assessment alongside other clinical investigations. Consistent with this approach, testing is delivered by health care professionals who are not medical geneticists, and where results represent risks, as opposed to clinical diagnosis of disease, to be interpreted alongside the entirety of a patient’s health and medical data. In this review we consider the evidence concerning the application of such personalized genomics within the context of population screening, and potential implications that arise from this. We highlight two general approaches which illustrate potential uses of genomic information in screening. The first is a narrowly targeted approach in which genetic profiling is linked with standard population-based screening for diseases; the second is a broader targeting of variants associated with multiple single gene disorders, performed opportunistically on patients being investigated for unrelated conditions. In doing so we consider the organization and evaluation of tests and services, the challenge of interpretation with less targeted testing, professional confidence, barriers in practice, and education needs. We conclude by discussing several issues pertinent to health policy, namely: avoiding the conflation of genetics with biological determinism, resisting the “technological imperative”, due consideration of the organization of screening services, the need for professional education, as well as informed decision making and public understanding. PMID:25733939

  11. UTGB toolkit for personalized genome browsers

    PubMed Central

    Saito, Taro L.; Yoshimura, Jun; Sasaki, Shin; Ahsan, Budrul; Sasaki, Atsushi; Kuroshu, Reginaldo; Morishita, Shinichi

    2009-01-01

    The advent of high-throughput DNA sequencers has increased the pace of collecting enormous amounts of genomic information, yielding billions of nucleotides on a weekly basis. This advance represents an improvement of two orders of magnitude over traditional Sanger sequencers in terms of the number of nucleotides per unit time, allowing even small groups of researchers to obtain huge volumes of genomic data over fairly short period. Consequently, a pressing need exists for the development of personalized genome browsers for analyzing these immense amounts of locally stored data. The UTGB (University of Tokyo Genome Browser) Toolkit is designed to meet three major requirements for personalization of genome browsers: easy installation of the system with minimum efforts, browsing locally stored data and rapid interactive design of web interfaces tailored to individual needs. The UTGB Toolkit is licensed under an open source license. Availability: The software is freely available at http://utgenome.org/. Contact: moris@cb.k.u-tokyo.ac.jp PMID:19497937

  12. 2010 Translational bioinformatics year in review

    PubMed Central

    Miller, Katharine S

    2011-01-01

    A review of 2010 research in translational bioinformatics provides much to marvel at. We have seen notable advances in personal genomics, pharmacogenetics, and sequencing. At the same time, the infrastructure for the field has burgeoned. While acknowledging that, according to researchers, the members of this field tend to be overly optimistic, the authors predict a bright future. PMID:21672905

  13. Optimal Drug Prediction from Personal Genomics Profiles

    PubMed Central

    Sheng, Jianting; Li, Fuhai; Wong, Stephen T.C.

    2015-01-01

    Cancer patients often show heterogeneous drug responses such that only a small subset of patients is sensitive to a given anti-cancer drug. With the availability of large-scale genomic profiling via next generation sequencing (NGS), it is now economically feasible to profile the whole transcriptome and genome of individual patients in order to identify their unique genetic mutations and differentially expressed genes, which are believed to be responsible for heterogeneous drug responses. Although subtyping analysis has identified patient subgroups sharing common biomarkers, there is no effective method to predict the drug response of individual patients precisely and reliably. Herein, we propose a novel computational algorithm to predict the drug response of individual patients based on personal genomic profiles, as well as pharmacogenomic and drug sensitivity data. Specifically, more than 600 cancer cell lines (viewed as individual patients) across over 50 types of cancers and their responses to 75 drugs were obtained from the Genomics of Drug Sensitivity in Cancer (GDSC) database. The drug-specific sensitivity signatures were determined from the changes in genomic profiles of individual cell lines in response to a specific drug. The optimal drugs for individual cell lines were predicted by integrating the votes from other cell lines. The experimental results show that the proposed drug prediction algorithm can be used to improve greatly the reliability of finding optimal drugs for individual patients and will thus form a key component in the precision medicine infrastructure for oncology care. PMID:25781964

  14. MSeqDR: A Centralized Knowledge Repository and Bioinformatics Web Resource to Facilitate Genomic Investigations in Mitochondrial Disease.

    PubMed

    Shen, Lishuang; Diroma, Maria Angela; Gonzalez, Michael; Navarro-Gomez, Daniel; Leipzig, Jeremy; Lott, Marie T; van Oven, Mannis; Wallace, Douglas C; Muraresku, Colleen Clarke; Zolkipli-Cunningham, Zarazuela; Chinnery, Patrick F; Attimonelli, Marcella; Zuchner, Stephan; Falk, Marni J; Gai, Xiaowu

    2016-06-01

    MSeqDR is the Mitochondrial Disease Sequence Data Resource, a centralized and comprehensive genome and phenome bioinformatics resource built by the mitochondrial disease community to facilitate clinical diagnosis and research investigations of individual patient phenotypes, genomes, genes, and variants. A central Web portal (https://mseqdr.org) integrates community knowledge from expert-curated databases with genomic and phenotype data shared by clinicians and researchers. MSeqDR also functions as a centralized application server for Web-based tools to analyze data across both mitochondrial and nuclear DNA, including investigator-driven whole exome or genome dataset analyses through MSeqDR-Genesis. MSeqDR-GBrowse genome browser supports interactive genomic data exploration and visualization with custom tracks relevant to mtDNA variation and mitochondrial disease. MSeqDR-LSDB is a locus-specific database that currently manages 178 mitochondrial diseases, 1,363 genes associated with mitochondrial biology or disease, and 3,711 pathogenic variants in those genes. MSeqDR Disease Portal allows hierarchical tree-style disease exploration to evaluate their unique descriptions, phenotypes, and causative variants. Automated genomic data submission tools are provided that capture ClinVar compliant variant annotations. PhenoTips will be used for phenotypic data submission on deidentified patients using human phenotype ontology terminology. The development of a dynamic informed patient consent process to guide data access is underway to realize the full potential of these resources. PMID:26919060

  15. Ethical Considerations Regarding Classroom Use of Personal Genomic Information

    PubMed Central

    Parker, Lisa S.; Grubs, Robin

    2014-01-01

    Rapidly decreasing costs of genetic technologies—especially next-generation sequencing—and intensifying need for a clinical workforce trained in genomic medicine have increased interest in having students use personal genomic information to motivate and enhance genomics education. Numerous ethical issues attend classroom/pedagogical use of students’ personal genomic information, including their informed decision to participate, pressures to participate, privacy concerns, and psychosocial sequelae of learning genomic information. This paper addresses these issues, advocates explicit discussion of these issues to cultivate students’ ethical reasoning skills, suggests ways to mitigate potential harms, and recommends collection of ethically relevant data regarding pedagogical use of personal genomic information. PMID:25574277

  16. Genomic expression profiling and bioinformatics analysis on diabetic nephrology with ginsenoside Rg3

    PubMed Central

    Wang, Juan; Cui, Chunli; Fu, Li; Xiao, Zili; Xie, Nanzi; Liu, Yang; Yu, Lu; Wang, Haifeng; Luo, Bangzhen

    2016-01-01

    Diabetic nephropathy (DN), a common diabetes-related complication, is the leading cause of progressive chronic kidney disease (CKD) and end-stage renal disease. Despite the rapid development in the treatment of DN, currently available therapies used in early DN cannot prevent progressive CKD. The exact pathogenic mechanisms and the molecular events underlying DN development remain unclear. Ginsenoside Rg3 is a herbal medicine with numerous pharmacological effects. To gain a greater understanding of the molecular mechanism and signaling pathway underlying the effect of ginsenoside Rg3 in DN therapy, an RNA sequencing approach was performed to screen differential gene expression in a rat model of DN treated with ginsenoside Rg3. A combined bioinformatics analysis was then conducted to obtain insights into the underlying molecular mechanisms of the disease development, in order to identify potential novel targets for the treatment of DN. Six Sprague-Dawley male rats were randomly divided into 3 groups: Normal control group, DN group and ginsenoside-Rg3 treatment group, with two rats in each group. RNA sequencing was adopted for transcriptome profiling of cells from the renal cortex of DN rat model. Differentially expressed genes were screened out. Cluster analysis, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis were used to analyze the differentially expressed genes. In total, 78 differentially expressed genes in the DN control group were identified when compared with the normal control group, of which 52 genes were upregulated and 26 genes were downregulated. Differential expression of 43 genes was observed in the ginsenoside-Rg3 treatment group when compared with the DN control group, consisting of 10 upregulated genes and 33 downregulated genes. Notably, 21 that were downregulated in the DN control group compared with the control were then shown to be upregulated in the ginsenoside-Rg3 treatment group compared with the DN

  17. Breast Cancer in the Personal Genomics Era

    PubMed Central

    Ellsworth, Rachel E.; Decewicz, David J.; Shriver, Craig D.; Ellsworth, Darrell L.

    2010-01-01

    Breast cancer is a heterogeneous disease with a complex etiology that develops from different cellular lineages, progresses along multiple molecular pathways, and demonstrates wide variability in response to treatment. The “standard of care” approach to breast cancer treatment in which all patients receive similar interventions is rapidly being replaced by personalized medicine, based on molecular characteristics of individual patients. Both inherited and somatic genomic variation is providing useful information for customizing treatment regimens for breast cancer to maximize efficacy and minimize adverse side effects. In this article, we review (1) hereditary breast cancer and current use of inherited susceptibility genes in patient management; (2) the potential of newly-identified breast cancer-susceptibility variants for improving risk assessment; (3) advantages and disadvantages of direct-to-consumer testing; (4) molecular characterization of sporadic breast cancer through immunohistochemistry and gene expression profiling and opportunities for personalized prognostics; and (5) pharmacogenomic influences on the effectiveness of current breast cancer treatments. Molecular genomics has the potential to revolutionize clinical practice and improve the lives of women with breast cancer. PMID:21037853

  18. Putative lipoproteins identified by bioinformatic genome analysis of Leifsonia xyli ssp. xyli, the causative agent of sugarcane ratoon stunting disease.

    PubMed

    Sutcliffe, Iain C; Hutchings, Matthew I

    2007-01-01

    SUMMARY Leifsonia xyli ssp. xyli is the causative agent of ratoon stunting disease, a major cause of economic loss in sugarcane crops. Understanding of the biology of this pathogen has been hampered by its fastidious growth characteristics in vitro. However, the recent release of a genome sequence for this organism has allowed significant novel insights. Further to this, we have performed a bioinformatic analysis of the lipoproteins encoded in the L. xyli genome. These analyses suggest that lipoproteins represent c. 2.0% of the L. xyli predicted proteome. Functional analyses suggest that lipoproteins make an important contribution to the physiology of the pathogen and may influence its ability to cause disease in planta. PMID:20507484

  19. Personalized genomic disease risk of volunteers

    PubMed Central

    Gonzalez-Garay, Manuel L.; McGuire, Amy L.; Pereira, Stacey; Caskey, C. Thomas

    2013-01-01

    Next-generation sequencing (NGS) is commonly used for researching the causes of genetic disorders. However, its usefulness in clinical practice for medical diagnosis is in early development. In this report, we demonstrate the value of NGS for genetic risk assessment and evaluate the limitations and barriers for the adoption of this technology into medical practice. We performed whole exome sequencing (WES) on 81 volunteers, and for each volunteer, we requested personal medical histories, constructed a three-generation pedigree, and required their participation in a comprehensive educational program. We limited our clinical reporting to disease risks based on only rare damaging mutations and known pathogenic variations in genes previously reported to be associated with human disorders. We identified 271 recessive risk alleles (214 genes), 126 dominant risk alleles (101 genes), and 3 X-recessive risk alleles (3 genes). We linked personal disease histories with causative disease genes in 18 volunteers. Furthermore, by incorporating family histories into our genetic analyses, we identified an additional five heritable diseases. Traditional genetic counseling and disease education were provided in verbal and written reports to all volunteers. Our report demonstrates that when genome results are carefully interpreted and integrated with an individual’s medical records and pedigree data, NGS is a valuable diagnostic tool for genetic disease risk. PMID:24082139

  20. Genomic Discoveries and Personalized Medicine in Neurological Diseases

    PubMed Central

    Zhang, Li; Hong, Huixiao

    2015-01-01

    In the past decades, we have witnessed dramatic changes in clinical diagnoses and treatments due to the revolutions of genomics and personalized medicine. Undoubtedly we also met many challenges when we use those advanced technologies in drug discovery and development. In this review, we describe when genomic information is applied in personal healthcare in general. We illustrate some case examples of genomic discoveries and promising personalized medicine applications in the area of neurological disease particular. Available data suggest that individual genomics can be applied to better treat patients in the near future. PMID:26690205

  1. Integrated Bioinformatics, Environmental Epidemiologic and Genomic Approaches to Identify Environmental and Molecular Links between Endometriosis and Breast Cancer

    PubMed Central

    Roy, Deodutta; Morgan, Marisa; Yoo, Changwon; Deoraj, Alok; Roy, Sandhya; Yadav, Vijay Kumar; Garoub, Mohannad; Assaggaf, Hamza; Doke, Mayur

    2015-01-01

    We present a combined environmental epidemiologic, genomic, and bioinformatics approach to identify: exposure of environmental chemicals with estrogenic activity; epidemiologic association between endocrine disrupting chemical (EDC) and health effects, such as, breast cancer or endometriosis; and gene-EDC interactions and disease associations. Human exposure measurement and modeling confirmed estrogenic activity of three selected class of environmental chemicals, polychlorinated biphenyls (PCBs), bisphenols (BPs), and phthalates. Meta-analysis showed that PCBs exposure, not Bisphenol A (BPA) and phthalates, increased the summary odds ratio for breast cancer and endometriosis. Bioinformatics analysis of gene-EDC interactions and disease associations identified several hundred genes that were altered by exposure to PCBs, phthalate or BPA. EDCs-modified genes in breast neoplasms and endometriosis are part of steroid hormone signaling and inflammation pathways. All three EDCs–PCB 153, phthalates, and BPA influenced five common genes—CYP19A1, EGFR, ESR2, FOS, and IGF1—in breast cancer as well as in endometriosis. These genes are environmentally and estrogen responsive, altered in human breast and uterine tumors and endometriosis lesions, and part of Mitogen Activated Protein Kinase (MAPK) signaling pathways in cancer. Our findings suggest that breast cancer and endometriosis share some common environmental and molecular risk factors. PMID:26512648

  2. Personalized medicine, genomics, and pharmacogenomics: a primer for nurses.

    PubMed

    Blix, Andrew

    2014-08-01

    Personalized medicine is the study of patients' unique environmental influences as well as the totality of their genetic code-their genome-to tailor personalized risk assessments, diagnoses, prognoses, and treatments. The study of how patients' genomes affect responses to medications, or pharmacogenomics, is a related field. Personalized medicine and genomics are particularly relevant in oncology because of the genetic basis of cancer. Nurses need to understand related issues such as the role of genetic and genomic counseling, the ethical and legal questions surrounding genomics, and the growing direct-to-consumer genomics industry. As genomics research is incorporated into health care, nurses need to understand the technology to provide advocacy and education for patients and their families. PMID:25095297

  3. New bioinformatic tool for quick identification of functionally relevant endogenous retroviral inserts in human genome

    PubMed Central

    Garazha, Andrew; Ivanova, Alena; Suntsova, Maria; Malakhova, Galina; Roumiantsev, Sergey; Zhavoronkov, Alex; Buzdin, Anton

    2015-01-01

    Abstract Endogenous retroviruses (ERVs) and LTR retrotransposons (LRs) occupy ∼8% of human genome. Deep sequencing technologies provide clues to understanding of functional relevance of individual ERVs/LRs by enabling direct identification of transcription factor binding sites (TFBS) and other landmarks of functional genomic elements. Here, we performed the genome-wide identification of human ERVs/LRs containing TFBS according to the ENCODE project. We created the first interactive ERV/LRs database that groups the individual inserts according to their familial nomenclature, number of mapped TFBS and divergence from their consensus sequence. Information on any particular element can be easily extracted by the user. We also created a genome browser tool, which enables quick mapping of any ERV/LR insert according to genomic coordinates, known human genes and TFBS. These tools can be used to easily explore functionally relevant individual ERV/LRs, and for studying their impact on the regulation of human genes. Overall, we identified ∼110,000 ERV/LR genomic elements having TFBS. We propose a hypothesis of “domestication” of ERV/LR TFBS by the genome milieu including subsequent stages of initial epigenetic repression, partial functional release, and further mutation-driven reshaping of TFBS in tight coevolution with the enclosing genomic loci. PMID:25853282

  4. A Novel Bioinformatics Method for Efficient Knowledge Discovery by BLSOM from Big Genomic Sequence Data

    PubMed Central

    Iwasaki, Yuki; Kanaya, Shigehiko; Zhao, Yue; Ikemura, Toshimichi

    2014-01-01

    With remarkable increase of genomic sequence data of a wide range of species, novel tools are needed for comprehensive analyses of the big sequence data. Self-Organizing Map (SOM) is an effective tool for clustering and visualizing high-dimensional data such as oligonucleotide composition on one map. By modifying the conventional SOM, we have previously developed Batch-Learning SOM (BLSOM), which allows classification of sequence fragments according to species, solely depending on the oligonucleotide composition. In the present study, we introduce the oligonucleotide BLSOM used for characterization of vertebrate genome sequences. We first analyzed pentanucleotide compositions in 100 kb sequences derived from a wide range of vertebrate genomes and then the compositions in the human and mouse genomes in order to investigate an efficient method for detecting differences between the closely related genomes. BLSOM can recognize the species-specific key combination of oligonucleotide frequencies in each genome, which is called a “genome signature,” and the specific regions specifically enriched in transcription-factor-binding sequences. Because the classification and visualization power is very high, BLSOM is an efficient powerful tool for extracting a wide range of information from massive amounts of genomic sequences (i.e., big sequence data). PMID:24804244

  5. New bioinformatic tool for quick identification of functionally relevant endogenous retroviral inserts in human genome.

    PubMed

    Garazha, Andrew; Ivanova, Alena; Suntsova, Maria; Malakhova, Galina; Roumiantsev, Sergey; Zhavoronkov, Alex; Buzdin, Anton

    2015-01-01

    Endogenous retroviruses (ERVs) and LTR retrotransposons (LRs) occupy ∼8% of human genome. Deep sequencing technologies provide clues to understanding of functional relevance of individual ERVs/LRs by enabling direct identification of transcription factor binding sites (TFBS) and other landmarks of functional genomic elements. Here, we performed the genome-wide identification of human ERVs/LRs containing TFBS according to the ENCODE project. We created the first interactive ERV/LRs database that groups the individual inserts according to their familial nomenclature, number of mapped TFBS and divergence from their consensus sequence. Information on any particular element can be easily extracted by the user. We also created a genome browser tool, which enables quick mapping of any ERV/LR insert according to genomic coordinates, known human genes and TFBS. These tools can be used to easily explore functionally relevant individual ERV/LRs, and for studying their impact on the regulation of human genes. Overall, we identified ∼110,000 ERV/LR genomic elements having TFBS. We propose a hypothesis of "domestication" of ERV/LR TFBS by the genome milieu including subsequent stages of initial epigenetic repression, partial functional release, and further mutation-driven reshaping of TFBS in tight coevolution with the enclosing genomic loci. PMID:25853282

  6. WordSeeker: concurrent bioinformatics software for discovering genome-wide patterns and word-based genomic signatures

    PubMed Central

    2010-01-01

    Background An important focus of genomic science is the discovery and characterization of all functional elements within genomes. In silico methods are used in genome studies to discover putative regulatory genomic elements (called words or motifs). Although a number of methods have been developed for motif discovery, most of them lack the scalability needed to analyze large genomic data sets. Methods This manuscript presents WordSeeker, an enumerative motif discovery toolkit that utilizes multi-core and distributed computational platforms to enable scalable analysis of genomic data. A controller task coordinates activities of worker nodes, each of which (1) enumerates a subset of the DNA word space and (2) scores words with a distributed Markov chain model. Results A comprehensive suite of performance tests was conducted to demonstrate the performance, speedup and efficiency of WordSeeker. The scalability of the toolkit enabled the analysis of the entire genome of Arabidopsis thaliana; the results of the analysis were integrated into The Arabidopsis Gene Regulatory Information Server (AGRIS). A public version of WordSeeker was deployed on the Glenn cluster at the Ohio Supercomputer Center. Conclusion WordSeeker effectively utilizes concurrent computing platforms to enable the identification of putative functional elements in genomic data sets. This capability facilitates the analysis of the large quantity of sequenced genomic data. PMID:21210985

  7. Personal utility in genomic testing: is there such a thing?

    PubMed

    Bunnik, Eline M; Janssens, A Cecile J W; Schermer, Maartje H N

    2015-04-01

    In ethical and regulatory discussions on new applications of genomic testing technologies, the notion of 'personal utility' has been mentioned repeatedly. It has been used to justify direct access to commercially offered genomic testing or feedback of individual research results to research or biobank participants. Sometimes research participants or consumers claim a right to genomic information with an appeal to personal utility. As of yet, no systematic account of the umbrella notion of personal utility has been given. This paper offers a definition of personal utility that places it in the middle of the spectrum between clinical utility and personal perceptions of utility, and that acknowledges its normative charge. The paper discusses two perspectives on personal utility, the healthcare perspective and the consumer perspective, and argues that these are too narrow and too wide, respectively. Instead, it proposes a normative definition of personal utility that postulates information and potential use as necessary conditions of utility. This definition entails that perceived utility does not equal personal utility, and that expert judgment may be necessary to help determine whether a genomic test can have personal utility for someone. Two examples of genomic tests are presented to illustrate the discrepancies between perceived utility and our proposed definition of personal utility. The paper concludes that while there is room for the notion of personal utility in the ethical evaluation and regulation of genomic tests, the justificatory role of personal utility is not unlimited. For in the absence of clinical validity and reasonable potential use of information, there is no personal utility. PMID:24872596

  8. Personal Genomic Information Management and Personalized Medicine: Challenges, Current Solutions, and Roles of HIM Professionals

    PubMed Central

    Alzu'bi, Amal; Zhou, Leming; Watzlaf, Valerie

    2014-01-01

    In recent years, the term personalized medicine has received more and more attention in the field of healthcare. The increasing use of this term is closely related to the astonishing advancement in DNA sequencing technologies and other high-throughput biotechnologies. A large amount of personal genomic data can be generated by these technologies in a short time. Consequently, the needs for managing, analyzing, and interpreting these personal genomic data to facilitate personalized care are escalated. In this article, we discuss the challenges for implementing genomics-based personalized medicine in healthcare, current solutions to these challenges, and the roles of health information management (HIM) professionals in genomics-based personalized medicine. PMID:24808804

  9. A bioinformatics workflow for detecting signatures of selection in genomic data.

    PubMed

    Cadzow, Murray; Boocock, James; Nguyen, Hoang T; Wilcox, Phillip; Merriman, Tony R; Black, Michael A

    2014-01-01

    The detection of "signatures of selection" is now possible on a genome-wide scale in many plant and animal species, and can be performed in a population-specific manner due to the wealth of per-population genome-wide genotype data that is available. With genomic regions that exhibit evidence of having been under selection shown to also be enriched for genes associated with biologically important traits, detection of evidence of selective pressure is emerging as an additional approach for identifying novel gene-trait associations. While high-density genotype data is now relatively easy to obtain, for many researchers it is not immediately obvious how to go about identifying signatures of selection in these data sets. Here we describe a basic workflow, constructed from open source tools, for detecting and examining evidence of selection in genomic data. Code to install and implement the pipeline components, and instructions to run a basic analysis using the workflow described here, can be downloaded from our public GitHub repository: http://www.github.com/smilefreak/selectionTools/ PMID:25206364

  10. A bioinformatics workflow for detecting signatures of selection in genomic data

    PubMed Central

    Cadzow, Murray; Boocock, James; Nguyen, Hoang T.; Wilcox, Phillip; Merriman, Tony R.; Black, Michael A.

    2014-01-01

    The detection of “signatures of selection” is now possible on a genome-wide scale in many plant and animal species, and can be performed in a population-specific manner due to the wealth of per-population genome-wide genotype data that is available. With genomic regions that exhibit evidence of having been under selection shown to also be enriched for genes associated with biologically important traits, detection of evidence of selective pressure is emerging as an additional approach for identifying novel gene-trait associations. While high-density genotype data is now relatively easy to obtain, for many researchers it is not immediately obvious how to go about identifying signatures of selection in these data sets. Here we describe a basic workflow, constructed from open source tools, for detecting and examining evidence of selection in genomic data. Code to install and implement the pipeline components, and instructions to run a basic analysis using the workflow described here, can be downloaded from our public GitHub repository: http://www.github.com/smilefreak/selectionTools/ PMID:25206364

  11. Bioinformatic genome comparisons for taxonomic and phylogenic assignments using Aeromonas as a test case

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Prokaryotic taxonomy is the underpinning of microbiology, providing a framework for the proper identification and naming of organisms. The 'gold standard' of bacterial species delineation is the overall genome similarity as determined by DNA-DNA hybridization (DDH), a technically rigorous yet someti...

  12. Overview of personalized medicine in the disease genomic era.

    PubMed

    Hong, Kyung-Won; Oh, Bermseok

    2010-10-01

    Sir William Osler (1849-1919) recognized that "variability is the law of life, and as no two faces are the same, so no two bodies are alike, and no two individuals react alike and behave alike under the abnormal conditions we know as disease". Accordingly, the traditional methods of medicine are not always best for all patients. Over the last decade, the study of genomes and their derivatives (RNA, protein and metabolite) has rapidly advanced to the point that genomic research now serves as the basis for many medical decisions and public health initiatives. Genomic tools such as sequence variation, transcription and, more recently, personal genome sequencing enable the precise prediction and treatment of disease. At present, DNA-based risk assessment for common complex diseases, application of molecular signatures for cancer diagnosis and prognosis, genome-guided therapy, and dose selection of therapeutic drugs are the important issues in personalized medicine. In order to make personalized medicine effective, these genomic techniques must be standardized and integrated into health systems and clinical workflow. In addition, full application of personalized or genomic medicine requires dramatic changes in regulatory and reimbursement policies as well as legislative protection related to privacy. This review aims to provide a general overview of these topics in the field of personalized medicine. PMID:21034525

  13. Atlas2 Cloud: a framework for personal genome analysis in the cloud

    PubMed Central

    2012-01-01

    Background Until recently, sequencing has primarily been carried out in large genome centers which have invested heavily in developing the computational infrastructure that enables genomic sequence analysis. The recent advancements in next generation sequencing (NGS) have led to a wide dissemination of sequencing technologies and data, to highly diverse research groups. It is expected that clinical sequencing will become part of diagnostic routines shortly. However, limited accessibility to computational infrastructure and high quality bioinformatic tools, and the demand for personnel skilled in data analysis and interpretation remains a serious bottleneck. To this end, the cloud computing and Software-as-a-Service (SaaS) technologies can help address these issues. Results We successfully enabled the Atlas2 Cloud pipeline for personal genome analysis on two different cloud service platforms: a community cloud via the Genboree Workbench, and a commercial cloud via the Amazon Web Services using Software-as-a-Service model. We report a case study of personal genome analysis using our Atlas2 Genboree pipeline. We also outline a detailed cost structure for running Atlas2 Amazon on whole exome capture data, providing cost projections in terms of storage, compute and I/O when running Atlas2 Amazon on a large data set. Conclusions We find that providing a web interface and an optimized pipeline clearly facilitates usage of cloud computing for personal genome analysis, but for it to be routinely used for large scale projects there needs to be a paradigm shift in the way we develop tools, in standard operating procedures, and in funding mechanisms. PMID:23134663

  14. The personal genome browser: visualizing functions of genetic variants

    PubMed Central

    Juan, Liran; Teng, Mingxiang; Zang, Tianyi; Hao, Yafeng; Wang, Zhenxing; Yan, Chengwu; Liu, Yongzhuang; Li, Jie; Zhang, Tianjiao; Wang, Yadong

    2014-01-01

    Advances in high-throughput sequencing technologies have brought us into the individual genome era. Projects such as the 1000 Genomes Project have led the individual genome sequencing to become more and more popular. How to visualize, analyse and annotate individual genomes with knowledge bases to support genome studies and personalized healthcare is still a big challenge. The Personal Genome Browser (PGB) is developed to provide comprehensive functional annotation and visualization for individual genomes based on the genetic–molecular–phenotypic model. Investigators can easily view individual genetic variants, such as single nucleotide variants (SNVs), INDELs and structural variations (SVs), as well as genomic features and phenotypes associated to the individual genetic variants. The PGB especially highlights potential functional variants using the PGB built-in method or SIFT/PolyPhen2 scores. Moreover, the functional risks of genes could be evaluated by scanning individual genetic variants on the whole genome, a chromosome, or a cytoband based on functional implications of the variants. Investigators can then navigate to high risk genes on the scanned individual genome. The PGB accepts Variant Call Format (VCF) and Genetic Variation Format (GVF) files as the input. The functional annotation of input individual genome variants can be visualized in real time by well-defined symbols and shapes. The PGB is available at http://www.pgbrowser.org/. PMID:24799434

  15. The personal genome browser: visualizing functions of genetic variants.

    PubMed

    Juan, Liran; Teng, Mingxiang; Zang, Tianyi; Hao, Yafeng; Wang, Zhenxing; Yan, Chengwu; Liu, Yongzhuang; Li, Jie; Zhang, Tianjiao; Wang, Yadong

    2014-07-01

    Advances in high-throughput sequencing technologies have brought us into the individual genome era. Projects such as the 1000 Genomes Project have led the individual genome sequencing to become more and more popular. How to visualize, analyse and annotate individual genomes with knowledge bases to support genome studies and personalized healthcare is still a big challenge. The Personal Genome Browser (PGB) is developed to provide comprehensive functional annotation and visualization for individual genomes based on the genetic-molecular-phenotypic model. Investigators can easily view individual genetic variants, such as single nucleotide variants (SNVs), INDELs and structural variations (SVs), as well as genomic features and phenotypes associated to the individual genetic variants. The PGB especially highlights potential functional variants using the PGB built-in method or SIFT/PolyPhen2 scores. Moreover, the functional risks of genes could be evaluated by scanning individual genetic variants on the whole genome, a chromosome, or a cytoband based on functional implications of the variants. Investigators can then navigate to high risk genes on the scanned individual genome. The PGB accepts Variant Call Format (VCF) and Genetic Variation Format (GVF) files as the input. The functional annotation of input individual genome variants can be visualized in real time by well-defined symbols and shapes. The PGB is available at http://www.pgbrowser.org/. PMID:24799434

  16. Teaching Synthetic Biology, Bioinformatics and Engineering to Undergraduates: The Interdisciplinary Build-a-Genome Course

    PubMed Central

    Dymond, Jessica S.; Scheifele, Lisa Z.; Richardson, Sarah; Lee, Pablo; Chandrasegaran, Srinivasan; Bader, Joel S.; Boeke, Jef D.

    2009-01-01

    A major challenge in undergraduate life science curricula is the continual evaluation and development of courses that reflect the constantly shifting face of contemporary biological research. Synthetic biology offers an excellent framework within which students may participate in cutting-edge interdisciplinary research and is therefore an attractive addition to the undergraduate biology curriculum. This new discipline offers the promise of a deeper understanding of gene function, gene order, and chromosome structure through the de novo synthesis of genetic information, much as synthetic approaches informed organic chemistry. While considerable progress has been achieved in the synthesis of entire viral and prokaryotic genomes, fabrication of eukaryotic genomes requires synthesis on a scale that is orders of magnitude higher. These high-throughput but labor-intensive projects serve as an ideal way to introduce undergraduates to hands-on synthetic biology research. We are pursuing synthesis of Saccharomyces cerevisiae chromosomes in an undergraduate laboratory setting, the Build-a-Genome course, thereby exposing students to the engineering of biology on a genomewide scale while focusing on a limited region of the genome. A synthetic chromosome III sequence was designed, ordered from commercial suppliers in the form of oligonucleotides, and subsequently assembled by students into ∼750-bp fragments. Once trained in assembly of such DNA “building blocks” by PCR, the students accomplish high-yield gene synthesis, becoming not only technically proficient but also constructively critical and capable of adapting their protocols as independent researchers. Regular “lab meeting” sessions help prepare them for future roles in laboratory science. PMID:19015540

  17. A bioinformatic analysis of ribonucleotide reductase genes in phage genomes and metagenomes

    PubMed Central

    2013-01-01

    Background Ribonucleotide reductase (RNR), the enzyme responsible for the formation of deoxyribonucleotides from ribonucleotides, is found in all domains of life and many viral genomes. RNRs are also amongst the most abundant genes identified in environmental metagenomes. This study focused on understanding the distribution, diversity, and evolution of RNRs in phages (viruses that infect bacteria). Hidden Markov Model profiles were used to analyze the proteins encoded by 685 completely sequenced double-stranded DNA phages and 22 environmental viral metagenomes to identify RNR homologs in cultured phages and uncultured viral communities, respectively. Results RNRs were identified in 128 phage genomes, nearly tripling the number of phages known to encode RNRs. Class I RNR was the most common RNR class observed in phages (70%), followed by class II (29%) and class III (28%). Twenty-eight percent of the phages contained genes belonging to multiple RNR classes. RNR class distribution varied according to phage type, isolation environment, and the host’s ability to utilize oxygen. The majority of the phages containing RNRs are Myoviridae (65%), followed by Siphoviridae (30%) and Podoviridae (3%). The phylogeny and genomic organization of phage and host RNRs reveal several distinct evolutionary scenarios involving horizontal gene transfer, co-evolution, and differential selection pressure. Several putative split RNR genes interrupted by self-splicing introns or inteins were identified, providing further evidence for the role of frequent genetic exchange. Finally, viral metagenomic data indicate that RNRs are prevalent and highly dynamic in uncultured viral communities, necessitating future research to determine the environmental conditions under which RNRs provide a selective advantage. Conclusions This comprehensive study describes the distribution, diversity, and evolution of RNRs in phage genomes and environmental viral metagenomes. The distinct distributions of

  18. Genome mining of mycosporine-like amino acid (MAA) synthesizing and non-synthesizing cyanobacteria: A bioinformatics study.

    PubMed

    Singh, Shailendra P; Klisch, Manfred; Sinha, Rajeshwar P; Häder, Donat-P

    2010-02-01

    Mycosporine-like amino acids (MAAs) are a family of more than 20 compounds having absorption maxima between 310 and 362 nm. These compounds are well known for their UV-absorbing/screening role in various organisms and seem to have evolutionary significance. In the present investigation we tested four cyanobacteria, e.g., Anabaena variabilis PCC 7937, Anabaena sp. PCC 7120, Synechocystis sp. PCC 6803 and Synechococcus sp. PCC 6301, for their ability to synthesize MAA and conducted genomic and phylogenetic analysis to identify the possible set of genes that might be involved in the biosynthesis of these compounds. Out of the four investigated species, only A. variabilis PCC 7937 was able to synthesize MAA. Genome mining identified a combination of genes, YP_324358 (predicted DHQ synthase) and YP_324357 (O-methyltransferase), which were present only in A. variabilis PCC 7937 and missing in the other studied cyanobacteria. Phylogenetic analysis revealed that these two genes are transferred from a cyanobacterial donor to dinoflagellates and finally to metazoa by a lateral gene transfer event. All other cyanobacteria, which have these two genes, also had another copy of the DHQ synthase gene. The predicted protein structure for YP_324358 also suggested that this product is different from the chemically characterized DHQ synthase of Aspergillus nidulans contrary to the YP_324879, which was predicted to be similar to the DHQ synthase. The present study provides a first insight into the genes of cyanobacteria involved in MAA biosynthesis and thus widens the field of research for molecular, bioinformatics and phylogenetic analysis of these evolutionary and industrially important compounds. Based on the results we propose that YP_324358 and YP_324357 gene products are involved in the biosynthesis of the common core (deoxygadusol) of all MAAs. PMID:19879348

  19. Challenges of web-based personal genomic data sharing.

    PubMed

    Shabani, Mahsa; Borry, Pascal

    2015-01-01

    In order to study the relationship between genes and diseases, the increasing availability and sharing of phenotypic and genotypic data have been promoted as an imperative within the scientific community. In parallel with data sharing practices by clinicians and researchers, recent initiatives have been observed in which individuals are sharing personal genomic data. The involvement of individuals in such initiatives is facilitated by the increased accessibility of personal genomic data, offered by private test providers along with availability of online networks. Personal webpages and on-line data sharing platforms such as Consent to Research (Portable Legal Consent), Free the Data, and Genomes Unzipped are being utilized to host and share genotypes, electronic health records and family history uploaded by individuals. Although personal genomic data sharing initiatives vary in nature, the emphasis on the individuals' control on their data in order to benefit research and ultimately health care has seen as a key theme across these initiatives. In line with the growing practice of personal genomic data sharing, this paper aims to shed light on the potential challenges surrounding these initiatives. As in the course of these initiatives individuals are solicited to individually balance the risks and benefits of sharing their genomic data, their awareness of the implications of personal genomic data sharing for themselves and their family members is a necessity. Furthermore, given the sensitivity of genomic data and the controversies around their complete de-identifiability, potential privacy risks and harms originating from unintended uses of data have to be taken into consideration. PMID:26085313

  20. Genomic and Bioinformatics Analysis of HAdV-4, a Human Adenovirus Causing Acute Respiratory Disease: Implications for Gene Therapy and Vaccine Vector Development

    PubMed Central

    Purkayastha, Anjan; Ditty, Susan E.; Su, Jing; McGraw, John; Hadfield, Ted L.; Tibbetts, Clark; Seto, Donald

    2005-01-01

    Human adenovirus serotype 4 (HAdV-4) is a reemerging viral pathogenic agent implicated in epidemic outbreaks of acute respiratory disease (ARD). This report presents a genomic and bioinformatics analysis of the prototype 35,990-nucleotide genome (GenBank accession no. AY594253). Intriguingly, the genome analysis suggests a closer phylogenetic relationship with the chimpanzee adenoviruses (simian adenoviruses) rather than with other human adenoviruses, suggesting a recent origin of HAdV-4, and therefore species E, through a zoonotic event from chimpanzees to humans. Bioinformatics analysis also suggests a pre-zoonotic recombination event, as well, between species B-like and species C-like simian adenoviruses. These observations may have implications for the current interest in using chimpanzee adenoviruses in the development of vectors for human gene therapy and for DNA-based vaccines. Also, the reemergence, surveillance, and treatment of HAdV-4 as an ARD pathogen is an opportunity to demonstrate the use of genome determination as a tool for viral infectious disease characterization and epidemic outbreak surveillance: for example, rapid and accurate low-pass sequencing and analysis of the genome. In particular, this approach allows the rapid identification and development of unique probes for the differentiation of family, species, serotype, and strain (e.g., pathogen genome signatures) for monitoring epidemic outbreaks of ARD. PMID:15681456

  1. Genomic and bioinformatics analysis of HAdV-4, a human adenovirus causing acute respiratory disease: implications for gene therapy and vaccine vector development.

    PubMed

    Purkayastha, Anjan; Ditty, Susan E; Su, Jing; McGraw, John; Hadfield, Ted L; Tibbetts, Clark; Seto, Donald

    2005-02-01

    Human adenovirus serotype 4 (HAdV-4) is a reemerging viral pathogenic agent implicated in epidemic outbreaks of acute respiratory disease (ARD). This report presents a genomic and bioinformatics analysis of the prototype 35,990-nucleotide genome (GenBank accession no. AY594253). Intriguingly, the genome analysis suggests a closer phylogenetic relationship with the chimpanzee adenoviruses (simian adenoviruses) rather than with other human adenoviruses, suggesting a recent origin of HAdV-4, and therefore species E, through a zoonotic event from chimpanzees to humans. Bioinformatics analysis also suggests a pre-zoonotic recombination event, as well, between species B-like and species C-like simian adenoviruses. These observations may have implications for the current interest in using chimpanzee adenoviruses in the development of vectors for human gene therapy and for DNA-based vaccines. Also, the reemergence, surveillance, and treatment of HAdV-4 as an ARD pathogen is an opportunity to demonstrate the use of genome determination as a tool for viral infectious disease characterization and epidemic outbreak surveillance: for example, rapid and accurate low-pass sequencing and analysis of the genome. In particular, this approach allows the rapid identification and development of unique probes for the differentiation of family, species, serotype, and strain (e.g., pathogen genome signatures) for monitoring epidemic outbreaks of ARD. PMID:15681456

  2. Integrative bioinformatics for functional genome annotation: trawling for G protein-coupled receptors.

    PubMed

    Flower, Darren R; Attwood, Teresa K

    2004-12-01

    G protein-coupled receptors (GPCR) are amongst the best studied and most functionally diverse types of cell-surface protein. The importance of GPCRs as mediates or cell function and organismal developmental underlies their involvement in key physiological roles and their prominence as targets for pharmacological therapeutics. In this review, we highlight the requirement for integrated protocols which underline the different perspectives offered by different sequence analysis methods. BLAST and FastA offer broad brush strokes. Motif-based search methods add the fine detail. Structural modelling offers another perspective which allows us to elucidate the physicochemical properties that underlie ligand binding. Together, these different views provide a more informative and a more detailed picture of GPCR structure and function. Many GPCRs remain orphan receptors with no identified ligand, yet as computer-driven functional genomics starts to elaborate their functions, a new understanding of their roles in cell and developmental biology will follow. PMID:15561589

  3. AnnoTALE: bioinformatics tools for identification, annotation, and nomenclature of TALEs from Xanthomonas genomic sequences

    PubMed Central

    Grau, Jan; Reschke, Maik; Erkes, Annett; Streubel, Jana; Morgan, Richard D.; Wilson, Geoffrey G.; Koebnik, Ralf; Boch, Jens

    2016-01-01

    Transcription activator-like effectors (TALEs) are virulence factors, produced by the bacterial plant-pathogen Xanthomonas, that function as gene activators inside plant cells. Although the contribution of individual TALEs to infectivity has been shown, the specific roles of most TALEs, and the overall TALE diversity in Xanthomonas spp. is not known. TALEs possess a highly repetitive DNA-binding domain, which is notoriously difficult to sequence. Here, we describe an improved method for characterizing TALE genes by the use of PacBio sequencing. We present ‘AnnoTALE’, a suite of applications for the analysis and annotation of TALE genes from Xanthomonas genomes, and for grouping similar TALEs into classes. Based on these classes, we propose a unified nomenclature for Xanthomonas TALEs that reveals similarities pointing to related functionalities. This new classification enables us to compare related TALEs and to identify base substitutions responsible for the evolution of TALE specificities. PMID:26876161

  4. Clinical evaluation incorporating a personal genome

    PubMed Central

    Ashley, Euan A.; Butte, Atul J.; Wheeler, Matthew T.; Chen, Rong; Klein, Teri E.; Dewey, Frederick E.; Dudley, Joel T.; Ormond, Kelly E.; Pavlovic, Aleksandra; Hudgins, Louanne; Gong, Li; Hodges, Laura M.; Berlin, Dorit S.; Thorn, Caroline F.; Sangkuhl, Katrin; Hebert, Joan M.; Woon, Mark; Sagreiya, Hersh; Whaley, Ryan; Morgan, Alexander A.; Pushkarev, Dmitry; Neff, Norma F; Knowles, Joshua W.; Chou, Mike; Thakuria, Joseph; Rosenbaum, Abraham; Zaranek, Alexander Wait; Church, George; Greely, Henry T.; Quake, Stephen R.; Altman, Russ B.

    2010-01-01

    Background The cost of genomic information has fallen steeply but the path to clinical translation of risk estimates for common variants found in genome wide association studies remains unclear. Since the speed and cost of sequencing complete genomes is rapidly declining, more comprehensive means of analyzing these data in concert with rare variants for genetic risk assessment and individualisation of therapy are required. Here, we present the first integrated analysis of a complete human genome in a clinical context. Methods An individual with a family history of vascular disease and early sudden death was evaluated. Clinical assessment included risk prediction for coronary artery disease, screening for causes of sudden cardiac death, and genetic counselling. Genetic analysis included the development of novel methods for the integration of whole genome sequence data including 2.6 million single nucleotide polymorphisms and 752 copy number variations. The algorithm focused on predicting genetic risk of genes associated with known Mendelian disease, recognised drug responses, and pathogenicity for novel variants. In addition, since integration of risk ratios derived from case control studies is challenging, we estimated posterior probabilities from age and sex appropriate prior probability and likelihood ratios derived for each genotype. In addition, we developed a visualisation approach to account for gene-environment interactions and conditionally dependent risks. Findings We found increased genetic risk for myocardial infarction, type II diabetes and certain cancers. Rare variants in LPA are consistent with the family history of coronary artery disease. Pharmacogenomic analysis suggested a positive response to lipid lowering therapy, likely clopidogrel resistance, and a low initial dosing requirement for warfarin. Many variants of uncertain significance were reported. Interpretation Although challenges remain, our results suggest that whole genome sequencing can

  5. Cancer Genome Sequencing and Its Implications for Personalized Cancer Vaccines

    PubMed Central

    Li, Lijin; Goedegebuure, Peter; Mardis, Elaine R.; Ellis, Matthew J.C.; Zhang, Xiuli; Herndon, John M.; Fleming, Timothy P.; Carreno, Beatriz M.; Hansen, Ted H.; Gillanders, William E.

    2011-01-01

    New DNA sequencing platforms have revolutionized human genome sequencing. The dramatic advances in genome sequencing technologies predict that the $1,000 genome will become a reality within the next few years. Applied to cancer, the availability of cancer genome sequences permits real-time decision-making with the potential to affect diagnosis, prognosis, and treatment, and has opened the door towards personalized medicine. A promising strategy is the identification of mutated tumor antigens, and the design of personalized cancer vaccines. Supporting this notion are preliminary analyses of the epitope landscape in breast cancer suggesting that individual tumors express significant numbers of novel antigens to the immune system that can be specifically targeted through cancer vaccines. PMID:24213133

  6. Assessing Student Understanding of the "New Biology": Development and Evaluation of a Criterion-Referenced Genomics and Bioinformatics Assessment

    NASA Astrophysics Data System (ADS)

    Campbell, Chad Edward

    Over the past decade, hundreds of studies have introduced genomics and bioinformatics (GB) curricula and laboratory activities at the undergraduate level. While these publications have facilitated the teaching and learning of cutting-edge content, there has yet to be an evaluation of these assessment tools to determine if they are meeting the quality control benchmarks set forth by the educational research community. An analysis of these assessment tools indicated that <10% referenced any quality control criteria and that none of the assessments met more than one of the quality control benchmarks. In the absence of evidence that these benchmarks had been met, it is unclear whether these assessment tools are capable of generating valid and reliable inferences about student learning. To remedy this situation the development of a robust GB assessment aligned with the quality control benchmarks was undertaken in order to ensure evidence-based evaluation of student learning outcomes. Content validity is a central piece of construct validity, and it must be used to guide instrument and item development. This study reports on: (1) the correspondence of content validity evidence gathered from independent sources; (2) the process of item development using this evidence; (3) the results from a pilot administration of the assessment; (4) the subsequent modification of the assessment based on the pilot administration results and; (5) the results from the second administration of the assessment. Twenty-nine different subtopics within GB (Appendix B: Genomics and Bioinformatics Expert Survey) were developed based on preliminary GB textbook analyses. These subtopics were analyzed using two methods designed to gather content validity evidence: (1) a survey of GB experts (n=61) and (2) a detailed content analyses of GB textbooks (n=6). By including only the subtopics that were shown to have robust support across these sources, 22 GB subtopics were established for inclusion in the

  7. Genome-wide bioinformatics analysis of steroid metabolism-associated genes in Nocardioides simplex VKM Ac-2033D.

    PubMed

    Shtratnikova, Victoria Y; Schelkunov, Mikhail I; Fokina, Victoria V; Pekov, Yury A; Ivashina, Tanya; Donova, Marina V

    2016-08-01

    Actinobacteria comprise diverse groups of bacteria capable of full degradation, or modification of different steroid compounds. Steroid catabolism has been characterized best for the representatives of suborder Corynebacterineae, such as Mycobacteria, Rhodococcus and Gordonia, with high content of mycolic acids in the cell envelope, while it is poorly understood for other steroid-transforming actinobacteria, such as representatives of Nocardioides genus belonging to suborder Propionibacterineae. Nocardioides simplex VKM Ac-2033D is an important biotechnological strain which is known for its ability to introduce ∆(1)-double bond in various 1(2)-saturated 3-ketosteroids, and perform convertion of 3β-hydroxy-5-ene steroids to 3-oxo-4-ene steroids, hydrolysis of acetylated steroids, reduction of carbonyl groups at C-17 and C-20 of androstanes and pregnanes, respectively. The strain is also capable of utilizing cholesterol and phytosterol as carbon and energy sources. In this study, a comprehensive bioinformatics genome-wide screening was carried out to predict genes related to steroid metabolism in this organism, their clustering and possible regulation. The predicted operon structure and number of candidate gene copies paralogs have been estimated. Binding sites of steroid catabolism regulators KstR and KstR2 specified for N. simplex VKM Ac-2033D have been calculated de novo. Most of the candidate genes grouped within three main clusters, one of the predicted clusters having no analogs in other actinobacteria studied so far. The results offer a base for further functional studies, expand the understanding of steroid catabolism by actinobacteria, and will contribute to modifying of metabolic pathways in order to generate effective biocatalysts capable of producing valuable bioactive steroids. PMID:26832142

  8. Chemogenomics: a discipline at the crossroad of high throughput technologies, biomarker research, combinatorial chemistry, genomics, cheminformatics, bioinformatics and artificial intelligence.

    PubMed

    Maréchal, Eric

    2008-09-01

    Chemogenomics is the study of the interaction of functional biological systems with exogenous small molecules, or in broader sense the study of the intersection of biological and chemical spaces. Chemogenomics requires expertises in biology, chemistry and computational sciences (bioinformatics, cheminformatics, large scale statistics and machine learning methods) but it is more than the simple apposition of each of these disciplines. Biological entities interacting with small molecules can be isolated proteins or more elaborate systems, from single cells to complete organisms. The biological space is therefore analyzed at various postgenomic levels (genomic, transcriptomic, proteomic or any phenotypic level). The space of small molecules is partially real, corresponding to commercial and academic collections of compounds, and partially virtual, corresponding to the chemical space possibly synthesizable. Synthetic chemistry has developed novel strategies allowing a physical exploration of this universe of possibilities. A major challenge of cheminformatics is to charter the virtual space of small molecules using realistic biological constraints (bioavailability, druggability, structural biological information). Chemogenomics is a descendent of conventional pharmaceutical approaches, since it involves the screening of chemolibraries for their effect on biological targets, and benefits from the advances in the corresponding enabling technologies and the introduction of new biological markers. Screening was originally motivated by the rigorous discovery of new drugs, neglecting and throwing away any molecule that would fail to meet the standards required for a therapeutic treatment. It is now the basis for the discovery of small molecules that might or might not be directly used as drugs, but which have an immense potential for basic research, as probes to explore an increasing number of biological phenomena. Concerns about the environmental impact of chemical industry

  9. Genome Science and Personalized Cancer Treatment

    SciTech Connect

    Gray, Joe

    2009-08-07

    August 4, 2009 Berkeley Lab lecture: Results from the Human Genome Project are enabling scientists to understand how individual cancers form and progress. This information, when combined with newly developed drugs, can optimize the treatment of individual cancers. Joe Gray, director of Berkeley Labs Life Sciences Division and Associate Laboratory Director for Life and Environmental Sciences, will focus on this approach, its promise, and its current roadblocks — particularly with regard to breast cancer.

  10. Genome Science and Personalized Cancer Treatment

    SciTech Connect

    Gray, Joe

    2009-08-04

    Summer Lecture Series 2009: Results from the Human Genome Project are enabling scientists to understand how individual cancers form and progress. This information, when combined with newly developed drugs, can optimize the treatment of individual cancers. Joe Gray, director of Berkeley Labs Life Sciences Division and Associate Laboratory Director for Life and Environmental Sciences, will focus on this approach, its promise, and its current roadblocks — particularly with regard to breast cancer.

  11. Genome Science and Personalized Cancer Treatment

    ScienceCinema

    Gray, Joe

    2010-01-08

    August 4, 2009 Berkeley Lab lecture: Results from the Human Genome Project are enabling scientists to understand how individual cancers form and progress. This information, when combined with newly developed drugs, can optimize the treatment of individual cancers. Joe Gray, director of Berkeley Labs Life Sciences Division and Associate Laboratory Director for Life and Environmental Sciences, will focus on this approach, its promise, and its current roadblocks ? particularly with regard to breast cancer.

  12. The predictive capacity of personal genome sequencing.

    PubMed

    Roberts, Nicholas J; Vogelstein, Joshua T; Parmigiani, Giovanni; Kinzler, Kenneth W; Vogelstein, Bert; Velculescu, Victor E

    2012-05-01

    New DNA sequencing methods will soon make it possible to identify all germline variants in any individual at a reasonable cost. However, the ability of whole-genome sequencing to predict predisposition to common diseases in the general population is unknown. To estimate this predictive capacity, we use the concept of a "genometype." A specific genometype represents the genomes in the population conferring a specific level of genetic risk for a specified disease. Using this concept, we estimated the maximum capacity of whole-genome sequencing to identify individuals at clinically significant risk for 24 different diseases. Our estimates were derived from the analysis of large numbers of monozygotic twin pairs; twins of a pair share the same genometype and therefore identical genetic risk factors. Our analyses indicate that (i) for 23 of the 24 diseases, most of the individuals will receive negative test results; (ii) these negative test results will, in general, not be very informative, because the risk of developing 19 of the 24 diseases in those who test negative will still be, at minimum, 50 to 80% of that in the general population; and (iii) on the positive side, in the best-case scenario, more than 90% of tested individuals might be alerted to a clinically significant predisposition to at least one disease. These results have important implications for the valuation of genetic testing by industry, health insurance companies, public policy-makers, and consumers. PMID:22472521

  13. Genome Paths: A Way to Personalized and Predictive Medicine

    PubMed Central

    2009-01-01

    The review is devoted to the impact of human genome research on progress in modern medicine. Basic achievements in genome research have resulted in the deciphering of the human genome and creation of a molecular landmarks map of the human haploid genome (HapMap Project), which has made a tremendous contribution to our understanding of common genetic and multifactorial (complex) disorders. Current genome studies mainly focus on genetic testing and gene association studies of multifactorial (complex) diseases, with the purpose of their efficient diagnostics and prevention . Identification of candidate ("predisposition") genes participating in the functional genetic modules underlying each common disorder and the use of this genetic background to elaborate sophisticated measures to efficiently prevent them constitutes a major goal in personalized molecular medicine. The concept of a genetic pass as an individual DNA databank reflecting inherited human predisposition to different complex and monogenic disorders, with special emphasis on its present state, and the numerous difficulties related to the practical implementation of personalized medicine are outlined. The problems related to the uncertainness of the results of genetic testing could be overcome at least partly by means of new technological achievements in genome research methods, such as genome-wide association studies (GWAS), massive parallel DNA sequencing, and genetic and epigenetic profiling. The basic tasks of genomic today could be determined as the need to properly estimate the clinical value of genetic testing and its applicability in clinical practice. Feasible ways towards the gradual implementation of personal genetic data, in line with routine laboratory tests, for the benefit of clinical practice are discussed. PMID:22649616

  14. Anticipation of Personal Genomics Data Enhances Interest and Learning Environment in Genomics and Molecular Biology Undergraduate Courses.

    PubMed

    Weber, K Scott; Jensen, Jamie L; Johnson, Steven M

    2015-01-01

    An important discussion at colleges is centered on determining more effective models for teaching undergraduates. As personalized genomics has become more common, we hypothesized it could be a valuable tool to make science education more hands on, personal, and engaging for college undergraduates. We hypothesized that providing students with personal genome testing kits would enhance the learning experience of students in two undergraduate courses at Brigham Young University: Advanced Molecular Biology and Genomics. These courses have an emphasis on personal genomics the last two weeks of the semester. Students taking these courses were given the option to receive personal genomics kits in 2014, whereas in 2015 they were not. Students sent their personal genomics samples in on their own and received the data after the course ended. We surveyed students in these courses before and after the two-week emphasis on personal genomics to collect data on whether anticipation of obtaining their own personal genomic data impacted undergraduate student learning. We also tested to see if specific personal genomic assignments improved the learning experience by analyzing the data from the undergraduate students who completed both the pre- and post-course surveys. Anticipation of personal genomic data significantly enhanced student interest and the learning environment based on the time students spent researching personal genomic material and their self-reported attitudes compared to those who did not anticipate getting their own data. Personal genomics homework assignments significantly enhanced the undergraduate student interest and learning based on the same criteria and a personal genomics quiz. We found that for the undergraduate students in both molecular biology and genomics courses, incorporation of personal genomic testing can be an effective educational tool in undergraduate science education. PMID:26241308

  15. Getting up close and personal with your genome.

    PubMed

    Bonetta, Laura

    2008-05-30

    A new type of company is offering to scan a person's genome and reveal the information it holds for as little as $1000. Are these services fun novelty items or do they provide valuable information that will help people take better care of their health? PMID:18510915

  16. Re-Examining the Gene in Personalized Genomics

    ERIC Educational Resources Information Center

    Bartol, Jordan

    2013-01-01

    Personalized genomics companies (PG; also called "direct-to-consumer genetics") are businesses marketing genetic testing to consumers over the Internet. While much has been written about these new businesses, little attention has been given to their roles in science communication. This paper provides an analysis of the gene concept…

  17. Making Personalized Health Care Even More Personalized: Insights From Activities of the IOM Genomics Roundtable

    PubMed Central

    David, Sean P.; Johnson, Samuel G.; Berger, Adam C.; Feero, W. Gregory; Terry, Sharon F.; Green, Larry A.; Phillips, Robert L.; Ginsburg, Geoffrey S.

    2015-01-01

    Genomic research has generated much new knowledge into mechanisms of human disease, with the potential to catalyze novel drug discovery and development, prenatal and neonatal screening, clinical pharmacogenomics, more sensitive risk prediction, and enhanced diagnostics. Genomic medicine, however, has been limited by critical evidence gaps, especially those related to clinical utility and applicability to diverse populations. Genomic medicine may have the greatest impact on health care if it is integrated into primary care, where most health care is received and where evidence supports the value of personalized medicine grounded in continuous healing relationships. Redesigned primary care is the most relevant setting for clinically useful genomic medicine research. Taking insights gained from the activities of the Institute of Medicine (IOM) Roundtable on Translating Genomic-Based Research for Health, we apply lessons learned from the patient-centered medical home national experience to implement genomic medicine in a patient-centered, learning health care system. PMID:26195686

  18. Bioinformatics for Genome Analysis

    SciTech Connect

    Gary J. Olsen

    2005-06-30

    Nesbo, Boucher and Doolittle (2001) used phylogenetic trees of four taxa to assess whether euryarchaeal genes share a common history. They have suggested that of the 521 genes examined, each of the three possible tree topologies relating the four taxa was supported essentially equal numbers of times. They suggest that this might be the result of numerous horizontal gene transfer events, essentially randomizing the relationships between gene histories (as inferred in the 521 gene trees) and organismal relationships (which would be a single underlying tree). Motivated by the fact that the order in which sequences are added to a multiple sequence alignment influences the alignment, and ultimately inferred tree, they were interested in the extent to which the variations among inferred trees might be due to variations in the alignment order. This bears directly on their efforts to evaluate and improve upon methods of multiple sequence alignment. They set out to analyze the influence of alignment order on the tree inferred for 43 genes shared among these same 4 taxa. Because alignments produced by CLUSTALW are directed by a rooted guide tree (the denderogram), there are 15 possible alignment orders of 4 taxa. For each gene they tested all 15 alignment orders, and as a 16th option, allowed CLUSTALW to generate its own guide tree. If we supply all 15 possible rooted guide trees, they expected that at least one of them should be as good at CLUSTAL's own guide tree, but most of the time they differed (sometimes being better than CLUSTAL's default tree and sometimes being worse). The difference seems to be that the user-supplied tree is not given meaningful branch lengths, which effect the assumed probability of amino acid changes. They examined the practicality of modifying CLUSTALW to improve its treatment of user-supplied guide trees. This work became ever increasing bogged down in finding and repairing minor bugs in the CLUSTALW code. This effort was put on hold as we feel that our other proposed approaches will ultimately be better.

  19. Bayesian predictive modeling for genomic based personalized treatment selection.

    PubMed

    Ma, Junsheng; Stingo, Francesco C; Hobbs, Brian P

    2016-06-01

    Efforts to personalize medicine in oncology have been limited by reductive characterizations of the intrinsically complex underlying biological phenomena. Future advances in personalized medicine will rely on molecular signatures that derive from synthesis of multifarious interdependent molecular quantities requiring robust quantitative methods. However, highly parameterized statistical models when applied in these settings often require a prohibitively large database and are sensitive to proper characterizations of the treatment-by-covariate interactions, which in practice are difficult to specify and may be limited by generalized linear models. In this article, we present a Bayesian predictive framework that enables the integration of a high-dimensional set of genomic features with clinical responses and treatment histories of historical patients, providing a probabilistic basis for using the clinical and molecular information to personalize therapy for future patients. Our work represents one of the first attempts to define personalized treatment assignment rules based on large-scale genomic data. We use actual gene expression data acquired from The Cancer Genome Atlas in the settings of leukemia and glioma to explore the statistical properties of our proposed Bayesian approach for personalizing treatment selection. The method is shown to yield considerable improvements in predictive accuracy when compared to penalized regression approaches. PMID:26575856

  20. Education and personalized genomics: deciphering the public's genetic health report

    PubMed Central

    Lamb, Neil E; Myers, Richard M; Gunter, Chris

    2010-01-01

    Where do members of the public turn to understand what genetic tests mean in terms of their own health? Now that genome-wide association studies and complete genome sequencing are widely available, the importance of education in personalized genomics cannot be overstated. Although some media have introduced the concept of genetic testing to better understand health and disease, the public's understanding of the scope and impact of genetic variation has not kept up with the pace of the science or technology. Unfortunately, the likely sources to which the public turn to for guidance – their physician and the media – are often no better prepared. We examine several venues for information, including print and online guides for both lay and health-oriented audiences, and summarize selected resources in multiple formats. We also note on the roadblocks to progress and discuss ways to remove them, as urgent action is needed to connect people with their genomes in a meaningful way. PMID:20161675

  1. Identification of conserved and polymorphic STRs for personal genomes

    PubMed Central

    2014-01-01

    Background Short tandem repeats (STRs) are abundant in human genomes. Numerous STRs have been shown to be associated with genetic diseases and gene regulatory functions, and have been selected as genetic markers for evolutionary and forensic analyses. High-throughput next generation sequencers have fostered new cutting-edge computing techniques for genome-scale analyses, and cross-genome comparisons have facilitated the efficient identification of polymorphic STR markers for various applications. Results An automated and efficient system for detecting human polymorphic STRs at the genome scale is proposed in this study. Assembled contigs from next generation sequencing data were aligned and calibrated according to selected reference sequences. To verify identified polymorphic STRs, human genomes from the 1000 Genomes Project were employed for comprehensive analyses, and STR markers from the Combined DNA Index System (CODIS) and disease-related STR motifs were also applied as cases for evaluation. In addition, we analyzed STR variations for highly conserved homologous genes and human-unique genes. In total 477 polymorphic STRs were identified from 492 human-unique genes, among which 26 STRs were retrieved and clustered into three different groups for efficient comparison. Conclusions We have developed an online system that efficiently identifies polymorphic STRs and provides novel distinguishable STR biomarkers for different levels of specificity. Candidate polymorphic STRs within a personal genome could be easily retrieved and compared to the constructed STR profile through query keywords, gene names, or assembled contigs. PMID:25560225

  2. SNPedia: a wiki supporting personal genome annotation, interpretation and analysis.

    PubMed

    Cariaso, Michael; Lennon, Greg

    2012-01-01

    SNPedia (http://www.SNPedia.com) is a wiki resource of the functional consequences of human genetic variation as published in peer-reviewed studies. Online since 2006 and freely available for personal use, SNPedia has focused on the medical, phenotypic and genealogical associations of single nucleotide polymorphisms. Entries are formatted to allow associations to be assigned to single genotypes as well as sets of genotypes (genosets). In this article, we discuss the growth of this resource and its use by affiliated software to create personal genome reports. PMID:22140107

  3. Personalized Genomic Medicine and the Rhetoric of Empowerment

    PubMed Central

    Juengst, Eric T.; Flatt, Michael A.; Settersten, Richard A.

    2013-01-01

    Advocates of “personalized” genomic medicine maintain that it is revolutionary not just in what it can reveal to us, but in how it will enable us to take control of our health. But we should not assume that patient empowerment always yields positive outcomes. To assess the social impact of personalized medicine, we must anticipate how the virtue might go awry in practice. PMID:22976411

  4. Mitochondrial and nuclear genomics and the emergence of personalized medicine

    PubMed Central

    2012-01-01

    Developing early detection biosensors for disease has been the long‒held goal of the Human Genome Project, but with little success. Conversely, the biological properties of the mitochondrion coupled with the relative simplicity of the mitochondrial genome give this organelle extraordinary functionality as a biosensor and places the field of mitochondrial genomics in a position of strategic advantage to launch significant advances in personalized medicine. Numerous factors make the mitochondrion organelle uniquely suited to be an early detection biosensor with applications in oncology as well as many other aspects of human health and disease. Early detection of disease translates into more effective, less expensive treatments for disease and overall better prognoses for those at greater risk for developing diseases. PMID:23244780

  5. Systematic evaluation of personal genome services for Japanese individuals.

    PubMed

    Kido, Takashi; Kawashima, Minae; Nishino, Seiji; Swan, Melanie; Kamatani, Naoyuki; Butte, Atul J

    2013-11-01

    Disease risk prediction (DRP) is one of the most important challenges in personal genome research. Although many direct-to-consumer genetic test (DTC) companies have begun to offer personal genome services for DRP, there is still no consensus on what constitutes a gold-standard service. Here, we systematically evaluated the distributions of DRPs from three DTC companies, that is, 23andMe, Navigenics and deCODEme, for 22 diseases using three Japanese samples. We systematically quantified and analyzed the differences between each DTC company's DRPs. Our independency test showed that the overall prediction results were correlated with each other, but not perfectly matched; less than onethird mismatching of the opposite direction occurred in eight diseases. Moreover, we found that the differences could mainly be attributed to four factors: (1) single nucleotide polymorphism (SNP) selection, (2) average risk estimation, (3) the disease risk calculation algorithm and (4) ethnicity adjustment. In particular, only 7.1% of SNPs over 22 diseases were reviewed by all three companies. Therefore, development of a universal core SNPs list for non-Caucasian samples will be important for achieving better prediction capacity for Japanese samples. This systematic methodology provides useful insights for improving the capacity of DRPs in future personal genome services. PMID:24067293

  6. Biology in 'silico': The Bioinformatics Revolution.

    ERIC Educational Resources Information Center

    Bloom, Mark

    2001-01-01

    Explains the Human Genome Project (HGP) and efforts to sequence the human genome. Describes the role of bioinformatics in the project and considers it the genetics Swiss Army Knife, which has many different uses, for use in forensic science, medicine, agriculture, and environmental sciences. Discusses the use of bioinformatics in the high school…

  7. Attitudes regarding privacy of genomic information in personalized cancer therapy

    PubMed Central

    Rogith, Deevakar; Yusuf, Rafeek A; Hovick, Shelley R; Peterson, Susan K; Burton-Chase, Allison M; Li, Yisheng; Meric-Bernstam, Funda; Bernstam, Elmer V

    2014-01-01

    Objective To evaluate attitudes regarding privacy of genomic data in a sample of patients with breast cancer. Methods Female patients with breast cancer (n=100) completed a questionnaire assessing attitudes regarding concerns about privacy of genomic data. Results Most patients (83%) indicated that genomic data should be protected. However, only 13% had significant concerns regarding privacy of such data. Patients expressed more concern about insurance discrimination than employment discrimination (43% vs 28%, p<0.001). They expressed less concern about research institutions protecting the security of their molecular data than government agencies or drug companies (20% vs 38% vs 44%; p<0.001). Most did not express concern regarding the association of their genomic data with their name and personal identity (49% concerned), billing and insurance information (44% concerned), or clinical data (27% concerned). Significantly fewer patients were concerned about the association with clinical data than other data types (p<0.001). In the absence of direct benefit, patients were more willing to consent to sharing of deidentified than identified data with researchers not involved in their care (76% vs 60%; p<0.001). Most (85%) patients were willing to consent to DNA banking. Discussion While patients are opposed to indiscriminate release of genomic data, privacy does not appear to be their primary concern. Furthermore, we did not find any specific predictors of privacy concerns. Conclusions Patients generally expressed low levels of concern regarding privacy of genomic data, and many expressed willingness to consent to sharing their genomic data with researchers. PMID:24737606

  8. SpeedSeq: Ultra-fast personal genome analysis and interpretation

    PubMed Central

    Chiang, Colby; Layer, Ryan M.; Faust, Gregory G.; Lindberg, Michael R.; Rose, David B.; Garrison, Erik P.; Marth, Gabor T.; Quinlan, Aaron R.; Hall, Ira M.

    2015-01-01

    SpeedSeq is an open-source genome analysis platform that accomplishes alignment, variant detection and functional annotation of a 50× human genome in 13 hours on a low-cost server, alleviating a bioinformatics bottleneck that typically demands weeks of computation with extensive hands-on expert involvement. SpeedSeq offers competitive or superior performance to current methods for detecting germline and somatic single nucleotide variants, indels, and structural variants, and includes novel functionality for streamlined interpretation. PMID:26258291

  9. Illuminating the Black Box of Genome Sequence Assembly: A Free Online Tool to Introduce Students to Bioinformatics

    ERIC Educational Resources Information Center

    Taylor, D. Leland; Campbell, A. Malcolm; Heyer, Laurie J.

    2013-01-01

    Next-generation sequencing technologies have greatly reduced the cost of sequencing genomes. With the current sequencing technology, a genome is broken into fragments and sequenced, producing millions of "reads." A computer algorithm pieces these reads together in the genome assembly process. PHAST is a set of online modules…

  10. Diagnosis of an imprinted-gene syndrome by a novel bioinformatics analysis of whole-genome sequences from a family trio.

    PubMed

    Bodian, Dale L; Solomon, Benjamin D; Khromykh, Alina; Thach, Dzung C; Iyer, Ramaswamy K; Link, Kathleen; Baker, Robin L; Baveja, Rajiv; Vockley, Joseph G; Niederhuber, John E

    2014-11-01

    Whole-genome sequencing and whole-exome sequencing are becoming more widely applied in clinical medicine to help diagnose rare genetic diseases. Identification of the underlying causative mutations by genome-wide sequencing is greatly facilitated by concurrent analysis of multiple family members, most often the mother-father-proband trio, using bioinformatics pipelines that filter genetic variants by mode of inheritance. However, current pipelines are limited to Mendelian inheritance patterns and do not specifically address disorders caused by mutations in imprinted genes, such as forms of Angelman syndrome and Beckwith-Wiedemann syndrome. Using publicly available tools, we implemented a genetic inheritance search mode to identify imprinted-gene mutations. Application of this search mode to whole-genome sequences from a family trio led to a diagnosis for a proband for whom extensive clinical testing and Mendelian inheritance-based sequence analysis were nondiagnostic. The condition in this patient, IMAGe syndrome, is likely caused by the heterozygous mutation c.832A>G (p.Lys278Glu) in the imprinted gene CDKN1C. The genotypes and disease status of six members of the family are consistent with maternal expression of the gene, and allele-biased expression was confirmed by RNA-Seq for the heterozygotes. This analysis demonstrates that an imprinted-gene search mode is a valuable addition to genome sequence analysis pipelines for identifying disease-causative variants. PMID:25614875

  11. Diagnosis of an imprinted-gene syndrome by a novel bioinformatics analysis of whole-genome sequences from a family trio

    PubMed Central

    Bodian, Dale L; Solomon, Benjamin D; Khromykh, Alina; Thach, Dzung C; Iyer, Ramaswamy K; Link, Kathleen; Baker, Robin L; Baveja, Rajiv; Vockley, Joseph G; Niederhuber, John E

    2014-01-01

    Whole-genome sequencing and whole-exome sequencing are becoming more widely applied in clinical medicine to help diagnose rare genetic diseases. Identification of the underlying causative mutations by genome-wide sequencing is greatly facilitated by concurrent analysis of multiple family members, most often the mother–father–proband trio, using bioinformatics pipelines that filter genetic variants by mode of inheritance. However, current pipelines are limited to Mendelian inheritance patterns and do not specifically address disorders caused by mutations in imprinted genes, such as forms of Angelman syndrome and Beckwith–Wiedemann syndrome. Using publicly available tools, we implemented a genetic inheritance search mode to identify imprinted-gene mutations. Application of this search mode to whole-genome sequences from a family trio led to a diagnosis for a proband for whom extensive clinical testing and Mendelian inheritance-based sequence analysis were nondiagnostic. The condition in this patient, IMAGe syndrome, is likely caused by the heterozygous mutation c.832A>G (p.Lys278Glu) in the imprinted gene CDKN1C. The genotypes and disease status of six members of the family are consistent with maternal expression of the gene, and allele-biased expression was confirmed by RNA-Seq for the heterozygotes. This analysis demonstrates that an imprinted-gene search mode is a valuable addition to genome sequence analysis pipelines for identifying disease-causative variants. PMID:25614875

  12. Bioinformatic tools for using whole genome sequencing as a rapid high resolution diagnostic typing tool when tracing bioterror organisms in the food and feed chain.

    PubMed

    Segerman, Bo; De Medici, Dario; Ehling Schulz, Monika; Fach, Patrick; Fenicia, Lucia; Fricker, Martina; Wielinga, Peter; Van Rotterdam, Bart; Knutsson, Rickard

    2011-03-01

    The rapid technological development in the field of parallel sequencing offers new opportunities when tracing and tracking microorganisms in the food and feed chain. If a bioterror organism is deliberately spread it is of crucial importance to get as much information as possible regarding the strain as fast as possible to aid the decision process and select suitable controls, tracing and tracking tools. A lot of efforts have been made to sequence multiple strains of potential bioterror organisms so there is a relatively large set of reference genomes available. This study is focused on how to use parallel sequencing for rapid phylogenomic analysis and screen for genetic modifications. A bioinformatic methodology has been developed to rapidly analyze sequence data with minimal post-processing. Instead of assembling the genome, defining genes, defining orthologous relations and calculating distances, the present method can achieve a similar high resolution directly from the raw sequence data. The method defines orthologous sequence reads instead of orthologous genes and the average similarity of the core genome (ASC) is calculated. The sequence reads from the core and from the non-conserved genomic regions can also be separated for further analysis. Finally, the comparison algorithm is used to visualize the phylogenomic diversity of the bacterial bioterror organisms Bacillus anthracis and Clostridium botulinum using heat plot diagrams. PMID:20826036

  13. MISIS-2: A bioinformatics tool for in-depth analysis of small RNAs and representation of consensus master genome in viral quasispecies.

    PubMed

    Seguin, Jonathan; Otten, Patricia; Baerlocher, Loïc; Farinelli, Laurent; Pooggin, Mikhail M

    2016-07-01

    In most eukaryotes, small RNA (sRNA) molecules such as miRNAs, siRNAs and piRNAs regulate gene expression and repress transposons and viruses. AGO/PIWI family proteins sort functional sRNAs based on size, 5'-nucleotide and other sequence features. In plants and some animals, viral sRNAs are extremely diverse and cover the entire viral genome sequences, which allows for de novo reconstruction of a complete viral genome by deep sequencing and bioinformatics analysis of viral sRNAs. Previously, we have developed a tool MISIS to view and analyze sRNA maps of viruses and cellular genome regions which spawn multiple sRNAs. Here we describe a new release of MISIS, MISIS-2, which enables to determine and visualize a consensus sequence and count sRNAs of any chosen sizes and 5'-terminal nucleotide identities. Furthermore we demonstrate the utility of MISIS-2 for identification of single nucleotide polymorphisms (SNPs) at each position of a reference sequence and reconstruction of a consensus master genome in evolving viral quasispecies. MISIS-2 is a Java standalone program. It is freely available along with the source code at the website http://www.fasteris.com/apps. PMID:26994965

  14. Bioinformatics Pipelines for Targeted Resequencing and Whole-Exome Sequencing of Human and Mouse Genomes: A Virtual Appliance Approach for Instant Deployment

    PubMed Central

    Saeed, Isaam; Wong, Stephen Q.; Mar, Victoria; Goode, David L.; Caramia, Franco; Doig, Ken; Ryland, Georgina L.; Thompson, Ella R.; Hunter, Sally M.; Halgamuge, Saman K.; Ellul, Jason; Dobrovic, Alexander; Campbell, Ian G.; Papenfuss, Anthony T.; McArthur, Grant A.; Tothill, Richard W.

    2014-01-01

    Targeted resequencing by massively parallel sequencing has become an effective and affordable way to survey small to large portions of the genome for genetic variation. Despite the rapid development in open source software for analysis of such data, the practical implementation of these tools through construction of sequencing analysis pipelines still remains a challenging and laborious activity, and a major hurdle for many small research and clinical laboratories. We developed TREVA (Targeted REsequencing Virtual Appliance), making pre-built pipelines immediately available as a virtual appliance. Based on virtual machine technologies, TREVA is a solution for rapid and efficient deployment of complex bioinformatics pipelines to laboratories of all sizes, enabling reproducible results. The analyses that are supported in TREVA include: somatic and germline single-nucleotide and insertion/deletion variant calling, copy number analysis, and cohort-based analyses such as pathway and significantly mutated genes analyses. TREVA is flexible and easy to use, and can be customised by Linux-based extensions if required. TREVA can also be deployed on the cloud (cloud computing), enabling instant access without investment overheads for additional hardware. TREVA is available at http://bioinformatics.petermac.org/treva/. PMID:24752294

  15. Re-examining the Gene in Personalized Genomics

    NASA Astrophysics Data System (ADS)

    Bartol, Jordan

    2013-10-01

    Personalized genomics companies (PG; also called `direct-to-consumer genetics') are businesses marketing genetic testing to consumers over the Internet. While much has been written about these new businesses, little attention has been given to their roles in science communication. This paper provides an analysis of the gene concept presented to customers and the relation between the information given and the science behind PG. Two quite different gene concepts are present in company rhetoric, but only one features in the science. To explain this, we must appreciate the delicate tension between PG, academic science, public expectation, and market forces.

  16. Genomics and Bioinformatics in Undergraduate Curricula: Contexts for Hybrid Laboratory/Lecture Courses for Entering and Advanced Science Students

    ERIC Educational Resources Information Center

    Temple, Louise; Cresawn, Steven G.; Monroe, Jonathan D.

    2010-01-01

    Emerging interest in genomics in the scientific community prompted biologists at James Madison University to create two courses at different levels to modernize the biology curriculum. The courses are hybrids of classroom and laboratory experiences. An upper level class uses raw sequence of a genome (plasmid or virus) as the subject on which to…

  17. Incidentalome from Genomic Sequencing: A Barrier to Personalized Medicine?

    PubMed Central

    Jamuar, Saumya Shekhar; Kuan, Jyn Ling; Brett, Maggie; Tiang, Zenia; Tan, Wilson Lek Wen; Lim, Jiin Ying; Liew, Wendy Kein Meng; Javed, Asif; Liew, Woei Kang; Law, Hai Yang; Tan, Ee Shien; Lai, Angeline; Ng, Ivy; Teo, Yik Ying; Venkatesh, Byrappa; Reversade, Bruno; Tan, Ene Choo; Foo, Roger

    2016-01-01

    Background In Western cohorts, the prevalence of incidental findings (IFs) or incidentalome, referring to variants in genes that are unrelated to the patient's primary condition, is between 0.86% and 8.8%. However, data on prevalence and type of IFs in Asian population is lacking. Methods In 2 cohorts of individuals with genomic sequencing performed in Singapore (total n = 377), we extracted and annotated variants in the 56 ACMG-recommended genes and filtered these variants based on the level of pathogenicity. We then analyzed the precise distribution of IFs, class of genes, related medical conditions, and potential clinical impact. Results We found a total of 41,607 variants in the 56 genes in our cohort of 377 individuals. After filtering for rare and coding variants, we identified 14 potential variants. After reviewing primary literature, only 4 out of the 14 variants were classified to be pathogenic, while an additional two variants were classified as likely pathogenic. Overall, the cumulative prevalence of IFs (pathogenic and likely pathogenic variants) in our cohort was 1.6%. Conclusion The cumulative prevalence of IFs through genomic sequencing is low and the incidentalome may not be a significant barrier to implementation of genomics for personalized medicine. PMID:27077130

  18. The Genome Sequencer FLX System--longer reads, more applications, straight forward bioinformatics and more complete data sets.

    PubMed

    Droege, Marcus; Hill, Brendon

    2008-08-31

    The Genome Sequencer FLX System (GS FLX), powered by 454 Sequencing, is a next-generation DNA sequencing technology featuring a unique mix of long reads, exceptional accuracy, and ultra-high throughput. It has been proven to be the most versatile of all currently available next-generation sequencing technologies, supporting many high-profile studies in over seven applications categories. GS FLX users have pursued innovative research in de novo sequencing, re-sequencing of whole genomes and target DNA regions, metagenomics, and RNA analysis. 454 Sequencing is a powerful tool for human genetics research, having recently re-sequenced the genome of an individual human, currently re-sequencing the complete human exome and targeted genomic regions using the NimbleGen sequence capture process, and detected low-frequency somatic mutations linked to cancer. PMID:18616967

  19. Playing with heart and soul…and genomes: sports implications and applications of personal genomics

    PubMed Central

    2013-01-01

    Whether the integration of genetic/omic technologies in sports contexts will facilitate player success, promote player safety, or spur genetic discrimination depends largely upon the game rules established by those currently designing genomic sports medicine programs. The integration has already begun, but there is not yet a playbook for best practices. Thus far discussions have focused largely on whether the integration would occur and how to prevent the integration from occurring, rather than how it could occur in such a way that maximizes benefits, minimizes risks, and avoids the exacerbation of racial disparities. Previous empirical research has identified members of the personal genomics industry offering sports-related DNA tests, and previous legal research has explored the impact of collective bargaining in professional sports as it relates to the employment protections of the Genetic Information Nondiscrimination Act (GINA). Building upon that research and upon participant observations with specific sports-related DNA tests purchased from four direct-to-consumer companies in 2011 and broader personal genomics (PGx) services, this anthropological, legal, and ethical (ALE) discussion highlights fundamental issues that must be addressed by those developing personal genomic sports medicine programs, either independently or through collaborations with commercial providers. For example, the vulnerability of student-athletes creates a number of issues that require careful, deliberate consideration. More broadly, however, this ALE discussion highlights potential sports-related implications (that ultimately might mitigate or, conversely, exacerbate racial disparities among athletes) of whole exome/genome sequencing conducted by biomedical researchers and clinicians for non-sports purposes. For example, the possibility that exome/genome sequencing of individuals who are considered to be non-patients, asymptomatic, normal, etc. will reveal the presence of variants of

  20. [Genome sequencing and personalized medicine: perspectives and limitations].

    PubMed

    Le Gall, Jean-Yves; Debré, Patrice

    2014-01-01

    (e.g. imatinib and Bcr/Abl rearrangement; verumafemib and the BRAF V600E mutation). Systematic sequencing of all the genes involved in drug metabolism and responsiveness will lead to individualized pharmacogenetics. Finally, sequencing of the tumoral and constitutional genomes, identfication of somatic mutations, and detection of pharmacogenetic variants will open up the era of personalized medicine. The first results of these targeted therapeutic indications show a gain in the duration of remission and survival, although the cost-effectiveness of these approaches remains to be determined. Finally, this huge capacity for genome sequencing raises a number of regulatory and ethical issues. PMID:26259290

  1. Web-based Gene Pathogenicity Analysis (WGPA): a web platform to interpret gene pathogenicity from personal genome data

    PubMed Central

    Diaz-Montana, Juan J.; Rackham, Owen J.L.; Diaz-Diaz, Norberto; Petretto, Enrico

    2016-01-01

    Summary: As the volume of patient-specific genome sequences increases the focus of biomedical research is switching from the detection of disease-mutations to their interpretation. To this end a number of techniques have been developed that use mutation data collected within a population to predict whether individual genes are likely to be disease-causing or not. As both sequence data and associated analysis tools proliferate, it becomes increasingly difficult for the community to make sense of these data and their implications. Moreover, no single analysis tool is likely to capture all relevant genomic features that contribute to the gene’s pathogenicity. Here, we introduce Web-based Gene Pathogenicity Analysis (WGPA), a web-based tool to analyze genes impacted by mutations and rank them through the integration of existing prioritization tools, which assess different aspects of gene pathogenicity using population-level sequence data. Additionally, to explore the polygenic contribution of mutations to disease, WGPA implements gene set enrichment analysis to prioritize disease-causing genes and gene interaction networks, therefore providing a comprehensive annotation of personal genomes data in disease. Availability and implementation: wgpa.systems-genetics.net Contact: enrico.petretto@duke-nus.edu.sg Supplementary information: Supplementary data are available at Bioinformatics online. PMID:26490503

  2. Personal genomics and individual identities: motivations and moral imperatives of early users

    PubMed Central

    McGowan, Michelle L.; Fishman, Jennifer R.; Lambrix, Marcie A.

    2010-01-01

    Since 2007, consumer genomics companies have marketed personal genome scanning services to assess users’ genetic predispositions to a variety of complex diseases and traits. This study investigates early users’ reasons for utilizing personal genome services, their evaluation of the technology, how they interpret the results, and how they incorporate the results into health-related decision-making. The analysis contextualizes early users’ relationships to the technology, the knowledge generated by it, and how it mediates their relationship to their own health and to biomedicine more broadly. The results reveal that early users approach personal genome scanning with both optimism for genomic research and scepticism about the technology’s current capabilities, which runs contrary to concerns that consumers may be ill equipped to interpret and understand genome scan results. These findings provide important qualitative insight into early users’ conceptualizations of personal genomic risk assessment and illuminate their involvement in configuring this technology in the making. PMID:21076647

  3. Rapid Development of Bioinformatics Education in China

    ERIC Educational Resources Information Center

    Zhong, Yang; Zhang, Xiaoyan; Ma, Jian; Zhang, Liang

    2003-01-01

    As the Human Genome Project experiences remarkable success and a flood of biological data is produced, bioinformatics becomes a very "hot" cross-disciplinary field, yet experienced bioinformaticians are urgently needed worldwide. This paper summarises the rapid development of bioinformatics education in China, especially related undergraduate…

  4. Fuzzy Logic in Medicine and Bioinformatics

    PubMed Central

    Torres, Angela; Nieto, Juan J.

    2006-01-01

    The purpose of this paper is to present a general view of the current applications of fuzzy logic in medicine and bioinformatics. We particularly review the medical literature using fuzzy logic. We then recall the geometrical interpretation of fuzzy sets as points in a fuzzy hypercube and present two concrete illustrations in medicine (drug addictions) and in bioinformatics (comparison of genomes). PMID:16883057

  5. Bioinformatics of prokaryotic RNAs

    PubMed Central

    Backofen, Rolf; Amman, Fabian; Costa, Fabrizio; Findeiß, Sven; Richter, Andreas S; Stadler, Peter F

    2014-01-01

    The genome of most prokaryotes gives rise to surprisingly complex transcriptomes, comprising not only protein-coding mRNAs, often organized as operons, but also harbors dozens or even hundreds of highly structured small regulatory RNAs and unexpectedly large levels of anti-sense transcripts. Comprehensive surveys of prokaryotic transcriptomes and the need to characterize also their non-coding components is heavily dependent on computational methods and workflows, many of which have been developed or at least adapted specifically for the use with bacterial and archaeal data. This review provides an overview on the state-of-the-art of RNA bioinformatics focusing on applications to prokaryotes. PMID:24755880

  6. Bioinformatics of prokaryotic RNAs.

    PubMed

    Backofen, Rolf; Amman, Fabian; Costa, Fabrizio; Findeiß, Sven; Richter, Andreas S; Stadler, Peter F

    2014-01-01

    The genome of most prokaryotes gives rise to surprisingly complex transcriptomes, comprising not only protein-coding mRNAs, often organized as operons, but also harbors dozens or even hundreds of highly structured small regulatory RNAs and unexpectedly large levels of anti-sense transcripts. Comprehensive surveys of prokaryotic transcriptomes and the need to characterize also their non-coding components is heavily dependent on computational methods and workflows, many of which have been developed or at least adapted specifically for the use with bacterial and archaeal data. This review provides an overview on the state-of-the-art of RNA bioinformatics focusing on applications to prokaryotes. PMID:24755880

  7. Genome-wide expression profiling and bioinformatics analysis of diurnally regulated genes in the mouse prefrontal cortex

    PubMed Central

    Yang, Shuzhang; Wang, Kai; Valladares, Otto; Hannenhalli, Sridhar; Bucan, Maja

    2007-01-01

    Background The prefrontal cortex is important in regulating sleep and mood. Diurnally regulated genes in the prefrontal cortex may be controlled by the circadian system, by sleep:wake states, or by cellular metabolism or environmental responses. Bioinformatics analysis of these genes will provide insights into a wide-range of pathways that are involved in the pathophysiology of sleep disorders and psychiatric disorders with sleep disturbances. Results We examined gene expression in the mouse prefrontal cortex at four time points during a 24 hour (12 hour light:12 hour dark) cycle using microarrays, and identified 3,890 transcripts corresponding to 2,927 genes with diurnally regulated expression patterns. We show that 16% of the genes identified in our study are orthologs of identified clock, clock controlled or sleep/wakefulness induced genes in the mouse liver and suprachiasmatic nucleus, rat cortex and cerebellum, or Drosophila head. The diurnal expression patterns were confirmed for 16 out of 18 genes in an independent set of RNA samples. The diurnal genes fall into eight temporal categories with distinct functional attributes, as assessed by Gene Ontology classification and analysis of enriched transcription factor binding sites. Conclusion Our analysis demonstrates that approximately 10% of transcripts have diurnally regulated expression patterns in the mouse prefrontal cortex. Functional annotation of these genes will be important for the selection of candidate genes for behavioral mutants in the mouse and for genetic studies of disorders associated with anomalies in the sleep:wake cycle and circadian rhythm. PMID:18028544

  8. Evaluation of next generation mtGenome sequencing using the Ion Torrent Personal Genome Machine (PGM).

    PubMed

    Parson, Walther; Strobl, Christina; Huber, Gabriela; Zimmermann, Bettina; Gomes, Sibylle M; Souto, Luis; Fendt, Liane; Delport, Rhena; Langit, Reina; Wootton, Sharon; Lagacé, Robert; Irwin, Jodi

    2013-09-01

    Insights into the human mitochondrial phylogeny have been primarily achieved by sequencing full mitochondrial genomes (mtGenomes). In forensic genetics (partial) mtGenome information can be used to assign haplotypes to their phylogenetic backgrounds, which may, in turn, have characteristic geographic distributions that would offer useful information in a forensic case. In addition and perhaps even more relevant in the forensic context, haplogroup-specific patterns of mutations form the basis for quality control of mtDNA sequences. The current method for establishing (partial) mtDNA haplotypes is Sanger-type sequencing (STS), which is laborious, time-consuming, and expensive. With the emergence of Next Generation Sequencing (NGS) technologies, the body of available mtDNA data can potentially be extended much more quickly and cost-efficiently. Customized chemistries, laboratory workflows and data analysis packages could support the community and increase the utility of mtDNA analysis in forensics. We have evaluated the performance of mtGenome sequencing using the Personal Genome Machine (PGM) and compared the resulting haplotypes directly with conventional Sanger-type sequencing. A total of 64mtGenomes (>1 million bases) were established that yielded high concordance with the corresponding STS haplotypes (<0.02% differences). About two-thirds of the differences were observed in or around homopolymeric sequence stretches. In addition, the sequence alignment algorithm employed to align NGS reads played a significant role in the analysis of the data and the resulting mtDNA haplotypes. Further development of alignment software would be desirable to facilitate the application of NGS in mtDNA forensic genetics. PMID:23948325

  9. Crowdsourcing for bioinformatics

    PubMed Central

    Good, Benjamin M.; Su, Andrew I.

    2013-01-01

    Motivation: Bioinformatics is faced with a variety of problems that require human involvement. Tasks like genome annotation, image analysis, knowledge-base population and protein structure determination all benefit from human input. In some cases, people are needed in vast quantities, whereas in others, we need just a few with rare abilities. Crowdsourcing encompasses an emerging collection of approaches for harnessing such distributed human intelligence. Recently, the bioinformatics community has begun to apply crowdsourcing in a variety of contexts, yet few resources are available that describe how these human-powered systems work and how to use them effectively in scientific domains. Results: Here, we provide a framework for understanding and applying several different types of crowdsourcing. The framework considers two broad classes: systems for solving large-volume ‘microtasks’ and systems for solving high-difficulty ‘megatasks’. Within these classes, we discuss system types, including volunteer labor, games with a purpose, microtask markets and open innovation contests. We illustrate each system type with successful examples in bioinformatics and conclude with a guide for matching problems to crowdsourcing solutions that highlights the positives and negatives of different approaches. Contact: bgood@scripps.edu PMID:23782614

  10. BIOINFORMATIC INTEGRATION OF STRUCTURAL AND FUNCTIONAL GENOMICS DATA ACROSS SPECIES TO DEVELOP PORCINE INFLAMMATORY GENE REGULATORY PATHWAY INFORMATION

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Integration of structural and functional genomic data across species holds great promise in finding genes controlling disease resistance. We are investigating the porcine gut immune response to infection through gene expression profiling. We have collected porcine Affymetrix GeneChip data from RNA ...

  11. Genome-wide association study of antisocial personality disorder.

    PubMed

    Rautiainen, M-R; Paunio, T; Repo-Tiihonen, E; Virkkunen, M; Ollila, H M; Sulkava, S; Jolanki, O; Palotie, A; Tiihonen, J

    2016-01-01

    The pathophysiology of antisocial personality disorder (ASPD) remains unclear. Although the most consistent biological finding is reduced grey matter volume in the frontal cortex, about 50% of the total liability to developing ASPD has been attributed to genetic factors. The contributing genes remain largely unknown. Therefore, we sought to study the genetic background of ASPD. We conducted a genome-wide association study (GWAS) and a replication analysis of Finnish criminal offenders fulfilling DSM-IV criteria for ASPD (N=370, N=5850 for controls, GWAS; N=173, N=3766 for controls and replication sample). The GWAS resulted in suggestive associations of two clusters of single-nucleotide polymorphisms at 6p21.2 and at 6p21.32 at the human leukocyte antigen (HLA) region. Imputation of HLA alleles revealed an independent association with DRB1*01:01 (odds ratio (OR)=2.19 (1.53-3.14), P=1.9 × 10(-5)). Two polymorphisms at 6p21.2 LINC00951-LRFN2 gene region were replicated in a separate data set, and rs4714329 reached genome-wide significance (OR=1.59 (1.37-1.85), P=1.6 × 10(-9)) in the meta-analysis. The risk allele also associated with antisocial features in the general population conditioned for severe problems in childhood family (β=0.68, P=0.012). Functional analysis in brain tissue in open access GTEx and Braineac databases revealed eQTL associations of rs4714329 with LINC00951 and LRFN2 in cerebellum. In humans, LINC00951 and LRFN2 are both expressed in the brain, especially in the frontal cortex, which is intriguing considering the role of the frontal cortex in behavior and the neuroanatomical findings of reduced gray matter volume in ASPD. To our knowledge, this is the first study showing genome-wide significant and replicable findings on genetic variants associated with any personality disorder. PMID:27598967

  12. Genome-wide identification and evolutionary analysis of algal LPAT genes involved in TAG biosynthesis using bioinformatic approaches.

    PubMed

    Misra, Namrata; Panda, Prasanna Kumar; Parida, Bikram Kumar

    2014-12-01

    Lysophosphatidyl acyltransferase (LPAT) is one of the major triacylglycerol synthesis enzymes, controlling the metabolic flow of lysophosphatidic acid to phosphatidic acid. Experimental studies in Arabidopsis have shown that LPAT activity is exhibited primarily by three distinct isoforms, namely the plastid-located LPAT1, the endoplasmic reticulum-located LPAT2, and the soluble isoform of LPAT (solLPAT). In this study, 24 putative genes representing all LPAT isoforms were identified from the analysis of 11 complete genomes including green algae, red algae, diatoms and higher plants. We observed LPAT1 and solLPAT genes to be ubiquitously present in nearly all genomes examined, whereas LPAT2 genes to have evolved more recently in the plant lineage. Phylogenetic analysis indicated that LPAT1, LPAT2 and solLPAT have convergently evolved through separate evolutionary paths and belong to three different gene families, which was further evidenced by their wide divergence at gene structure and sequence level. The genome distribution supports the hypothesis that each gene encoding a LPAT is not duplicated. Mapping of exon-intron structure of LPAT genes to the domain structure of proteins across different algal and plant species indicates that exon shuffling plays no role in the evolution of LPAT genes. Besides the previously defined motifs, several conserved consensus sequences were discovered which could be useful to distinguish different LPAT isoforms. Taken together, this study will enable the generation of experimental approximations to better understand the functional role of algal LPAT in lipid accumulation. PMID:25280541

  13. [Construction and application of bioinformatic analysis platform for aquatic pathogen based on the MilkyWay-2 supercomputer].

    PubMed

    Xiang, Fang; Ningqiu, Li; Xiaozhe, Fu; Kaibin, Li; Qiang, Lin; Lihui, Liu; Cunbin, Shi; Shuqin, Wu

    2015-07-01

    As a key component of life science, bioinformatics has been widely applied in genomics, transcriptomics, and proteomics. However, the requirement of high-performance computers rather than common personal computers for constructing a bioinformatics platform significantly limited the application of bioinformatics in aquatic science. In this study, we constructed a bioinformatic analysis platform for aquatic pathogen based on the MilkyWay-2 supercomputer. The platform consisted of three functional modules, including genomic and transcriptomic sequencing data analysis, protein structure prediction, and molecular dynamics simulations. To validate the practicability of the platform, we performed bioinformatic analysis on aquatic pathogenic organisms. For example, genes of Flavobacterium johnsoniae M168 were identified and annotated via Blast searches, GO and InterPro annotations. Protein structural models for five small segments of grass carp reovirus HZ-08 were constructed by homology modeling. Molecular dynamics simulations were performed on out membrane protein A of Aeromonas hydrophila, and the changes of system temperature, total energy, root mean square deviation and conformation of the loops during equilibration were also observed. These results showed that the bioinformatic analysis platform for aquatic pathogen has been successfully built on the MilkyWay-2 supercomputer. This study will provide insights into the construction of bioinformatic analysis platform for other subjects. PMID:26351170

  14. Genome-Wide Profiling of RNA from Dried Blood Spots: Convergence with Bioinformatic Results Derived from Whole Venous Blood and Peripheral Blood Mononuclear Cells.

    PubMed

    McDade, Thomas W; M Ross, Kharah; L Fried, Ruby; Arevalo, Jesusa M G; Ma, Jeffrey; Miller, Gregory E; Cole, Steve W

    2016-01-01

    Genome-wide transcriptional profiling has emerged as a powerful tool for analyzing biological mechanisms underlying social gradients in health, but utilization in population-based studies has been hampered by logistical constraints and costs associated with venipuncture blood sampling. Dried blood spots (DBS) provide a minimally invasive, low-cost alternative to venipuncture, and in this article we evaluate how closely the substantive results from DBS transcriptional profiling correspond to those derived from parallel analyses of gold-standard venous blood samples (PAXgene whole blood and peripheral blood mononuclear cells [PBMC]). Analyses focused on differences in gene expression between African-Americans and Caucasians in a community sample of 82 healthy adults (age 18-70 years; mean 35). Across 19,679 named gene transcripts, DBS-derived values correlated r = .85 with both PAXgene and PBMC values. Results from bioinformatics analyses of gene expression derived from DBS samples were concordant with PAXgene and PBMC samples in identifying increased Type I interferon signaling and up-regulated activity of monocytes and natural killer (NK) cells in African-Americans compared to Caucasian participants. These findings demonstrate the feasibility of DBS in field-based studies of gene expression and encourage future studies of human transcriptome dynamics in larger, more representative samples than are possible with clinic- or lab-based research designs. PMID:27337553

  15. Genomic insights into ayurvedic and western approaches to personalized medicine.

    PubMed

    Prasher, Bhavana; Gibson, Greg; Mukerji, Mitali

    2016-03-01

    Ayurveda, an ancient Indian system of medicine documented and practised since 1500 B.C., follows a systems approach that has interesting parallels with contemporary personalized genomic medicine approaches to the understanding and management of health and disease. It is based on the trisutra, which are the three aspects of causes, features and therapeutics that are interconnected through a common organizing principle termed 'tridosha'. Tridosha comprise three ascertainable physiological entities; vata (kinetic), pitta (metabolic) and kapha (potential) that are pervasive across systems, work in conjunction with each other, respond to the external environment and maintain homeostasis. Each individual is born with a specific proportion of tridosha that are not only genetically determined but also influenced by the environment during foetal development. Jointly they determine a person's basic constitution, which is termed their 'prakriti'. Development and progressi on of different diseases with their subtypes are thought to depend on the origin and mechanism of perturbation of the doshas, and the aim of therapeutic practice is to ensure that the doshas retain their homeostatic state. Similarly, western systems biology epitomized by translational P4 medicine envisages the integration of multiscalar genetic, cellular, physiological and environmental networks to predict phenotypic outcomes of perturbations. In this perspective article, we aim to outline the shape of a unifying scaffold that may allow the two intellectual traditions to enhance one another. Specifically, we illustrate how a unique integrative 'Ayurgenomics' approach can be used to integrate the trisutra concept of Ayurveda with genomics. We observe biochemical and molecular correlates of prakriti and show how these differ significantly in processes that are linked to intermediate patho-phenotypes, known to take different course in diseases. We also observe a significant enr ichment of the highly connected

  16. iHOPerator: user-scripting a personalized bioinformatics Web, starting with the iHOP website

    PubMed Central

    Good, Benjamin M; Kawas, Edward A; Kuo, Byron Yu-Lin; Wilkinson, Mark D

    2006-01-01

    Background User-scripts are programs stored in Web browsers that can manipulate the content of websites prior to display in the browser. They provide a novel mechanism by which users can conveniently gain increased control over the content and the display of the information presented to them on the Web. As the Web is the primary medium by which scientists retrieve biological information, any improvements in the mechanisms that govern the utility or accessibility of this information may have profound effects. GreaseMonkey is a Mozilla Firefox extension that facilitates the development and deployment of user-scripts for the Firefox web-browser. We utilize this to enhance the content and the presentation of the iHOP (information Hyperlinked Over Proteins) website. Results The iHOPerator is a GreaseMonkey user-script that augments the gene-centred pages on iHOP by providing a compact, configurable visualization of the defining information for each gene and by enabling additional data, such as biochemical pathway diagrams, to be collected automatically from third party resources and displayed in the same browsing context. Conclusion This open-source script provides an extension to the iHOP website, demonstrating how user-scripts can personalize and enhance the Web browsing experience in a relevant biological setting. The novel, user-driven controls over the content and the display of Web resources made possible by user-scripts, such as the iHOPerator, herald the beginning of a transition from a resource-centric to a user-centric Web experience. We believe that this transition is a necessary step in the development of Web technology that will eventually result in profound improvements in the way life scientists interact with information. PMID:17173692

  17. Multifunctionality and diversity of GDSL esterase/lipase gene family in rice (Oryza sativa L. japonica) genome: new insights from bioinformatics analysis

    PubMed Central

    2012-01-01

    Background GDSL esterases/lipases are a newly discovered subclass of lipolytic enzymes that are very important and attractive research subjects because of their multifunctional properties, such as broad substrate specificity and regiospecificity. Compared with the current knowledge regarding these enzymes in bacteria, our understanding of the plant GDSL enzymes is very limited, although the GDSL gene family in plant species include numerous members in many fully sequenced plant genomes. Only two genes from a large rice GDSL esterase/lipase gene family were previously characterised, and the majority of the members remain unknown. In the present study, we describe the rice OsGELP (Oryza sativa GDSL esterase/lipase protein) gene family at the genomic and proteomic levels, and use this knowledge to provide insights into the multifunctionality of the rice OsGELP enzymes. Results In this study, an extensive bioinformatics analysis identified 114 genes in the rice OsGELP gene family. A complete overview of this family in rice is presented, including the chromosome locations, gene structures, phylogeny, and protein motifs. Among the OsGELPs and the plant GDSL esterase/lipase proteins of known functions, 41 motifs were found that represent the core secondary structure elements or appear specifically in different phylogenetic subclades. The specification and distribution of identified putative conserved clade-common and -specific peptide motifs, and their location on the predicted protein three dimensional structure may possibly signify their functional roles. Potentially important regions for substrate specificity are highlighted, in accordance with protein three-dimensional model and location of the phylogenetic specific conserved motifs. The differential expression of some representative genes were confirmed by quantitative real-time PCR. The phylogenetic analysis, together with protein motif architectures, and the expression profiling were analysed to predict the

  18. Bioinformatics Analysis of the Complete Genome Sequence of the Mango Tree Pathogen Pseudomonas syringae pv. syringae UMAF0158 Reveals Traits Relevant to Virulence and Epiphytic Lifestyle

    PubMed Central

    Arrebola, Eva; Carrión, Víctor J.; Gutiérrez-Barranquero, José Antonio; Pérez-García, Alejandro; Ramos, Cayo; Cazorla, Francisco M.; de Vicente, Antonio

    2015-01-01

    The genome sequence of more than 100 Pseudomonas syringae strains has been sequenced to date; however only few of them have been fully assembled, including P. syringae pv. syringae B728a. Different strains of pv. syringae cause different diseases and have different host specificities; so, UMAF0158 is a P. syringae pv. syringae strain related to B728a but instead of being a bean pathogen it causes apical necrosis of mango trees, and the two strains belong to different phylotypes of pv.syringae and clades of P. syringae. In this study we report the complete sequence and annotation of P. syringae pv. syringae UMAF0158 chromosome and plasmid pPSS158. A comparative analysis with the available sequenced genomes of other 25 P. syringae strains, both closed (the reference genomes DC3000, 1448A and B728a) and draft genomes was performed. The 5.8 Mb UMAF0158 chromosome has 59.3% GC content and comprises 5017 predicted protein-coding genes. Bioinformatics analysis revealed the presence of genes potentially implicated in the virulence and epiphytic fitness of this strain. We identified several genetic features, which are absent in B728a, that may explain the ability of UMAF0158 to colonize and infect mango trees: the mangotoxin biosynthetic operon mbo, a gene cluster for cellulose production, two different type III and two type VI secretion systems, and a particular T3SS effector repertoire. A mutant strain defective in the rhizobial-like T3SS Rhc showed no differences compared to wild-type during its interaction with host and non-host plants and worms. Here we report the first complete sequence of the chromosome of a pv. syringae strain pathogenic to a woody plant host. Our data also shed light on the genetic factors that possibly determine the pathogenic and epiphytic lifestyle of UMAF0158. This work provides the basis for further analysis on specific mechanisms that enable this strain to infect woody plants and for the functional analysis of host specificity in the P

  19. Bioinformatics Analysis of the Complete Genome Sequence of the Mango Tree Pathogen Pseudomonas syringae pv. syringae UMAF0158 Reveals Traits Relevant to Virulence and Epiphytic Lifestyle.

    PubMed

    Martínez-García, Pedro Manuel; Rodríguez-Palenzuela, Pablo; Arrebola, Eva; Carrión, Víctor J; Gutiérrez-Barranquero, José Antonio; Pérez-García, Alejandro; Ramos, Cayo; Cazorla, Francisco M; de Vicente, Antonio

    2015-01-01

    The genome sequence of more than 100 Pseudomonas syringae strains has been sequenced to date; however only few of them have been fully assembled, including P. syringae pv. syringae B728a. Different strains of pv. syringae cause different diseases and have different host specificities; so, UMAF0158 is a P. syringae pv. syringae strain related to B728a but instead of being a bean pathogen it causes apical necrosis of mango trees, and the two strains belong to different phylotypes of pv.syringae and clades of P. syringae. In this study we report the complete sequence and annotation of P. syringae pv. syringae UMAF0158 chromosome and plasmid pPSS158. A comparative analysis with the available sequenced genomes of other 25 P. syringae strains, both closed (the reference genomes DC3000, 1448A and B728a) and draft genomes was performed. The 5.8 Mb UMAF0158 chromosome has 59.3% GC content and comprises 5017 predicted protein-coding genes. Bioinformatics analysis revealed the presence of genes potentially implicated in the virulence and epiphytic fitness of this strain. We identified several genetic features, which are absent in B728a, that may explain the ability of UMAF0158 to colonize and infect mango trees: the mangotoxin biosynthetic operon mbo, a gene cluster for cellulose production, two different type III and two type VI secretion systems, and a particular T3SS effector repertoire. A mutant strain defective in the rhizobial-like T3SS Rhc showed no differences compared to wild-type during its interaction with host and non-host plants and worms. Here we report the first complete sequence of the chromosome of a pv. syringae strain pathogenic to a woody plant host. Our data also shed light on the genetic factors that possibly determine the pathogenic and epiphytic lifestyle of UMAF0158. This work provides the basis for further analysis on specific mechanisms that enable this strain to infect woody plants and for the functional analysis of host specificity in the P

  20. Interpretation of personal genome sequencing data in terms of disease ranks based on mutual information

    PubMed Central

    2015-01-01

    Background The rapid advances in genome sequencing technologies have resulted in an unprecedented number of genome variations being discovered in humans. However, there has been very limited coverage of interpretation of the personal genome sequencing data in terms of diseases. Methods In this paper we present the first computational analysis scheme for interpreting personal genome data by simultaneously considering the functional impact of damaging variants and curated disease-gene association data. This method is based on mutual information as a measure of the relative closeness between the personal genome and diseases. We hypothesize that a higher mutual information score implies that the personal genome is more susceptible to a particular disease than other diseases. Results The method was applied to the sequencing data of 50 acute myeloid leukemia (AML) patients in The Cancer Genome Atlas. The utility of associations between a disease and the personal genome was explored using data of healthy (control) people obtained from the 1000 Genomes Project. The ranks of the disease terms in the AML patient group were compared with those in the healthy control group using "Leukemia, Myeloid, Acute" (C04.557.337.539.550) as the corresponding MeSH disease term. The mutual information rank of the disease term was substantially higher in the AML patient group than in the healthy control group, which demonstrates that the proposed methodology can be successfully applied to infer associations between the personal genome and diseases. Conclusions Overall, the area under the receiver operating characteristics curve was significantly larger for the AML patient data than for the healthy controls. This methodology could contribute to consequential discoveries and explanations for mining personal genome sequencing data in terms of diseases, and have versatility with respect to genomic-based knowledge such as drug-gene and environmental-factor-gene interactions. PMID:26045178

  1. Genomic and bioinformatics analysis of HAdV-7, a human adenovirus of species B1 that causes acute respiratory disease: implications for vector development in human gene therapy.

    PubMed

    Purkayastha, Anjan; Su, Jing; Carlisle, Steve; Tibbetts, Clark; Seto, Donald

    2005-02-01

    Human adenovirus serotype 7 (HAdV-7) is a reemerging pathogen identified in acute respiratory disease (ARD), particularly in epidemics affecting basic military trainee populations of otherwise healthy young adults. The genome has been sequenced and annotated (GenBank accession no. ). Comparative genomics and bioinformatics analyses of the HAdV-7 genome sequence provide insight into its natural history and phylogenetic relationships. A putative origin of HAdV-7 from a chimpanzee host is observed. This has implications within the current biotechnological interest of using chimpanzee adenoviruses as vectors for human gene therapy and DNA vaccine delivery. Rapid genome sequencing and analyses of this species B1 member provide an example of exploiting accurate low-pass DNA sequencing technology in pathogen characterization and epidemic outbreak surveillance through the identification, validation, and application of unique pathogen genome signatures. PMID:15661145

  2. "Personalizing" academic medicine: opportunities and challenges in implementing genomic profiling.

    PubMed

    Tweardy, David J; Belmont, John W

    2009-12-01

    BCM faculty members spearheaded the development of a first-generation Personal Genome Profile (Baylor PGP) assay to assist physicians in diagnosing and managing patients in this new era of medicine. The principles that guided the design and implementation of the Baylor PGP were high quality, robustness, low expense, flexibility, practical clinical utility, and the ability to facilitate broad areas of clinical research. The most distinctive feature of the approach taken is an emphasis on extensive screening for rare disease-causing mutations rather than common risk-increasing polymorphisms. Because these variants have large direct effects, the ability to screen for them inexpensively could have a major immediate clinical impact in disease diagnosis, carrier detection, presymptomatic detection of late onset disease, and even prenatal diagnosis. In addition to creating a counseling tool for individual "consumers," this system will fit into the established medical record and be used by physicians involved in direct patient care. This article describes an overall framework for clinical diagnostic array genotyping and the available technologies, as well as highlights the opportunities and challenges for implementation. PMID:19931194

  3. Generations of interdisciplinarity in bioinformatics

    PubMed Central

    Bartlett, Andrew; Lewis, Jamie; Williams, Matthew L.

    2016-01-01

    Bioinformatics, a specialism propelled into relevance by the Human Genome Project and the subsequent -omic turn in the life science, is an interdisciplinary field of research. Qualitative work on the disciplinary identities of bioinformaticians has revealed the tensions involved in work in this “borderland.” As part of our ongoing work on the emergence of bioinformatics, between 2010 and 2011, we conducted a survey of United Kingdom-based academic bioinformaticians. Building on insights drawn from our fieldwork over the past decade, we present results from this survey relevant to a discussion of disciplinary generation and stabilization. Not only is there evidence of an attitudinal divide between the different disciplinary cultures that make up bioinformatics, but there are distinctions between the forerunners, founders and the followers; as inter/disciplines mature, they face challenges that are both inter-disciplinary and inter-generational in nature. PMID:27453689

  4. Bioinformatic Analyses of Integral Membrane Transport Proteins Encoded Within the Genome of the Planctomycetes species, Rhodopirellula baltica

    PubMed Central

    Paparoditis, Philipp; Vastermark, Ake; Le, Andrew J.; Fuerst, John A.; Saier, Milton H.

    2013-01-01

    Rhodopirellula baltica (R. baltica) is a Planctomycete, known to have intracellular membranes. Because of its unusual cell structure and ecological significance, we have conducted comprehensive analyses of its transmembrane transport proteins. The complete proteome of R. baltica was screened against the Transporter Classification Database (TCDB) to identify recognizable integral membrane transport proteins. 342 proteins were identified with a high degree of confidence, and these fell into several different classes. R. baltica encodes in its genome channels (12%), secondary carriers (33%), and primary active transport proteins (41%) in addition to classes represented in smaller numbers. Relative to most non-marine bacteria, R. baltica possesses a larger number of sodium-dependent symporters but fewer proton-dependent symporters, and it has dimethylsulfoxide (DMSO) and trimethyl-amine-oxide (TMAO) reductases, consistent with its Na+-rich marine environment. R. baltica also possesses a Na+-translocating NADH:quinone dehydrogenase (Na+-NDH), a Na+ efflux decarboxylase, two Na+-exporting ABC pumps, two Na+-translocating F-type ATPases, two Na+:H+ antiporters and two K+:H+ antiporters. Flagellar motility probably depends on the sodium electrochemical gradient. Surprisingly, R. baltica also has a complete set of H+-translocating electron transport complexes similar to those present in β-proteobacteria and eukaryotic mitochondria. The transport proteins identified proved to be typical of the bacterial domain with little or no indication of the presence of eukaryotic-type transporters. However, novel functionally uncharacterized multispanning membrane proteins were identified, some of which are found only in Rhodopirellula species, but others of which are widely distributed in bacteria. The analyses lead to predictions regarding the physiology, ecology and evolution of R. baltica. PMID:23969110

  5. CGAT: a model for immersive personalized training in computational genomics.

    PubMed

    Sims, David; Ponting, Chris P; Heger, Andreas

    2016-01-01

    How should the next generation of genomics scientists be trained while simultaneously pursuing high quality and diverse research? CGAT, the Computational Genomics Analysis and Training programme, was set up in 2010 by the UK Medical Research Council to complement its investment in next-generation sequencing capacity. CGAT was conceived around the twin goals of training future leaders in genome biology and medicine, and providing much needed capacity to UK science for analysing genome scale data sets. Here we outline the training programme employed by CGAT and describe how it dovetails with collaborative research projects to launch scientists on the road towards independent research careers in genomics. PMID:25981124

  6. CGAT: a model for immersive personalized training in computational genomics

    PubMed Central

    Sims, David; Ponting, Chris P.

    2016-01-01

    How should the next generation of genomics scientists be trained while simultaneously pursuing high quality and diverse research? CGAT, the Computational Genomics Analysis and Training programme, was set up in 2010 by the UK Medical Research Council to complement its investment in next-generation sequencing capacity. CGAT was conceived around the twin goals of training future leaders in genome biology and medicine, and providing much needed capacity to UK science for analysing genome scale data sets. Here we outline the training programme employed by CGAT and describe how it dovetails with collaborative research projects to launch scientists on the road towards independent research careers in genomics. PMID:25981124

  7. INTERPRETOME: A FREELY AVAILABLE, MODULAR, AND SECURE PERSONAL GENOME INTERPRETATION ENGINE

    PubMed Central

    CORDERO, PABLO; TATONETTI, NICHOLAS P.; DUDLEY, JOEL T.; SALARI, KEYAN; SNYDER, MICHAEL; ALTMAN, RUSS B.; KIM, STUART K.

    2016-01-01

    The decreasing cost of genotyping and genome sequencing has ushered in an era of genomic personalized medicine. More than 100,000 individuals have been genotyped by direct-to-consumer genetic testing services, which offer a glimpse into the interpretation and exploration of a personal genome. However, these interpretations, which require extensive manual curation, are subject to the preferences of the company and are not customizable by the individual. Academic institutions teaching personalized medicine, as well as genetic hobbyists, may prefer to customize their analysis and have full control over the content and method of interpretation. We present the Interpretome, a system for private genome interpretation, which contains all genotype information in client-side interpretation scripts, supported by server-side databases. We provide state-of-the-art analyses for teaching clinical implications of personal genomics, including disease risk assessment and pharmacogenomics. Additionally, we have implemented client-side algorithms for ancestry inference, demonstrating the power of these methods without excessive computation. Finally, the modular nature of the system allows for plugin capabilities for custom analyses. This system will allow for personal genome exploration without compromising privacy, facilitating hands-on courses in genomics and personalized medicine. PMID:22174289

  8. Microbial bioinformatics 2020.

    PubMed

    Pallen, Mark J

    2016-09-01

    Microbial bioinformatics in 2020 will remain a vibrant, creative discipline, adding value to the ever-growing flood of new sequence data, while embracing novel technologies and fresh approaches. Databases and search strategies will struggle to cope and manual curation will not be sustainable during the scale-up to the million-microbial-genome era. Microbial taxonomy will have to adapt to a situation in which most microorganisms are discovered and characterised through the analysis of sequences. Genome sequencing will become a routine approach in clinical and research laboratories, with fresh demands for interpretable user-friendly outputs. The "internet of things" will penetrate healthcare systems, so that even a piece of hospital plumbing might have its own IP address that can be integrated with pathogen genome sequences. Microbiome mania will continue, but the tide will turn from molecular barcoding towards metagenomics. Crowd-sourced analyses will collide with cloud computing, but eternal vigilance will be the price of preventing the misinterpretation and overselling of microbial sequence data. Output from hand-held sequencers will be analysed on mobile devices. Open-source training materials will address the need for the development of a skilled labour force. As we boldly go into the third decade of the twenty-first century, microbial sequence space will remain the final frontier! PMID:27471065

  9. Personal Genome Sequencing in Ostensibly Healthy Individuals and the PeopleSeq Consortium

    PubMed Central

    Linderman, Michael D.; Nielsen, Daiva E.; Green, Robert C.

    2016-01-01

    Thousands of ostensibly healthy individuals have had their exome or genome sequenced, but a much smaller number of these individuals have received any personal genomic results from that sequencing. We term those projects in which ostensibly healthy participants can receive sequencing-derived genetic findings and may also have access to their genomic data as participatory predispositional personal genome sequencing (PPGS). Here we are focused on genome sequencing applied in a pre-symptomatic context and so define PPGS to exclude diagnostic genome sequencing intended to identify the molecular cause of suspected or diagnosed genetic disease. In this report we describe the design of completed and underway PPGS projects, briefly summarize the results reported to date and introduce the PeopleSeq Consortium, a newly formed collaboration of PPGS projects designed to collect much-needed longitudinal outcome data. PMID:27023617

  10. Informing the Design of Direct-to-Consumer Interactive Personal Genomics Reports

    PubMed Central

    Shaer, Orit; Okerlund, Johanna; Balestra, Martina; Stowell, Elizabeth; Ascher, Laura; Bi, Joanna; Schlenker, Claire; Ball, Madeleine

    2015-01-01

    Background In recent years, people who sought direct-to-consumer genetic testing services have been increasingly confronted with an unprecedented amount of personal genomic information, which influences their decisions, emotional state, and well-being. However, these users of direct-to-consumer genetic services, who vary in their education and interests, frequently have little relevant experience or tools for understanding, reasoning about, and interacting with their personal genomic data. Online interactive techniques can play a central role in making personal genomic data useful for these users. Objective We sought to (1) identify the needs of diverse users as they make sense of their personal genomic data, (2) consequently develop effective interactive visualizations of genomic trait data to address these users’ needs, and (3) evaluate the effectiveness of the developed visualizations in facilitating comprehension. Methods The first two user studies, conducted with 63 volunteers in the Personal Genome Project and with 36 personal genomic users who participated in a design workshop, respectively, employed surveys and interviews to identify the needs and expectations of diverse users. Building on the two initial studies, the third study was conducted with 730 Amazon Mechanical Turk users and employed a controlled experimental design to examine the effectiveness of different design interventions on user comprehension. Results The first two studies identified searching, comparing, sharing, and organizing data as fundamental to users’ understanding of personal genomic data. The third study demonstrated that interactive and visual design interventions could improve the understandability of personal genomic reports for consumers. In particular, results showed that a new interactive bubble chart visualization designed for the study resulted in the highest comprehension scores, as well as the highest perceived comprehension scores. These scores were significantly

  11. Privacy Preserving PCA on Distributed Bioinformatics Datasets

    ERIC Educational Resources Information Center

    Li, Xin

    2011-01-01

    In recent years, new bioinformatics technologies, such as gene expression microarray, genome-wide association study, proteomics, and metabolomics, have been widely used to simultaneously identify a huge number of human genomic/genetic biomarkers, generate a tremendously large amount of data, and dramatically increase the knowledge on human…

  12. Motivations and Perceptions of Early Adopters of Personalized Genomics: Perspectives from Research Participants

    PubMed Central

    Gollust, S.E.; Gordon, E.S.; Zayac, C.; Griffin, G.; Christman, M.F.; Pyeritz, R.E.; Wawak, L.; Bernhardt, B.A.

    2011-01-01

    Background/Aims: To predict the potential public health impact of personal genomics, empirical research on public perceptions of these services is needed. In this study, ‘early adopters’ of personal genomics were surveyed to assess their motivations, perceptions and intentions. Methods: Participants were recruited from everyone who registered to attend an enrollment event for the Coriell Personalized Medicine Collaborative, a United States-based (Camden, N.J.) research study of the utility of personalized medicine, between March 31, 2009 and April 1, 2010 (n = 369). Participants completed an Internet-based survey about their motivations, awareness of personalized medicine, perceptions of study risks and benefits, and intentions to share results with health care providers. Results: Respondents were motivated to participate for their own curiosity and to find out their disease risk to improve their health. Fewer than 10% expressed deterministic perspectives about genetic risk, but 32% had misperceptions about the research study or personal genomic testing. Most respondents perceived the study to have health-related benefits. Nearly all (92%) intended to share their results with physicians, primarily to request specific medical recommendations. Conclusion: Early adopters of personal genomics are prospectively enthusiastic about using genomic profiling information to improve their health, in close consultation with their physicians. This suggests that early users (i.e. through direct-to-consumer companies or research) may follow up with the health care system. Further research should address whether intentions to seek care match actual behaviors. PMID:21654153

  13. Integrating Genomics into Clinical Oncology: Ethical and Social Challenges from Proponents of Personalized Medicine

    PubMed Central

    Settersten, Richard A.; Juengst, Eric T.; Fishman, Jennifer R.

    2013-01-01

    Summary The use of molecular tools to individualize health care, predict appropriate therapies and prevent adverse health outcomes has gained significant traction in the field of oncology, under the banner of “personalized medicine.” Enthusiasm for personalized medicine in oncology has been fueled by success stories of targeted treatments for a variety of cancers based on their molecular profiles. Though these are clear indications of optimism for personalized medicine, little is known about the ethical and social implications of personalized approaches in clinical oncology. The objective of this study is to assess how a range of stakeholders engaged in promoting, monitoring, and providing personalized medicine understand the challenges of integrating genomic testing and targeted therapies into clinical oncology. The study involved the analysis of in-depth interviews with 117 basic scientists, clinician-researchers, clinicians in private practice, health professional educators, representatives of funding agencies, medical journal editors, entrepreneurs, and insurers whose experiences and perspectives on personalized medicine span a wide variety of institutional and professional settings. Despite considerable enthusiasm for this shift, promoters, monitors and providers of personalized medicine identified four domains which will still provoke heightened ethical and social concerns: (1) informed consent for cancer genomic testing, (2) privacy, confidentiality, and disclosure of genomic test results, (3) access to genomic testing and targeted therapies in oncology, and (4) the costs of scaling up pharmacogenomic testing and targeted cancer therapies. These specific concerns are not unique to oncology, or even genomics. However, those most invested in the success of personalized medicine view oncologists’ responses to these challenges as precedent-setting because oncology is farther along the path of clinical integration of genomic technologies than other fields

  14. What can whole genome expression data tell us about the ecology and evolution of personality?

    PubMed Central

    Bell, Alison M.; Aubin-Horth, Nadia

    2010-01-01

    Consistent individual differences in behaviour, aka personality, pose several evolutionary questions. For example, it is difficult to explain within-individual consistency in behaviour because behavioural plasticity is often advantageous. In addition, selection erodes heritable behavioural variation that is related to fitness, therefore we wish to know the mechanisms that can maintain between-individual variation in behaviour. In this paper, we argue that whole genome expression data can reveal new insights into the proximate mechanisms underlying personality, as well as its evolutionary consequences. After introducing the basics of whole genome expression analysis, we show how whole genome expression data can be used to understand whether behaviours in different contexts are affected by the same molecular mechanisms. We suggest strategies for using the power of genomics to understand what maintains behavioural variation, to study the evolution of behavioural correlations and to compare personality traits across diverse organisms. PMID:21078652

  15. Bioinformatics and Moonlighting Proteins

    PubMed Central

    Hernández, Sergio; Franco, Luís; Calvo, Alejandra; Ferragut, Gabriela; Hermoso, Antoni; Amela, Isaac; Gómez, Antonio; Querol, Enrique; Cedano, Juan

    2015-01-01

    Multitasking or moonlighting is the capability of some proteins to execute two or more biochemical functions. Usually, moonlighting proteins are experimentally revealed by serendipity. For this reason, it would be helpful that Bioinformatics could predict this multifunctionality, especially because of the large amounts of sequences from genome projects. In the present work, we analyze and describe several approaches that use sequences, structures, interactomics, and current bioinformatics algorithms and programs to try to overcome this problem. Among these approaches are (a) remote homology searches using Psi-Blast, (b) detection of functional motifs and domains, (c) analysis of data from protein–protein interaction databases (PPIs), (d) match the query protein sequence to 3D databases (i.e., algorithms as PISITE), and (e) mutation correlation analysis between amino acids by algorithms as MISTIC. Programs designed to identify functional motif/domains detect mainly the canonical function but usually fail in the detection of the moonlighting one, Pfam and ProDom being the best methods. Remote homology search by Psi-Blast combined with data from interactomics databases (PPIs) has the best performance. Structural information and mutation correlation analysis can help us to map the functional sites. Mutation correlation analysis can only be used in very specific situations – it requires the existence of multialigned family protein sequences – but can suggest how the evolutionary process of second function acquisition took place. The multitasking protein database MultitaskProtDB (http://wallace.uab.es/multitask/), previously published by our group, has been used as a benchmark for the all of the analyses. PMID:26157797

  16. Bioinformatics and Moonlighting Proteins.

    PubMed

    Hernández, Sergio; Franco, Luís; Calvo, Alejandra; Ferragut, Gabriela; Hermoso, Antoni; Amela, Isaac; Gómez, Antonio; Querol, Enrique; Cedano, Juan

    2015-01-01

    Multitasking or moonlighting is the capability of some proteins to execute two or more biochemical functions. Usually, moonlighting proteins are experimentally revealed by serendipity. For this reason, it would be helpful that Bioinformatics could predict this multifunctionality, especially because of the large amounts of sequences from genome projects. In the present work, we analyze and describe several approaches that use sequences, structures, interactomics, and current bioinformatics algorithms and programs to try to overcome this problem. Among these approaches are (a) remote homology searches using Psi-Blast, (b) detection of functional motifs and domains, (c) analysis of data from protein-protein interaction databases (PPIs), (d) match the query protein sequence to 3D databases (i.e., algorithms as PISITE), and (e) mutation correlation analysis between amino acids by algorithms as MISTIC. Programs designed to identify functional motif/domains detect mainly the canonical function but usually fail in the detection of the moonlighting one, Pfam and ProDom being the best methods. Remote homology search by Psi-Blast combined with data from interactomics databases (PPIs) has the best performance. Structural information and mutation correlation analysis can help us to map the functional sites. Mutation correlation analysis can only be used in very specific situations - it requires the existence of multialigned family protein sequences - but can suggest how the evolutionary process of second function acquisition took place. The multitasking protein database MultitaskProtDB (http://wallace.uab.es/multitask/), previously published by our group, has been used as a benchmark for the all of the analyses. PMID:26157797

  17. Basic principles of yeast genomics, a personal recollection.

    PubMed

    Dujon, Bernard

    2015-08-01

    The genomes of many yeast species or strain isolates have now been sequenced with an accelerating momentum that quickly relegates initial data to history, albeit that they are less than two decades old. Today, novel yeast genomes are entirely sequenced for a variety of reasons, often only to identify a few expected genes of specific interest, thus providing a wealth of data, heterogenous in quality and completion but informative about the origin and evolution of this heterogeneous collection of unicellular modern fungi. However, how many scientists fully appreciate the important conceptual and technological roles played by yeasts in the extraordinary development of today's genomics? Novel notions of general significance emerged from the very first eukaryote sequenced, Saccharomyces cerevisiae, and were successively refined and extended over time. Tools with general applications were originally developed with this yeast; and surprises emerged from the results. Here, I have tried to recollect the gradual building up of knowledge as yeast genomics developed, and then briefly summarize our present views about the basic nature of yeast genomes, based on the most recent data. PMID:26071597

  18. Simultaneous Whole Mitochondrial Genome Sequencing with Short Overlapping Amplicons Suitable for Degraded DNA Using the Ion Torrent Personal Genome Machine.

    PubMed

    Chaitanya, Lakshmi; Ralf, Arwin; van Oven, Mannis; Kupiec, Tomasz; Chang, Joseph; Lagacé, Robert; Kayser, Manfred

    2015-12-01

    Whole mitochondrial (mt) genome analysis enables a considerable increase in analysis throughput, and improves the discriminatory power to the maximum possible phylogenetic resolution. Most established protocols on the different massively parallel sequencing (MPS) platforms, however, invariably involve the PCR amplification of large fragments, typically several kilobases in size, which may fail due to mtDNA fragmentation in the available degraded materials. We introduce a MPS tiling approach for simultaneous whole human mt genome sequencing using 161 short overlapping amplicons (average 200 bp) with the Ion Torrent Personal Genome Machine. We illustrate the performance of this new method by sequencing 20 DNA samples belonging to different worldwide mtDNA haplogroups. Additional quality control, particularly regarding the potential detection of nuclear insertions of mtDNA (NUMTs), was performed by comparative MPS analysis using the conventional long-range amplification method. Preliminary sensitivity testing revealed that detailed haplogroup inference was feasible with 100 pg genomic input DNA. Complete mt genome coverage was achieved from DNA samples experimentally degraded down to genomic fragment sizes of about 220 bp, and up to 90% coverage from naturally degraded samples. Overall, we introduce a new approach for whole mt genome MPS analysis from degraded and nondegraded materials relevant to resolve and infer maternal genetic ancestry at complete resolution in anthropological, evolutionary, medical, and forensic applications. PMID:26387877

  19. [Ethical issues of personal genome: a legal perspective--ethical and legal ramifications of personal genome research].

    PubMed

    Maruyama, Eiji

    2009-06-01

    Whole-genome research projects, especially those involving whole-genome sequencing, tend to raise intractable ethical and legal challenges. In this kind of research, genetic and genomic data obtained by typing or sequencing are usually put in open or limited access scientific databases on the Internet to promote studies by many researchers. Once data become available on the Internet, it will be virtually meaningless to withdraw the information, effectively nullifying participants' right to revoke consent. Although the author favors the governance system that will assure research subjects of the right to withdraw their participation, considering these characteristics of whole-genome research, he finds those recommendations offered in Caulfield T, et al: Research ethics recommendations for whole-genome research: Consensus statement. PLoS Biol 6(3): e73(2008), especially to the effect that the consent process should include information about data security and the governance structure and, in particular, the mechanism for considering future research protocols, well reasoned and acceptable. PMID:19507516

  20. An integrated framework of personalized medicine: from individual genomes to participatory health care.

    PubMed

    Evers, Andrea W M; Rovers, Maroeska M; Kremer, Jan A M; Veltman, Joris A; Schalken, Jack A; Bloem, Bas R; van Gool, Alain J

    2012-08-01

    Promising research developments in both basic and applied sciences, such as genomics and participatory health care approaches, have generated widespread interest in personalized medicine among almost all scientific areas and clinicians. The term personalized medicine is, however, frequently used without defining a clear theoretical and methodological background. In addition, to date most personalized medicine approaches still lack convincing empirical evidence regarding their contribution and advantages in comparison to traditional models. Here, we propose that personalized medicine can only fulfill the promise of optimizing our health care system by an interdisciplinary and translational view that extends beyond traditional diagnostic and classification systems. PMID:22911520

  1. Getting Personal: Head and Neck Cancer Management in the Era of Genomic Medicine

    PubMed Central

    Birkeland, Andrew C.; Uhlmann, Wendy R.; Brenner, J. Chad; Shuman, Andrew G.

    2015-01-01

    Background Genetic testing is rapidly becoming an important tool in the management of patients with head and neck cancer. As we enter the era of genomics and personalized medicine, providers should be aware of testing options, counseling resources, and the benefits, limitations and future of personalized therapy. Methods This manuscript offers a primer to assist clinicians treating patients in anticipating and managing the inherent practical and ethical challenges of cancer care in the genomic era. Results Clinical applications of genomics for head and neck cancer are emerging. We discuss the indications for genetic testing, types of testing available, implications for care, privacy/disclosure concerns and ethical considerations. Hereditary genetic syndromes associated with head and neck neoplasms are reviewed, and online genetics resources are provided. Conclusions This article summarizes and contextualizes the evolving diagnostic and therapeutic options that impact the care of patients with head and neck cancer in the genomic era. PMID:25995036

  2. Computational Biology and Bioinformatics in Nigeria

    PubMed Central

    Fatumo, Segun A.; Adoga, Moses P.; Ojo, Opeolu O.; Oluwagbemi, Olugbenga; Adeoye, Tolulope; Ewejobi, Itunuoluwa; Adebiyi, Marion; Adebiyi, Ezekiel; Bewaji, Clement; Nashiru, Oyekanmi

    2014-01-01

    Over the past few decades, major advances in the field of molecular biology, coupled with advances in genomic technologies, have led to an explosive growth in the biological data generated by the scientific community. The critical need to process and analyze such a deluge of data and turn it into useful knowledge has caused bioinformatics to gain prominence and importance. Bioinformatics is an interdisciplinary research area that applies techniques, methodologies, and tools in computer and information science to solve biological problems. In Nigeria, bioinformatics has recently played a vital role in the advancement of biological sciences. As a developing country, the importance of bioinformatics is rapidly gaining acceptance, and bioinformatics groups comprised of biologists, computer scientists, and computer engineers are being constituted at Nigerian universities and research institutes. In this article, we present an overview of bioinformatics education and research in Nigeria. We also discuss professional societies and academic and research institutions that play central roles in advancing the discipline in Nigeria. Finally, we propose strategies that can bolster bioinformatics education and support from policy makers in Nigeria, with potential positive implications for other developing countries. PMID:24763310

  3. Genome Science and Personalized Cancer Treatment (LBNL Summer Lecture Series)

    ScienceCinema

    Gray, Joe

    2011-04-28

    Summer Lecture Series 2009: Results from the Human Genome Project are enabling scientists to understand how individual cancers form and progress. This information, when combined with newly developed drugs, can optimize the treatment of individual cancers. Joe Gray, director of Berkeley Labs Life Sciences Division and Associate Laboratory Director for Life and Environmental Sciences, will focus on this approach, its promise, and its current roadblocks ? particularly with regard to breast cancer.

  4. Genome Science and Personalized Cancer Treatment (LBNL Summer Lecture Series)

    SciTech Connect

    Gray, Joe

    2009-08-04

    Summer Lecture Series 2009: Results from the Human Genome Project are enabling scientists to understand how individual cancers form and progress. This information, when combined with newly developed drugs, can optimize the treatment of individual cancers. Joe Gray, director of Berkeley Labs Life Sciences Division and Associate Laboratory Director for Life and Environmental Sciences, will focus on this approach, its promise, and its current roadblocks — particularly with regard to breast cancer.

  5. Attitudes towards personal genomics among older Swiss adults: An exploratory study

    PubMed Central

    Mählmann, Laura; Röcke, Christina; Brand, Angela; Hafen, Ernst; Vayena, Effy

    2016-01-01

    Objectives To explore attitudes of Swiss older adults towards personal genomics (PG). Methods Using an anonymized voluntary paper-and-pencil survey, data were collected from 151 men and women aged 60–89 years attending the Seniorenuniversität Zurich, Switzerland (Seniors' University). Analyses were conducted using descriptive and inferential statistics. Results One third of the respondents were aware of PG, and more than half indicated interest in undergoing PG testing. The primary motivation provided was respondents' interest in finding out about their own disease risk, followed by willingness to contribute to scientific research. Forty-four percent were not interested in undergoing testing because results might be worrisome, or due to concerns about the validity of the results. Only a minority of respondents mentioned privacy-related concerns. Further, 66% were interested in undergoing clinic-based PG motivated by the opportunity to contribute to scientific research (78%) and 75% of all study participants indicated strong preferences to donate genomic data to public research institutions. Conclusion This study indicates a relatively positive overall attitude towards personal genomic testing among older Swiss adults, a group not typically represented in surveys about personal genomics. Genomic data of older adults can be highly relevant to late life health and maintenance of quality of life. In addition they can be an invaluable source for better understanding of longevity, health and disease. Understanding the attitudes of this population towards genomic analyses, although important, remains under-examined. PMID:27047754

  6. Personal genome testing: Test characteristics to clarify the discourse on ethical, legal and societal issues

    PubMed Central

    2011-01-01

    Background As genetics technology proceeds, practices of genetic testing have become more heterogeneous: many different types of tests are finding their way to the public in different settings and for a variety of purposes. This diversification is relevant to the discourse on ethical, legal and societal issues (ELSI) surrounding genetic testing, which must evolve to encompass these differences. One important development is the rise of personal genome testing on the basis of genetic profiling: the testing of multiple genetic variants simultaneously for the prediction of common multifactorial diseases. Currently, an increasing number of companies are offering personal genome tests directly to consumers and are spurring ELSI-discussions, which stand in need of clarification. This paper presents a systematic approach to the ELSI-evaluation of personal genome testing for multifactorial diseases along the lines of its test characteristics. Discussion This paper addresses four test characteristics of personal genome testing: its being a non-targeted type of testing, its high analytical validity, low clinical validity and problematic clinical utility. These characteristics raise their own specific ELSI, for example: non-targeted genetic profiling poses serious problems for information provision and informed consent. Questions about the quantity and quality of the necessary information, as well as about moral responsibilities with regard to the provision of information are therefore becoming central themes within ELSI-discussions of personal genome testing. Further, the current low level of clinical validity of genetic profiles raises questions concerning societal risks and regulatory requirements, whereas simultaneously it causes traditional ELSI-issues of clinical genetics, such as psychological and health risks, discrimination, and stigmatization, to lose part of their relevance. Also, classic notions of clinical utility are challenged by the newer notion of 'personal

  7. Population genetic inference from personal genome data: impact of ancestry and admixture on human genomic variation.

    PubMed

    Kidd, Jeffrey M; Gravel, Simon; Byrnes, Jake; Moreno-Estrada, Andres; Musharoff, Shaila; Bryc, Katarzyna; Degenhardt, Jeremiah D; Brisbin, Abra; Sheth, Vrunda; Chen, Rong; McLaughlin, Stephen F; Peckham, Heather E; Omberg, Larsson; Bormann Chung, Christina A; Stanley, Sarah; Pearlstein, Kevin; Levandowsky, Elizabeth; Acevedo-Acevedo, Suehelay; Auton, Adam; Keinan, Alon; Acuña-Alonzo, Victor; Barquera-Lozano, Rodrigo; Canizales-Quinteros, Samuel; Eng, Celeste; Burchard, Esteban G; Russell, Archie; Reynolds, Andy; Clark, Andrew G; Reese, Martin G; Lincoln, Stephen E; Butte, Atul J; De La Vega, Francisco M; Bustamante, Carlos D

    2012-10-01

    Full sequencing of individual human genomes has greatly expanded our understanding of human genetic variation and population history. Here, we present a systematic analysis of 50 human genomes from 11 diverse global populations sequenced at high coverage. Our sample includes 12 individuals who have admixed ancestry and who have varying degrees of recent (within the last 500 years) African, Native American, and European ancestry. We found over 21 million single-nucleotide variants that contribute to a 1.75-fold range in nucleotide heterozygosity across diverse human genomes. This heterozygosity ranged from a high of one heterozygous site per kilobase in west African genomes to a low of 0.57 heterozygous sites per kilobase in segments inferred to have diploid Native American ancestry from the genomes of Mexican and Puerto Rican individuals. We show evidence of all three continental ancestries in the genomes of Mexican, Puerto Rican, and African American populations, and the genome-wide statistics are highly consistent across individuals from a population once ancestry proportions have been accounted for. Using a generalized linear model, we identified subtle variations across populations in the proportion of neutral versus deleterious variation and found that genome-wide statistics vary in admixed populations even once ancestry proportions have been factored in. We further infer that multiple periods of gene flow shaped the diversity of admixed populations in the Americas-70% of the European ancestry in today's African Americans dates back to European gene flow happening only 7-8 generations ago. PMID:23040495

  8. Population Genetic Inference from Personal Genome Data: Impact of Ancestry and Admixture on Human Genomic Variation

    PubMed Central

    Kidd, Jeffrey M.; Gravel, Simon; Byrnes, Jake; Moreno-Estrada, Andres; Musharoff, Shaila; Bryc, Katarzyna; Degenhardt, Jeremiah D.; Brisbin, Abra; Sheth, Vrunda; Chen, Rong; McLaughlin, Stephen F.; Peckham, Heather E.; Omberg, Larsson; Bormann Chung, Christina A.; Stanley, Sarah; Pearlstein, Kevin; Levandowsky, Elizabeth; Acevedo-Acevedo, Suehelay; Auton, Adam; Keinan, Alon; Acuña-Alonzo, Victor; Barquera-Lozano, Rodrigo; Canizales-Quinteros, Samuel; Eng, Celeste; Burchard, Esteban G.; Russell, Archie; Reynolds, Andy; Clark, Andrew G.; Reese, Martin G.; Lincoln, Stephen E.; Butte, Atul J.; De La Vega, Francisco M.; Bustamante, Carlos D.

    2012-01-01

    Full sequencing of individual human genomes has greatly expanded our understanding of human genetic variation and population history. Here, we present a systematic analysis of 50 human genomes from 11 diverse global populations sequenced at high coverage. Our sample includes 12 individuals who have admixed ancestry and who have varying degrees of recent (within the last 500 years) African, Native American, and European ancestry. We found over 21 million single-nucleotide variants that contribute to a 1.75-fold range in nucleotide heterozygosity across diverse human genomes. This heterozygosity ranged from a high of one heterozygous site per kilobase in west African genomes to a low of 0.57 heterozygous sites per kilobase in segments inferred to have diploid Native American ancestry from the genomes of Mexican and Puerto Rican individuals. We show evidence of all three continental ancestries in the genomes of Mexican, Puerto Rican, and African American populations, and the genome-wide statistics are highly consistent across individuals from a population once ancestry proportions have been accounted for. Using a generalized linear model, we identified subtle variations across populations in the proportion of neutral versus deleterious variation and found that genome-wide statistics vary in admixed populations even once ancestry proportions have been factored in. We further infer that multiple periods of gene flow shaped the diversity of admixed populations in the Americas—70% of the European ancestry in today’s African Americans dates back to European gene flow happening only 7–8 generations ago. PMID:23040495

  9. Bioinformatics in protein analysis.

    PubMed

    Persson, B

    2000-01-01

    The chapter gives an overview of bioinformatic techniques of importance in protein analysis. These include database searches, sequence comparisons and structural predictions. Links to useful World Wide Web (WWW) pages are given in relation to each topic. Databases with biological information are reviewed with emphasis on databases for nucleotide sequences (EMBL, GenBank, DDBJ), genomes, amino acid sequences (Swissprot, PIR, TrEMBL, GenePept), and three-dimensional structures (PDB). Integrated user interfaces for databases (SRS and Entrez) are described. An introduction to databases of sequence patterns and protein families is also given (Prosite, Pfam, Blocks). Furthermore, the chapter describes the widespread methods for sequence comparisons, FASTA and BLAST, and the corresponding WWW services. The techniques involving multiple sequence alignments are also reviewed: alignment creation with the Clustal programs, phylogenetic tree calculation with the Clustal or Phylip packages and tree display using Drawtree, njplot or phylo_win. Finally, the chapter also treats the issue of structural prediction. Different methods for secondary structure predictions are described (Chou-Fasman, Garnier-Osguthorpe-Robson, Predator, PHD). Techniques for predicting membrane proteins, antigenic sites and postranslational modifications are also reviewed. PMID:10803381

  10. A Survey of Scholarly Literature Describing the Field of Bioinformatics Education and Bioinformatics Educational Research

    PubMed Central

    Taleyarkhan, Manaz; Alvarado, Daniela Rivera; Kane, Michael; Springer, John; Clase, Kari

    2014-01-01

    Bioinformatics education can be broadly defined as the teaching and learning of the use of computer and information technology, along with mathematical and statistical analysis for gathering, storing, analyzing, interpreting, and integrating data to solve biological problems. The recent surge of genomics, proteomics, and structural biology in the potential advancement of research and development in complex biomedical systems has created a need for an educated workforce in bioinformatics. However, effectively integrating bioinformatics education through formal and informal educational settings has been a challenge due in part to its cross-disciplinary nature. In this article, we seek to provide an overview of the state of bioinformatics education. This article identifies: 1) current approaches of bioinformatics education at the undergraduate and graduate levels; 2) the most common concepts and skills being taught in bioinformatics education; 3) pedagogical approaches and methods of delivery for conveying bioinformatics concepts and skills; and 4) assessment results on the impact of these programs, approaches, and methods in students’ attitudes or learning. Based on these findings, it is our goal to describe the landscape of scholarly work in this area and, as a result, identify opportunities and challenges in bioinformatics education. PMID:25452484

  11. A survey of scholarly literature describing the field of bioinformatics education and bioinformatics educational research.

    PubMed

    Magana, Alejandra J; Taleyarkhan, Manaz; Alvarado, Daniela Rivera; Kane, Michael; Springer, John; Clase, Kari

    2014-01-01

    Bioinformatics education can be broadly defined as the teaching and learning of the use of computer and information technology, along with mathematical and statistical analysis for gathering, storing, analyzing, interpreting, and integrating data to solve biological problems. The recent surge of genomics, proteomics, and structural biology in the potential advancement of research and development in complex biomedical systems has created a need for an educated workforce in bioinformatics. However, effectively integrating bioinformatics education through formal and informal educational settings has been a challenge due in part to its cross-disciplinary nature. In this article, we seek to provide an overview of the state of bioinformatics education. This article identifies: 1) current approaches of bioinformatics education at the undergraduate and graduate levels; 2) the most common concepts and skills being taught in bioinformatics education; 3) pedagogical approaches and methods of delivery for conveying bioinformatics concepts and skills; and 4) assessment results on the impact of these programs, approaches, and methods in students' attitudes or learning. Based on these findings, it is our goal to describe the landscape of scholarly work in this area and, as a result, identify opportunities and challenges in bioinformatics education. PMID:25452484

  12. Sequencing and analysis of a South Asian-Indian personal genome

    PubMed Central

    2012-01-01

    Background With over 1.3 billion people, India is estimated to contain three times more genetic diversity than does Europe. Next-generation sequencing technologies have facilitated the understanding of diversity by enabling whole genome sequencing at greater speed and lower cost. While genomes from people of European and Asian descent have been sequenced, only recently has a single male genome from the Indian subcontinent been published at sufficient depth and coverage. In this study we have sequenced and analyzed the genome of a South Asian Indian female (SAIF) from the Indian state of Kerala. Results We identified over 3.4 million SNPs in this genome including over 89,873 private variations. Comparison of the SAIF genome with several published personal genomes revealed that this individual shared ~50% of the SNPs with each of these genomes. Analysis of the SAIF mitochondrial genome showed that it was closely related to the U1 haplogroup which has been previously observed in Kerala. We assessed the SAIF genome for SNPs with health and disease consequences and found that the individual was at a higher risk for multiple sclerosis and a few other diseases. In analyzing SNPs that modulate drug response, we found a variation that predicts a favorable response to metformin, a drug used to treat diabetes. SNPs predictive of adverse reaction to warfarin indicated that the SAIF individual is not at risk for bleeding if treated with typical doses of warfarin. In addition, we report the presence of several additional SNPs of medical relevance. Conclusions This is the first study to report the complete whole genome sequence of a female from the state of Kerala in India. The availability of this complete genome and variants will further aid studies aimed at understanding genetic diversity, identifying clinically relevant changes and assessing disease burden in the Indian population. PMID:22938532

  13. openSNP–A Crowdsourced Web Resource for Personal Genomics

    PubMed Central

    Greshake, Bastian; Bayer, Philipp E.; Rausch, Helge; Reda, Julia

    2014-01-01

    Genome-Wide Association Studies are widely used to correlate phenotypic traits with genetic variants. These studies usually compare the genetic variation between two groups to single out certain Single Nucleotide Polymorphisms (SNPs) that are linked to a phenotypic variation in one of the groups. However, it is necessary to have a large enough sample size to find statistically significant correlations. Direct-To-Consumer (DTC) genetic testing can supply additional data: DTC-companies offer the analysis of a large amount of SNPs for an individual at low cost without the need to consult a physician or geneticist. Over 100,000 people have already been genotyped through Direct-To-Consumer genetic testing companies. However, this data is not public for a variety of reasons and thus cannot be used in research. It seems reasonable to create a central open data repository for such data. Here we present the web platform openSNP, an open database which allows participants of Direct-To-Consumer genetic testing to publish their genetic data at no cost along with phenotypic information. Through this crowdsourced effort of collecting genetic and phenotypic information, openSNP has become a resource for a wide area of studies, including Genome-Wide Association Studies. openSNP is hosted at http://www.opensnp.org, and the code is released under MIT-license at http://github.com/gedankenstuecke/snpr. PMID:24647222

  14. Bioinformatics in the information age

    SciTech Connect

    Spengler, Sylvia J.

    2000-02-01

    There is a well-known story about the blind man examining the elephant: the part of the elephant examined determines his perception of the whole beast. Perhaps bioinformatics--the shotgun marriage between biology and mathematics, computer science, and engineering--is like an elephant that occupies a large chair in the scientific living room. Given the demand for and shortage of researchers with the computer skills to handle large volumes of biological data, where exactly does the bioinformatics elephant sit? There are probably many biologists who feel that a major product of this bioinformatics elephant is large piles of waste material. If you have tried to plow through Web sites and software packages in search of a specific tool for analyzing and collating large amounts of research data, you may well feel the same way. But there has been progress with major initiatives to develop more computing power, educate biologists about computers, increase funding, and set standards. For our purposes, bioinformatics is not simply a biologically inclined rehash of information theory (1) nor is it a hodgepodge of computer science techniques for building, updating, and accessing biological data. Rather bioinformatics incorporates both of these capabilities into a broad interdisciplinary science that involves both conceptual and practical tools for the understanding, generation, processing, and propagation of biological information. As such, bioinformatics is the sine qua non of 21st-century biology. Analyzing gene expression using cDNA microarrays immobilized on slides or other solid supports (gene chips) is set to revolutionize biology and medicine and, in so doing, generate vast quantities of data that have to be accurately interpreted (Fig. 1). As discussed at a meeting a few months ago (Microarray Algorithms and Statistical Analysis: Methods and Standards; Tahoe City, California; 9-12 November 1999), experiments with cDNA arrays must be subjected to quality control

  15. The origins of bioinformatics.

    PubMed

    Hagen, J B

    2000-12-01

    Bioinformatics is often described as being in its infancy, but computers emerged as important tools in molecular biology during the early 1960s. A decade before DNA sequencing became feasible, computational biologists focused on the rapidly accumulating data from protein biochemistry. Without the benefits of super computers or computer networks, these scientists laid important conceptual and technical foundations for bioinformatics today. PMID:11252753

  16. BreCAN-DB: a repository cum browser of personalized DNA breakpoint profiles of cancer genomes

    PubMed Central

    Narang, Pankaj; Dhapola, Parashar; Chowdhury, Shantanu

    2016-01-01

    BreCAN-DB (http://brecandb.igib.res.in) is a repository cum browser of whole genome somatic DNA breakpoint profiles of cancer genomes, mapped at single nucleotide resolution using deep sequencing data. These breakpoints are associated with deletions, insertions, inversions, tandem duplications, translocations and a combination of these structural genomic alterations. The current release of BreCAN-DB features breakpoint profiles from 99 cancer-normal pairs, comprising five cancer types. We identified DNA breakpoints across genomes using high-coverage next-generation sequencing data obtained from TCGA and dbGaP. Further, in these cancer genomes, we methodically identified breakpoint hotspots which were significantly enriched with somatic structural alterations. To visualize the breakpoint profiles, a next-generation genome browser was integrated with BreCAN-DB. Moreover, we also included previously reported breakpoint profiles from 138 cancer-normal pairs, spanning 10 cancer types into the browser. Additionally, BreCAN-DB allows one to identify breakpoint hotspots in user uploaded data set. We have also included a functionality to query overlap of any breakpoint profile with regions of user's interest. Users can download breakpoint profiles from the database or may submit their data to be integrated in BreCAN-DB. We believe that BreCAN-DB will be useful resource for genomics scientific community and is a step towards personalized cancer genomics. PMID:26586806

  17. BreCAN-DB: a repository cum browser of personalized DNA breakpoint profiles of cancer genomes.

    PubMed

    Narang, Pankaj; Dhapola, Parashar; Chowdhury, Shantanu

    2016-01-01

    BreCAN-DB (http://brecandb.igib.res.in) is a repository cum browser of whole genome somatic DNA breakpoint profiles of cancer genomes, mapped at single nucleotide resolution using deep sequencing data. These breakpoints are associated with deletions, insertions, inversions, tandem duplications, translocations and a combination of these structural genomic alterations. The current release of BreCAN-DB features breakpoint profiles from 99 cancer-normal pairs, comprising five cancer types. We identified DNA breakpoints across genomes using high-coverage next-generation sequencing data obtained from TCGA and dbGaP. Further, in these cancer genomes, we methodically identified breakpoint hotspots which were significantly enriched with somatic structural alterations. To visualize the breakpoint profiles, a next-generation genome browser was integrated with BreCAN-DB. Moreover, we also included previously reported breakpoint profiles from 138 cancer-normal pairs, spanning 10 cancer types into the browser. Additionally, BreCAN-DB allows one to identify breakpoint hotspots in user uploaded data set. We have also included a functionality to query overlap of any breakpoint profile with regions of user's interest. Users can download breakpoint profiles from the database or may submit their data to be integrated in BreCAN-DB. We believe that BreCAN-DB will be useful resource for genomics scientific community and is a step towards personalized cancer genomics. PMID:26586806

  18. Informed consent in direct-to-consumer personal genome testing: the outline of a model between specific and generic consent.

    PubMed

    Bunnik, Eline M; Janssens, A Cecile J W; Schermer, Maartje H N

    2014-09-01

    Broad genome-wide testing is increasingly finding its way to the public through the online direct-to-consumer marketing of so-called personal genome tests. Personal genome tests estimate genetic susceptibilities to multiple diseases and other phenotypic traits simultaneously. Providers commonly make use of Terms of Service agreements rather than informed consent procedures. However, to protect consumers from the potential physical, psychological and social harms associated with personal genome testing and to promote autonomous decision-making with regard to the testing offer, we argue that current practices of information provision are insufficient and that there is a place--and a need--for informed consent in personal genome testing, also when it is offered commercially. The increasing quantity, complexity and diversity of most testing offers, however, pose challenges for information provision and informed consent. Both specific and generic models for informed consent fail to meet its moral aims when applied to personal genome testing. Consumers should be enabled to know the limitations, risks and implications of personal genome testing and should be given control over the genetic information they do or do not wish to obtain. We present the outline of a new model for informed consent which can meet both the norm of providing sufficient information and the norm of providing understandable information. The model can be used for personal genome testing, but will also be applicable to other, future forms of broad genetic testing or screening in commercial and clinical settings. PMID:23137034

  19. Attitudes towards Social Networking and Sharing Behaviors among Consumers of Direct-to-Consumer Personal Genomics

    PubMed Central

    Lee, Sandra Soo-Jin; Vernez, Simone L.; Ormond, K.E.; Granovetter, Mark

    2013-01-01

    Little is known about how consumers of direct-to-consumer personal genetic services share personal genetic risk information. In an age of ubiquitous online networking and rapid development of social networking tools, understanding how consumers share personal genetic risk assessments is critical in the development of appropriate and effective policies. This exploratory study investigates how consumers share personal genetic information and attitudes towards social networking behaviors. Methods: Adult participants aged 23 to 72 years old who purchased direct-to-consumer genetic testing from a personal genomics company were administered a web-based survey regarding their sharing activities and social networking behaviors related to their personal genetic test results. Results: 80 participants completed the survey; of those, 45% shared results on Facebook and 50.9% reported meeting or reconnecting with more than 10 other individuals through the sharing of their personal genetic information. For help interpreting test results, 70.4% turned to Internet websites and online sources, compared to 22.7% who consulted their healthcare providers. Amongst participants, 51.8% reported that they believe the privacy of their personal genetic information would be breached in the future. Conclusion: Consumers actively utilize online social networking tools to help them share and interpret their personal genetic information. These findings suggest a need for careful consideration of policy recommendations in light of the current ambiguity of regulation and oversight of consumer initiated sharing activities. PMID:25562728

  20. Evaluation of next generation mtGenome sequencing using the Ion Torrent Personal Genome Machine (PGM)☆

    PubMed Central

    Parson, Walther; Strobl, Christina; Huber, Gabriela; Zimmermann, Bettina; Gomes, Sibylle M.; Souto, Luis; Fendt, Liane; Delport, Rhena; Langit, Reina; Wootton, Sharon; Lagacé, Robert; Irwin, Jodi

    2013-01-01

    Insights into the human mitochondrial phylogeny have been primarily achieved by sequencing full mitochondrial genomes (mtGenomes). In forensic genetics (partial) mtGenome information can be used to assign haplotypes to their phylogenetic backgrounds, which may, in turn, have characteristic geographic distributions that would offer useful information in a forensic case. In addition and perhaps even more relevant in the forensic context, haplogroup-specific patterns of mutations form the basis for quality control of mtDNA sequences. The current method for establishing (partial) mtDNA haplotypes is Sanger-type sequencing (STS), which is laborious, time-consuming, and expensive. With the emergence of Next Generation Sequencing (NGS) technologies, the body of available mtDNA data can potentially be extended much more quickly and cost-efficiently. Customized chemistries, laboratory workflows and data analysis packages could support the community and increase the utility of mtDNA analysis in forensics. We have evaluated the performance of mtGenome sequencing using the Personal Genome Machine (PGM) and compared the resulting haplotypes directly with conventional Sanger-type sequencing. A total of 64 mtGenomes (>1 million bases) were established that yielded high concordance with the corresponding STS haplotypes (<0.02% differences). About two-thirds of the differences were observed in or around homopolymeric sequence stretches. In addition, the sequence alignment algorithm employed to align NGS reads played a significant role in the analysis of the data and the resulting mtDNA haplotypes. Further development of alignment software would be desirable to facilitate the application of NGS in mtDNA forensic genetics. PMID:23948325

  1. Integrating Sequencing Technologies in Personal Genomics: Optimal Low Cost Reconstruction of Structural Variants

    PubMed Central

    Du, Jiang; Bjornson, Robert D.; Zhang, Zhengdong D.; Kong, Yong; Snyder, Michael; Gerstein, Mark B.

    2009-01-01

    The goal of human genome re-sequencing is obtaining an accurate assembly of an individual's genome. Recently, there has been great excitement in the development of many technologies for this (e.g. medium and short read sequencing from companies such as 454 and SOLiD, and high-density oligo-arrays from Affymetrix and NimbelGen), with even more expected to appear. The costs and sensitivities of these technologies differ considerably from each other. As an important goal of personal genomics is to reduce the cost of re-sequencing to an affordable point, it is worthwhile to consider optimally integrating technologies. Here, we build a simulation toolbox that will help us optimally combine different technologies for genome re-sequencing, especially in reconstructing large structural variants (SVs). SV reconstruction is considered the most challenging step in human genome re-sequencing. (It is sometimes even harder than de novo assembly of small genomes because of the duplications and repetitive sequences in the human genome.) To this end, we formulate canonical problems that are representative of issues in reconstruction and are of small enough scale to be computationally tractable and simulatable. Using semi-realistic simulations, we show how we can combine different technologies to optimally solve the assembly at low cost. With mapability maps, our simulations efficiently handle the inhomogeneous repeat-containing structure of the human genome and the computational complexity of practical assembly algorithms. They quantitatively show how combining different read lengths is more cost-effective than using one length, how an optimal mixed sequencing strategy for reconstructing large novel SVs usually also gives accurate detection of SNPs/indels, how paired-end reads can improve reconstruction efficiency, and how adding in arrays is more efficient than just sequencing for disentangling some complex SVs. Our strategy should facilitate the sequencing of human genomes at

  2. The potential of translational bioinformatics approaches for pharmacology research.

    PubMed

    Li, Lang

    2015-10-01

    The field of bioinformatics has allowed the interpretation of massive amounts of biological data, ushering in the era of 'omics' to biomedical research. Its potential impact on pharmacology research is enormous and it has shown some emerging successes. A full realization of this potential, however, requires standardized data annotation for large health record databases and molecular data resources. Improved standardization will further stimulate the development of system pharmacology models, using translational bioinformatics methods. This new translational bioinformatics paradigm is highly complementary to current pharmacological research fields, such as personalized medicine, pharmacoepidemiology and drug discovery. In this review, I illustrate the application of transformational bioinformatics to research in numerous pharmacology subdisciplines. PMID:25753093

  3. Public health genomics and personalized prevention: lessons from the COGS project

    PubMed Central

    Pashayan, N; Hall, A; Chowdhury, S; Dent, T; Pharoah, P D P; Burton, H

    2013-01-01

    Using the principles of public health genomics, we examined the opportunities and challenges of implementing personalized prevention programmes for cancer at the population level. Our model-based estimates indicate that polygenic risk stratification can potentially improve the effectiveness and cost-effectiveness of screening programmes. However, compared with ‘one-size-fits-all’ screening programmes, personalized screening adds further layers of complexity to the organization of screening services and raises ethical, legal and social challenges. Before polygenic inheritance is translated into population screening strategy, evidence from empirical research and engagement with and education of the public and the health professionals are needed. PMID:24127941

  4. Pathway analysis of genome-wide association datasets of personality traits.

    PubMed

    Kim, H-N; Kim, B-H; Cho, J; Ryu, S; Shin, H; Sung, J; Shin, C; Cho, N H; Sung, Y A; Choi, B-O; Kim, H-L

    2015-04-01

    Although several genome-wide association (GWA) studies of human personality have been recently published, genetic variants that are highly associated with certain personality traits remain unknown, due to difficulty reproducing results. To further investigate these genetic variants, we assessed biological pathways using GWA datasets. Pathway analysis using GWA data was performed on 1089 Korean women whose personality traits were measured with the Revised NEO Personality Inventory for the 5-factor model of personality. A total of 1042 pathways containing 8297 genes were included in our study. Of these, 14 pathways were highly enriched with association signals that were validated in 1490 independent samples. These pathways include association of: Neuroticism with axon guidance [L1 cell adhesion molecule (L1CAM) interactions]; Extraversion with neuronal system and voltage-gated potassium channels; Agreeableness with L1CAM interaction, neurotransmitter receptor binding and downstream transmission in postsynaptic cells; and Conscientiousness with the interferon-gamma and platelet-derived growth factor receptor beta polypeptide pathways. Several genes that contribute to top-ranked pathways in this study were previously identified in GWA studies or by pathway analysis in schizophrenia or other neuropsychiatric disorders. Here we report the first pathway analysis of all five personality traits. Importantly, our analysis identified novel pathways that contribute to understanding the etiology of personality traits. PMID:25809424

  5. From prenatal genomic diagnosis to fetal personalized medicine: progress and challenges

    PubMed Central

    Bianchi, Diana W

    2015-01-01

    Thus far, the focus of personalized medicine has been the prevention and treatment of conditions that affect adults. Although advances in genetic technology have been applied more frequently to prenatal diagnosis than to fetal treatment, genetic and genomic information is beginning to influence pregnancy management. Recent developments in sequencing the fetal genome combined with progress in understanding fetal physiology using gene expression arrays indicate that we could have the technical capabilities to apply an individualized medicine approach to the fetus. Here I review recent advances in prenatal genetic diagnostics, the challenges associated with these new technologies and how the information derived from them can be used to advance fetal care. Historically, the goal of prenatal diagnosis has been to provide an informed choice to prospective parents. We are now at a point where that goal can and should be expanded to incorporate genetic, genomic and transcriptomic data to develop new approaches to fetal treatment. PMID:22772565

  6. Eyes wide open: the personal genome project, citizen science and veracity in informed consent

    PubMed Central

    Angrist, Misha

    2012-01-01

    I am a close observer of the Personal Genome Project (PGP) and one of the original ten participants. The PGP was originally conceived as a way to test novel DNA sequencing technologies on human samples and to begin to build a database of human genomes and traits. However, its founder, Harvard geneticist George Church, was concerned about the fact that DNA is the ultimate digital identifier – individuals and many of their traits can be identified. Therefore, he believed that promising participants privacy and confidentiality would be impractical and disingenuous. Moreover, deidentification of samples would impoverish both genotypic and phenotypic data. As a result, the PGP has arguably become best known for its unprecedented approach to informed consent. All participants must pass an exam testing their knowledge of genomic science and privacy issues and agree to forgo the privacy and confidentiality of their genomic data and personal health records. Church aims to scale up to 100,000 participants. This special report discusses the impetus for the project, its early history and its potential to have a lasting impact on the treatment of human subjects in biomedical research. PMID:22328898

  7. Perceptions of genetic counseling services in direct-to-consumer personal genomic testing.

    PubMed

    Darst, B F; Madlensky, L; Schork, N J; Topol, E J; Bloss, C S

    2013-10-01

    To describe consumers' perceptions of genetic counseling services in the context of direct-to-consumer personal genomic testing is the purpose of this research. Utilizing data from the Scripps Genomic Health Initiative, we assessed direct-to-consumer genomic test consumers' utilization and perceptions of genetic counseling services. At long-term follow-up, approximately 14 months post-testing, participants were asked to respond to several items gauging their interactions, if any, with a Navigenics genetic counselor, and their perceptions of those interactions. Out of 1325 individuals who completed long-term follow-up, 187 (14.1%) indicated that they had spoken with a genetic counselor. The most commonly given reason for not utilizing the counseling service was a lack of need due to the perception of already understanding one's results (55.6%). The most common reasons for utilizing the service included wanting to take advantage of a free service (43.9%) and wanting more information on risk calculations (42.2%). Among those who utilized the service, a large fraction reported that counseling improved their understanding of their results (54.5%) and genetics in general (43.9%). A relatively small proportion of participants utilized genetic counseling after direct-to-consumer personal genomic testing. Among those individuals who did utilize the service, however, a large fraction perceived it to be informative, and thus presumably beneficial. PMID:23590221

  8. Should direct-to-consumer personalized genomic medicine remain unregulated?: a rebuttal of the defenses.

    PubMed

    Valles, Sean A

    2012-01-01

    Direct-to-consumer personalized genomic medicine has recently grown into a small industry that sells mail-order DNA sample kits and then provides disease risk assessments, typically based upon results from genome-trait association studies. The companies selling these services have been largely exempted from FDA regulation in the United States. Testing kit companies and their supporters have defended the industry's unregulated status using two arguments. First, defenders have argued that mere absence of harm is all that must be proved for mail-order tests to be acceptable. Second, defenders of mail-order testing have argued that there is an individual right to the tests' information. This article rebuts these arguments. The article demonstrates that the direct-to-consumer market has resulted in the sidelining of clinical utility (medical value to patients), leading to the development of certain mail-order tests that do not promote customers' interests and to defenders' downplaying of a potentially damaging empirical study of mail-order genomic testing's effects on consumers. The article also shows that the notion of an individual right to these tests rests on a flawed reading of the key service provided by mail-order companies, which is the provision of medical interpretations, not simply genetic information. Absent these two justifications, there is no reason to exempt direct-to-consumer personalized genomic medicine from stringent federal oversight. PMID:22643762

  9. A Survey of Scholarly Literature Describing the Field of Bioinformatics Education and Bioinformatics Educational Research

    ERIC Educational Resources Information Center

    Magana, Alejandra J.; Taleyarkhan, Manaz; Alvarado, Daniela Rivera; Kane, Michael; Springer, John; Clase, Kari

    2014-01-01

    Bioinformatics education can be broadly defined as the teaching and learning of the use of computer and information technology, along with mathematical and statistical analysis for gathering, storing, analyzing, interpreting, and integrating data to solve biological problems. The recent surge of genomics, proteomics, and structural biology in the…

  10. Translational Bioinformatics and Healthcare Informatics: Computational and Ethical Challenges

    PubMed Central

    Sethi, Prerna; Theodos, Kimberly

    2009-01-01

    Exponentially growing biological and bioinformatics data sets present a challenge and an opportunity for researchers to contribute to the understanding of the genetic basis of phenotypes. Due to breakthroughs in microarray technology, it is possible to simultaneously monitor the expressions of thousands of genes, and it is imperative that researchers have access to the clinical data to understand the genetics and proteomics of the diseased tissue. This technology could be a landmark in personalized medicine, which will provide storage for clinical and genetic data in electronic health records (EHRs). In this paper, we explore the computational and ethical challenges that emanate from the intersection of bioinformatics and healthcare informatics research. We describe the current situation of the EHR and its capabilities to store clinical and genetic data and then discuss the Genetic Information Nondiscrimination Act. Finally, we posit that the synergy obtained from the collaborative efforts between the genomics, clinical, and healthcare disciplines has potential to enhance and promote faster and more advanced breakthroughs in healthcare. PMID:20169020

  11. A tiered-layered-staged model for informed consent in personal genome testing.

    PubMed

    Bunnik, Eline M; Janssens, A Cecile J W; Schermer, Maartje H N

    2013-06-01

    In recent years, developments in genomics technologies have led to the rise of commercial personal genome testing (PGT): broad genome-wide testing for multiple diseases simultaneously. While some commercial providers require physicians to order a personal genome test, others can be accessed directly. All providers advertise directly to consumers and offer genetic risk information about dozens of diseases in one single purchase. The quantity and the complexity of risk information pose challenges to adequate pre-test and post-test information provision and informed consent. There are currently no guidelines for what should constitute informed consent in PGT or how adequate informed consent can be achieved. In this paper, we propose a tiered-layered-staged model for informed consent. First, the proposed model is tiered as it offers choices between categories of diseases that are associated with distinct ethical, personal or societal issues. Second, the model distinguishes layers of information with a first layer offering minimal, indispensable information that is material to all consumers, and additional layers offering more detailed information made available upon request. Finally, the model stages informed consent as a process by feeding information to consumers in each subsequent stage of the process of undergoing a test, and by accommodating renewed consent for test result updates, resulting from the ongoing development of the science underlying PGT. A tiered-layered-staged model for informed consent with a focus on the consumer perspective can help overcome the ethical problems of information provision and informed consent in direct-to-consumer PGT. PMID:23169494

  12. An Online Bioinformatics Curriculum

    PubMed Central

    Searls, David B.

    2012-01-01

    Online learning initiatives over the past decade have become increasingly comprehensive in their selection of courses and sophisticated in their presentation, culminating in the recent announcement of a number of consortium and startup activities that promise to make a university education on the internet, free of charge, a real possibility. At this pivotal moment it is appropriate to explore the potential for obtaining comprehensive bioinformatics training with currently existing free video resources. This article presents such a bioinformatics curriculum in the form of a virtual course catalog, together with editorial commentary, and an assessment of strengths, weaknesses, and likely future directions for open online learning in this field. PMID:23028269

  13. Towards personalized agriculture: what chemical genomics can bring to plant biotechnology

    PubMed Central

    Stokes, Michael E.; McCourt, Peter

    2014-01-01

    In contrast to the dominant drug paradigm in which compounds were developed to “fit all,” new models focused around personalized medicine are appearing in which treatments are developed and customized for individual patients. The agricultural biotechnology industry (Ag-biotech) should also think about these new personalized models. For example, most common herbicides are generic in action, which led to the development of genetically modified crops to add specificity. The ease and accessibility of modern genomic analysis, when wedded to accessible large chemical space, should facilitate the discovery of chemicals that are more selective in their utility. Is it possible to develop species-selective herbicides and growth regulators? More generally put, is plant research at a stage where chemicals can be developed that streamline plant development and growth to various environments? We believe the advent of chemical genomics now opens up these and other opportunities to “personalize” agriculture. Furthermore, chemical genomics does not necessarily require genetically tractable plant models, which in principle should allow quick translation to practical applications. For this to happen, however, will require collaboration between the Ag-biotech industry and academic labs for early stage research and development, a situation that has proven very fruitful for Big Pharma. PMID:25183965

  14. Gene Variant Databases and Sharing: Creating a Global Genomic Variant Database for Personalized Medicine.

    PubMed

    Bean, Lora J H; Hegde, Madhuri R

    2016-06-01

    Revolutionary changes in sequencing technology and the desire to develop therapeutics for rare diseases have led to the generation of an enormous amount of genomic data in the last 5 years. Large-scale sequencing done in both research and diagnostic laboratories has linked many new genes to rare diseases, but has also generated a number of variants that we cannot interpret today. It is clear that we remain a long way from a complete understanding of the genomic variation in the human genome and its association with human health and disease. Recent studies identified susceptibility markers to infectious diseases and also the contribution of rare variants to complex diseases in different populations. The sequencing revolution has also led to the creation of a large number of databases that act as "keepers" of data, and in many cases give an interpretation of the effect of the variant. This interpretation is based on reports in the literature, prediction models, and in some cases is accompanied by functional evidence. As we move toward the practice of genomic medicine, and consider its place in "personalized medicine," it is time to ask ourselves how we can aggregate this wealth of data into a single database for multiple users with different goals. PMID:26931283

  15. Bioinformatics and School Biology

    ERIC Educational Resources Information Center

    Dalpech, Roger

    2006-01-01

    The rapidly changing field of bioinformatics is fuelling the need for suitably trained personnel with skills in relevant biological "sub-disciplines" such as proteomics, transcriptomics and metabolomics, etc. But because of the complexity--and sheer weight of data--associated with these new areas of biology, many school teachers feel…

  16. Bioinformatics Methods and Tools to Advance Clinical Care

    PubMed Central

    Lecroq, T.

    2015-01-01

    Summary Objectives To summarize excellent current research in the field of Bioinformatics and Translational Informatics with application in the health domain and clinical care. Method We provide a synopsis of the articles selected for the IMIA Yearbook 2015, from which we attempt to derive a synthetic overview of current and future activities in the field. As last year, a first step of selection was performed by querying MEDLINE with a list of MeSH descriptors completed by a list of terms adapted to the section. Each section editor has evaluated separately the set of 1,594 articles and the evaluation results were merged for retaining 15 articles for peer-review. Results The selection and evaluation process of this Yearbook’s section on Bioinformatics and Translational Informatics yielded four excellent articles regarding data management and genome medicine that are mainly tool-based papers. In the first article, the authors present PPISURV a tool for uncovering the role of specific genes in cancer survival outcome. The second article describes the classifier PredictSNP which combines six performing tools for predicting disease-related mutations. In the third article, by presenting a high-coverage map of the human proteome using high resolution mass spectrometry, the authors highlight the need for using mass spectrometry to complement genome annotation. The fourth article is also related to patient survival and decision support. The authors present datamining methods of large-scale datasets of past transplants. The objective is to identify chances of survival. Conclusions The current research activities still attest the continuous convergence of Bioinformatics and Medical Informatics, with a focus this year on dedicated tools and methods to advance clinical care. Indeed, there is a need for powerful tools for managing and interpreting complex, large-scale genomic and biological datasets, but also a need for user-friendly tools developed for the clinicians in their

  17. Online Tools for Bioinformatics Analyses in Nutrition Sciences12

    PubMed Central

    Malkaram, Sridhar A.; Hassan, Yousef I.; Zempleni, Janos

    2012-01-01

    Recent advances in “omics” research have resulted in the creation of large datasets that were generated by consortiums and centers, small datasets that were generated by individual investigators, and bioinformatics tools for mining these datasets. It is important for nutrition laboratories to take full advantage of the analysis tools to interrogate datasets for information relevant to genomics, epigenomics, transcriptomics, proteomics, and metabolomics. This review provides guidance regarding bioinformatics resources that are currently available in the public domain, with the intent to provide a starting point for investigators who want to take advantage of the opportunities provided by the bioinformatics field. PMID:22983844

  18. Towards a career in bioinformatics

    PubMed Central

    2009-01-01

    The 2009 annual conference of the Asia Pacific Bioinformatics Network (APBioNet), Asia's oldest bioinformatics organisation from 1998, was organized as the 8th International Conference on Bioinformatics (InCoB), Sept. 9-11, 2009 at Biopolis, Singapore. InCoB has actively engaged researchers from the area of life sciences, systems biology and clinicians, to facilitate greater synergy between these groups. To encourage bioinformatics students and new researchers, tutorials and student symposium, the Singapore Symposium on Computational Biology (SYMBIO) were organized, along with the Workshop on Education in Bioinformatics and Computational Biology (WEBCB) and the Clinical Bioinformatics (CBAS) Symposium. However, to many students and young researchers, pursuing a career in a multi-disciplinary area such as bioinformatics poses a Himalayan challenge. A collection to tips is presented here to provide signposts on the road to a career in bioinformatics. An overview of the application of bioinformatics to traditional and emerging areas, published in this supplement, is also presented to provide possible future avenues of bioinformatics investigation. A case study on the application of e-learning tools in undergraduate bioinformatics curriculum provides information on how to go impart targeted education, to sustain bioinformatics in the Asia-Pacific region. The next InCoB is scheduled to be held in Tokyo, Japan, Sept. 26-28, 2010. PMID:19958508

  19. Meta-analysis of genome-wide association studies for personality

    PubMed Central

    de Moor, Marleen H.M.; Costa, Paul T.; Terracciano, Antonio; Krueger, Robert F.; de Geus, Eco J.C.; Toshiko, Tanaka; Penninx, Brenda W.J.H.; Esko, Tõnu; Madden, Pamela A F; Derringer, Jaime; Amin, Najaf; Willemsen, Gonneke; Hottenga, Jouke-Jan; Distel, Marijn A.; Uda, Manuela; Sanna, Serena; Spinhoven, Philip; Hartman, Catharina A.; Sullivan, Patrick; Realo, Anu; Allik, Jüri; Heath, Andrew C; Pergadia, Michele L; Agrawal, Arpana; Lin, Peng; Grucza, Richard; Nutile, Teresa; Ciullo, Marina; Rujescu, Dan; Giegling, Ina; Konte, Bettina; Widen, Elisabeth; Cousminer, Diana L; Eriksson, Johan G.; Palotie, Aarno; Luciano, Michelle; Tenesa, Albert; Davies, Gail; Lopez, Lorna M.; Hansell, Narelle K.; Medland, Sarah E.; Ferrucci, Luigi; Schlessinger, David; Montgomery, Grant W.; Wright, Margaret J.; Aulchenko, Yurii S.; Janssens, A.Cecile J.W.; Oostra, Ben A.; Metspalu, Andres; Abecasis, Gonçalo R.; Deary, Ian J.; Räikkönen, Katri; Bierut, Laura J.; Martin, Nicholas G.; van Duijn, Cornelia M.; Boomsma, Dorret I.

    2013-01-01

    Personality can be thought of as a set of characteristics that influence people’s thoughts, feelings, and behaviour across a variety of settings. Variation in personality is predictive of many outcomes in life, including mental health. Here we report on a meta-analysis of genome-wide association (GWA) data for personality in ten discovery samples (17 375 adults) and five in-silico replication samples (3 294 adults). All participants were of European ancestry. Personality scores for Neuroticism, Extraversion, Openness to Experience, Agreeableness, and Conscientiousness were based on the NEO Five-Factor Inventory. Genotype data were available of ~2.4M Single Nucleotide Polymorphisms (SNPs; directly typed and imputed using HAPMAP data). In the discovery samples, classical association analyses were performed under an additive model followed by meta-analysis using the weighted inverse variance method. Results showed genome-wide significance for Openness to Experience near the RASA1 gene on 5q14.3 (rs1477268 and rs2032794, P = 2.8 × 10−8 and 3.1 × 10−8) and for Conscientiousness in the brain-expressed KATNAL2 gene on 18q21.1 (rs2576037, P = 4.9 × 10−8). We further conducted a gene-based test that confirmed the association of KATNAL2 to Conscientiousness. In-silico replication did not, however, show significant associations of the top SNPs with Openness and Conscientiousness, although the direction of effect of the KATNAL2 SNP on Conscientiousness was consistent in all replication samples. Larger scale GWA studies and alternative approaches are required for confirmation of KATNAL2 as a novel gene affecting Conscientiousness. PMID:21173776

  20. From Molecules to Patients: The Clinical Applications of Translational Bioinformatics

    PubMed Central

    Regan, K.

    2015-01-01

    Summary Objective In order to realize the promise of personalized medicine, Translational Bioinformatics (TBI) research will need to continue to address implementation issues across the clinical spectrum. In this review, we aim to evaluate the expanding field of TBI towards clinical applications, and define common themes and current gaps in order to motivate future research. Methods Here we present the state-of-the-art of clinical implementation of TBI-based tools and resources. Our thematic analyses of a targeted literature search of recent TBI-related articles ranged across topics in genomics, data management, hypothesis generation, molecular epidemiology, diagnostics, therapeutics and personalized medicine. Results Open areas of clinically-relevant TBI research identified in this review include developing data standards and best practices, publicly available resources, integrative systems-level approaches, user-friendly tools for clinical support, cloud computing solutions, emerging technologies and means to address pressing legal, ethical and social issues. Conclusions There is a need for further research bridging the gap from foundational TBI-based theories and methodologies to clinical implementation. We have organized the topic themes presented in this review into four conceptual foci – domain analyses, knowledge engineering, computational architectures and computation methods alongside three stages of knowledge development in order to orient future TBI efforts to accelerate the goals of personalized medicine. PMID:26293863

  1. How Well Do Customers of Direct-to-Consumer Personal Genomic Testing Services Comprehend Genetic Test Results? Findings from the Impact of Personal Genomics Study

    PubMed Central

    Ostergren, Jenny E.; Gornick, Michele C.; Carere, Deanna Alexis; Kalia, Sarah S.; Uhlmann, Wendy R.; Ruffin, Mack T.; Mountain, Joanna L.; Green, Robert C.; Roberts, J. Scott

    2016-01-01

    Aim To assess customer comprehension of health-related personal genomic testing (PGT) results. Methods We presented sample reports of genetic results and examined responses to comprehension questions in 1,030 PGT customers (mean age: 46.7 years; 59.9% female; 79.0% college graduates; 14.9% non-White; 4.7% of Hispanic/Latino ethnicity). Sample reports presented a genetic risk for Alzheimer’s disease and type 2 diabetes, carrier screening summary results for >30 conditions, results for phenylketonuria and cystic fibrosis, and drug response results for a statin drug. Logistic regression was used to identify correlates of participant comprehension. Results Participants exhibited high overall comprehension (mean score: 79.1% correct). The highest comprehension (range: 81.1–97.4% correct) was observed in the statin drug response and carrier screening summary results, and lower comprehension (range: 63.6–74.8% correct) on specific carrier screening results. Higher levels of numeracy, genetic knowledge, and education were significantly associated with greater comprehension. Older age (≥ 60 years) was associated with lower comprehension scores. Conclusions Most customers accurately interpreted the health implications of PGT results; however, comprehension varied by demographic characteristics, numeracy and genetic knowledge, and types and format of the genetic information presented. Results suggest a need to tailor the presentation of PGT results by test type and customer characteristics. PMID:26087778

  2. Bioinformatics for Exploration

    NASA Technical Reports Server (NTRS)

    Johnson, Kathy A.

    2006-01-01

    For the purpose of this paper, bioinformatics is defined as the application of computer technology to the management of biological information. It can be thought of as the science of developing computer databases and algorithms to facilitate and expedite biological research. This is a crosscutting capability that supports nearly all human health areas ranging from computational modeling, to pharmacodynamics research projects, to decision support systems within autonomous medical care. Bioinformatics serves to increase the efficiency and effectiveness of the life sciences research program. It provides data, information, and knowledge capture which further supports management of the bioastronautics research roadmap - identifying gaps that still remain and enabling the determination of which risks have been addressed.

  3. Phylogenetic trees in bioinformatics

    SciTech Connect

    Burr, Tom L

    2008-01-01

    Genetic data is often used to infer evolutionary relationships among a collection of viruses, bacteria, animal or plant species, or other operational taxonomic units (OTU). A phylogenetic tree depicts such relationships and provides a visual representation of the estimated branching order of the OTUs. Tree estimation is unique for several reasons, including: the types of data used to represent each OTU; the use ofprobabilistic nucleotide substitution models; the inference goals involving both tree topology and branch length, and the huge number of possible trees for a given sample of a very modest number of OTUs, which implies that fmding the best tree(s) to describe the genetic data for each OTU is computationally demanding. Bioinformatics is too large a field to review here. We focus on that aspect of bioinformatics that includes study of similarities in genetic data from multiple OTUs. Although research questions are diverse, a common underlying challenge is to estimate the evolutionary history of the OTUs. Therefore, this paper reviews the role of phylogenetic tree estimation in bioinformatics, available methods and software, and identifies areas for additional research and development.

  4. Genetics, Genomics and Cancer Risk Assessment: State of the art and future directions in the era of personalized medicine

    PubMed Central

    Weitzel, Jeffrey N.; Blazer, Kathleen R.; MacDonald, Deborah J.; Culver, Julie O.; Offit, Kenneth

    2012-01-01

    Scientific and technologic advances are revolutionizing our approach to genetic cancer risk assessment, cancer screening and prevention, and targeted therapy, fulfilling the promise of personalized medicine. In this monograph we review the evolution of scientific discovery in cancer genetics and genomics, and describe current approaches, benefits and barriers to the translation of this information to the practice of preventive medicine. Summaries of known hereditary cancer syndromes and highly penetrant genes are provided and contrasted with recently-discovered genomic variants associated with modest increases in cancer risk. We describe the scope of knowledge, tools, and expertise required for the translation of complex genetic and genomic test information into clinical practice. The challenges of genomic counseling include the need for genetics and genomics professional education and multidisciplinary team training, the need for evidence-based information regarding the clinical utility of testing for genomic variants, the potential dangers posed by premature marketing of first-generation genomic profiles, and the need for new clinical models to improve access to and responsible communication of complex disease-risk information. We conclude that given the experiences and lessons learned in the genetics era, the multidisciplinary model of genetic cancer risk assessment and management will serve as a solid foundation to support the integration of personalized genomic information into the practice of cancer medicine. PMID:21858794

  5. STORMSeq: an open-source, user-friendly pipeline for processing personal genomics data in the cloud.

    PubMed

    Karczewski, Konrad J; Fernald, Guy Haskin; Martin, Alicia R; Snyder, Michael; Tatonetti, Nicholas P; Dudley, Joel T

    2014-01-01

    The increasing public availability of personal complete genome sequencing data has ushered in an era of democratized genomics. However, read mapping and variant calling software is constantly improving and individuals with personal genomic data may prefer to customize and update their variant calls. Here, we describe STORMSeq (Scalable Tools for Open-Source Read Mapping), a graphical interface cloud computing solution that does not require a parallel computing environment or extensive technical experience. This customizable and modular system performs read mapping, read cleaning, and variant calling and annotation. At present, STORMSeq costs approximately $2 and 5-10 hours to process a full exome sequence and $30 and 3-8 days to process a whole genome sequence. We provide this open-access and open-source resource as a user-friendly interface in Amazon EC2. PMID:24454756

  6. Genome-wide association scan for five major dimensions of personality

    PubMed Central

    Terracciano, Antonio; Sanna, Serena; Uda, Manuela; Deiana, Barbara; Usala, Gianluca; Busonero, Fabio; Maschio, Andrea; Scally, Matthew; Patriciu, Nicholas; Chen, Wei-Min; Distel, Marijn A; Slagboom, Eline P; Boomsma, Dorret I; Villafuerte, Sandra; Śliwerska, Elżbieta; Burmeister, Margit; Amin, Najaf; Janssens, A. Cecile J.W.; van Duijn, Cornelia M.; Schlessinger, David; Abecasis, Gonçalo R.; Costa, Paul T.

    2008-01-01

    Personality traits are summarized by five broad dimensions with pervasive influences on major life outcomes, strong links to psychiatric disorders, and clear heritable components. To identify genetic variants associated with each of the five dimensions of personality we performed a genome wide association (GWA) scan of 3,972 individuals from a genetically isolated population within Sardinia, Italy. Based on analyses of 362,129 single nucleotide polymorphisms (SNPs) we found several strong signals within or near genes previously implicated in psychiatric disorders. They include the association of Neuroticism with SNAP25 (rs362584, P = 5 × 10−5), Extraversion with BDNF and two cadherin genes (CDH13 and CDH23; Ps < 5 × 10−5), Openness with CNTNAP2 (rs10251794, P = 3 × 10−5), Agreeableness with CLOCK (rs6832769, P = 9 × 10−6), and Conscientiousness with DYRK1A (rs2835731, P = 3 × 10−5). Effect sizes were small (less than 1% of variance), and most failed to replicate in the follow-up independent samples (N up to 3,903), though the association between Agreeableness and CLOCK was supported in two of three replication samples (overall P = 2 × 10−5). We infer that a large number of loci may influence personality traits and disorders, requiring larger sample sizes for the GWA approach to identify significant genetic variants. PMID:18957941

  7. Agile parallel bioinformatics workflow management using Pwrake

    PubMed Central

    2011-01-01

    Background In bioinformatics projects, scientific workflow systems are widely used to manage computational procedures. Full-featured workflow systems have been proposed to fulfil the demand for workflow management. However, such systems tend to be over-weighted for actual bioinformatics practices. We realize that quick deployment of cutting-edge software implementing advanced algorithms and data formats, and continuous adaptation to changes in computational resources and the environment are often prioritized in scientific workflow management. These features have a greater affinity with the agile software development method through iterative development phases after trial and error. Here, we show the application of a scientific workflow system Pwrake to bioinformatics workflows. Pwrake is a parallel workflow extension of Ruby's standard build tool Rake, the flexibility of which has been demonstrated in the astronomy domain. Therefore, we hypothesize that Pwrake also has advantages in actual bioinformatics workflows. Findings We implemented the Pwrake workflows to process next generation sequencing data using the Genomic Analysis Toolkit (GATK) and Dindel. GATK and Dindel workflows are typical examples of sequential and parallel workflows, respectively. We found that in practice, actual scientific workflow development iterates over two phases, the workflow definition phase and the parameter adjustment phase. We introduced separate workflow definitions to help focus on each of the two developmental phases, as well as helper methods to simplify the descriptions. This approach increased iterative development efficiency. Moreover, we implemented combined workflows to demonstrate modularity of the GATK and Dindel workflows. Conclusions Pwrake enables agile management of scientific workflows in the bioinformatics domain. The internal domain specific language design built on Ruby gives the flexibility of rakefiles for writing scientific workflows. Furthermore, readability

  8. Novel bioinformatic developments for exome sequencing.

    PubMed

    Lelieveld, Stefan H; Veltman, Joris A; Gilissen, Christian

    2016-06-01

    With the widespread adoption of next generation sequencing technologies by the genetics community and the rapid decrease in costs per base, exome sequencing has become a standard within the repertoire of genetic experiments for both research and diagnostics. Although bioinformatics now offers standard solutions for the analysis of exome sequencing data, many challenges still remain; especially the increasing scale at which exome data are now being generated has given rise to novel challenges in how to efficiently store, analyze and interpret exome data of this magnitude. In this review we discuss some of the recent developments in bioinformatics for exome sequencing and the directions that this is taking us to. With these developments, exome sequencing is paving the way for the next big challenge, the application of whole genome sequencing. PMID:27075447

  9. Bioinformatic analysis of expression data to identify effector candidates.

    PubMed

    Reid, Adam J; Jones, John T

    2014-01-01

    Pathogens produce effectors that manipulate the host to the benefit of the pathogen. These effectors are often secreted proteins that are upregulated during the early phases of infection. These properties can be used to identify candidate effectors from genomes and transcriptomes of pathogens. Here we describe commonly used bioinformatic approaches that (1) allow identification of genes encoding predicted secreted proteins within a genome and (2) allow the identification of genes encoding predicted secreted proteins that are upregulated at important stages of the life cycle. Other approaches for bioinformatic identification of effector candidates, including OrthoMCL analysis to identify expanded gene families, are also described. PMID:24643549

  10. Intrageneric primer design: Bringing bioinformatics tools to the class.

    PubMed

    Lima, André O S; Garcês, Sérgio P S

    2006-09-01

    Bioinformatics is one of the fastest growing scientific areas over the last decade. It focuses on the use of informatics tools for the organization and analysis of biological data. An example of their importance is the availability nowadays of dozens of software programs for genomic and proteomic studies. Thus, there is a growing field (private and academic) with a need for bachelor of science students with bioinformatics skills. In consideration of this need, described here is a problem-based class in which students are asked to design a set of intrageneric primers for PCR. The exercise is divided into five classes of 1 h each, in which students use freeware bioinformatics tools and data bases available through the Internet. Besides designing the set of primers, the students will consequently learn the significance and use of the major bioinformatics procedures, such as searching a data base, conducting and analyzing sequence multialignment, comparing sequences with a data base, and selecting primers. PMID:21638710

  11. After the revolution? Ethical and social challenges in ‘personalized genomic medicine’

    PubMed Central

    Juengst, Eric T; Settersten, Richard A; Fishman, Jennifer R; McGowan, Michelle L

    2013-01-01

    Personalized genomic medicine (PGM) is a goal that currently unites a wide array of biomedical initiatives, and is promoted as a ‘new paradigm for healthcare’ by its champions. Its promissory virtues include individualized diagnosis and risk prediction, more effective prevention and health promotion, and patient empowerment. Beyond overcoming scientific and technological hurdles to realizing PGM, proponents may interpret and rank these promises differently, which carries ethical and social implications for the realization of PGM as an approach to healthcare. We examine competing visions of PGM’s virtues and the directions in which they could take the field, in order to anticipate policy choices that may lie ahead for researchers, healthcare providers and the public. PMID:23662108

  12. Consumers report lower confidence in their genetics knowledge following direct-to-consumer personal genomic testing

    PubMed Central

    Carere, Deanna Alexis; Kraft, Peter; Kaphingst, Kimberly A.; Roberts, J. Scott; Green, Robert C.

    2015-01-01

    Purpose To measure changes to genetics knowledge and self-efficacy following personal genomic testing (PGT). Methods New customers of 23andMe and Pathway Genomics completed a series of online surveys. Prior to receipt of results, and 6 months post-results, we measured genetics knowledge (9 true/false items) and genetics self-efficacy (5 Likert-scale items) and used paired methods to evaluate change over time. Correlates of change (e.g., decision regret) were identified using linear regression. Results 998 PGT customers (59.9% female; 85.8% White; mean age 46.9±15.5 years) were included in our analyses. Mean genetics knowledge score out of 9 was 8.15±0.95 at baseline and 8.25±0.92 at 6 months (p = .0024). Mean self-efficacy score out of 35 was 29.06±5.59 at baseline and 27.7±5.46 at 6 months (p < .0001); on each item, 30–45% of participants reported lower self-efficacy following PGT. Change in self-efficacy was positively associated with health care provider consultation (p = .0042), impact of PGT on perceived control over one’s health (p < .0001), and perceived value of PGT (p < .0001), and negatively associated with decision regret (p < .0001). Conclusion Lowered genetics self-efficacy following PGT may reflect an appropriate reevaluation by consumers in response to receiving complex genetic information. PMID:25812042

  13. Genomic classification of the RAS network identifies a personalized treatment strategy for lung cancer

    PubMed Central

    El-Chaar, Nader N.; Piccolo, Stephen R.; Boucher, Kenneth M.; Cohen, Adam L.; Chang, Jeffrey T.; Moos, Philip J.; Bild, Andrea H.

    2014-01-01

    Better approaches are needed to evaluate a single patient's drug response at the genomic level. Targeted therapy for signaling pathways in cancer has met limited success in part due to the exceedingly interwoven nature of the pathways. In particular, the highly complex RAS network has been challenging to target. Effectively targeting the pathway requires development of techniques that measure global network activity to account for pathway complexity. For this purpose, we used a gene-expression-based biomarker for RAS network activity in non-small cell lung cancer (NSCLC) cells, and screened for drugs whose efficacy were significantly highly correlated to RAS network activity. Results identified EGFR and MEK co-inhibition as the most effective treatment for RAS-active NSCLC amongst a panel of over 360 compounds and fractions. RAS activity was identified in both RAS-mutant and wild-type lines, indicating broad characterization of RAS signaling inclusive of multiple mechanisms of RAS activity, and not solely based on mutation status. Mechanistic studies demonstrated that co-inhibition of EGFR and MEK induced apoptosis and blocked both EGFR-RAS-RAF-MEK-ERK and EGFR-PI3K-AKT-RPS6 nodes simultaneously in RAS-active, but not RAS-inactive NSCLC. These results provide a comprehensive strategy to personalize treatment of NSCLC based on RAS network dysregulation and provide proof-of-concept of a genomic approach to classify and target complex signaling networks. PMID:24908424

  14. [Genome-cohort studies for the development of personalized cancer prevention programs in Japan].

    PubMed

    Tanaka, Hideo

    2015-05-01

    One of the most important roles of molecular epidemiology is to investigate gene-environment interactions in order to provide data for personalized risk modification. A case-control study conducted in Aichi showed that an aldehyde dehydrogenase- 2(ALDH2)polymorphism together with cigarette smoking significantly affects the risk of lung cancer. The main purpose of this large-scale genome-cohort study of healthy individuals is to confirm that these factors are associated with the development of diseases and to set optimal thresholds for the environmental factors. The Japan Multi-Institutional Collaborative Cohort(J-MICC)Study was launched in 2005. It has recruited 100,600 healthy participants up to the end of 2014, and plans to follow them until 2025. Although Japanese genome-cohort studies, including the J-MICC Study, the Japan Public Health Center-based Prospective(JPHC)Study, and the Tohoku Medical Megabank Organization Study, consist of different research teams with different financial resources, collaboration to standardize the data collection format for successful pooled analysis is being discussed. PMID:25981648

  15. Bioinformatics-Aided Venomics

    PubMed Central

    Kaas, Quentin; Craik, David J.

    2015-01-01

    Venomics is a modern approach that combines transcriptomics and proteomics to explore the toxin content of venoms. This review will give an overview of computational approaches that have been created to classify and consolidate venomics data, as well as algorithms that have helped discovery and analysis of toxin nucleic acid and protein sequences, toxin three-dimensional structures and toxin functions. Bioinformatics is used to tackle specific challenges associated with the identification and annotations of toxins. Recognizing toxin transcript sequences among second generation sequencing data cannot rely only on basic sequence similarity because toxins are highly divergent. Mass spectrometry sequencing of mature toxins is challenging because toxins can display a large number of post-translational modifications. Identifying the mature toxin region in toxin precursor sequences requires the prediction of the cleavage sites of proprotein convertases, most of which are unknown or not well characterized. Tracing the evolutionary relationships between toxins should consider specific mechanisms of rapid evolution as well as interactions between predatory animals and prey. Rapidly determining the activity of toxins is the main bottleneck in venomics discovery, but some recent bioinformatics and molecular modeling approaches give hope that accurate predictions of toxin specificity could be made in the near future. PMID:26110505

  16. Pattern recognition in bioinformatics.

    PubMed

    de Ridder, Dick; de Ridder, Jeroen; Reinders, Marcel J T

    2013-09-01

    Pattern recognition is concerned with the development of systems that learn to solve a given problem using a set of example instances, each represented by a number of features. These problems include clustering, the grouping of similar instances; classification, the task of assigning a discrete label to a given instance; and dimensionality reduction, combining or selecting features to arrive at a more useful representation. The use of statistical pattern recognition algorithms in bioinformatics is pervasive. Classification and clustering are often applied to high-throughput measurement data arising from microarray, mass spectrometry and next-generation sequencing experiments for selecting markers, predicting phenotype and grouping objects or genes. Less explicitly, classification is at the core of a wide range of tools such as predictors of genes, protein function, functional or genetic interactions, etc., and used extensively in systems biology. A course on pattern recognition (or machine learning) should therefore be at the core of any bioinformatics education program. In this review, we discuss the main elements of a pattern recognition course, based on material developed for courses taught at the BSc, MSc and PhD levels to an audience of bioinformaticians, computer scientists and life scientists. We pay attention to common problems and pitfalls encountered in applications and in interpretation of the results obtained. PMID:23559637

  17. Identification of anticancer drugs for hepatocellular carcinoma through personalized genome-scale metabolic modeling.

    PubMed

    Agren, Rasmus; Mardinoglu, Adil; Asplund, Anna; Kampf, Caroline; Uhlen, Mathias; Nielsen, Jens

    2014-01-01

    Genome-scale metabolic models (GEMs) have proven useful as scaffolds for the integration of omics data for understanding the genotype-phenotype relationship in a mechanistic manner. Here, we evaluated the presence/absence of proteins encoded by 15,841 genes in 27 hepatocellular carcinoma (HCC) patients using immunohistochemistry. We used this information to reconstruct personalized GEMs for six HCC patients based on the proteomics data, HMR 2.0, and a task-driven model reconstruction algorithm (tINIT). The personalized GEMs were employed to identify anticancer drugs using the concept of antimetabolites; i.e., drugs that are structural analogs to metabolites. The toxicity of each antimetabolite was predicted by assessing the in silico functionality of 83 healthy cell type-specific GEMs, which were also reconstructed with the tINIT algorithm. We predicted 101 antimetabolites that could be effective in preventing tumor growth in all HCC patients, and 46 antimetabolites which were specific to individual patients. Twenty-two of the 101 predicted antimetabolites have already been used in different cancer treatment strategies, while the remaining antimetabolites represent new potential drugs. Finally, one of the identified targets was validated experimentally, and it was confirmed to attenuate growth of the HepG2 cell line. PMID:24646661

  18. THE PATIENT AS PERSON IN AN INCREASINGLY GENE-CENTRIC UNIVERSE: HOW HEALTHCARE PROFESSIONALS SHOULD THINK ABOUT GENOMICS AND EVOLUTION

    PubMed Central

    Jackson, Timothy P.

    2009-01-01

    In the past, the primary threat to the patient as person was a medical utilitarianism that would sacrifice the individual for the collective, that would coercively (ab)use a person for the sake of an in-group’s health or happiness. Today, the threat is not only from vainglorious social groups but also from valorized genes and genomes. An over-valuation of genes risks making persons seem epiphenomenal. A central thesis of this paper is that religious healthcare professionals have unique resources to combat this. PMID:19170083

  19. The patient as person in an increasingly gene-centric universe: how healthcare professionals should think about genomics and evolution.

    PubMed

    Jackson, Timothy P

    2009-02-15

    In the past, the primary threat to the patient as person was a medical utilitarianism that would sacrifice the individual for the collective, that would coercively (ab)use a person for the sake of an in-group's health or happiness. Today, the threat is not only from vainglorious social groups but also from valorized genes and genomes. An over-valuation of genes risks making persons seem epiphenomenal. A central thesis of this article is that religious healthcare professionals have unique resources to combat this. PMID:19170083

  20. Genome-Wide Association Analysis of Eating Disorder-Related Symptoms, Behaviors, and Personality Traits

    PubMed Central

    Boraska, Vesna; Davis, Oliver SP; Cherkas, Lynn F; Helder, Sietske G; Harris, Juliette; Krug, Isabel; Pei-Chi Liao, Thomas; Treasure, Janet; Ntalla, Ioanna; Karhunen, Leila; Keski-Rahkonen, Anna; Christakopoulou, Danai; Raevuori, Anu; Shin, So-Youn; Dedoussis, George V; Kaprio, Jaakko; Soranzo, Nicole; Spector, Tim D; Collier, David A; Zeggini, Eleftheria

    2012-01-01

    Eating disorders (EDs) are common, complex psychiatric disorders thought to be caused by both genetic and environmental factors. They share many symptoms, behaviors, and personality traits, which may have overlapping heritability. The aim of the present study is to perform a genome-wide association scan (GWAS) of six ED phenotypes comprising three symptom traits from the Eating Disorders Inventory 2 [Drive for Thinness (DT), Body Dissatisfaction (BD), and Bulimia], Weight Fluctuation symptom, Breakfast Skipping behavior and Childhood Obsessive-Compulsive Personality Disorder trait (CHIRP). Investigated traits were derived from standardized self-report questionnaires completed by the TwinsUK population-based cohort. We tested 283,744 directly typed SNPs across six phenotypes of interest in the TwinsUK discovery dataset and followed-up signals from various strata using a two-stage replication strategy in two independent cohorts of European ancestry. We meta-analyzed a total of 2,698 individuals for DT, 2,680 for BD, 2,789 (821 cases/1,968 controls) for Bulimia, 1,360 (633 cases/727 controls) for Childhood Obsessive-Compulsive Personality Disorder trait, 2,773 (761 cases/2,012 controls) for Breakfast Skipping, and 2,967 (798 cases/2,169 controls) for Weight Fluctuation symptom. In this GWAS analysis of six ED-related phenotypes, we detected association of eight genetic variants with P < 10−5. Genetic variants that showed suggestive evidence of association were previously associated with several psychiatric disorders and ED-related phenotypes. Our study indicates that larger-scale collaborative studies will be needed to achieve the necessary power to detect loci underlying ED-related traits. © 2012 Wiley Periodicals, Inc. PMID:22911880

  1. Integration of bioinformatics into an undergraduate biology curriculum and the impact on development of mathematical skills.

    PubMed

    Wightman, Bruce; Hark, Amy T

    2012-01-01

    The development of fields such as bioinformatics and genomics has created new challenges and opportunities for undergraduate biology curricula. Students preparing for careers in science, technology, and medicine need more intensive study of bioinformatics and more sophisticated training in the mathematics on which this field is based. In this study, we deliberately integrated bioinformatics instruction at multiple course levels into an existing biology curriculum. Students in an introductory biology course, intermediate lab courses, and advanced project-oriented courses all participated in new course components designed to sequentially introduce bioinformatics skills and knowledge, as well as computational approaches that are common to many bioinformatics applications. In each course, bioinformatics learning was embedded in an existing disciplinary instructional sequence, as opposed to having a single course where all bioinformatics learning occurs. We designed direct and indirect assessment tools to follow student progress through the course sequence. Our data show significant gains in both student confidence and ability in bioinformatics during individual courses and as course level increases. Despite evidence of substantial student learning in both bioinformatics and mathematics, students were skeptical about the link between learning bioinformatics and learning mathematics. While our approach resulted in substantial learning gains, student "buy-in" and engagement might be better in longer project-based activities that demand application of skills to research problems. Nevertheless, in situations where a concentrated focus on project-oriented bioinformatics is not possible or desirable, our approach of integrating multiple smaller components into an existing curriculum provides an alternative. PMID:22987552

  2. Visualizing and Sharing Results in Bioinformatics Projects: GBrowse and GenBank Exports

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Effective tools for presenting and sharing data are necessary for collaborative projects, typical for bioinformatics. In order to facilitate sharing our data with other genomics, molecular biology, and bioinformatics researchers, we have developed software to export our data to GenBank and combined ...

  3. Integration of Bioinformatics into an Undergraduate Biology Curriculum and the Impact on Development of Mathematical Skills

    ERIC Educational Resources Information Center

    Wightman, Bruce; Hark, Amy T.

    2012-01-01

    The development of fields such as bioinformatics and genomics has created new challenges and opportunities for undergraduate biology curricula. Students preparing for careers in science, technology, and medicine need more intensive study of bioinformatics and more sophisticated training in the mathematics on which this field is based. In this…

  4. Making Bioinformatics Projects a Meaningful Experience in an Undergraduate Biotechnology or Biomedical Science Programme

    ERIC Educational Resources Information Center

    Sutcliffe, Iain C.; Cummings, Stephen P.

    2007-01-01

    Bioinformatics has emerged as an important discipline within the biological sciences that allows scientists to decipher and manage the vast quantities of data (such as genome sequences) that are now available. Consequently, there is an obvious need to provide graduates in biosciences with generic, transferable skills in bioinformatics. We present…

  5. Virtual Bioinformatics Distance Learning Suite

    ERIC Educational Resources Information Center

    Tolvanen, Martti; Vihinen, Mauno

    2004-01-01

    Distance learning as a computer-aided concept allows students to take courses from anywhere at any time. In bioinformatics, computers are needed to collect, store, process, and analyze massive amounts of biological and biomedical data. We have applied the concept of distance learning in virtual bioinformatics to provide university course material…

  6. Channelrhodopsins: a bioinformatics perspective.

    PubMed

    Del Val, Coral; Royuela-Flor, José; Milenkovic, Stefan; Bondar, Ana-Nicoleta

    2014-05-01

    Channelrhodopsins are microbial-type rhodopsins that function as light-gated cation channels. Understanding how the detailed architecture of the protein governs its dynamics and specificity for ions is important, because it has the potential to assist in designing site-directed channelrhodopsin mutants for specific neurobiology applications. Here we use bioinformatics methods to derive accurate alignments of channelrhodopsin sequences, assess the sequence conservation patterns and find conserved motifs in channelrhodopsins, and use homology modeling to construct three-dimensional structural models of channelrhodopsins. The analyses reveal that helices C and D of channelrhodopsins contain Cys, Ser, and Thr groups that can engage in both intra- and inter-helical hydrogen bonds. We propose that these polar groups participate in inter-helical hydrogen-bonding clusters important for the protein conformational dynamics and for the local water interactions. This article is part of a Special Issue entitled: Retinal Proteins - You can teach an old dog new tricks. PMID:24252597

  7. Intrageneric Primer Design: Bringing Bioinformatics Tools to the Class

    ERIC Educational Resources Information Center

    Lima, Andre O. S.; Garces, Sergio P. S.

    2006-01-01

    Bioinformatics is one of the fastest growing scientific areas over the last decade. It focuses on the use of informatics tools for the organization and analysis of biological data. An example of their importance is the availability nowadays of dozens of software programs for genomic and proteomic studies. Thus, there is a growing field (private…

  8. Bioinformatics in high school biology curricula: a study of state science standards.

    PubMed

    Wefer, Stephen H; Sheppard, Keith

    2008-01-01

    The proliferation of bioinformatics in modern biology marks a modern revolution in science that promises to influence science education at all levels. This study analyzed secondary school science standards of 49 U.S. states (Iowa has no science framework) and the District of Columbia for content related to bioinformatics. The bioinformatics content of each state's biology standards was analyzed and categorized into nine areas: Human Genome Project/genomics, forensics, evolution, classification, nucleotide variations, medicine, computer use, agriculture/food technology, and science technology and society/socioscientific issues. Findings indicated a generally low representation of bioinformatics-related content, which varied substantially across the different areas, with Human Genome Project/genomics and computer use being the lowest (8%), and evolution being the highest (64%) among states' science frameworks. This essay concludes with recommendations for reworking/rewording existing standards to facilitate the goal of promoting science literacy among secondary school students. PMID:18316818

  9. Bioinformatics in High School Biology Curricula: A Study of State Science Standards

    PubMed Central

    Sheppard, Keith

    2008-01-01

    The proliferation of bioinformatics in modern biology marks a modern revolution in science that promises to influence science education at all levels. This study analyzed secondary school science standards of 49 U.S. states (Iowa has no science framework) and the District of Columbia for content related to bioinformatics. The bioinformatics content of each state's biology standards was analyzed and categorized into nine areas: Human Genome Project/genomics, forensics, evolution, classification, nucleotide variations, medicine, computer use, agriculture/food technology, and science technology and society/socioscientific issues. Findings indicated a generally low representation of bioinformatics-related content, which varied substantially across the different areas, with Human Genome Project/genomics and computer use being the lowest (8%), and evolution being the highest (64%) among states' science frameworks. This essay concludes with recommendations for reworking/rewording existing standards to facilitate the goal of promoting science literacy among secondary school students. PMID:18316818

  10. Translational bioinformatics in psychoneuroimmunology: methods and applications.

    PubMed

    Yan, Qing

    2012-01-01

    Translational bioinformatics plays an indispensable role in transforming psychoneuroimmunology (PNI) into personalized medicine. It provides a powerful method to bridge the gaps between various knowledge domains in PNI and systems biology. Translational bioinformatics methods at various systems levels can facilitate pattern recognition, and expedite and validate the discovery of systemic biomarkers to allow their incorporation into clinical trials and outcome assessments. Analysis of the correlations between genotypes and phenotypes including the behavioral-based profiles will contribute to the transition from the disease-based medicine to human-centered medicine. Translational bioinformatics would also enable the establishment of predictive models for patient responses to diseases, vaccines, and drugs. In PNI research, the development of systems biology models such as those of the neurons would play a critical role. Methods based on data integration, data mining, and knowledge representation are essential elements in building health information systems such as electronic health records and computerized decision support systems. Data integration of genes, pathophysiology, and behaviors are needed for a broad range of PNI studies. Knowledge discovery approaches such as network-based systems biology methods are valuable in studying the cross-talks among pathways in various brain regions involved in disorders such as Alzheimer's disease. PMID:22933157