WorldWideScience

Sample records for bioinformatics supporting discovery

  1. Bioinformatics in translational drug discovery.

    Science.gov (United States)

    Wooller, Sarah K; Benstead-Hume, Graeme; Chen, Xiangrong; Ali, Yusuf; Pearl, Frances M G

    2017-08-31

    Bioinformatics approaches are becoming ever more essential in translational drug discovery both in academia and within the pharmaceutical industry. Computational exploitation of the increasing volumes of data generated during all phases of drug discovery is enabling key challenges of the process to be addressed. Here, we highlight some of the areas in which bioinformatics resources and methods are being developed to support the drug discovery pipeline. These include the creation of large data warehouses, bioinformatics algorithms to analyse 'big data' that identify novel drug targets and/or biomarkers, programs to assess the tractability of targets, and prediction of repositioning opportunities that use licensed drugs to treat additional indications. © 2017 The Author(s).

  2. Bioinformatics for cancer immunotherapy target discovery

    DEFF Research Database (Denmark)

    Olsen, Lars Rønn; Campos, Benito; Barnkob, Mike Stein

    2014-01-01

    therapy target discovery in a bioinformatics analysis pipeline. We describe specialized bioinformatics tools and databases for three main bottlenecks in immunotherapy target discovery: the cataloging of potentially antigenic proteins, the identification of potential HLA binders, and the selection epitopes...

  3. Open discovery: An integrated live Linux platform of Bioinformatics tools.

    Science.gov (United States)

    Vetrivel, Umashankar; Pilla, Kalabharath

    2008-01-01

    Historically, live linux distributions for Bioinformatics have paved way for portability of Bioinformatics workbench in a platform independent manner. Moreover, most of the existing live Linux distributions limit their usage to sequence analysis and basic molecular visualization programs and are devoid of data persistence. Hence, open discovery - a live linux distribution has been developed with the capability to perform complex tasks like molecular modeling, docking and molecular dynamics in a swift manner. Furthermore, it is also equipped with complete sequence analysis environment and is capable of running windows executable programs in Linux environment. Open discovery portrays the advanced customizable configuration of fedora, with data persistency accessible via USB drive or DVD. The Open Discovery is distributed free under Academic Free License (AFL) and can be downloaded from http://www.OpenDiscovery.org.in.

  4. Integration of Proteomics, Bioinformatics, and Systems Biology in Traumatic Brain Injury Biomarker Discovery

    Science.gov (United States)

    Guingab-Cagmat, J.D.; Cagmat, E.B.; Hayes, R.L.; Anagli, J.

    2013-01-01

    Traumatic brain injury (TBI) is a major medical crisis without any FDA-approved pharmacological therapies that have been demonstrated to improve functional outcomes. It has been argued that discovery of disease-relevant biomarkers might help to guide successful clinical trials for TBI. Major advances in mass spectrometry (MS) have revolutionized the field of proteomic biomarker discovery and facilitated the identification of several candidate markers that are being further evaluated for their efficacy as TBI biomarkers. However, several hurdles have to be overcome even during the discovery phase which is only the first step in the long process of biomarker development. The high-throughput nature of MS-based proteomic experiments generates a massive amount of mass spectral data presenting great challenges in downstream interpretation. Currently, different bioinformatics platforms are available for functional analysis and data mining of MS-generated proteomic data. These tools provide a way to convert data sets to biologically interpretable results and functional outcomes. A strategy that has promise in advancing biomarker development involves the triad of proteomics, bioinformatics, and systems biology. In this review, a brief overview of how bioinformatics and systems biology tools analyze, transform, and interpret complex MS datasets into biologically relevant results is discussed. In addition, challenges and limitations of proteomics, bioinformatics, and systems biology in TBI biomarker discovery are presented. A brief survey of researches that utilized these three overlapping disciplines in TBI biomarker discovery is also presented. Finally, examples of TBI biomarkers and their applications are discussed. PMID:23750150

  5. The web server of IBM's Bioinformatics and Pattern Discovery group.

    Science.gov (United States)

    Huynh, Tien; Rigoutsos, Isidore; Parida, Laxmi; Platt, Daniel; Shibuya, Tetsuo

    2003-07-01

    We herein present and discuss the services and content which are available on the web server of IBM's Bioinformatics and Pattern Discovery group. The server is operational around the clock and provides access to a variety of methods that have been published by the group's members and collaborators. The available tools correspond to applications ranging from the discovery of patterns in streams of events and the computation of multiple sequence alignments, to the discovery of genes in nucleic acid sequences and the interactive annotation of amino acid sequences. Additionally, annotations for more than 70 archaeal, bacterial, eukaryotic and viral genomes are available on-line and can be searched interactively. The tools and code bundles can be accessed beginning at http://cbcsrv.watson.ibm.com/Tspd.html whereas the genomics annotations are available at http://cbcsrv.watson.ibm.com/Annotations/.

  6. Bioinformatics Tools for the Discovery of New Nonribosomal Peptides

    DEFF Research Database (Denmark)

    Leclère, Valérie; Weber, Tilmann; Jacques, Philippe

    2016-01-01

    -dimensional structure of the peptides can be compared with the structural patterns of all known NRPs. The presented workflow leads to an efficient and rapid screening of genomic data generated by high throughput technologies. The exploration of such sequenced genomes may lead to the discovery of new drugs (i......This chapter helps in the use of bioinformatics tools relevant to the discovery of new nonribosomal peptides (NRPs) produced by microorganisms. The strategy described can be applied to draft or fully assembled genome sequences. It relies on the identification of the synthetase genes...... and the deciphering of the domain architecture of the nonribosomal peptide synthetases (NRPSs). In the next step, candidate peptides synthesized by these NRPSs are predicted in silico, considering the specificity of incorporated monomers together with their isomery. To assess their novelty, the two...

  7. XMPP for cloud computing in bioinformatics supporting discovery and invocation of asynchronous web services.

    Science.gov (United States)

    Wagener, Johannes; Spjuth, Ola; Willighagen, Egon L; Wikberg, Jarl E S

    2009-09-04

    Life sciences make heavily use of the web for both data provision and analysis. However, the increasing amount of available data and the diversity of analysis tools call for machine accessible interfaces in order to be effective. HTTP-based Web service technologies, like the Simple Object Access Protocol (SOAP) and REpresentational State Transfer (REST) services, are today the most common technologies for this in bioinformatics. However, these methods have severe drawbacks, including lack of discoverability, and the inability for services to send status notifications. Several complementary workarounds have been proposed, but the results are ad-hoc solutions of varying quality that can be difficult to use. We present a novel approach based on the open standard Extensible Messaging and Presence Protocol (XMPP), consisting of an extension (IO Data) to comprise discovery, asynchronous invocation, and definition of data types in the service. That XMPP cloud services are capable of asynchronous communication implies that clients do not have to poll repetitively for status, but the service sends the results back to the client upon completion. Implementations for Bioclipse and Taverna are presented, as are various XMPP cloud services in bio- and cheminformatics. XMPP with its extensions is a powerful protocol for cloud services that demonstrate several advantages over traditional HTTP-based Web services: 1) services are discoverable without the need of an external registry, 2) asynchronous invocation eliminates the need for ad-hoc solutions like polling, and 3) input and output types defined in the service allows for generation of clients on the fly without the need of an external semantics description. The many advantages over existing technologies make XMPP a highly interesting candidate for next generation online services in bioinformatics.

  8. XMPP for cloud computing in bioinformatics supporting discovery and invocation of asynchronous web services

    Science.gov (United States)

    Wagener, Johannes; Spjuth, Ola; Willighagen, Egon L; Wikberg, Jarl ES

    2009-01-01

    Background Life sciences make heavily use of the web for both data provision and analysis. However, the increasing amount of available data and the diversity of analysis tools call for machine accessible interfaces in order to be effective. HTTP-based Web service technologies, like the Simple Object Access Protocol (SOAP) and REpresentational State Transfer (REST) services, are today the most common technologies for this in bioinformatics. However, these methods have severe drawbacks, including lack of discoverability, and the inability for services to send status notifications. Several complementary workarounds have been proposed, but the results are ad-hoc solutions of varying quality that can be difficult to use. Results We present a novel approach based on the open standard Extensible Messaging and Presence Protocol (XMPP), consisting of an extension (IO Data) to comprise discovery, asynchronous invocation, and definition of data types in the service. That XMPP cloud services are capable of asynchronous communication implies that clients do not have to poll repetitively for status, but the service sends the results back to the client upon completion. Implementations for Bioclipse and Taverna are presented, as are various XMPP cloud services in bio- and cheminformatics. Conclusion XMPP with its extensions is a powerful protocol for cloud services that demonstrate several advantages over traditional HTTP-based Web services: 1) services are discoverable without the need of an external registry, 2) asynchronous invocation eliminates the need for ad-hoc solutions like polling, and 3) input and output types defined in the service allows for generation of clients on the fly without the need of an external semantics description. The many advantages over existing technologies make XMPP a highly interesting candidate for next generation online services in bioinformatics. PMID:19732427

  9. XMPP for cloud computing in bioinformatics supporting discovery and invocation of asynchronous web services

    Directory of Open Access Journals (Sweden)

    Willighagen Egon L

    2009-09-01

    Full Text Available Abstract Background Life sciences make heavily use of the web for both data provision and analysis. However, the increasing amount of available data and the diversity of analysis tools call for machine accessible interfaces in order to be effective. HTTP-based Web service technologies, like the Simple Object Access Protocol (SOAP and REpresentational State Transfer (REST services, are today the most common technologies for this in bioinformatics. However, these methods have severe drawbacks, including lack of discoverability, and the inability for services to send status notifications. Several complementary workarounds have been proposed, but the results are ad-hoc solutions of varying quality that can be difficult to use. Results We present a novel approach based on the open standard Extensible Messaging and Presence Protocol (XMPP, consisting of an extension (IO Data to comprise discovery, asynchronous invocation, and definition of data types in the service. That XMPP cloud services are capable of asynchronous communication implies that clients do not have to poll repetitively for status, but the service sends the results back to the client upon completion. Implementations for Bioclipse and Taverna are presented, as are various XMPP cloud services in bio- and cheminformatics. Conclusion XMPP with its extensions is a powerful protocol for cloud services that demonstrate several advantages over traditional HTTP-based Web services: 1 services are discoverable without the need of an external registry, 2 asynchronous invocation eliminates the need for ad-hoc solutions like polling, and 3 input and output types defined in the service allows for generation of clients on the fly without the need of an external semantics description. The many advantages over existing technologies make XMPP a highly interesting candidate for next generation online services in bioinformatics.

  10. The web server of IBM's Bioinformatics and Pattern Discovery group: 2004 update.

    Science.gov (United States)

    Huynh, Tien; Rigoutsos, Isidore

    2004-07-01

    In this report, we provide an update on the services and content which are available on the web server of IBM's Bioinformatics and Pattern Discovery group. The server, which is operational around the clock, provides access to a large number of methods that have been developed and published by the group's members. There is an increasing number of problems that these tools can help tackle; these problems range from the discovery of patterns in streams of events and the computation of multiple sequence alignments, to the discovery of genes in nucleic acid sequences, the identification--directly from sequence--of structural deviations from alpha-helicity and the annotation of amino acid sequences for antimicrobial activity. Additionally, annotations for more than 130 archaeal, bacterial, eukaryotic and viral genomes are now available on-line and can be searched interactively. The tools and code bundles continue to be accessible from http://cbcsrv.watson.ibm.com/Tspd.html whereas the genomics annotations are available at http://cbcsrv.watson.ibm.com/Annotations/.

  11. Translational Bioinformatics and Clinical Research (Biomedical) Informatics.

    Science.gov (United States)

    Sirintrapun, S Joseph; Zehir, Ahmet; Syed, Aijazuddin; Gao, JianJiong; Schultz, Nikolaus; Cheng, Donavan T

    2015-06-01

    Translational bioinformatics and clinical research (biomedical) informatics are the primary domains related to informatics activities that support translational research. Translational bioinformatics focuses on computational techniques in genetics, molecular biology, and systems biology. Clinical research (biomedical) informatics involves the use of informatics in discovery and management of new knowledge relating to health and disease. This article details 3 projects that are hybrid applications of translational bioinformatics and clinical research (biomedical) informatics: The Cancer Genome Atlas, the cBioPortal for Cancer Genomics, and the Memorial Sloan Kettering Cancer Center clinical variants and results database, all designed to facilitate insights into cancer biology and clinical/therapeutic correlations. Copyright © 2015 Elsevier Inc. All rights reserved.

  12. Opportunities and challenges provided by cloud repositories for bioinformatics-enabled drug discovery.

    Science.gov (United States)

    Dalpé, Gratien; Joly, Yann

    2014-09-01

    Healthcare-related bioinformatics databases are increasingly offering the possibility to maintain, organize, and distribute DNA sequencing data. Different national and international institutions are currently hosting such databases that offer researchers website platforms where they can obtain sequencing data on which they can perform different types of analysis. Until recently, this process remained mostly one-dimensional, with most analysis concentrated on a limited amount of data. However, newer genome sequencing technology is producing a huge amount of data that current computer facilities are unable to handle. An alternative approach has been to start adopting cloud computing services for combining the information embedded in genomic and model system biology data, patient healthcare records, and clinical trials' data. In this new technological paradigm, researchers use virtual space and computing power from existing commercial or not-for-profit cloud service providers to access, store, and analyze data via different application programming interfaces. Cloud services are an alternative to the need of larger data storage; however, they raise different ethical, legal, and social issues. The purpose of this Commentary is to summarize how cloud computing can contribute to bioinformatics-based drug discovery and to highlight some of the outstanding legal, ethical, and social issues that are inherent in the use of cloud services. © 2014 Wiley Periodicals, Inc.

  13. Bioinformatics and biomarker discovery "Omic" data analysis for personalized medicine

    CERN Document Server

    Azuaje, Francisco

    2010-01-01

    This book is designed to introduce biologists, clinicians and computational researchers to fundamental data analysis principles, techniques and tools for supporting the discovery of biomarkers and the implementation of diagnostic/prognostic systems. The focus of the book is on how fundamental statistical and data mining approaches can support biomarker discovery and evaluation, emphasising applications based on different types of "omic" data. The book also discusses design factors, requirements and techniques for disease screening, diagnostic and prognostic applications. Readers are provided w

  14. Applications and Methods Utilizing the Simple Semantic Web Architecture and Protocol (SSWAP) for Bioinformatics Resource Discovery and Disparate Data and Service Integration

    Science.gov (United States)

    Scientific data integration and computational service discovery are challenges for the bioinformatic community. This process is made more difficult by the separate and independent construction of biological databases, which makes the exchange of scientific data between information resources difficu...

  15. jORCA: easily integrating bioinformatics Web Services.

    Science.gov (United States)

    Martín-Requena, Victoria; Ríos, Javier; García, Maximiliano; Ramírez, Sergio; Trelles, Oswaldo

    2010-02-15

    Web services technology is becoming the option of choice to deploy bioinformatics tools that are universally available. One of the major strengths of this approach is that it supports machine-to-machine interoperability over a network. However, a weakness of this approach is that various Web Services differ in their definition and invocation protocols, as well as their communication and data formats-and this presents a barrier to service interoperability. jORCA is a desktop client aimed at facilitating seamless integration of Web Services. It does so by making a uniform representation of the different web resources, supporting scalable service discovery, and automatic composition of workflows. Usability is at the top of the jORCA agenda; thus it is a highly customizable and extensible application that accommodates a broad range of user skills featuring double-click invocation of services in conjunction with advanced execution-control, on the fly data standardization, extensibility of viewer plug-ins, drag-and-drop editing capabilities, plus a file-based browsing style and organization of favourite tools. The integration of bioinformatics Web Services is made easier to support a wider range of users. .

  16. Recent developments in life sciences research: Role of bioinformatics

    African Journals Online (AJOL)

    Life sciences research and development has opened up new challenges and opportunities for bioinformatics. The contribution of bioinformatics advances made possible the mapping of the entire human genome and genomes of many other organisms in just over a decade. These discoveries, along with current efforts to ...

  17. Tools and data services registry: a community effort to document bioinformatics resources

    Science.gov (United States)

    Ison, Jon; Rapacki, Kristoffer; Ménager, Hervé; Kalaš, Matúš; Rydza, Emil; Chmura, Piotr; Anthon, Christian; Beard, Niall; Berka, Karel; Bolser, Dan; Booth, Tim; Bretaudeau, Anthony; Brezovsky, Jan; Casadio, Rita; Cesareni, Gianni; Coppens, Frederik; Cornell, Michael; Cuccuru, Gianmauro; Davidsen, Kristian; Vedova, Gianluca Della; Dogan, Tunca; Doppelt-Azeroual, Olivia; Emery, Laura; Gasteiger, Elisabeth; Gatter, Thomas; Goldberg, Tatyana; Grosjean, Marie; Grüning, Björn; Helmer-Citterich, Manuela; Ienasescu, Hans; Ioannidis, Vassilios; Jespersen, Martin Closter; Jimenez, Rafael; Juty, Nick; Juvan, Peter; Koch, Maximilian; Laibe, Camille; Li, Jing-Woei; Licata, Luana; Mareuil, Fabien; Mičetić, Ivan; Friborg, Rune Møllegaard; Moretti, Sebastien; Morris, Chris; Möller, Steffen; Nenadic, Aleksandra; Peterson, Hedi; Profiti, Giuseppe; Rice, Peter; Romano, Paolo; Roncaglia, Paola; Saidi, Rabie; Schafferhans, Andrea; Schwämmle, Veit; Smith, Callum; Sperotto, Maria Maddalena; Stockinger, Heinz; Vařeková, Radka Svobodová; Tosatto, Silvio C.E.; de la Torre, Victor; Uva, Paolo; Via, Allegra; Yachdav, Guy; Zambelli, Federico; Vriend, Gert; Rost, Burkhard; Parkinson, Helen; Løngreen, Peter; Brunak, Søren

    2016-01-01

    Life sciences are yielding huge data sets that underpin scientific discoveries fundamental to improvement in human health, agriculture and the environment. In support of these discoveries, a plethora of databases and tools are deployed, in technically complex and diverse implementations, across a spectrum of scientific disciplines. The corpus of documentation of these resources is fragmented across the Web, with much redundancy, and has lacked a common standard of information. The outcome is that scientists must often struggle to find, understand, compare and use the best resources for the task at hand. Here we present a community-driven curation effort, supported by ELIXIR—the European infrastructure for biological information—that aspires to a comprehensive and consistent registry of information about bioinformatics resources. The sustainable upkeep of this Tools and Data Services Registry is assured by a curation effort driven by and tailored to local needs, and shared amongst a network of engaged partners. As of November 2015, the registry includes 1785 resources, with depositions from 126 individual registrations including 52 institutional providers and 74 individuals. With community support, the registry can become a standard for dissemination of information about bioinformatics resources: we welcome everyone to join us in this common endeavour. The registry is freely available at https://bio.tools. PMID:26538599

  18. Bioinformatics for discovery of microbiome variation

    DEFF Research Database (Denmark)

    Brejnrod, Asker Daniel

    of various molecular methods to build hypotheses about the impact of a copper contaminated soil. The introduction is a broad introduction to the field of microbiome research with a focus on the technologies that enable these discoveries and how some of the broader issues have related to this thesis......Sequencing based tools have revolutionized microbiology in recent years. Highthroughput DNA sequencing have allowed high-resolution studies on microbial life in many different environments and at unprecedented low cost. These culture-independent methods have helped discovery of novel bacteria...... 1 ,“Large-scale benchmarking reveals false discoveries and count transformation sensitivity in 16S rRNA gene amplicon data analysis methods used in microbiome studies”, benchmarked the performance of a variety of popular statistical methods for discovering differentially abundant bacteria . between...

  19. Bioinformatics Training: A Review of Challenges, Actions and Support Requirements

    DEFF Research Database (Denmark)

    Schneider, M.V.; Watson, J.; Attwood, T.

    2010-01-01

    As bioinformatics becomes increasingly central to research in the molecular life sciences, the need to train non-bioinformaticians to make the most of bioinformatics resources is growing. Here, we review the key challenges and pitfalls to providing effective training for users of bioinformatics...... services, and discuss successful training strategies shared by a diverse set of bioinformatics trainers. We also identify steps that trainers in bioinformatics could take together to advance the state of the art in current training practices. The ideas presented in this article derive from the first...

  20. Bioinformatics-Aided Venomics

    Directory of Open Access Journals (Sweden)

    Quentin Kaas

    2015-06-01

    Full Text Available 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.

  1. Establishing a distributed national research infrastructure providing bioinformatics support to life science researchers in Australia.

    Science.gov (United States)

    Schneider, Maria Victoria; Griffin, Philippa C; Tyagi, Sonika; Flannery, Madison; Dayalan, Saravanan; Gladman, Simon; Watson-Haigh, Nathan; Bayer, Philipp E; Charleston, Michael; Cooke, Ira; Cook, Rob; Edwards, Richard J; Edwards, David; Gorse, Dominique; McConville, Malcolm; Powell, David; Wilkins, Marc R; Lonie, Andrew

    2017-06-30

    EMBL Australia Bioinformatics Resource (EMBL-ABR) is a developing national research infrastructure, providing bioinformatics resources and support to life science and biomedical researchers in Australia. EMBL-ABR comprises 10 geographically distributed national nodes with one coordinating hub, with current funding provided through Bioplatforms Australia and the University of Melbourne for its initial 2-year development phase. The EMBL-ABR mission is to: (1) increase Australia's capacity in bioinformatics and data sciences; (2) contribute to the development of training in bioinformatics skills; (3) showcase Australian data sets at an international level and (4) enable engagement in international programs. The activities of EMBL-ABR are focussed in six key areas, aligning with comparable international initiatives such as ELIXIR, CyVerse and NIH Commons. These key areas-Tools, Data, Standards, Platforms, Compute and Training-are described in this article. © The Author 2017. Published by Oxford University Press.

  2. Bioinformatics for Exploration

    Science.gov (United States)

    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. Microsoft Biology Initiative: .NET Bioinformatics Platform and Tools

    Science.gov (United States)

    Diaz Acosta, B.

    2011-01-01

    The Microsoft Biology Initiative (MBI) is an effort in Microsoft Research to bring new technology and tools to the area of bioinformatics and biology. This initiative is comprised of two primary components, the Microsoft Biology Foundation (MBF) and the Microsoft Biology Tools (MBT). MBF is a language-neutral bioinformatics toolkit built as an extension to the Microsoft .NET Framework—initially aimed at the area of Genomics research. Currently, it implements a range of parsers for common bioinformatics file formats; a range of algorithms for manipulating DNA, RNA, and protein sequences; and a set of connectors to biological web services such as NCBI BLAST. MBF is available under an open source license, and executables, source code, demo applications, documentation and training materials are freely downloadable from http://research.microsoft.com/bio. MBT is a collection of tools that enable biology and bioinformatics researchers to be more productive in making scientific discoveries.

  4. Aligning experimental design with bioinformatics analysis to meet discovery research objectives.

    Science.gov (United States)

    Kane, Michael D

    2002-01-01

    The utility of genomic technology and bioinformatic analytical support to provide new and needed insight into the molecular basis of disease, development, and diversity continues to grow as more research model systems and populations are investigated. Yet deriving results that meet a specific set of research objectives requires aligning or coordinating the design of the experiment, the laboratory techniques, and the data analysis. The following paragraphs describe several important interdependent factors that need to be considered to generate high quality data from the microarray platform. These factors include aligning oligonucleotide probe design with the sample labeling strategy if oligonucleotide probes are employed, recognizing that compromises are inherent in different sample procurement methods, normalizing 2-color microarray raw data, and distinguishing the difference between gene clustering and sample clustering. These factors do not represent an exhaustive list of technical variables in microarray-based research, but this list highlights those variables that span both experimental execution and data analysis. Copyright 2001 Wiley-Liss, Inc.

  5. Computational biology and bioinformatics in Nigeria.

    Science.gov (United States)

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

    2014-04-01

    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.

  6. Computational biology and bioinformatics in Nigeria.

    Directory of Open Access Journals (Sweden)

    Segun A Fatumo

    2014-04-01

    Full Text Available 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.

  7. Bioinformatics approaches for identifying new therapeutic bioactive peptides in food

    Directory of Open Access Journals (Sweden)

    Nora Khaldi

    2012-10-01

    Full Text Available ABSTRACT:The traditional methods for mining foods for bioactive peptides are tedious and long. Similar to the drug industry, the length of time to identify and deliver a commercial health ingredient that reduces disease symptoms can take anything between 5 to 10 years. Reducing this time and effort is crucial in order to create new commercially viable products with clear and important health benefits. In the past few years, bioinformatics, the science that brings together fast computational biology, and efficient genome mining, is appearing as the long awaited solution to this problem. By quickly mining food genomes for characteristics of certain food therapeutic ingredients, researchers can potentially find new ones in a matter of a few weeks. Yet, surprisingly, very little success has been achieved so far using bioinformatics in mining for food bioactives.The absence of food specific bioinformatic mining tools, the slow integration of both experimental mining and bioinformatics, and the important difference between different experimental platforms are some of the reasons for the slow progress of bioinformatics in the field of functional food and more specifically in bioactive peptide discovery.In this paper I discuss some methods that could be easily translated, using a rational peptide bioinformatics design, to food bioactive peptide mining. I highlight the need for an integrated food peptide database. I also discuss how to better integrate experimental work with bioinformatics in order to improve the mining of food for bioactive peptides, therefore achieving a higher success rates.

  8. Development of Bioinformatics Infrastructure for Genomics Research.

    Science.gov (United States)

    Mulder, Nicola J; Adebiyi, Ezekiel; Adebiyi, Marion; Adeyemi, Seun; Ahmed, Azza; Ahmed, Rehab; Akanle, Bola; Alibi, Mohamed; Armstrong, Don L; Aron, Shaun; Ashano, Efejiro; Baichoo, Shakuntala; Benkahla, Alia; Brown, David K; Chimusa, Emile R; Fadlelmola, Faisal M; Falola, Dare; Fatumo, Segun; Ghedira, Kais; Ghouila, Amel; Hazelhurst, Scott; Isewon, Itunuoluwa; Jung, Segun; Kassim, Samar Kamal; Kayondo, Jonathan K; Mbiyavanga, Mamana; Meintjes, Ayton; Mohammed, Somia; Mosaku, Abayomi; Moussa, Ahmed; Muhammd, Mustafa; Mungloo-Dilmohamud, Zahra; Nashiru, Oyekanmi; Odia, Trust; Okafor, Adaobi; Oladipo, Olaleye; Osamor, Victor; Oyelade, Jellili; Sadki, Khalid; Salifu, Samson Pandam; Soyemi, Jumoke; Panji, Sumir; Radouani, Fouzia; Souiai, Oussama; Tastan Bishop, Özlem

    2017-06-01

    Although pockets of bioinformatics excellence have developed in Africa, generally, large-scale genomic data analysis has been limited by the availability of expertise and infrastructure. H3ABioNet, a pan-African bioinformatics network, was established to build capacity specifically to enable H3Africa (Human Heredity and Health in Africa) researchers to analyze their data in Africa. Since the inception of the H3Africa initiative, H3ABioNet's role has evolved in response to changing needs from the consortium and the African bioinformatics community. H3ABioNet set out to develop core bioinformatics infrastructure and capacity for genomics research in various aspects of data collection, transfer, storage, and analysis. Various resources have been developed to address genomic data management and analysis needs of H3Africa researchers and other scientific communities on the continent. NetMap was developed and used to build an accurate picture of network performance within Africa and between Africa and the rest of the world, and Globus Online has been rolled out to facilitate data transfer. A participant recruitment database was developed to monitor participant enrollment, and data is being harmonized through the use of ontologies and controlled vocabularies. The standardized metadata will be integrated to provide a search facility for H3Africa data and biospecimens. Because H3Africa projects are generating large-scale genomic data, facilities for analysis and interpretation are critical. H3ABioNet is implementing several data analysis platforms that provide a large range of bioinformatics tools or workflows, such as Galaxy, the Job Management System, and eBiokits. A set of reproducible, portable, and cloud-scalable pipelines to support the multiple H3Africa data types are also being developed and dockerized to enable execution on multiple computing infrastructures. In addition, new tools have been developed for analysis of the uniquely divergent African data and for

  9. BLSSpeller: exhaustive comparative discovery of conserved cis-regulatory elements.

    Science.gov (United States)

    De Witte, Dieter; Van de Velde, Jan; Decap, Dries; Van Bel, Michiel; Audenaert, Pieter; Demeester, Piet; Dhoedt, Bart; Vandepoele, Klaas; Fostier, Jan

    2015-12-01

    The accurate discovery and annotation of regulatory elements remains a challenging problem. The growing number of sequenced genomes creates new opportunities for comparative approaches to motif discovery. Putative binding sites are then considered to be functional if they are conserved in orthologous promoter sequences of multiple related species. Existing methods for comparative motif discovery usually rely on pregenerated multiple sequence alignments, which are difficult to obtain for more diverged species such as plants. As a consequence, misaligned regulatory elements often remain undetected. We present a novel algorithm that supports both alignment-free and alignment-based motif discovery in the promoter sequences of related species. Putative motifs are exhaustively enumerated as words over the IUPAC alphabet and screened for conservation using the branch length score. Additionally, a confidence score is established in a genome-wide fashion. In order to take advantage of a cloud computing infrastructure, the MapReduce programming model is adopted. The method is applied to four monocotyledon plant species and it is shown that high-scoring motifs are significantly enriched for open chromatin regions in Oryza sativa and for transcription factor binding sites inferred through protein-binding microarrays in O.sativa and Zea mays. Furthermore, the method is shown to recover experimentally profiled ga2ox1-like KN1 binding sites in Z.mays. BLSSpeller was written in Java. Source code and manual are available at http://bioinformatics.intec.ugent.be/blsspeller Klaas.Vandepoele@psb.vib-ugent.be or jan.fostier@intec.ugent.be. Supplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press.

  10. Developing library bioinformatics services in context: the Purdue University Libraries bioinformationist program.

    Science.gov (United States)

    Rein, Diane C

    2006-07-01

    Purdue University is a major agricultural, engineering, biomedical, and applied life science research institution with an increasing focus on bioinformatics research that spans multiple disciplines and campus academic units. The Purdue University Libraries (PUL) hired a molecular biosciences specialist to discover, engage, and support bioinformatics needs across the campus. After an extended period of information needs assessment and environmental scanning, the specialist developed a week of focused bioinformatics instruction (Bioinformatics Week) to launch system-wide, library-based bioinformatics services. The specialist employed a two-tiered approach to assess user information requirements and expectations. The first phase involved careful observation and collection of information needs in-context throughout the campus, attending laboratory meetings, interviewing department chairs and individual researchers, and engaging in strategic planning efforts. Based on the information gathered during the integration phase, several survey instruments were developed to facilitate more critical user assessment and the recovery of quantifiable data prior to planning. Given information gathered while working with clients and through formal needs assessments, as well as the success of instructional approaches used in Bioinformatics Week, the specialist is developing bioinformatics support services for the Purdue community. The specialist is also engaged in training PUL faculty librarians in bioinformatics to provide a sustaining culture of library-based bioinformatics support and understanding of Purdue's bioinformatics-related decision and policy making.

  11. Taking Bioinformatics to Systems Medicine.

    Science.gov (United States)

    van Kampen, Antoine H C; Moerland, Perry D

    2016-01-01

    Systems medicine promotes a range of approaches and strategies to study human health and disease at a systems level with the aim of improving the overall well-being of (healthy) individuals, and preventing, diagnosing, or curing disease. In this chapter we discuss how bioinformatics critically contributes to systems medicine. First, we explain the role of bioinformatics in the management and analysis of data. In particular we show the importance of publicly available biological and clinical repositories to support systems medicine studies. Second, we discuss how the integration and analysis of multiple types of omics data through integrative bioinformatics may facilitate the determination of more predictive and robust disease signatures, lead to a better understanding of (patho)physiological molecular mechanisms, and facilitate personalized medicine. Third, we focus on network analysis and discuss how gene networks can be constructed from omics data and how these networks can be decomposed into smaller modules. We discuss how the resulting modules can be used to generate experimentally testable hypotheses, provide insight into disease mechanisms, and lead to predictive models. Throughout, we provide several examples demonstrating how bioinformatics contributes to systems medicine and discuss future challenges in bioinformatics that need to be addressed to enable the advancement of systems medicine.

  12. Bioinformatics education dissemination with an evolutionary problem solving perspective.

    Science.gov (United States)

    Jungck, John R; Donovan, Samuel S; Weisstein, Anton E; Khiripet, Noppadon; Everse, Stephen J

    2010-11-01

    Bioinformatics is central to biology education in the 21st century. With the generation of terabytes of data per day, the application of computer-based tools to stored and distributed data is fundamentally changing research and its application to problems in medicine, agriculture, conservation and forensics. In light of this 'information revolution,' undergraduate biology curricula must be redesigned to prepare the next generation of informed citizens as well as those who will pursue careers in the life sciences. The BEDROCK initiative (Bioinformatics Education Dissemination: Reaching Out, Connecting and Knitting together) has fostered an international community of bioinformatics educators. The initiative's goals are to: (i) Identify and support faculty who can take leadership roles in bioinformatics education; (ii) Highlight and distribute innovative approaches to incorporating evolutionary bioinformatics data and techniques throughout undergraduate education; (iii) Establish mechanisms for the broad dissemination of bioinformatics resource materials and teaching models; (iv) Emphasize phylogenetic thinking and problem solving; and (v) Develop and publish new software tools to help students develop and test evolutionary hypotheses. Since 2002, BEDROCK has offered more than 50 faculty workshops around the world, published many resources and supported an environment for developing and sharing bioinformatics education approaches. The BEDROCK initiative builds on the established pedagogical philosophy and academic community of the BioQUEST Curriculum Consortium to assemble the diverse intellectual and human resources required to sustain an international reform effort in undergraduate bioinformatics education.

  13. Incorporating Genomics and Bioinformatics across the Life Sciences Curriculum

    Energy Technology Data Exchange (ETDEWEB)

    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

  14. G-DOC Plus - an integrative bioinformatics platform for precision medicine.

    Science.gov (United States)

    Bhuvaneshwar, Krithika; Belouali, Anas; Singh, Varun; Johnson, Robert M; Song, Lei; Alaoui, Adil; Harris, Michael A; Clarke, Robert; Weiner, Louis M; Gusev, Yuriy; Madhavan, Subha

    2016-04-30

    G-DOC Plus is a data integration and bioinformatics platform that uses cloud computing and other advanced computational tools to handle a variety of biomedical BIG DATA including gene expression arrays, NGS and medical images so that they can be analyzed in the full context of other omics and clinical information. G-DOC Plus currently holds data from over 10,000 patients selected from private and public resources including Gene Expression Omnibus (GEO), The Cancer Genome Atlas (TCGA) and the recently added datasets from REpository for Molecular BRAin Neoplasia DaTa (REMBRANDT), caArray studies of lung and colon cancer, ImmPort and the 1000 genomes data sets. The system allows researchers to explore clinical-omic data one sample at a time, as a cohort of samples; or at the level of population, providing the user with a comprehensive view of the data. G-DOC Plus tools have been leveraged in cancer and non-cancer studies for hypothesis generation and validation; biomarker discovery and multi-omics analysis, to explore somatic mutations and cancer MRI images; as well as for training and graduate education in bioinformatics, data and computational sciences. Several of these use cases are described in this paper to demonstrate its multifaceted usability. G-DOC Plus can be used to support a variety of user groups in multiple domains to enable hypothesis generation for precision medicine research. The long-term vision of G-DOC Plus is to extend this translational bioinformatics platform to stay current with emerging omics technologies and analysis methods to continue supporting novel hypothesis generation, analysis and validation for integrative biomedical research. By integrating several aspects of the disease and exposing various data elements, such as outpatient lab workup, pathology, radiology, current treatments, molecular signatures and expected outcomes over a web interface, G-DOC Plus will continue to strengthen precision medicine research. G-DOC Plus is available

  15. Anthelmintics: From discovery to resistance II (San Diego, 2016

    Directory of Open Access Journals (Sweden)

    Richard J. Martin

    2016-12-01

    Full Text Available The second scientific meeting in the series: “Anthelmintics: From Discovery to Resistance” was held in San Diego in February, 2016. The focus topics of the meeting, related to anthelmintic discovery and resistance, were novel technologies, bioinformatics, commercial interests, anthelmintic modes of action and anthelmintic resistance. Basic scientific, human and veterinary interests were addressed in oral and poster presentations. The delegates were from universities and industries in the US, Europe, Australia and New Zealand. The papers were a great representation of the field, and included the use of C. elegans for lead discovery, mechanisms of anthelmintic resistance, nematode neuropeptides, proteases, B. thuringiensis crystal protein, nicotinic receptors, emodepside, benzimidazoles, P-glycoproteins, natural products, microfluidic techniques and bioinformatics approaches. The NIH also presented NIAID-specific parasite genomic priorities and initiatives. From these papers we introduce below selected papers with a focus on anthelmintic drug screening and development.

  16. Bioinformatics Meets Virology: The European Virus Bioinformatics Center's Second Annual Meeting.

    Science.gov (United States)

    Ibrahim, Bashar; Arkhipova, Ksenia; Andeweg, Arno C; Posada-Céspedes, Susana; Enault, François; Gruber, Arthur; Koonin, Eugene V; Kupczok, Anne; Lemey, Philippe; McHardy, Alice C; McMahon, Dino P; Pickett, Brett E; Robertson, David L; Scheuermann, Richard H; Zhernakova, Alexandra; Zwart, Mark P; Schönhuth, Alexander; Dutilh, Bas E; Marz, Manja

    2018-05-14

    The Second Annual Meeting of the European Virus Bioinformatics Center (EVBC), held in Utrecht, Netherlands, focused on computational approaches in virology, with topics including (but not limited to) virus discovery, diagnostics, (meta-)genomics, modeling, epidemiology, molecular structure, evolution, and viral ecology. The goals of the Second Annual Meeting were threefold: (i) to bring together virologists and bioinformaticians from across the academic, industrial, professional, and training sectors to share best practice; (ii) to provide a meaningful and interactive scientific environment to promote discussion and collaboration between students, postdoctoral fellows, and both new and established investigators; (iii) to inspire and suggest new research directions and questions. Approximately 120 researchers from around the world attended the Second Annual Meeting of the EVBC this year, including 15 renowned international speakers. This report presents an overview of new developments and novel research findings that emerged during the meeting.

  17. Academic Training - Bioinformatics: Decoding the Genome

    CERN Multimedia

    Chris Jones

    2006-01-01

    ACADEMIC TRAINING LECTURE SERIES 27, 28 February 1, 2, 3 March 2006 from 11:00 to 12:00 - Auditorium, bldg. 500 Decoding the Genome A special series of 5 lectures on: Recent extraordinary advances in the life sciences arising through new detection technologies and bioinformatics The past five years have seen an extraordinary change in the information and tools available in the life sciences. The sequencing of the human genome, the discovery that we possess far fewer genes than foreseen, the measurement of the tiny changes in the genomes that differentiate us, the sequencing of the genomes of many pathogens that lead to diseases such as malaria are all examples of completely new information that is now available in the quest for improved healthcare. New tools have allowed similar strides in the discovery of the associated protein structures, providing invaluable information for those searching for new drugs. New DNA microarray chips permit simultaneous measurement of the state of expression of tens...

  18. Bioinformatics meets user-centred design: a perspective.

    Directory of Open Access Journals (Sweden)

    Katrina Pavelin

    Full Text Available Designers have a saying that "the joy of an early release lasts but a short time. The bitterness of an unusable system lasts for years." It is indeed disappointing to discover that your data resources are not being used to their full potential. Not only have you invested your time, effort, and research grant on the project, but you may face costly redesigns if you want to improve the system later. This scenario would be less likely if the product was designed to provide users with exactly what they need, so that it is fit for purpose before its launch. We work at EMBL-European Bioinformatics Institute (EMBL-EBI, and we consult extensively with life science researchers to find out what they need from biological data resources. We have found that although users believe that the bioinformatics community is providing accurate and valuable data, they often find the interfaces to these resources tricky to use and navigate. We believe that if you can find out what your users want even before you create the first mock-up of a system, the final product will provide a better user experience. This would encourage more people to use the resource and they would have greater access to the data, which could ultimately lead to more scientific discoveries. In this paper, we explore the need for a user-centred design (UCD strategy when designing bioinformatics resources and illustrate this with examples from our work at EMBL-EBI. Our aim is to introduce the reader to how selected UCD techniques may be successfully applied to software design for bioinformatics.

  19. G2LC: Resources Autoscaling for Real Time Bioinformatics Applications in IaaS

    Directory of Open Access Journals (Sweden)

    Rongdong Hu

    2015-01-01

    Full Text Available Cloud computing has started to change the way how bioinformatics research is being carried out. Researchers who have taken advantage of this technology can process larger amounts of data and speed up scientific discovery. The variability in data volume results in variable computing requirements. Therefore, bioinformatics researchers are pursuing more reliable and efficient methods for conducting sequencing analyses. This paper proposes an automated resource provisioning method, G2LC, for bioinformatics applications in IaaS. It enables application to output the results in a real time manner. Its main purpose is to guarantee applications performance, while improving resource utilization. Real sequence searching data of BLAST is used to evaluate the effectiveness of G2LC. Experimental results show that G2LC guarantees the application performance, while resource is saved up to 20.14%.

  20. Antibody informatics for drug discovery

    DEFF Research Database (Denmark)

    Shirai, Hiroki; Prades, Catherine; Vita, Randi

    2014-01-01

    to the antibody science in every project in antibody drug discovery. Recent experimental technologies allow for the rapid generation of large-scale data on antibody sequences, affinity, potency, structures, and biological functions; this should accelerate drug discovery research. Therefore, a robust bioinformatic...... infrastructure for these large data sets has become necessary. In this article, we first identify and discuss the typical obstacles faced during the antibody drug discovery process. We then summarize the current status of three sub-fields of antibody informatics as follows: (i) recent progress in technologies...... for antibody rational design using computational approaches to affinity and stability improvement, as well as ab-initio and homology-based antibody modeling; (ii) resources for antibody sequences, structures, and immune epitopes and open drug discovery resources for development of antibody drugs; and (iii...

  1. PayDIBI: Pay-as-you-go data integration for bioinformatics

    NARCIS (Netherlands)

    Wanders, B.

    2012-01-01

    Background: Scientific research in bio-informatics is often data-driven and supported by biolog- ical databases. In a growing number of research projects, researchers like to ask questions that require the combination of information from more than one database. Most bio-informatics papers do not

  2. BioShaDock: a community driven bioinformatics shared Docker-based tools registry.

    Science.gov (United States)

    Moreews, François; Sallou, Olivier; Ménager, Hervé; Le Bras, Yvan; Monjeaud, Cyril; Blanchet, Christophe; Collin, Olivier

    2015-01-01

    Linux container technologies, as represented by Docker, provide an alternative to complex and time-consuming installation processes needed for scientific software. The ease of deployment and the process isolation they enable, as well as the reproducibility they permit across environments and versions, are among the qualities that make them interesting candidates for the construction of bioinformatic infrastructures, at any scale from single workstations to high throughput computing architectures. The Docker Hub is a public registry which can be used to distribute bioinformatic software as Docker images. However, its lack of curation and its genericity make it difficult for a bioinformatics user to find the most appropriate images needed. BioShaDock is a bioinformatics-focused Docker registry, which provides a local and fully controlled environment to build and publish bioinformatic software as portable Docker images. It provides a number of improvements over the base Docker registry on authentication and permissions management, that enable its integration in existing bioinformatic infrastructures such as computing platforms. The metadata associated with the registered images are domain-centric, including for instance concepts defined in the EDAM ontology, a shared and structured vocabulary of commonly used terms in bioinformatics. The registry also includes user defined tags to facilitate its discovery, as well as a link to the tool description in the ELIXIR registry if it already exists. If it does not, the BioShaDock registry will synchronize with the registry to create a new description in the Elixir registry, based on the BioShaDock entry metadata. This link will help users get more information on the tool such as its EDAM operations, input and output types. This allows integration with the ELIXIR Tools and Data Services Registry, thus providing the appropriate visibility of such images to the bioinformatics community.

  3. Using the iPlant collaborative discovery environment.

    Science.gov (United States)

    Oliver, Shannon L; Lenards, Andrew J; Barthelson, Roger A; Merchant, Nirav; McKay, Sheldon J

    2013-06-01

    The iPlant Collaborative is an academic consortium whose mission is to develop an informatics and social infrastructure to address the "grand challenges" in plant biology. Its cyberinfrastructure supports the computational needs of the research community and facilitates solving major challenges in plant science. The Discovery Environment provides a powerful and rich graphical interface to the iPlant Collaborative cyberinfrastructure by creating an accessible virtual workbench that enables all levels of expertise, ranging from students to traditional biology researchers and computational experts, to explore, analyze, and share their data. By providing access to iPlant's robust data-management system and high-performance computing resources, the Discovery Environment also creates a unified space in which researchers can access scalable tools. Researchers can use available Applications (Apps) to execute analyses on their data, as well as customize or integrate their own tools to better meet the specific needs of their research. These Apps can also be used in workflows that automate more complicated analyses. This module describes how to use the main features of the Discovery Environment, using bioinformatics workflows for high-throughput sequence data as examples. © 2013 by John Wiley & Sons, Inc.

  4. The GMOD Drupal bioinformatic server framework.

    Science.gov (United States)

    Papanicolaou, Alexie; Heckel, David G

    2010-12-15

    Next-generation sequencing technologies have led to the widespread use of -omic applications. As a result, there is now a pronounced bioinformatic bottleneck. The general model organism database (GMOD) tool kit (http://gmod.org) has produced a number of resources aimed at addressing this issue. It lacks, however, a robust online solution that can deploy heterogeneous data and software within a Web content management system (CMS). We present a bioinformatic framework for the Drupal CMS. It consists of three modules. First, GMOD-DBSF is an application programming interface module for the Drupal CMS that simplifies the programming of bioinformatic Drupal modules. Second, the Drupal Bioinformatic Software Bench (biosoftware_bench) allows for a rapid and secure deployment of bioinformatic software. An innovative graphical user interface (GUI) guides both use and administration of the software, including the secure provision of pre-publication datasets. Third, we present genes4all_experiment, which exemplifies how our work supports the wider research community. Given the infrastructure presented here, the Drupal CMS may become a powerful new tool set for bioinformaticians. The GMOD-DBSF base module is an expandable community resource that decreases development time of Drupal modules for bioinformatics. The biosoftware_bench module can already enhance biologists' ability to mine their own data. The genes4all_experiment module has already been responsible for archiving of more than 150 studies of RNAi from Lepidoptera, which were previously unpublished. Implemented in PHP and Perl. Freely available under the GNU Public License 2 or later from http://gmod-dbsf.googlecode.com.

  5. Development of a cloud-based Bioinformatics Training Platform.

    Science.gov (United States)

    Revote, Jerico; Watson-Haigh, Nathan S; Quenette, Steve; Bethwaite, Blair; McGrath, Annette; Shang, Catherine A

    2017-05-01

    The Bioinformatics Training Platform (BTP) has been developed to provide access to the computational infrastructure required to deliver sophisticated hands-on bioinformatics training courses. The BTP is a cloud-based solution that is in active use for delivering next-generation sequencing training to Australian researchers at geographically dispersed locations. The BTP was built to provide an easy, accessible, consistent and cost-effective approach to delivering workshops at host universities and organizations with a high demand for bioinformatics training but lacking the dedicated bioinformatics training suites required. To support broad uptake of the BTP, the platform has been made compatible with multiple cloud infrastructures. The BTP is an open-source and open-access resource. To date, 20 training workshops have been delivered to over 700 trainees at over 10 venues across Australia using the BTP. © The Author 2016. Published by Oxford University Press.

  6. Emerging role of bioinformatics tools and software in evolution of clinical research

    Directory of Open Access Journals (Sweden)

    Supreet Kaur Gill

    2016-01-01

    Full Text Available Clinical research is making toiling efforts for promotion and wellbeing of the health status of the people. There is a rapid increase in number and severity of diseases like cancer, hepatitis, HIV etc, resulting in high morbidity and mortality. Clinical research involves drug discovery and development whereas clinical trials are performed to establish safety and efficacy of drugs. Drug discovery is a long process starting with the target identification, validation and lead optimization. This is followed by the preclinical trials, intensive clinical trials and eventually post marketing vigilance for drug safety. Softwares and the bioinformatics tools play a great role not only in the drug discovery but also in drug development. It involves the use of informatics in the development of new knowledge pertaining to health and disease, data management during clinical trials and to use clinical data for secondary research. In addition, new technology likes molecular docking, molecular dynamics simulation, proteomics and quantitative structure activity relationship in clinical research results in faster and easier drug discovery process. During the preclinical trials, the software is used for randomization to remove bias and to plan study design. In clinical trials software like electronic data capture, Remote data capture and electronic case report form (eCRF is used to store the data. eClinical, Oracle clinical are software used for clinical data management and for statistical analysis of the data. After the drug is marketed the safety of a drug could be monitored by drug safety software like Oracle Argus or ARISg. Therefore, softwares are used from the very early stages of drug designing, to drug development, clinical trials and during pharmacovigilance. This review describes different aspects related to application of computers and bioinformatics in drug designing, discovery and development, formulation designing and clinical research.

  7. BioWarehouse: a bioinformatics database warehouse toolkit.

    Science.gov (United States)

    Lee, Thomas J; Pouliot, Yannick; Wagner, Valerie; Gupta, Priyanka; Stringer-Calvert, David W J; Tenenbaum, Jessica D; Karp, Peter D

    2006-03-23

    This article addresses the problem of interoperation of heterogeneous bioinformatics databases. We introduce BioWarehouse, an open source toolkit for constructing bioinformatics database warehouses using the MySQL and Oracle relational database managers. BioWarehouse integrates its component databases into a common representational framework within a single database management system, thus enabling multi-database queries using the Structured Query Language (SQL) but also facilitating a variety of database integration tasks such as comparative analysis and data mining. BioWarehouse currently supports the integration of a pathway-centric set of databases including ENZYME, KEGG, and BioCyc, and in addition the UniProt, GenBank, NCBI Taxonomy, and CMR databases, and the Gene Ontology. Loader tools, written in the C and JAVA languages, parse and load these databases into a relational database schema. The loaders also apply a degree of semantic normalization to their respective source data, decreasing semantic heterogeneity. The schema supports the following bioinformatics datatypes: chemical compounds, biochemical reactions, metabolic pathways, proteins, genes, nucleic acid sequences, features on protein and nucleic-acid sequences, organisms, organism taxonomies, and controlled vocabularies. As an application example, we applied BioWarehouse to determine the fraction of biochemically characterized enzyme activities for which no sequences exist in the public sequence databases. The answer is that no sequence exists for 36% of enzyme activities for which EC numbers have been assigned. These gaps in sequence data significantly limit the accuracy of genome annotation and metabolic pathway prediction, and are a barrier for metabolic engineering. Complex queries of this type provide examples of the value of the data warehousing approach to bioinformatics research. BioWarehouse embodies significant progress on the database integration problem for bioinformatics.

  8. Engineering bioinformatics: building reliability, performance and productivity into bioinformatics software.

    Science.gov (United States)

    Lawlor, Brendan; Walsh, Paul

    2015-01-01

    There is a lack of software engineering skills in bioinformatic contexts. We discuss the consequences of this lack, examine existing explanations and remedies to the problem, point out their shortcomings, and propose alternatives. Previous analyses of the problem have tended to treat the use of software in scientific contexts as categorically different from the general application of software engineering in commercial settings. In contrast, we describe bioinformatic software engineering as a specialization of general software engineering, and examine how it should be practiced. Specifically, we highlight the difference between programming and software engineering, list elements of the latter and present the results of a survey of bioinformatic practitioners which quantifies the extent to which those elements are employed in bioinformatics. We propose that the ideal way to bring engineering values into research projects is to bring engineers themselves. We identify the role of Bioinformatic Engineer and describe how such a role would work within bioinformatic research teams. We conclude by recommending an educational emphasis on cross-training software engineers into life sciences, and propose research on Domain Specific Languages to facilitate collaboration between engineers and bioinformaticians.

  9. Engineering bioinformatics: building reliability, performance and productivity into bioinformatics software

    Science.gov (United States)

    Lawlor, Brendan; Walsh, Paul

    2015-01-01

    There is a lack of software engineering skills in bioinformatic contexts. We discuss the consequences of this lack, examine existing explanations and remedies to the problem, point out their shortcomings, and propose alternatives. Previous analyses of the problem have tended to treat the use of software in scientific contexts as categorically different from the general application of software engineering in commercial settings. In contrast, we describe bioinformatic software engineering as a specialization of general software engineering, and examine how it should be practiced. Specifically, we highlight the difference between programming and software engineering, list elements of the latter and present the results of a survey of bioinformatic practitioners which quantifies the extent to which those elements are employed in bioinformatics. We propose that the ideal way to bring engineering values into research projects is to bring engineers themselves. We identify the role of Bioinformatic Engineer and describe how such a role would work within bioinformatic research teams. We conclude by recommending an educational emphasis on cross-training software engineers into life sciences, and propose research on Domain Specific Languages to facilitate collaboration between engineers and bioinformaticians. PMID:25996054

  10. Influenza research database: an integrated bioinformatics resource for influenza virus research

    Science.gov (United States)

    The Influenza Research Database (IRD) is a U.S. National Institute of Allergy and Infectious Diseases (NIAID)-sponsored Bioinformatics Resource Center dedicated to providing bioinformatics support for influenza virus research. IRD facilitates the research and development of vaccines, diagnostics, an...

  11. The GMOD Drupal Bioinformatic Server Framework

    Science.gov (United States)

    Papanicolaou, Alexie; Heckel, David G.

    2010-01-01

    Motivation: Next-generation sequencing technologies have led to the widespread use of -omic applications. As a result, there is now a pronounced bioinformatic bottleneck. The general model organism database (GMOD) tool kit (http://gmod.org) has produced a number of resources aimed at addressing this issue. It lacks, however, a robust online solution that can deploy heterogeneous data and software within a Web content management system (CMS). Results: We present a bioinformatic framework for the Drupal CMS. It consists of three modules. First, GMOD-DBSF is an application programming interface module for the Drupal CMS that simplifies the programming of bioinformatic Drupal modules. Second, the Drupal Bioinformatic Software Bench (biosoftware_bench) allows for a rapid and secure deployment of bioinformatic software. An innovative graphical user interface (GUI) guides both use and administration of the software, including the secure provision of pre-publication datasets. Third, we present genes4all_experiment, which exemplifies how our work supports the wider research community. Conclusion: Given the infrastructure presented here, the Drupal CMS may become a powerful new tool set for bioinformaticians. The GMOD-DBSF base module is an expandable community resource that decreases development time of Drupal modules for bioinformatics. The biosoftware_bench module can already enhance biologists' ability to mine their own data. The genes4all_experiment module has already been responsible for archiving of more than 150 studies of RNAi from Lepidoptera, which were previously unpublished. Availability and implementation: Implemented in PHP and Perl. Freely available under the GNU Public License 2 or later from http://gmod-dbsf.googlecode.com Contact: alexie@butterflybase.org PMID:20971988

  12. Web-based services for drug design and discovery.

    Science.gov (United States)

    Frey, Jeremy G; Bird, Colin L

    2011-09-01

    Reviews of the development of drug discovery through the 20(th) century recognised the importance of chemistry and increasingly bioinformatics, but had relatively little to say about the importance of computing and networked computing in particular. However, the design and discovery of new drugs is arguably the most significant single application of bioinformatics and cheminformatics to have benefitted from the increases in the range and power of the computational techniques since the emergence of the World Wide Web, commonly now referred to as simply 'the Web'. Web services have enabled researchers to access shared resources and to deploy standardized calculations in their search for new drugs. This article first considers the fundamental principles of Web services and workflows, and then explores the facilities and resources that have evolved to meet the specific needs of chem- and bio-informatics. This strategy leads to a more detailed examination of the basic components that characterise molecules and the essential predictive techniques, followed by a discussion of the emerging networked services that transcend the basic provisions, and the growing trend towards embracing modern techniques, in particular the Semantic Web. In the opinion of the authors, the issues that require community action are: increasing the amount of chemical data available for open access; validating the data as provided; and developing more efficient links between the worlds of cheminformatics and bioinformatics. The goal is to create ever better drug design services.

  13. A bioinformatics potpourri.

    Science.gov (United States)

    Schönbach, Christian; Li, Jinyan; Ma, Lan; Horton, Paul; Sjaugi, Muhammad Farhan; Ranganathan, Shoba

    2018-01-19

    The 16th International Conference on Bioinformatics (InCoB) was held at Tsinghua University, Shenzhen from September 20 to 22, 2017. The annual conference of the Asia-Pacific Bioinformatics Network featured six keynotes, two invited talks, a panel discussion on big data driven bioinformatics and precision medicine, and 66 oral presentations of accepted research articles or posters. Fifty-seven articles comprising a topic assortment of algorithms, biomolecular networks, cancer and disease informatics, drug-target interactions and drug efficacy, gene regulation and expression, imaging, immunoinformatics, metagenomics, next generation sequencing for genomics and transcriptomics, ontologies, post-translational modification, and structural bioinformatics are the subject of this editorial for the InCoB2017 supplement issues in BMC Genomics, BMC Bioinformatics, BMC Systems Biology and BMC Medical Genomics. New Delhi will be the location of InCoB2018, scheduled for September 26-28, 2018.

  14. LXtoo: an integrated live Linux distribution for the bioinformatics community.

    Science.gov (United States)

    Yu, Guangchuang; Wang, Li-Gen; Meng, Xiao-Hua; He, Qing-Yu

    2012-07-19

    Recent advances in high-throughput technologies dramatically increase biological data generation. However, many research groups lack computing facilities and specialists. This is an obstacle that remains to be addressed. Here, we present a Linux distribution, LXtoo, to provide a flexible computing platform for bioinformatics analysis. Unlike most of the existing live Linux distributions for bioinformatics limiting their usage to sequence analysis and protein structure prediction, LXtoo incorporates a comprehensive collection of bioinformatics software, including data mining tools for microarray and proteomics, protein-protein interaction analysis, and computationally complex tasks like molecular dynamics. Moreover, most of the programs have been configured and optimized for high performance computing. LXtoo aims to provide well-supported computing environment tailored for bioinformatics research, reducing duplication of efforts in building computing infrastructure. LXtoo is distributed as a Live DVD and freely available at http://bioinformatics.jnu.edu.cn/LXtoo.

  15. Viral pathogen discovery

    Science.gov (United States)

    Chiu, Charles Y

    2015-01-01

    Viral pathogen discovery is of critical importance to clinical microbiology, infectious diseases, and public health. Genomic approaches for pathogen discovery, including consensus polymerase chain reaction (PCR), microarrays, and unbiased next-generation sequencing (NGS), have the capacity to comprehensively identify novel microbes present in clinical samples. Although numerous challenges remain to be addressed, including the bioinformatics analysis and interpretation of large datasets, these technologies have been successful in rapidly identifying emerging outbreak threats, screening vaccines and other biological products for microbial contamination, and discovering novel viruses associated with both acute and chronic illnesses. Downstream studies such as genome assembly, epidemiologic screening, and a culture system or animal model of infection are necessary to establish an association of a candidate pathogen with disease. PMID:23725672

  16. BioWarehouse: a bioinformatics database warehouse toolkit

    Directory of Open Access Journals (Sweden)

    Stringer-Calvert David WJ

    2006-03-01

    Full Text Available Abstract Background This article addresses the problem of interoperation of heterogeneous bioinformatics databases. Results We introduce BioWarehouse, an open source toolkit for constructing bioinformatics database warehouses using the MySQL and Oracle relational database managers. BioWarehouse integrates its component databases into a common representational framework within a single database management system, thus enabling multi-database queries using the Structured Query Language (SQL but also facilitating a variety of database integration tasks such as comparative analysis and data mining. BioWarehouse currently supports the integration of a pathway-centric set of databases including ENZYME, KEGG, and BioCyc, and in addition the UniProt, GenBank, NCBI Taxonomy, and CMR databases, and the Gene Ontology. Loader tools, written in the C and JAVA languages, parse and load these databases into a relational database schema. The loaders also apply a degree of semantic normalization to their respective source data, decreasing semantic heterogeneity. The schema supports the following bioinformatics datatypes: chemical compounds, biochemical reactions, metabolic pathways, proteins, genes, nucleic acid sequences, features on protein and nucleic-acid sequences, organisms, organism taxonomies, and controlled vocabularies. As an application example, we applied BioWarehouse to determine the fraction of biochemically characterized enzyme activities for which no sequences exist in the public sequence databases. The answer is that no sequence exists for 36% of enzyme activities for which EC numbers have been assigned. These gaps in sequence data significantly limit the accuracy of genome annotation and metabolic pathway prediction, and are a barrier for metabolic engineering. Complex queries of this type provide examples of the value of the data warehousing approach to bioinformatics research. Conclusion BioWarehouse embodies significant progress on the

  17. Modern bioinformatics meets traditional Chinese medicine.

    Science.gov (United States)

    Gu, Peiqin; Chen, Huajun

    2014-11-01

    Traditional Chinese medicine (TCM) is gaining increasing attention with the emergence of integrative medicine and personalized medicine, characterized by pattern differentiation on individual variance and treatments based on natural herbal synergism. Investigating the effectiveness and safety of the potential mechanisms of TCM and the combination principles of drug therapies will bridge the cultural gap with Western medicine and improve the development of integrative medicine. Dealing with rapidly growing amounts of biomedical data and their heterogeneous nature are two important tasks among modern biomedical communities. Bioinformatics, as an emerging interdisciplinary field of computer science and biology, has become a useful tool for easing the data deluge pressure by automating the computation processes with informatics methods. Using these methods to retrieve, store and analyze the biomedical data can effectively reveal the associated knowledge hidden in the data, and thus promote the discovery of integrated information. Recently, these techniques of bioinformatics have been used for facilitating the interactional effects of both Western medicine and TCM. The analysis of TCM data using computational technologies provides biological evidence for the basic understanding of TCM mechanisms, safety and efficacy of TCM treatments. At the same time, the carrier and targets associated with TCM remedies can inspire the rethinking of modern drug development. This review summarizes the significant achievements of applying bioinformatics techniques to many aspects of the research in TCM, such as analysis of TCM-related '-omics' data and techniques for analyzing biological processes and pharmaceutical mechanisms of TCM, which have shown certain potential of bringing new thoughts to both sides. © The Author 2013. Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

  18. Applying Instructional Design Theories to Bioinformatics Education in Microarray Analysis and Primer Design Workshops

    Science.gov (United States)

    Shachak, Aviv; Ophir, Ron; Rubin, Eitan

    2005-01-01

    The need to support bioinformatics training has been widely recognized by scientists, industry, and government institutions. However, the discussion of instructional methods for teaching bioinformatics is only beginning. Here we report on a systematic attempt to design two bioinformatics workshops for graduate biology students on the basis of…

  19. The secondary metabolite bioinformatics portal

    DEFF Research Database (Denmark)

    Weber, Tilmann; Kim, Hyun Uk

    2016-01-01

    . In this context, this review gives a summary of tools and databases that currently are available to mine, identify and characterize natural product biosynthesis pathways and their producers based on ‘omics data. A web portal called Secondary Metabolite Bioinformatics Portal (SMBP at http...... analytical and chemical methods gave access to this group of compounds, nowadays genomics-based methods offer complementary approaches to find, identify and characterize such molecules. This paradigm shift also resulted in a high demand for computational tools to assist researchers in their daily work......Natural products are among the most important sources of lead molecules for drug discovery. With the development of affordable whole-genome sequencing technologies and other ‘omics tools, the field of natural products research is currently undergoing a shift in paradigms. While, for decades, mainly...

  20. Keemei: cloud-based validation of tabular bioinformatics file formats in Google Sheets.

    Science.gov (United States)

    Rideout, Jai Ram; Chase, John H; Bolyen, Evan; Ackermann, Gail; González, Antonio; Knight, Rob; Caporaso, J Gregory

    2016-06-13

    Bioinformatics software often requires human-generated tabular text files as input and has specific requirements for how those data are formatted. Users frequently manage these data in spreadsheet programs, which is convenient for researchers who are compiling the requisite information because the spreadsheet programs can easily be used on different platforms including laptops and tablets, and because they provide a familiar interface. It is increasingly common for many different researchers to be involved in compiling these data, including study coordinators, clinicians, lab technicians and bioinformaticians. As a result, many research groups are shifting toward using cloud-based spreadsheet programs, such as Google Sheets, which support the concurrent editing of a single spreadsheet by different users working on different platforms. Most of the researchers who enter data are not familiar with the formatting requirements of the bioinformatics programs that will be used, so validating and correcting file formats is often a bottleneck prior to beginning bioinformatics analysis. We present Keemei, a Google Sheets Add-on, for validating tabular files used in bioinformatics analyses. Keemei is available free of charge from Google's Chrome Web Store. Keemei can be installed and run on any web browser supported by Google Sheets. Keemei currently supports the validation of two widely used tabular bioinformatics formats, the Quantitative Insights into Microbial Ecology (QIIME) sample metadata mapping file format and the Spatially Referenced Genetic Data (SRGD) format, but is designed to easily support the addition of others. Keemei will save researchers time and frustration by providing a convenient interface for tabular bioinformatics file format validation. By allowing everyone involved with data entry for a project to easily validate their data, it will reduce the validation and formatting bottlenecks that are commonly encountered when human-generated data files are

  1. A P2P Framework for Developing Bioinformatics Applications in Dynamic Cloud Environments

    Directory of Open Access Journals (Sweden)

    Chun-Hung Richard Lin

    2013-01-01

    Full Text Available Bioinformatics is advanced from in-house computing infrastructure to cloud computing for tackling the vast quantity of biological data. This advance enables large number of collaborative researches to share their works around the world. In view of that, retrieving biological data over the internet becomes more and more difficult because of the explosive growth and frequent changes. Various efforts have been made to address the problems of data discovery and delivery in the cloud framework, but most of them suffer the hindrance by a MapReduce master server to track all available data. In this paper, we propose an alternative approach, called PRKad, which exploits a Peer-to-Peer (P2P model to achieve efficient data discovery and delivery. PRKad is a Kademlia-based implementation with Round-Trip-Time (RTT as the associated key, and it locates data according to Distributed Hash Table (DHT and XOR metric. The simulation results exhibit that our PRKad has the low link latency to retrieve data. As an interdisciplinary application of P2P computing for bioinformatics, PRKad also provides good scalability for servicing a greater number of users in dynamic cloud environments.

  2. Data mining for bioinformatics applications

    CERN Document Server

    Zengyou, He

    2015-01-01

    Data Mining for Bioinformatics Applications provides valuable information on the data mining methods have been widely used for solving real bioinformatics problems, including problem definition, data collection, data preprocessing, modeling, and validation. The text uses an example-based method to illustrate how to apply data mining techniques to solve real bioinformatics problems, containing 45 bioinformatics problems that have been investigated in recent research. For each example, the entire data mining process is described, ranging from data preprocessing to modeling and result validation. Provides valuable information on the data mining methods have been widely used for solving real bioinformatics problems Uses an example-based method to illustrate how to apply data mining techniques to solve real bioinformatics problems Contains 45 bioinformatics problems that have been investigated in recent research.

  3. Applications and methods utilizing the Simple Semantic Web Architecture and Protocol (SSWAP for bioinformatics resource discovery and disparate data and service integration

    Directory of Open Access Journals (Sweden)

    Nelson Rex T

    2010-06-01

    Full Text Available Abstract Background Scientific data integration and computational service discovery are challenges for the bioinformatic community. This process is made more difficult by the separate and independent construction of biological databases, which makes the exchange of data between information resources difficult and labor intensive. A recently described semantic web protocol, the Simple Semantic Web Architecture and Protocol (SSWAP; pronounced "swap" offers the ability to describe data and services in a semantically meaningful way. We report how three major information resources (Gramene, SoyBase and the Legume Information System [LIS] used SSWAP to semantically describe selected data and web services. Methods We selected high-priority Quantitative Trait Locus (QTL, genomic mapping, trait, phenotypic, and sequence data and associated services such as BLAST for publication, data retrieval, and service invocation via semantic web services. Data and services were mapped to concepts and categories as implemented in legacy and de novo community ontologies. We used SSWAP to express these offerings in OWL Web Ontology Language (OWL, Resource Description Framework (RDF and eXtensible Markup Language (XML documents, which are appropriate for their semantic discovery and retrieval. We implemented SSWAP services to respond to web queries and return data. These services are registered with the SSWAP Discovery Server and are available for semantic discovery at http://sswap.info. Results A total of ten services delivering QTL information from Gramene were created. From SoyBase, we created six services delivering information about soybean QTLs, and seven services delivering genetic locus information. For LIS we constructed three services, two of which allow the retrieval of DNA and RNA FASTA sequences with the third service providing nucleic acid sequence comparison capability (BLAST. Conclusions The need for semantic integration technologies has preceded

  4. A Bioinformatics Facility for NASA

    Science.gov (United States)

    Schweighofer, Karl; Pohorille, Andrew

    2006-01-01

    Building on an existing prototype, we have fielded a facility with bioinformatics technologies that will help NASA meet its unique requirements for biological research. This facility consists of a cluster of computers capable of performing computationally intensive tasks, software tools, databases and knowledge management systems. Novel computational technologies for analyzing and integrating new biological data and already existing knowledge have been developed. With continued development and support, the facility will fulfill strategic NASA s bioinformatics needs in astrobiology and space exploration. . As a demonstration of these capabilities, we will present a detailed analysis of how spaceflight factors impact gene expression in the liver and kidney for mice flown aboard shuttle flight STS-108. We have found that many genes involved in signal transduction, cell cycle, and development respond to changes in microgravity, but that most metabolic pathways appear unchanged.

  5. Deep learning in bioinformatics.

    Science.gov (United States)

    Min, Seonwoo; Lee, Byunghan; Yoon, Sungroh

    2017-09-01

    In the era of big data, transformation of biomedical big data into valuable knowledge has been one of the most important challenges in bioinformatics. Deep learning has advanced rapidly since the early 2000s and now demonstrates state-of-the-art performance in various fields. Accordingly, application of deep learning in bioinformatics to gain insight from data has been emphasized in both academia and industry. Here, we review deep learning in bioinformatics, presenting examples of current research. To provide a useful and comprehensive perspective, we categorize research both by the bioinformatics domain (i.e. omics, biomedical imaging, biomedical signal processing) and deep learning architecture (i.e. deep neural networks, convolutional neural networks, recurrent neural networks, emergent architectures) and present brief descriptions of each study. Additionally, we discuss theoretical and practical issues of deep learning in bioinformatics and suggest future research directions. We believe that this review will provide valuable insights and serve as a starting point for researchers to apply deep learning approaches in their bioinformatics studies. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

  6. Bioinformatics Identification of Antigenic Peptide: Predicting the Specificity of Major MHC Class I and II Pathway Players

    DEFF Research Database (Denmark)

    Lund, Ole; Karosiene, Edita; Lundegaard, Claus

    2013-01-01

    Bioinformatics methods for immunology have become increasingly used over the last decade and now form an integrated part of most epitope discovery projects. This wide usage has led to the confusion of defining which of the many methods to use for what problems. In this chapter, an overview is given...

  7. Mass spectrometry for protein quantification in biomarker discovery.

    Science.gov (United States)

    Wang, Mu; You, Jinsam

    2012-01-01

    Major technological advances have made proteomics an extremely active field for biomarker discovery in recent years due primarily to the development of newer mass spectrometric technologies and the explosion in genomic and protein bioinformatics. This leads to an increased emphasis on larger scale, faster, and more efficient methods for detecting protein biomarkers in human tissues, cells, and biofluids. Most current proteomic methodologies for biomarker discovery, however, are not highly automated and are generally labor-intensive and expensive. More automation and improved software programs capable of handling a large amount of data are essential to reduce the cost of discovery and to increase throughput. In this chapter, we discuss and describe mass spectrometry-based proteomic methods for quantitative protein analysis.

  8. Discovery of putative salivary biomarkers for Sjögren's syndrome using high resolution mass spectrometry and bioinformatics.

    Science.gov (United States)

    Zoukhri, Driss; Rawe, Ian; Singh, Mabi; Brown, Ashley; Kublin, Claire L; Dawson, Kevin; Haddon, William F; White, Earl L; Hanley, Kathleen M; Tusé, Daniel; Malyj, Wasyl; Papas, Athena

    2012-03-01

    The purpose of the current study was to determine if saliva contains biomarkers that can be used as diagnostic tools for Sjögren's syndrome (SjS). Twenty seven SjS patients and 27 age-matched healthy controls were recruited for these studies. Unstimulated glandular saliva was collected from the Wharton's duct using a suction device. Two µl of salvia were processed for mass spectrometry analyses on a prOTOF 2000 matrix-assisted laser desorption/ionization orthogonal time of flight (MALDI O-TOF) mass spectrometer. Raw data were analyzed using bioinformatic tools to identify biomarkers. MALDI O-TOF MS analyses of saliva samples were highly reproducible and the mass spectra generated were very rich in peptides and peptide fragments in the 750-7,500 Da range. Data analysis using bioinformatic tools resulted in several classification models being built and several biomarkers identified. One model based on 7 putative biomarkers yielded a sensitivity of 97.5%, specificity of 97.8% and an accuracy of 97.6%. One biomarker was present only in SjS samples and was identified as a proteolytic peptide originating from human basic salivary proline-rich protein 3 precursor. We conclude that salivary biomarkers detected by high-resolution mass spectrometry coupled with powerful bioinformatic tools offer the potential to serve as diagnostic/prognostic tools for SjS.

  9. Bioinformatics Education in Pathology Training: Current Scope and Future Direction

    Directory of Open Access Journals (Sweden)

    Michael R Clay

    2017-04-01

    Full Text Available Training anatomic and clinical pathology residents in the principles of bioinformatics is a challenging endeavor. Most residents receive little to no formal exposure to bioinformatics during medical education, and most of the pathology training is spent interpreting histopathology slides using light microscopy or focused on laboratory regulation, management, and interpretation of discrete laboratory data. At a minimum, residents should be familiar with data structure, data pipelines, data manipulation, and data regulations within clinical laboratories. Fellowship-level training should incorporate advanced principles unique to each subspecialty. Barriers to bioinformatics education include the clinical apprenticeship training model, ill-defined educational milestones, inadequate faculty expertise, and limited exposure during medical training. Online educational resources, case-based learning, and incorporation into molecular genomics education could serve as effective educational strategies. Overall, pathology bioinformatics training can be incorporated into pathology resident curricula, provided there is motivation to incorporate, institutional support, educational resources, and adequate faculty expertise.

  10. A review of bioinformatics training applied to research in molecular medicine, agriculture and biodiversity in Costa Rica and Central America.

    Science.gov (United States)

    Orozco, Allan; Morera, Jessica; Jiménez, Sergio; Boza, Ricardo

    2013-09-01

    Today, Bioinformatics has become a scientific discipline with great relevance for the Molecular Biosciences and for the Omics sciences in general. Although developed countries have progressed with large strides in Bioinformatics education and research, in other regions, such as Central America, the advances have occurred in a gradual way and with little support from the Academia, either at the undergraduate or graduate level. To address this problem, the University of Costa Rica's Medical School, a regional leader in Bioinformatics in Central America, has been conducting a series of Bioinformatics workshops, seminars and courses, leading to the creation of the region's first Bioinformatics Master's Degree. The recent creation of the Central American Bioinformatics Network (BioCANET), associated to the deployment of a supporting computational infrastructure (HPC Cluster) devoted to provide computing support for Molecular Biology in the region, is providing a foundational stone for the development of Bioinformatics in the area. Central American bioinformaticians have participated in the creation of as well as co-founded the Iberoamerican Bioinformatics Society (SOIBIO). In this article, we review the most recent activities in education and research in Bioinformatics from several regional institutions. These activities have resulted in further advances for Molecular Medicine, Agriculture and Biodiversity research in Costa Rica and the rest of the Central American countries. Finally, we provide summary information on the first Central America Bioinformatics International Congress, as well as the creation of the first Bioinformatics company (Indromics Bioinformatics), spin-off the Academy in Central America and the Caribbean.

  11. Proxy support for service discovery using mDNS/DNS-SD in low power networks

    NARCIS (Netherlands)

    Stolikj, M.; Verhoeven, R.; Cuijpers, P.J.L.; Lukkien, J.J.

    2014-01-01

    We present a solution for service discovery of resource constrained devices based on mDNS/DNS-SD. We extend the mDNS/DNS-SD service discovery protocol with support for proxy servers. Proxy servers temporarily store information about services offered on resource constrained devices and respond on

  12. Bioinformatics and Medical Informatics: Collaborations on the Road to Genomic Medicine?

    Science.gov (United States)

    Maojo, Victor; Kulikowski, Casimir A.

    2003-01-01

    In this report, the authors compare and contrast medical informatics (MI) and bioinformatics (BI) and provide a viewpoint on their complementarities and potential for collaboration in various subfields. The authors compare MI and BI along several dimensions, including: (1) historical development of the disciplines, (2) their scientific foundations, (3) data quality and analysis, (4) integration of knowledge and databases, (5) informatics tools to support practice, (6) informatics methods to support research (signal processing, imaging and vision, and computational modeling, (7) professional and patient continuing education, and (8) education and training. It is pointed out that, while the two disciplines differ in their histories, scientific foundations, and methodologic approaches to research in various areas, they nevertheless share methods and tools, which provides a basis for exchange of experience in their different applications. MI expertise in developing health care applications and the strength of BI in biological “discovery science” complement each other well. The new field of biomedical informatics (BMI) holds great promise for developing informatics methods that will be crucial in the development of genomic medicine. The future of BMI will be influenced strongly by whether significant advances in clinical practice and biomedical research come about from separate efforts in MI and BI, or from emerging, hybrid informatics subdisciplines at their interface. PMID:12925552

  13. BioShaDock: a community driven bioinformatics shared Docker-based tools registry [version 1; referees: 2 approved

    Directory of Open Access Journals (Sweden)

    François Moreews

    2015-12-01

    Full Text Available Linux container technologies, as represented by Docker, provide an alternative to complex and time-consuming installation processes needed for scientific software. The ease of deployment and the process isolation they enable, as well as the reproducibility they permit across environments and versions, are among the qualities that make them interesting candidates for the construction of bioinformatic infrastructures, at any scale from single workstations to high throughput computing architectures. The Docker Hub is a public registry which can be used to distribute bioinformatic software as Docker images. However, its lack of curation and its genericity make it difficult for a bioinformatics user to find the most appropriate images needed. BioShaDock is a bioinformatics-focused Docker registry, which provides a local and fully controlled environment to build and publish bioinformatic software as portable Docker images. It provides a number of improvements over the base Docker registry on authentication and permissions management, that enable its integration in existing bioinformatic infrastructures such as computing platforms. The metadata associated with the registered images are domain-centric, including for instance concepts defined in the EDAM ontology, a shared and structured vocabulary of commonly used terms in bioinformatics. The registry also includes user defined tags to facilitate its discovery, as well as a link to the tool description in the ELIXIR registry if it already exists. If it does not, the BioShaDock registry will synchronize with the registry to create a new description in the Elixir registry, based on the BioShaDock entry metadata. This link will help users get more information on the tool such as its EDAM operations, input and output types. This allows integration with the ELIXIR Tools and Data Services Registry, thus providing the appropriate visibility of such images to the bioinformatics community.

  14. Emerging strengths in Asia Pacific bioinformatics.

    Science.gov (United States)

    Ranganathan, Shoba; Hsu, Wen-Lian; Yang, Ueng-Cheng; Tan, Tin Wee

    2008-12-12

    The 2008 annual conference of the Asia Pacific Bioinformatics Network (APBioNet), Asia's oldest bioinformatics organisation set up in 1998, was organized as the 7th International Conference on Bioinformatics (InCoB), jointly with the Bioinformatics and Systems Biology in Taiwan (BIT 2008) Conference, Oct. 20-23, 2008 at Taipei, Taiwan. Besides bringing together scientists from the field of bioinformatics in this region, InCoB is actively involving researchers from the area of systems biology, to facilitate greater synergy between these two groups. Marking the 10th Anniversary of APBioNet, this InCoB 2008 meeting followed on from a series of successful annual events in Bangkok (Thailand), Penang (Malaysia), Auckland (New Zealand), Busan (South Korea), New Delhi (India) and Hong Kong. Additionally, tutorials and the Workshop on Education in Bioinformatics and Computational Biology (WEBCB) immediately prior to the 20th Federation of Asian and Oceanian Biochemists and Molecular Biologists (FAOBMB) Taipei Conference provided ample opportunity for inducting mainstream biochemists and molecular biologists from the region into a greater level of awareness of the importance of bioinformatics in their craft. In this editorial, we provide a brief overview of the peer-reviewed manuscripts accepted for publication herein, grouped into thematic areas. As the regional research expertise in bioinformatics matures, the papers fall into thematic areas, illustrating the specific contributions made by APBioNet to global bioinformatics efforts.

  15. Pay-as-you-go data integration for bio-informatics

    NARCIS (Netherlands)

    Wanders, B.

    2012-01-01

    Scientific research in bio-informatics is often data-driven and supported by numerous biological databases. A biological database contains factual information collected from scientific experiments and computational analyses about areas including genomics, proteomics, metabolomics, microarray gene

  16. Application of data mining and artificial intelligence techniques to mass spectrometry data for knowledge discovery

    Directory of Open Access Journals (Sweden)

    Hugo López-Fernández

    2016-05-01

    Full Text Available Mass spectrometry using matrix assisted laser desorption ionization coupled to time of flight analyzers (MALDI-TOF MS has become popular during the last decade due to its high speed, sensitivity and robustness for detecting proteins and peptides. This allows quickly analyzing large sets of samples are in one single batch and doing high-throughput proteomics. In this scenario, bioinformatics methods and computational tools play a key role in MALDI-TOF data analysis, as they are able handle the large amounts of raw data generated in order to extract new knowledge and useful conclusions. A typical MALDI-TOF MS data analysis workflow has three main stages: data acquisition, preprocessing and analysis. Although the most popular use of this technology is to identify proteins through their peptides, analyses that make use of artificial intelligence (AI, machine learning (ML, and statistical methods can be also carried out in order to perform biomarker discovery, automatic diagnosis, and knowledge discovery. In this research work, this workflow is deeply explored and new solutions based on the application of AI, ML, and statistical methods are proposed. In addition, an integrated software platform that supports the full MALDI-TOF MS data analysis workflow that facilitate the work of proteomics researchers without advanced bioinformatics skills has been developed and released to the scientific community.

  17. Biggest challenges in bioinformatics.

    Science.gov (United States)

    Fuller, Jonathan C; Khoueiry, Pierre; Dinkel, Holger; Forslund, Kristoffer; Stamatakis, Alexandros; Barry, Joseph; Budd, Aidan; Soldatos, Theodoros G; Linssen, Katja; Rajput, Abdul Mateen

    2013-04-01

    The third Heidelberg Unseminars in Bioinformatics (HUB) was held on 18th October 2012, at Heidelberg University, Germany. HUB brought together around 40 bioinformaticians from academia and industry to discuss the 'Biggest Challenges in Bioinformatics' in a 'World Café' style event.

  18. Biggest challenges in bioinformatics

    OpenAIRE

    Fuller, Jonathan C; Khoueiry, Pierre; Dinkel, Holger; Forslund, Kristoffer; Stamatakis, Alexandros; Barry, Joseph; Budd, Aidan; Soldatos, Theodoros G; Linssen, Katja; Rajput, Abdul Mateen

    2013-01-01

    The third Heidelberg Unseminars in Bioinformatics (HUB) was held in October at Heidelberg University in Germany. HUB brought together around 40 bioinformaticians from academia and industry to discuss the ‘Biggest Challenges in Bioinformatics' in a ‘World Café' style event.

  19. A Planetary Defense Gateway for Smart Discovery of relevant Information for Decision Support

    Science.gov (United States)

    Bambacus, Myra; Yang, Chaowei Phil; Leung, Ronald Y.; Barbee, Brent; Nuth, Joseph A.; Seery, Bernard; Jiang, Yongyao; Qin, Han; Li, Yun; Yu, Manzhu; hide

    2017-01-01

    A Planetary Defense Gateway for Smart Discovery of relevant Information for Decision Support presentation discussing background, framework architecture, current results, ongoing research, conclusions.

  20. New Link in Bioinformatics Services Value Chain: Position, Organization and Business Model

    Directory of Open Access Journals (Sweden)

    Mladen Čudanov

    2012-11-01

    Full Text Available This paper presents development in the bioinformatics services industry value chain, based on cloud computing paradigm. As genome sequencing costs per Megabase exponentially drop, industry needs to adopt. Paper has two parts: theoretical analysis and practical example of Seven Bridges Genomics Company. We are focused on explaining organizational, business and financial aspects of new business model in bioinformatics services, rather than technical side of the problem. In the light of that we present twofold business model fit for core bioinformatics research and Information and Communication Technologie (ICT support in the new environment, with higher level of capital utilization and better resistance to business risks.

  1. Established and Emerging Trends in Computational Drug Discovery in the Structural Genomics Era

    DEFF Research Database (Denmark)

    Taboureau, Olivier; Baell, Jonathan B.; Fernández-Recio, Juan

    2012-01-01

    Bioinformatics and chemoinformatics approaches contribute to hit discovery, hit-to-lead optimization, safety profiling, and target identification and enhance our overall understanding of the health and disease states. A vast repertoire of computational methods has been reported and increasingly...

  2. Establishing bioinformatics research in the Asia Pacific

    Directory of Open Access Journals (Sweden)

    Tammi Martti

    2006-12-01

    Full Text Available Abstract In 1998, the Asia Pacific Bioinformatics Network (APBioNet, Asia's oldest bioinformatics organisation was set up to champion the advancement of bioinformatics in the Asia Pacific. By 2002, APBioNet was able to gain sufficient critical mass to initiate the first International Conference on Bioinformatics (InCoB bringing together scientists working in the field of bioinformatics in the region. This year, the InCoB2006 Conference was organized as the 5th annual conference of the Asia-Pacific Bioinformatics Network, on Dec. 18–20, 2006 in New Delhi, India, following a series of successful events in Bangkok (Thailand, Penang (Malaysia, Auckland (New Zealand and Busan (South Korea. This Introduction provides a brief overview of the peer-reviewed manuscripts accepted for publication in this Supplement. It exemplifies a typical snapshot of the growing research excellence in bioinformatics of the region as we embark on a trajectory of establishing a solid bioinformatics research culture in the Asia Pacific that is able to contribute fully to the global bioinformatics community.

  3. Bioinformatics in New Generation Flavivirus Vaccines

    Directory of Open Access Journals (Sweden)

    Penelope Koraka

    2010-01-01

    Full Text Available Flavivirus infections are the most prevalent arthropod-borne infections world wide, often causing severe disease especially among children, the elderly, and the immunocompromised. In the absence of effective antiviral treatment, prevention through vaccination would greatly reduce morbidity and mortality associated with flavivirus infections. Despite the success of the empirically developed vaccines against yellow fever virus, Japanese encephalitis virus and tick-borne encephalitis virus, there is an increasing need for a more rational design and development of safe and effective vaccines. Several bioinformatic tools are available to support such rational vaccine design. In doing so, several parameters have to be taken into account, such as safety for the target population, overall immunogenicity of the candidate vaccine, and efficacy and longevity of the immune responses triggered. Examples of how bio-informatics is applied to assist in the rational design and improvements of vaccines, particularly flavivirus vaccines, are presented and discussed.

  4. Preface to Introduction to Structural Bioinformatics

    NARCIS (Netherlands)

    Feenstra, K. Anton; Abeln, Sanne

    2018-01-01

    While many good textbooks are available on Protein Structure, Molecular Simulations, Thermodynamics and Bioinformatics methods in general, there is no good introductory level book for the field of Structural Bioinformatics. This book aims to give an introduction into Structural Bioinformatics, which

  5. COMPARISON OF POPULAR BIOINFORMATICS DATABASES

    OpenAIRE

    Abdulganiyu Abdu Yusuf; Zahraddeen Sufyanu; Kabir Yusuf Mamman; Abubakar Umar Suleiman

    2016-01-01

    Bioinformatics is the application of computational tools to capture and interpret biological data. It has wide applications in drug development, crop improvement, agricultural biotechnology and forensic DNA analysis. There are various databases available to researchers in bioinformatics. These databases are customized for a specific need and are ranged in size, scope, and purpose. The main drawbacks of bioinformatics databases include redundant information, constant change, data spread over m...

  6. A Review of Recent Advances in Translational Bioinformatics: Bridges from Biology to Medicine.

    Science.gov (United States)

    Vamathevan, J; Birney, E

    2017-08-01

    Objectives: To highlight and provide insights into key developments in translational bioinformatics between 2014 and 2016. Methods: This review describes some of the most influential bioinformatics papers and resources that have been published between 2014 and 2016 as well as the national genome sequencing initiatives that utilize these resources to routinely embed genomic medicine into healthcare. Also discussed are some applications of the secondary use of patient data followed by a comprehensive view of the open challenges and emergent technologies. Results: Although data generation can be performed routinely, analyses and data integration methods still require active research and standardization to improve streamlining of clinical interpretation. The secondary use of patient data has resulted in the development of novel algorithms and has enabled a refined understanding of cellular and phenotypic mechanisms. New data storage and data sharing approaches are required to enable diverse biomedical communities to contribute to genomic discovery. Conclusion: The translation of genomics data into actionable knowledge for use in healthcare is transforming the clinical landscape in an unprecedented way. Exciting and innovative models that bridge the gap between clinical and academic research are set to open up the field of translational bioinformatics for rapid growth in a digital era. Georg Thieme Verlag KG Stuttgart.

  7. Bioinformatics in the Netherlands: the value of a nationwide community.

    Science.gov (United States)

    van Gelder, Celia W G; Hooft, Rob W W; van Rijswijk, Merlijn N; van den Berg, Linda; Kok, Ruben G; Reinders, Marcel; Mons, Barend; Heringa, Jaap

    2017-09-15

    This review provides a historical overview of the inception and development of bioinformatics research in the Netherlands. Rooted in theoretical biology by foundational figures such as Paulien Hogeweg (at Utrecht University since the 1970s), the developments leading to organizational structures supporting a relatively large Dutch bioinformatics community will be reviewed. We will show that the most valuable resource that we have built over these years is the close-knit national expert community that is well engaged in basic and translational life science research programmes. The Dutch bioinformatics community is accustomed to facing the ever-changing landscape of data challenges and working towards solutions together. In addition, this community is the stable factor on the road towards sustainability, especially in times where existing funding models are challenged and change rapidly. © The Author 2017. Published by Oxford University Press.

  8. A Performance/Cost Evaluation for a GPU-Based Drug Discovery Application on Volunteer Computing

    Science.gov (United States)

    Guerrero, Ginés D.; Imbernón, Baldomero; García, José M.

    2014-01-01

    Bioinformatics is an interdisciplinary research field that develops tools for the analysis of large biological databases, and, thus, the use of high performance computing (HPC) platforms is mandatory for the generation of useful biological knowledge. The latest generation of graphics processing units (GPUs) has democratized the use of HPC as they push desktop computers to cluster-level performance. Many applications within this field have been developed to leverage these powerful and low-cost architectures. However, these applications still need to scale to larger GPU-based systems to enable remarkable advances in the fields of healthcare, drug discovery, genome research, etc. The inclusion of GPUs in HPC systems exacerbates power and temperature issues, increasing the total cost of ownership (TCO). This paper explores the benefits of volunteer computing to scale bioinformatics applications as an alternative to own large GPU-based local infrastructures. We use as a benchmark a GPU-based drug discovery application called BINDSURF that their computational requirements go beyond a single desktop machine. Volunteer computing is presented as a cheap and valid HPC system for those bioinformatics applications that need to process huge amounts of data and where the response time is not a critical factor. PMID:25025055

  9. Using Just-in-Time Information to Support Scientific Discovery Learning in a Computer-Based Simulation

    Science.gov (United States)

    Hulshof, Casper D.; de Jong, Ton

    2006-01-01

    Students encounter many obstacles during scientific discovery learning with computer-based simulations. It is hypothesized that an effective type of support, that does not interfere with the scientific discovery learning process, should be delivered on a "just-in-time" base. This study explores the effect of facilitating access to…

  10. Establishing bioinformatics research in the Asia Pacific

    OpenAIRE

    Ranganathan, Shoba; Tammi, Martti; Gribskov, Michael; Tan, Tin Wee

    2006-01-01

    Abstract In 1998, the Asia Pacific Bioinformatics Network (APBioNet), Asia's oldest bioinformatics organisation was set up to champion the advancement of bioinformatics in the Asia Pacific. By 2002, APBioNet was able to gain sufficient critical mass to initiate the first International Conference on Bioinformatics (InCoB) bringing together scientists working in the field of bioinformatics in the region. This year, the InCoB2006 Conference was organized as the 5th annual conference of the Asia-...

  11. Informatics-guided procurement of patient samples for biomarker discovery projects in cancer research.

    Science.gov (United States)

    Suh, K Stephen; Remache, Yvonne K; Patel, Jalpa S; Chen, Steve H; Haystrand, Russell; Ford, Peggy; Shaikh, Anadil M; Wang, Jian; Goy, Andre H

    2009-02-01

    Modern cancer research for biomarker discovery program requires solving several tasks that are directly involved with patient sample procurement. One requirement is to construct a highly efficient workflow on the clinical side for the procurement to generate a consistent supply of high quality samples for research. This undertaking needs a network of interdepartmental collaborations and participations at various levels, including physical human interactions, information technology implementations and a bioinformatics tool that is highly effective and user-friendly to busy clinicians and researchers associated with the sample procurement. Collegial participation that is sequential but continual from one department to another demands dedicated bioinformatics software coordinating between the institutional clinic and the tissue repository facility. Participants in the process include admissions, consenting process, phlebotomy, surgery center and pathology. During this multiple step procedures, clinical data are collected for detailed analytical endpoints to supplement logistics of defining and validating the discovery of biomarkers.

  12. Biowep: a workflow enactment portal for bioinformatics applications.

    Science.gov (United States)

    Romano, Paolo; Bartocci, Ezio; Bertolini, Guglielmo; De Paoli, Flavio; Marra, Domenico; Mauri, Giancarlo; Merelli, Emanuela; Milanesi, Luciano

    2007-03-08

    The huge amount of biological information, its distribution over the Internet and the heterogeneity of available software tools makes the adoption of new data integration and analysis network tools a necessity in bioinformatics. ICT standards and tools, like Web Services and Workflow Management Systems (WMS), can support the creation and deployment of such systems. Many Web Services are already available and some WMS have been proposed. They assume that researchers know which bioinformatics resources can be reached through a programmatic interface and that they are skilled in programming and building workflows. Therefore, they are not viable to the majority of unskilled researchers. A portal enabling these to take profit from new technologies is still missing. We designed biowep, a web based client application that allows for the selection and execution of a set of predefined workflows. The system is available on-line. Biowep architecture includes a Workflow Manager, a User Interface and a Workflow Executor. The task of the Workflow Manager is the creation and annotation of workflows. These can be created by using either the Taverna Workbench or BioWMS. Enactment of workflows is carried out by FreeFluo for Taverna workflows and by BioAgent/Hermes, a mobile agent-based middleware, for BioWMS ones. Main workflows' processing steps are annotated on the basis of their input and output, elaboration type and application domain by using a classification of bioinformatics data and tasks. The interface supports users authentication and profiling. Workflows can be selected on the basis of users' profiles and can be searched through their annotations. Results can be saved. We developed a web system that support the selection and execution of predefined workflows, thus simplifying access for all researchers. The implementation of Web Services allowing specialized software to interact with an exhaustive set of biomedical databases and analysis software and the creation of

  13. Biowep: a workflow enactment portal for bioinformatics applications

    Directory of Open Access Journals (Sweden)

    Romano Paolo

    2007-03-01

    Full Text Available Abstract Background The huge amount of biological information, its distribution over the Internet and the heterogeneity of available software tools makes the adoption of new data integration and analysis network tools a necessity in bioinformatics. ICT standards and tools, like Web Services and Workflow Management Systems (WMS, can support the creation and deployment of such systems. Many Web Services are already available and some WMS have been proposed. They assume that researchers know which bioinformatics resources can be reached through a programmatic interface and that they are skilled in programming and building workflows. Therefore, they are not viable to the majority of unskilled researchers. A portal enabling these to take profit from new technologies is still missing. Results We designed biowep, a web based client application that allows for the selection and execution of a set of predefined workflows. The system is available on-line. Biowep architecture includes a Workflow Manager, a User Interface and a Workflow Executor. The task of the Workflow Manager is the creation and annotation of workflows. These can be created by using either the Taverna Workbench or BioWMS. Enactment of workflows is carried out by FreeFluo for Taverna workflows and by BioAgent/Hermes, a mobile agent-based middleware, for BioWMS ones. Main workflows' processing steps are annotated on the basis of their input and output, elaboration type and application domain by using a classification of bioinformatics data and tasks. The interface supports users authentication and profiling. Workflows can be selected on the basis of users' profiles and can be searched through their annotations. Results can be saved. Conclusion We developed a web system that support the selection and execution of predefined workflows, thus simplifying access for all researchers. The implementation of Web Services allowing specialized software to interact with an exhaustive set of biomedical

  14. Generalized Centroid Estimators in Bioinformatics

    Science.gov (United States)

    Hamada, Michiaki; Kiryu, Hisanori; Iwasaki, Wataru; Asai, Kiyoshi

    2011-01-01

    In a number of estimation problems in bioinformatics, accuracy measures of the target problem are usually given, and it is important to design estimators that are suitable to those accuracy measures. However, there is often a discrepancy between an employed estimator and a given accuracy measure of the problem. In this study, we introduce a general class of efficient estimators for estimation problems on high-dimensional binary spaces, which represent many fundamental problems in bioinformatics. Theoretical analysis reveals that the proposed estimators generally fit with commonly-used accuracy measures (e.g. sensitivity, PPV, MCC and F-score) as well as it can be computed efficiently in many cases, and cover a wide range of problems in bioinformatics from the viewpoint of the principle of maximum expected accuracy (MEA). It is also shown that some important algorithms in bioinformatics can be interpreted in a unified manner. Not only the concept presented in this paper gives a useful framework to design MEA-based estimators but also it is highly extendable and sheds new light on many problems in bioinformatics. PMID:21365017

  15. Introduction to bioinformatics.

    Science.gov (United States)

    Can, Tolga

    2014-01-01

    Bioinformatics is an interdisciplinary field mainly involving molecular biology and genetics, computer science, mathematics, and statistics. Data intensive, large-scale biological problems are addressed from a computational point of view. The most common problems are modeling biological processes at the molecular level and making inferences from collected data. A bioinformatics solution usually involves the following steps: Collect statistics from biological data. Build a computational model. Solve a computational modeling problem. Test and evaluate a computational algorithm. This chapter gives a brief introduction to bioinformatics by first providing an introduction to biological terminology and then discussing some classical bioinformatics problems organized by the types of data sources. Sequence analysis is the analysis of DNA and protein sequences for clues regarding function and includes subproblems such as identification of homologs, multiple sequence alignment, searching sequence patterns, and evolutionary analyses. Protein structures are three-dimensional data and the associated problems are structure prediction (secondary and tertiary), analysis of protein structures for clues regarding function, and structural alignment. Gene expression data is usually represented as matrices and analysis of microarray data mostly involves statistics analysis, classification, and clustering approaches. Biological networks such as gene regulatory networks, metabolic pathways, and protein-protein interaction networks are usually modeled as graphs and graph theoretic approaches are used to solve associated problems such as construction and analysis of large-scale networks.

  16. Bioinformatics clouds for big data manipulation.

    Science.gov (United States)

    Dai, Lin; Gao, Xin; Guo, Yan; Xiao, Jingfa; Zhang, Zhang

    2012-11-28

    As advances in life sciences and information technology bring profound influences on bioinformatics due to its interdisciplinary nature, bioinformatics is experiencing a new leap-forward from in-house computing infrastructure into utility-supplied cloud computing delivered over the Internet, in order to handle the vast quantities of biological data generated by high-throughput experimental technologies. Albeit relatively new, cloud computing promises to address big data storage and analysis issues in the bioinformatics field. Here we review extant cloud-based services in bioinformatics, classify them into Data as a Service (DaaS), Software as a Service (SaaS), Platform as a Service (PaaS), and Infrastructure as a Service (IaaS), and present our perspectives on the adoption of cloud computing in bioinformatics. This article was reviewed by Frank Eisenhaber, Igor Zhulin, and Sandor Pongor.

  17. Bioinformatics and systems biology research update from the 15th International Conference on Bioinformatics (InCoB2016).

    Science.gov (United States)

    Schönbach, Christian; Verma, Chandra; Bond, Peter J; Ranganathan, Shoba

    2016-12-22

    The International Conference on Bioinformatics (InCoB) has been publishing peer-reviewed conference papers in BMC Bioinformatics since 2006. Of the 44 articles accepted for publication in supplement issues of BMC Bioinformatics, BMC Genomics, BMC Medical Genomics and BMC Systems Biology, 24 articles with a bioinformatics or systems biology focus are reviewed in this editorial. InCoB2017 is scheduled to be held in Shenzen, China, September 20-22, 2017.

  18. Discovery of novel bacterial toxins by genomics and computational biology.

    Science.gov (United States)

    Doxey, Andrew C; Mansfield, Michael J; Montecucco, Cesare

    2018-06-01

    Hundreds and hundreds of bacterial protein toxins are presently known. Traditionally, toxin identification begins with pathological studies of bacterial infectious disease. Following identification and cultivation of a bacterial pathogen, the protein toxin is purified from the culture medium and its pathogenic activity is studied using the methods of biochemistry and structural biology, cell biology, tissue and organ biology, and appropriate animal models, supplemented by bioimaging techniques. The ongoing and explosive development of high-throughput DNA sequencing and bioinformatic approaches have set in motion a revolution in many fields of biology, including microbiology. One consequence is that genes encoding novel bacterial toxins can be identified by bioinformatic and computational methods based on previous knowledge accumulated from studies of the biology and pathology of thousands of known bacterial protein toxins. Starting from the paradigmatic cases of diphtheria toxin, tetanus and botulinum neurotoxins, this review discusses traditional experimental approaches as well as bioinformatics and genomics-driven approaches that facilitate the discovery of novel bacterial toxins. We discuss recent work on the identification of novel botulinum-like toxins from genera such as Weissella, Chryseobacterium, and Enteroccocus, and the implications of these computationally identified toxins in the field. Finally, we discuss the promise of metagenomics in the discovery of novel toxins and their ecological niches, and present data suggesting the existence of uncharacterized, botulinum-like toxin genes in insect gut metagenomes. Copyright © 2018. Published by Elsevier Ltd.

  19. Designing XML schemas for bioinformatics.

    Science.gov (United States)

    Bruhn, Russel Elton; Burton, Philip John

    2003-06-01

    Data interchange bioinformatics databases will, in the future, most likely take place using extensible markup language (XML). The document structure will be described by an XML Schema rather than a document type definition (DTD). To ensure flexibility, the XML Schema must incorporate aspects of Object-Oriented Modeling. This impinges on the choice of the data model, which, in turn, is based on the organization of bioinformatics data by biologists. Thus, there is a need for the general bioinformatics community to be aware of the design issues relating to XML Schema. This paper, which is aimed at a general bioinformatics audience, uses examples to describe the differences between a DTD and an XML Schema and indicates how Unified Modeling Language diagrams may be used to incorporate Object-Oriented Modeling in the design of schema.

  20. Bioinformatics

    DEFF Research Database (Denmark)

    Baldi, Pierre; Brunak, Søren

    , and medicine will be particularly affected by the new results and the increased understanding of life at the molecular level. Bioinformatics is the development and application of computer methods for analysis, interpretation, and prediction, as well as for the design of experiments. It has emerged...

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

    Science.gov (United States)

    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

  2. Bioinformatics clouds for big data manipulation

    Directory of Open Access Journals (Sweden)

    Dai Lin

    2012-11-01

    Full Text Available Abstract As advances in life sciences and information technology bring profound influences on bioinformatics due to its interdisciplinary nature, bioinformatics is experiencing a new leap-forward from in-house computing infrastructure into utility-supplied cloud computing delivered over the Internet, in order to handle the vast quantities of biological data generated by high-throughput experimental technologies. Albeit relatively new, cloud computing promises to address big data storage and analysis issues in the bioinformatics field. Here we review extant cloud-based services in bioinformatics, classify them into Data as a Service (DaaS, Software as a Service (SaaS, Platform as a Service (PaaS, and Infrastructure as a Service (IaaS, and present our perspectives on the adoption of cloud computing in bioinformatics. Reviewers This article was reviewed by Frank Eisenhaber, Igor Zhulin, and Sandor Pongor.

  3. Bioinformatics clouds for big data manipulation

    KAUST Repository

    Dai, Lin

    2012-11-28

    As advances in life sciences and information technology bring profound influences on bioinformatics due to its interdisciplinary nature, bioinformatics is experiencing a new leap-forward from in-house computing infrastructure into utility-supplied cloud computing delivered over the Internet, in order to handle the vast quantities of biological data generated by high-throughput experimental technologies. Albeit relatively new, cloud computing promises to address big data storage and analysis issues in the bioinformatics field. Here we review extant cloud-based services in bioinformatics, classify them into Data as a Service (DaaS), Software as a Service (SaaS), Platform as a Service (PaaS), and Infrastructure as a Service (IaaS), and present our perspectives on the adoption of cloud computing in bioinformatics.This article was reviewed by Frank Eisenhaber, Igor Zhulin, and Sandor Pongor. 2012 Dai et al.; licensee BioMed Central Ltd.

  4. Emerging trends in the discovery of natural product antibacterials

    DEFF Research Database (Denmark)

    Bologa, Cristian G; Ursu, Oleg; Oprea, Tudor

    2013-01-01

    This article highlights current trends and advances in exploiting natural sources for the deployment of novel and potent anti-infective countermeasures. The key challenge is to therapeutically target bacterial pathogens that exhibit a variety of puzzling and evolutionarily complex resistance...... mechanisms. Special emphasis is given to the strengths, weaknesses, and opportunities in the natural product antibacterial drug discovery arena, and to emerging applications driven by advances in bioinformatics, chemical biology, and synthetic biology in concert with exploiting bacterial phenotypes....... These efforts have identified a critical mass of natural product antibacterial lead compounds and discovery technologies with high probability of successful implementation against emerging bacterial pathogens....

  5. Toward Personalized Pressure Ulcer Care Planning: Development of a Bioinformatics System for Individualized Prioritization of Clinical Pratice Guideline

    Science.gov (United States)

    2016-10-01

    AWARD NUMBER: W81XWH-15-1-0342 TITLE: Toward Personalized Pressure Ulcer Care Planning: Development of a Bioinformatics System for Individualized...Planning: Development of a Bioinformatics System for Individualized Prioritization of Clinical Pratice Guideline 5a. CONTRACT NUMBER 5b. GRANT...recommendations of CPG has been identified by experts in the field. We will use bioinformatics to enable data extraction, storage, and analysis to support

  6. Interdisciplinary Introductory Course in Bioinformatics

    Science.gov (United States)

    Kortsarts, Yana; Morris, Robert W.; Utell, Janine M.

    2010-01-01

    Bioinformatics is a relatively new interdisciplinary field that integrates computer science, mathematics, biology, and information technology to manage, analyze, and understand biological, biochemical and biophysical information. We present our experience in teaching an interdisciplinary course, Introduction to Bioinformatics, which was developed…

  7. Cloud Infrastructures for In Silico Drug Discovery: Economic and Practical Aspects

    Science.gov (United States)

    Clematis, Andrea; Quarati, Alfonso; Cesini, Daniele; Milanesi, Luciano; Merelli, Ivan

    2013-01-01

    Cloud computing opens new perspectives for small-medium biotechnology laboratories that need to perform bioinformatics analysis in a flexible and effective way. This seems particularly true for hybrid clouds that couple the scalability offered by general-purpose public clouds with the greater control and ad hoc customizations supplied by the private ones. A hybrid cloud broker, acting as an intermediary between users and public providers, can support customers in the selection of the most suitable offers, optionally adding the provisioning of dedicated services with higher levels of quality. This paper analyses some economic and practical aspects of exploiting cloud computing in a real research scenario for the in silico drug discovery in terms of requirements, costs, and computational load based on the number of expected users. In particular, our work is aimed at supporting both the researchers and the cloud broker delivering an IaaS cloud infrastructure for biotechnology laboratories exposing different levels of nonfunctional requirements. PMID:24106693

  8. Cloud Infrastructures for In Silico Drug Discovery: Economic and Practical Aspects

    Directory of Open Access Journals (Sweden)

    Daniele D'Agostino

    2013-01-01

    Full Text Available Cloud computing opens new perspectives for small-medium biotechnology laboratories that need to perform bioinformatics analysis in a flexible and effective way. This seems particularly true for hybrid clouds that couple the scalability offered by general-purpose public clouds with the greater control and ad hoc customizations supplied by the private ones. A hybrid cloud broker, acting as an intermediary between users and public providers, can support customers in the selection of the most suitable offers, optionally adding the provisioning of dedicated services with higher levels of quality. This paper analyses some economic and practical aspects of exploiting cloud computing in a real research scenario for the in silico drug discovery in terms of requirements, costs, and computational load based on the number of expected users. In particular, our work is aimed at supporting both the researchers and the cloud broker delivering an IaaS cloud infrastructure for biotechnology laboratories exposing different levels of nonfunctional requirements.

  9. A Performance/Cost Evaluation for a GPU-Based Drug Discovery Application on Volunteer Computing

    Directory of Open Access Journals (Sweden)

    Ginés D. Guerrero

    2014-01-01

    Full Text Available Bioinformatics is an interdisciplinary research field that develops tools for the analysis of large biological databases, and, thus, the use of high performance computing (HPC platforms is mandatory for the generation of useful biological knowledge. The latest generation of graphics processing units (GPUs has democratized the use of HPC as they push desktop computers to cluster-level performance. Many applications within this field have been developed to leverage these powerful and low-cost architectures. However, these applications still need to scale to larger GPU-based systems to enable remarkable advances in the fields of healthcare, drug discovery, genome research, etc. The inclusion of GPUs in HPC systems exacerbates power and temperature issues, increasing the total cost of ownership (TCO. This paper explores the benefits of volunteer computing to scale bioinformatics applications as an alternative to own large GPU-based local infrastructures. We use as a benchmark a GPU-based drug discovery application called BINDSURF that their computational requirements go beyond a single desktop machine. Volunteer computing is presented as a cheap and valid HPC system for those bioinformatics applications that need to process huge amounts of data and where the response time is not a critical factor.

  10. Navigating the changing learning landscape: perspective from bioinformatics.ca.

    Science.gov (United States)

    Brazas, Michelle D; Ouellette, B F Francis

    2013-09-01

    With the advent of YouTube channels in bioinformatics, open platforms for problem solving in bioinformatics, active web forums in computing analyses and online resources for learning to code or use a bioinformatics tool, the more traditional continuing education bioinformatics training programs have had to adapt. Bioinformatics training programs that solely rely on traditional didactic methods are being superseded by these newer resources. Yet such face-to-face instruction is still invaluable in the learning continuum. Bioinformatics.ca, which hosts the Canadian Bioinformatics Workshops, has blended more traditional learning styles with current online and social learning styles. Here we share our growing experiences over the past 12 years and look toward what the future holds for bioinformatics training programs.

  11. The European Bioinformatics Institute in 2017: data coordination and integration

    Science.gov (United States)

    Cochrane, Guy; Apweiler, Rolf; Birney, Ewan

    2018-01-01

    Abstract The European Bioinformatics Institute (EMBL-EBI) supports life-science research throughout the world by providing open data, open-source software and analytical tools, and technical infrastructure (https://www.ebi.ac.uk). We accommodate an increasingly diverse range of data types and integrate them, so that biologists in all disciplines can explore life in ever-increasing detail. We maintain over 40 data resources, many of which are run collaboratively with partners in 16 countries (https://www.ebi.ac.uk/services). Submissions continue to increase exponentially: our data storage has doubled in less than two years to 120 petabytes. Recent advances in cellular imaging and single-cell sequencing techniques are generating a vast amount of high-dimensional data, bringing to light new cell types and new perspectives on anatomy. Accordingly, one of our main focus areas is integrating high-quality information from bioimaging, biobanking and other types of molecular data. This is reflected in our deep involvement in Open Targets, stewarding of plant phenotyping standards (MIAPPE) and partnership in the Human Cell Atlas data coordination platform, as well as the 2017 launch of the Omics Discovery Index. This update gives a birds-eye view of EMBL-EBI’s approach to data integration and service development as genomics begins to enter the clinic. PMID:29186510

  12. Crowdsourcing for bioinformatics.

    Science.gov (United States)

    Good, Benjamin M; Su, Andrew I

    2013-08-15

    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. 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.

  13. Is there room for ethics within bioinformatics education?

    Science.gov (United States)

    Taneri, Bahar

    2011-07-01

    When bioinformatics education is considered, several issues are addressed. At the undergraduate level, the main issue revolves around conveying information from two main and different fields: biology and computer science. At the graduate level, the main issue is bridging the gap between biology students and computer science students. However, there is an educational component that is rarely addressed within the context of bioinformatics education: the ethics component. Here, a different perspective is provided on bioinformatics education, and the current status of ethics is analyzed within the existing bioinformatics programs. Analysis of the existing undergraduate and graduate programs, in both Europe and the United States, reveals the minimal attention given to ethics within bioinformatics education. Given that bioinformaticians speedily and effectively shape the biomedical sciences and hence their implications for society, here redesigning of the bioinformatics curricula is suggested in order to integrate the necessary ethics education. Unique ethical problems awaiting bioinformaticians and bioinformatics ethics as a separate field of study are discussed. In addition, a template for an "Ethics in Bioinformatics" course is provided.

  14. MOWServ: a web client for integration of bioinformatic resources

    Science.gov (United States)

    Ramírez, Sergio; Muñoz-Mérida, Antonio; Karlsson, Johan; García, Maximiliano; Pérez-Pulido, Antonio J.; Claros, M. Gonzalo; Trelles, Oswaldo

    2010-01-01

    The productivity of any scientist is affected by cumbersome, tedious and time-consuming tasks that try to make the heterogeneous web services compatible so that they can be useful in their research. MOWServ, the bioinformatic platform offered by the Spanish National Institute of Bioinformatics, was released to provide integrated access to databases and analytical tools. Since its release, the number of available services has grown dramatically, and it has become one of the main contributors of registered services in the EMBRACE Biocatalogue. The ontology that enables most of the web-service compatibility has been curated, improved and extended. The service discovery has been greatly enhanced by Magallanes software and biodataSF. User data are securely stored on the main server by an authentication protocol that enables the monitoring of current or already-finished user’s tasks, as well as the pipelining of successive data processing services. The BioMoby standard has been greatly extended with the new features included in the MOWServ, such as management of additional information (metadata such as extended descriptions, keywords and datafile examples), a qualified registry, error handling, asynchronous services and service replication. All of them have increased the MOWServ service quality, usability and robustness. MOWServ is available at http://www.inab.org/MOWServ/ and has a mirror at http://www.bitlab-es.com/MOWServ/. PMID:20525794

  15. Perspective: Role of structure prediction in materials discovery and design

    Directory of Open Access Journals (Sweden)

    Richard J. Needs

    2016-05-01

    Full Text Available Materials informatics owes much to bioinformatics and the Materials Genome Initiative has been inspired by the Human Genome Project. But there is more to bioinformatics than genomes, and the same is true for materials informatics. Here we describe the rapidly expanding role of searching for structures of materials using first-principles electronic-structure methods. Structure searching has played an important part in unraveling structures of dense hydrogen and in identifying the record-high-temperature superconducting component in hydrogen sulfide at high pressures. We suggest that first-principles structure searching has already demonstrated its ability to determine structures of a wide range of materials and that it will play a central and increasing part in materials discovery and design.

  16. XML schemas for common bioinformatic data types and their application in workflow systems.

    Science.gov (United States)

    Seibel, Philipp N; Krüger, Jan; Hartmeier, Sven; Schwarzer, Knut; Löwenthal, Kai; Mersch, Henning; Dandekar, Thomas; Giegerich, Robert

    2006-11-06

    Today, there is a growing need in bioinformatics to combine available software tools into chains, thus building complex applications from existing single-task tools. To create such workflows, the tools involved have to be able to work with each other's data--therefore, a common set of well-defined data formats is needed. Unfortunately, current bioinformatic tools use a great variety of heterogeneous formats. Acknowledging the need for common formats, the Helmholtz Open BioInformatics Technology network (HOBIT) identified several basic data types used in bioinformatics and developed appropriate format descriptions, formally defined by XML schemas, and incorporated them in a Java library (BioDOM). These schemas currently cover sequence, sequence alignment, RNA secondary structure and RNA secondary structure alignment formats in a form that is independent of any specific program, thus enabling seamless interoperation of different tools. All XML formats are available at http://bioschemas.sourceforge.net, the BioDOM library can be obtained at http://biodom.sourceforge.net. The HOBIT XML schemas and the BioDOM library simplify adding XML support to newly created and existing bioinformatic tools, enabling these tools to interoperate seamlessly in workflow scenarios.

  17. XML schemas for common bioinformatic data types and their application in workflow systems

    Science.gov (United States)

    Seibel, Philipp N; Krüger, Jan; Hartmeier, Sven; Schwarzer, Knut; Löwenthal, Kai; Mersch, Henning; Dandekar, Thomas; Giegerich, Robert

    2006-01-01

    Background Today, there is a growing need in bioinformatics to combine available software tools into chains, thus building complex applications from existing single-task tools. To create such workflows, the tools involved have to be able to work with each other's data – therefore, a common set of well-defined data formats is needed. Unfortunately, current bioinformatic tools use a great variety of heterogeneous formats. Results Acknowledging the need for common formats, the Helmholtz Open BioInformatics Technology network (HOBIT) identified several basic data types used in bioinformatics and developed appropriate format descriptions, formally defined by XML schemas, and incorporated them in a Java library (BioDOM). These schemas currently cover sequence, sequence alignment, RNA secondary structure and RNA secondary structure alignment formats in a form that is independent of any specific program, thus enabling seamless interoperation of different tools. All XML formats are available at , the BioDOM library can be obtained at . Conclusion The HOBIT XML schemas and the BioDOM library simplify adding XML support to newly created and existing bioinformatic tools, enabling these tools to interoperate seamlessly in workflow scenarios. PMID:17087823

  18. Rising Strengths Hong Kong SAR in Bioinformatics.

    Science.gov (United States)

    Chakraborty, Chiranjib; George Priya Doss, C; Zhu, Hailong; Agoramoorthy, Govindasamy

    2017-06-01

    Hong Kong's bioinformatics sector is attaining new heights in combination with its economic boom and the predominance of the working-age group in its population. Factors such as a knowledge-based and free-market economy have contributed towards a prominent position on the world map of bioinformatics. In this review, we have considered the educational measures, landmark research activities and the achievements of bioinformatics companies and the role of the Hong Kong government in the establishment of bioinformatics as strength. However, several hurdles remain. New government policies will assist computational biologists to overcome these hurdles and further raise the profile of the field. There is a high expectation that bioinformatics in Hong Kong will be a promising area for the next generation.

  19. EURASIP journal on bioinformatics & systems biology

    National Research Council Canada - National Science Library

    2006-01-01

    "The overall aim of "EURASIP Journal on Bioinformatics and Systems Biology" is to publish research results related to signal processing and bioinformatics theories and techniques relevant to a wide...

  20. Virtual Bioinformatics Distance Learning Suite

    Science.gov (United States)

    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…

  1. The 2016 Bioinformatics Open Source Conference (BOSC).

    Science.gov (United States)

    Harris, Nomi L; Cock, Peter J A; Chapman, Brad; Fields, Christopher J; Hokamp, Karsten; Lapp, Hilmar; Muñoz-Torres, Monica; Wiencko, Heather

    2016-01-01

    Message from the ISCB: The Bioinformatics Open Source Conference (BOSC) is a yearly meeting organized by the Open Bioinformatics Foundation (OBF), a non-profit group dedicated to promoting the practice and philosophy of Open Source software development and Open Science within the biological research community. BOSC has been run since 2000 as a two-day Special Interest Group (SIG) before the annual ISMB conference. The 17th annual BOSC ( http://www.open-bio.org/wiki/BOSC_2016) took place in Orlando, Florida in July 2016. As in previous years, the conference was preceded by a two-day collaborative coding event open to the bioinformatics community. The conference brought together nearly 100 bioinformatics researchers, developers and users of open source software to interact and share ideas about standards, bioinformatics software development, and open and reproducible science.

  2. Bioclipse: an open source workbench for chemo- and bioinformatics

    Directory of Open Access Journals (Sweden)

    Wagener Johannes

    2007-02-01

    Full Text Available Abstract Background There is a need for software applications that provide users with a complete and extensible toolkit for chemo- and bioinformatics accessible from a single workbench. Commercial packages are expensive and closed source, hence they do not allow end users to modify algorithms and add custom functionality. Existing open source projects are more focused on providing a framework for integrating existing, separately installed bioinformatics packages, rather than providing user-friendly interfaces. No open source chemoinformatics workbench has previously been published, and no sucessful attempts have been made to integrate chemo- and bioinformatics into a single framework. Results Bioclipse is an advanced workbench for resources in chemo- and bioinformatics, such as molecules, proteins, sequences, spectra, and scripts. It provides 2D-editing, 3D-visualization, file format conversion, calculation of chemical properties, and much more; all fully integrated into a user-friendly desktop application. Editing supports standard functions such as cut and paste, drag and drop, and undo/redo. Bioclipse is written in Java and based on the Eclipse Rich Client Platform with a state-of-the-art plugin architecture. This gives Bioclipse an advantage over other systems as it can easily be extended with functionality in any desired direction. Conclusion Bioclipse is a powerful workbench for bio- and chemoinformatics as well as an advanced integration platform. The rich functionality, intuitive user interface, and powerful plugin architecture make Bioclipse the most advanced and user-friendly open source workbench for chemo- and bioinformatics. Bioclipse is released under Eclipse Public License (EPL, an open source license which sets no constraints on external plugin licensing; it is totally open for both open source plugins as well as commercial ones. Bioclipse is freely available at http://www.bioclipse.net.

  3. Natural Products as Leads in Schistosome Drug Discovery

    Directory of Open Access Journals (Sweden)

    Bruno J. Neves

    2015-01-01

    Full Text Available Schistosomiasis is a neglected parasitic tropical disease that claims around 200,000 human lives every year. Praziquantel (PZQ, the only drug recommended by the World Health Organization for the treatment and control of human schistosomiasis, is now facing the threat of drug resistance, indicating the urgent need for new effective compounds to treat this disease. Therefore, globally, there is renewed interest in natural products (NPs as a starting point for drug discovery and development for schistosomiasis. Recent advances in genomics, proteomics, bioinformatics, and cheminformatics have brought about unprecedented opportunities for the rapid and more cost-effective discovery of new bioactive compounds against neglected tropical diseases. This review highlights the main contributions that NP drug discovery and development have made in the treatment of schistosomiasis and it discusses how integration with virtual screening (VS strategies may contribute to accelerating the development of new schistosomidal leads, especially through the identification of unexplored, biologically active chemical scaffolds and structural optimization of NPs with previously established activity.

  4. Biomarker discovery in mass spectrometry-based urinary proteomics.

    Science.gov (United States)

    Thomas, Samuel; Hao, Ling; Ricke, William A; Li, Lingjun

    2016-04-01

    Urinary proteomics has become one of the most attractive topics in disease biomarker discovery. MS-based proteomic analysis has advanced continuously and emerged as a prominent tool in the field of clinical bioanalysis. However, only few protein biomarkers have made their way to validation and clinical practice. Biomarker discovery is challenged by many clinical and analytical factors including, but not limited to, the complexity of urine and the wide dynamic range of endogenous proteins in the sample. This article highlights promising technologies and strategies in the MS-based biomarker discovery process, including study design, sample preparation, protein quantification, instrumental platforms, and bioinformatics. Different proteomics approaches are discussed, and progresses in maximizing urinary proteome coverage and standardization are emphasized in this review. MS-based urinary proteomics has great potential in the development of noninvasive diagnostic assays in the future, which will require collaborative efforts between analytical scientists, systems biologists, and clinicians. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  5. BioinformatiqTM - integrating data types for proteomic discovery

    International Nuclear Information System (INIS)

    Arthur, J.W.; Harrison, M.; Manoharan, A.; Traini, M.; Shaw, E.; Wilkins, M.

    2001-01-01

    Proteomics (Wilkins et al. 1997) involves the large-scale analysis of expressed proteins. At each stage of the discovery process the researcher accumulates large volumes of data. These include: clinical or biological data about the sample being studied; details of sample purification and separation; images of 2D gels and associated information; MALDI mass spectra; MS/MS and PSD spectra; as well as meta-data relating to the projects undertaken and experiments performed. All this must be combined with existing databases of protein and EST sequences, post-translational modifications, and protein glycosylation, then processed with sophisticated bioinformatics tools in order to extract meaningful answers to questions of biological, clinical, and agricultural significance. BioinformatlQ TM is a web-based application for the storage, management, and automated bioinformatic analysis of proteomic information. This poster will demonstrate the integration of these disparate data sources in proteomics

  6. Navigating the changing learning landscape: perspective from bioinformatics.ca

    OpenAIRE

    Brazas, Michelle D.; Ouellette, B. F. Francis

    2013-01-01

    With the advent of YouTube channels in bioinformatics, open platforms for problem solving in bioinformatics, active web forums in computing analyses and online resources for learning to code or use a bioinformatics tool, the more traditional continuing education bioinformatics training programs have had to adapt. Bioinformatics training programs that solely rely on traditional didactic methods are being superseded by these newer resources. Yet such face-to-face instruction is still invaluable...

  7. An overview of bioinformatics methods for modeling biological pathways in yeast.

    Science.gov (United States)

    Hou, Jie; Acharya, Lipi; Zhu, Dongxiao; Cheng, Jianlin

    2016-03-01

    The advent of high-throughput genomics techniques, along with the completion of genome sequencing projects, identification of protein-protein interactions and reconstruction of genome-scale pathways, has accelerated the development of systems biology research in the yeast organism Saccharomyces cerevisiae In particular, discovery of biological pathways in yeast has become an important forefront in systems biology, which aims to understand the interactions among molecules within a cell leading to certain cellular processes in response to a specific environment. While the existing theoretical and experimental approaches enable the investigation of well-known pathways involved in metabolism, gene regulation and signal transduction, bioinformatics methods offer new insights into computational modeling of biological pathways. A wide range of computational approaches has been proposed in the past for reconstructing biological pathways from high-throughput datasets. Here we review selected bioinformatics approaches for modeling biological pathways inS. cerevisiae, including metabolic pathways, gene-regulatory pathways and signaling pathways. We start with reviewing the research on biological pathways followed by discussing key biological databases. In addition, several representative computational approaches for modeling biological pathways in yeast are discussed. © The Author 2015. Published by Oxford University Press. All rights reserved. For permissions, please email: journals.permissions@oup.com.

  8. SNP-PHAGE – High throughput SNP discovery pipeline

    Directory of Open Access Journals (Sweden)

    Cregan Perry B

    2006-10-01

    Full Text Available Abstract Background Single nucleotide polymorphisms (SNPs as defined here are single base sequence changes or short insertion/deletions between or within individuals of a given species. As a result of their abundance and the availability of high throughput analysis technologies SNP markers have begun to replace other traditional markers such as restriction fragment length polymorphisms (RFLPs, amplified fragment length polymorphisms (AFLPs and simple sequence repeats (SSRs or microsatellite markers for fine mapping and association studies in several species. For SNP discovery from chromatogram data, several bioinformatics programs have to be combined to generate an analysis pipeline. Results have to be stored in a relational database to facilitate interrogation through queries or to generate data for further analyses such as determination of linkage disequilibrium and identification of common haplotypes. Although these tasks are routinely performed by several groups, an integrated open source SNP discovery pipeline that can be easily adapted by new groups interested in SNP marker development is currently unavailable. Results We developed SNP-PHAGE (SNP discovery Pipeline with additional features for identification of common haplotypes within a sequence tagged site (Haplotype Analysis and GenBank (-dbSNP submissions. This tool was applied for analyzing sequence traces from diverse soybean genotypes to discover over 10,000 SNPs. This package was developed on UNIX/Linux platform, written in Perl and uses a MySQL database. Scripts to generate a user-friendly web interface are also provided with common queries for preliminary data analysis. A machine learning tool developed by this group for increasing the efficiency of SNP discovery is integrated as a part of this package as an optional feature. The SNP-PHAGE package is being made available open source at http://bfgl.anri.barc.usda.gov/ML/snp-phage/. Conclusion SNP-PHAGE provides a bioinformatics

  9. On reliable discovery of molecular signatures

    Directory of Open Access Journals (Sweden)

    Björkegren Johan

    2009-01-01

    Full Text Available Abstract Background Molecular signatures are sets of genes, proteins, genetic variants or other variables that can be used as markers for a particular phenotype. Reliable signature discovery methods could yield valuable insight into cell biology and mechanisms of human disease. However, it is currently not clear how to control error rates such as the false discovery rate (FDR in signature discovery. Moreover, signatures for cancer gene expression have been shown to be unstable, that is, difficult to replicate in independent studies, casting doubts on their reliability. Results We demonstrate that with modern prediction methods, signatures that yield accurate predictions may still have a high FDR. Further, we show that even signatures with low FDR may fail to replicate in independent studies due to limited statistical power. Thus, neither stability nor predictive accuracy are relevant when FDR control is the primary goal. We therefore develop a general statistical hypothesis testing framework that for the first time provides FDR control for signature discovery. Our method is demonstrated to be correct in simulation studies. When applied to five cancer data sets, the method was able to discover molecular signatures with 5% FDR in three cases, while two data sets yielded no significant findings. Conclusion Our approach enables reliable discovery of molecular signatures from genome-wide data with current sample sizes. The statistical framework developed herein is potentially applicable to a wide range of prediction problems in bioinformatics.

  10. MAPI: towards the integrated exploitation of bioinformatics Web Services.

    Science.gov (United States)

    Ramirez, Sergio; Karlsson, Johan; Trelles, Oswaldo

    2011-10-27

    Bioinformatics is commonly featured as a well assorted list of available web resources. Although diversity of services is positive in general, the proliferation of tools, their dispersion and heterogeneity complicate the integrated exploitation of such data processing capacity. To facilitate the construction of software clients and make integrated use of this variety of tools, we present a modular programmatic application interface (MAPI) that provides the necessary functionality for uniform representation of Web Services metadata descriptors including their management and invocation protocols of the services which they represent. This document describes the main functionality of the framework and how it can be used to facilitate the deployment of new software under a unified structure of bioinformatics Web Services. A notable feature of MAPI is the modular organization of the functionality into different modules associated with specific tasks. This means that only the modules needed for the client have to be installed, and that the module functionality can be extended without the need for re-writing the software client. The potential utility and versatility of the software library has been demonstrated by the implementation of several currently available clients that cover different aspects of integrated data processing, ranging from service discovery to service invocation with advanced features such as workflows composition and asynchronous services calls to multiple types of Web Services including those registered in repositories (e.g. GRID-based, SOAP, BioMOBY, R-bioconductor, and others).

  11. Translational Bioinformatics for Diagnostic and Prognostic Prediction of Prostate Cancer in the Next-Generation Sequencing Era

    Directory of Open Access Journals (Sweden)

    Jiajia Chen

    2013-01-01

    Full Text Available The discovery of prostate cancer biomarkers has been boosted by the advent of next-generation sequencing (NGS technologies. Nevertheless, many challenges still exist in exploiting the flood of sequence data and translating them into routine diagnostics and prognosis of prostate cancer. Here we review the recent developments in prostate cancer biomarkers by high throughput sequencing technologies. We highlight some fundamental issues of translational bioinformatics and the potential use of cloud computing in NGS data processing for the improvement of prostate cancer treatment.

  12. MACBenAbim: A Multi-platform Mobile Application for searching keyterms in Computational Biology and Bioinformatics.

    Science.gov (United States)

    Oluwagbemi, Olugbenga O; Adewumi, Adewole; Esuruoso, Abimbola

    2012-01-01

    Computational biology and bioinformatics are gradually gaining grounds in Africa and other developing nations of the world. However, in these countries, some of the challenges of computational biology and bioinformatics education are inadequate infrastructures, and lack of readily-available complementary and motivational tools to support learning as well as research. This has lowered the morale of many promising undergraduates, postgraduates and researchers from aspiring to undertake future study in these fields. In this paper, we developed and described MACBenAbim (Multi-platform Mobile Application for Computational Biology and Bioinformatics), a flexible user-friendly tool to search for, define and describe the meanings of keyterms in computational biology and bioinformatics, thus expanding the frontiers of knowledge of the users. This tool also has the capability of achieving visualization of results on a mobile multi-platform context. MACBenAbim is available from the authors for non-commercial purposes.

  13. Proceedings of the 2013 MidSouth Computational Biology and Bioinformatics Society (MCBIOS) Conference.

    Science.gov (United States)

    Wren, Jonathan D; Dozmorov, Mikhail G; Burian, Dennis; Kaundal, Rakesh; Perkins, Andy; Perkins, Ed; Kupfer, Doris M; Springer, Gordon K

    2013-01-01

    The tenth annual conference of the MidSouth Computational Biology and Bioinformatics Society (MCBIOS 2013), "The 10th Anniversary in a Decade of Change: Discovery in a Sea of Data", took place at the Stoney Creek Inn & Conference Center in Columbia, Missouri on April 5-6, 2013. This year's Conference Chairs were Gordon Springer and Chi-Ren Shyu from the University of Missouri and Edward Perkins from the US Army Corps of Engineers Engineering Research and Development Center, who is also the current MCBIOS President (2012-3). There were 151 registrants and a total of 111 abstracts (51 oral presentations and 60 poster session abstracts).

  14. An interdepartmental Ph.D. program in computational biology and bioinformatics: the Yale perspective.

    Science.gov (United States)

    Gerstein, Mark; Greenbaum, Dov; Cheung, Kei; Miller, Perry L

    2007-02-01

    Computational biology and bioinformatics (CBB), the terms often used interchangeably, represent a rapidly evolving biological discipline. With the clear potential for discovery and innovation, and the need to deal with the deluge of biological data, many academic institutions are committing significant resources to develop CBB research and training programs. Yale formally established an interdepartmental Ph.D. program in CBB in May 2003. This paper describes Yale's program, discussing the scope of the field, the program's goals and curriculum, as well as a number of issues that arose in implementing the program. (Further updated information is available from the program's website, www.cbb.yale.edu.)

  15. The 2015 Bioinformatics Open Source Conference (BOSC 2015).

    Science.gov (United States)

    Harris, Nomi L; Cock, Peter J A; Lapp, Hilmar; Chapman, Brad; Davey, Rob; Fields, Christopher; Hokamp, Karsten; Munoz-Torres, Monica

    2016-02-01

    The Bioinformatics Open Source Conference (BOSC) is organized by the Open Bioinformatics Foundation (OBF), a nonprofit group dedicated to promoting the practice and philosophy of open source software development and open science within the biological research community. Since its inception in 2000, BOSC has provided bioinformatics developers with a forum for communicating the results of their latest efforts to the wider research community. BOSC offers a focused environment for developers and users to interact and share ideas about standards; software development practices; practical techniques for solving bioinformatics problems; and approaches that promote open science and sharing of data, results, and software. BOSC is run as a two-day special interest group (SIG) before the annual Intelligent Systems in Molecular Biology (ISMB) conference. BOSC 2015 took place in Dublin, Ireland, and was attended by over 125 people, about half of whom were first-time attendees. Session topics included "Data Science;" "Standards and Interoperability;" "Open Science and Reproducibility;" "Translational Bioinformatics;" "Visualization;" and "Bioinformatics Open Source Project Updates". In addition to two keynote talks and dozens of shorter talks chosen from submitted abstracts, BOSC 2015 included a panel, titled "Open Source, Open Door: Increasing Diversity in the Bioinformatics Open Source Community," that provided an opportunity for open discussion about ways to increase the diversity of participants in BOSC in particular, and in open source bioinformatics in general. The complete program of BOSC 2015 is available online at http://www.open-bio.org/wiki/BOSC_2015_Schedule.

  16. Component-Based Approach for Educating Students in Bioinformatics

    Science.gov (United States)

    Poe, D.; Venkatraman, N.; Hansen, C.; Singh, G.

    2009-01-01

    There is an increasing need for an effective method of teaching bioinformatics. Increased progress and availability of computer-based tools for educating students have led to the implementation of a computer-based system for teaching bioinformatics as described in this paper. Bioinformatics is a recent, hybrid field of study combining elements of…

  17. Phylogenetic trees in bioinformatics

    Energy Technology Data Exchange (ETDEWEB)

    Burr, Tom L [Los Alamos National Laboratory

    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.

  18. Bioinformatics education in high school: implications for promoting science, technology, engineering, and mathematics careers.

    Science.gov (United States)

    Kovarik, Dina N; Patterson, Davis G; Cohen, Carolyn; Sanders, Elizabeth A; Peterson, Karen A; Porter, Sandra G; Chowning, Jeanne Ting

    2013-01-01

    We investigated the effects of our Bio-ITEST teacher professional development model and bioinformatics curricula on cognitive traits (awareness, engagement, self-efficacy, and relevance) in high school teachers and students that are known to accompany a developing interest in science, technology, engineering, and mathematics (STEM) careers. The program included best practices in adult education and diverse resources to empower teachers to integrate STEM career information into their classrooms. The introductory unit, Using Bioinformatics: Genetic Testing, uses bioinformatics to teach basic concepts in genetics and molecular biology, and the advanced unit, Using Bioinformatics: Genetic Research, utilizes bioinformatics to study evolution and support student research with DNA barcoding. Pre-post surveys demonstrated significant growth (n = 24) among teachers in their preparation to teach the curricula and infuse career awareness into their classes, and these gains were sustained through the end of the academic year. Introductory unit students (n = 289) showed significant gains in awareness, relevance, and self-efficacy. While these students did not show significant gains in engagement, advanced unit students (n = 41) showed gains in all four cognitive areas. Lessons learned during Bio-ITEST are explored in the context of recommendations for other programs that wish to increase student interest in STEM careers.

  19. A Mathematical Optimization Problem in Bioinformatics

    Science.gov (United States)

    Heyer, Laurie J.

    2008-01-01

    This article describes the sequence alignment problem in bioinformatics. Through examples, we formulate sequence alignment as an optimization problem and show how to compute the optimal alignment with dynamic programming. The examples and sample exercises have been used by the author in a specialized course in bioinformatics, but could be adapted…

  20. The secondary metabolite bioinformatics portal: Computational tools to facilitate synthetic biology of secondary metabolite production

    Directory of Open Access Journals (Sweden)

    Tilmann Weber

    2016-06-01

    Full Text Available Natural products are among the most important sources of lead molecules for drug discovery. With the development of affordable whole-genome sequencing technologies and other ‘omics tools, the field of natural products research is currently undergoing a shift in paradigms. While, for decades, mainly analytical and chemical methods gave access to this group of compounds, nowadays genomics-based methods offer complementary approaches to find, identify and characterize such molecules. This paradigm shift also resulted in a high demand for computational tools to assist researchers in their daily work. In this context, this review gives a summary of tools and databases that currently are available to mine, identify and characterize natural product biosynthesis pathways and their producers based on ‘omics data. A web portal called Secondary Metabolite Bioinformatics Portal (SMBP at http://www.secondarymetabolites.org is introduced to provide a one-stop catalog and links to these bioinformatics resources. In addition, an outlook is presented how the existing tools and those to be developed will influence synthetic biology approaches in the natural products field.

  1. Bioinformatics and Cancer

    Science.gov (United States)

    Researchers take on challenges and opportunities to mine "Big Data" for answers to complex biological questions. Learn how bioinformatics uses advanced computing, mathematics, and technological platforms to store, manage, analyze, and understand data.

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

    Science.gov (United States)

    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…

  3. Application of bioinformatics tools and databases in microbial dehalogenation research (a review).

    Science.gov (United States)

    Satpathy, R; Konkimalla, V B; Ratha, J

    2015-01-01

    Microbial dehalogenation is a biochemical process in which the halogenated substances are catalyzed enzymatically in to their non-halogenated form. The microorganisms have a wide range of organohalogen degradation ability both explicit and non-specific in nature. Most of these halogenated organic compounds being pollutants need to be remediated; therefore, the current approaches are to explore the potential of microbes at a molecular level for effective biodegradation of these substances. Several microorganisms with dehalogenation activity have been identified and characterized. In this aspect, the bioinformatics plays a key role to gain deeper knowledge in this field of dehalogenation. To facilitate the data mining, many tools have been developed to annotate these data from databases. Therefore, with the discovery of a microorganism one can predict a gene/protein, sequence analysis, can perform structural modelling, metabolic pathway analysis, biodegradation study and so on. This review highlights various methods of bioinformatics approach that describes the application of various databases and specific tools in the microbial dehalogenation fields with special focus on dehalogenase enzymes. Attempts have also been made to decipher some recent applications of in silico modeling methods that comprise of gene finding, protein modelling, Quantitative Structure Biodegradibility Relationship (QSBR) study and reconstruction of metabolic pathways employed in dehalogenation research area.

  4. Bioinformatics research in the Asia Pacific: a 2007 update.

    Science.gov (United States)

    Ranganathan, Shoba; Gribskov, Michael; Tan, Tin Wee

    2008-01-01

    We provide a 2007 update on the bioinformatics research in the Asia-Pacific from the Asia Pacific Bioinformatics Network (APBioNet), Asia's oldest bioinformatics organisation set up in 1998. From 2002, APBioNet has organized the first International Conference on Bioinformatics (InCoB) bringing together scientists working in the field of bioinformatics in the region. This year, the InCoB2007 Conference was organized as the 6th annual conference of the Asia-Pacific Bioinformatics Network, on Aug. 27-30, 2007 at Hong Kong, following a series of successful events in Bangkok (Thailand), Penang (Malaysia), Auckland (New Zealand), Busan (South Korea) and New Delhi (India). Besides a scientific meeting at Hong Kong, satellite events organized are a pre-conference training workshop at Hanoi, Vietnam and a post-conference workshop at Nansha, China. This Introduction provides a brief overview of the peer-reviewed manuscripts accepted for publication in this Supplement. We have organized the papers into thematic areas, highlighting the growing contribution of research excellence from this region, to global bioinformatics endeavours.

  5. ISEV position paper: extracellular vesicle RNA analysis and bioinformatics

    Directory of Open Access Journals (Sweden)

    Andrew F. Hill

    2013-12-01

    Full Text Available Extracellular vesicles (EVs are the collective term for the various vesicles that are released by cells into the extracellular space. Such vesicles include exosomes and microvesicles, which vary by their size and/or protein and genetic cargo. With the discovery that EVs contain genetic material in the form of RNA (evRNA has come the increased interest in these vesicles for their potential use as sources of disease biomarkers and potential therapeutic agents. Rapid developments in the availability of deep sequencing technologies have enabled the study of EV-related RNA in detail. In October 2012, the International Society for Extracellular Vesicles (ISEV held a workshop on “evRNA analysis and bioinformatics.” Here, we report the conclusions of one of the roundtable discussions where we discussed evRNA analysis technologies and provide some guidelines to researchers in the field to consider when performing such analysis.

  6. Challenge: A Multidisciplinary Degree Program in Bioinformatics

    Directory of Open Access Journals (Sweden)

    Mudasser Fraz Wyne

    2006-06-01

    Full Text Available Bioinformatics is a new field that is poorly served by any of the traditional science programs in Biology, Computer science or Biochemistry. Known to be a rapidly evolving discipline, Bioinformatics has emerged from experimental molecular biology and biochemistry as well as from the artificial intelligence, database, pattern recognition, and algorithms disciplines of computer science. While institutions are responding to this increased demand by establishing graduate programs in bioinformatics, entrance barriers for these programs are high, largely due to the significant prerequisite knowledge which is required, both in the fields of biochemistry and computer science. Although many schools currently have or are proposing graduate programs in bioinformatics, few are actually developing new undergraduate programs. In this paper I explore the blend of a multidisciplinary approach, discuss the response of academia and highlight challenges faced by this emerging field.

  7. When cloud computing meets bioinformatics: a review.

    Science.gov (United States)

    Zhou, Shuigeng; Liao, Ruiqi; Guan, Jihong

    2013-10-01

    In the past decades, with the rapid development of high-throughput technologies, biology research has generated an unprecedented amount of data. In order to store and process such a great amount of data, cloud computing and MapReduce were applied to many fields of bioinformatics. In this paper, we first introduce the basic concepts of cloud computing and MapReduce, and their applications in bioinformatics. We then highlight some problems challenging the applications of cloud computing and MapReduce to bioinformatics. Finally, we give a brief guideline for using cloud computing in biology research.

  8. Application of machine learning methods in bioinformatics

    Science.gov (United States)

    Yang, Haoyu; An, Zheng; Zhou, Haotian; Hou, Yawen

    2018-05-01

    Faced with the development of bioinformatics, high-throughput genomic technology have enabled biology to enter the era of big data. [1] Bioinformatics is an interdisciplinary, including the acquisition, management, analysis, interpretation and application of biological information, etc. It derives from the Human Genome Project. The field of machine learning, which aims to develop computer algorithms that improve with experience, holds promise to enable computers to assist humans in the analysis of large, complex data sets.[2]. This paper analyzes and compares various algorithms of machine learning and their applications in bioinformatics.

  9. Accelerating knowledge discovery through community data sharing and integration.

    Science.gov (United States)

    Yip, Y L

    2009-01-01

    To summarize current excellent research in the field of bioinformatics. Synopsis of the articles selected for the IMIA Yearbook 2009. The selection process for this yearbook's section on Bioinformatics results in six excellent articles highlighting several important trends First, it can be noted that Semantic Web technology continues to play an important role in heterogeneous data integration. Novel applications also put more emphasis on its ability to make logical inferences leading to new insights and discoveries. Second, translational research, due to its complex nature, increasingly relies on collective intelligence made available through the adoption of community-defined protocols or software architectures for secure data annotation, sharing and analysis. Advances in systems biology, bio-ontologies and text-ming can also be noted. Current biomedical research gradually evolves towards an environment characterized by intensive collaboration and more sophisticated knowledge processing activities. Enabling technologies, either Semantic Web or other solutions, are expected to play an increasingly important role in generating new knowledge in the foreseeable future.

  10. Bioinformatics Training Network (BTN): a community resource for bioinformatics trainers

    DEFF Research Database (Denmark)

    Schneider, Maria V.; Walter, Peter; Blatter, Marie-Claude

    2012-01-01

    and clearly tagged in relation to target audiences, learning objectives, etc. Ideally, they would also be peer reviewed, and easily and efficiently accessible for downloading. Here, we present the Bioinformatics Training Network (BTN), a new enterprise that has been initiated to address these needs and review...

  11. Planning bioinformatics workflows using an expert system

    Science.gov (United States)

    Chen, Xiaoling; Chang, Jeffrey T.

    2017-01-01

    Abstract Motivation: Bioinformatic analyses are becoming formidably more complex due to the increasing number of steps required to process the data, as well as the proliferation of methods that can be used in each step. To alleviate this difficulty, pipelines are commonly employed. However, pipelines are typically implemented to automate a specific analysis, and thus are difficult to use for exploratory analyses requiring systematic changes to the software or parameters used. Results: To automate the development of pipelines, we have investigated expert systems. We created the Bioinformatics ExperT SYstem (BETSY) that includes a knowledge base where the capabilities of bioinformatics software is explicitly and formally encoded. BETSY is a backwards-chaining rule-based expert system comprised of a data model that can capture the richness of biological data, and an inference engine that reasons on the knowledge base to produce workflows. Currently, the knowledge base is populated with rules to analyze microarray and next generation sequencing data. We evaluated BETSY and found that it could generate workflows that reproduce and go beyond previously published bioinformatics results. Finally, a meta-investigation of the workflows generated from the knowledge base produced a quantitative measure of the technical burden imposed by each step of bioinformatics analyses, revealing the large number of steps devoted to the pre-processing of data. In sum, an expert system approach can facilitate exploratory bioinformatic analysis by automating the development of workflows, a task that requires significant domain expertise. Availability and Implementation: https://github.com/jefftc/changlab Contact: jeffrey.t.chang@uth.tmc.edu PMID:28052928

  12. Snpdat: Easy and rapid annotation of results from de novo snp discovery projects for model and non-model organisms

    Directory of Open Access Journals (Sweden)

    Doran Anthony G

    2013-02-01

    Full Text Available Abstract Background Single nucleotide polymorphisms (SNPs are the most abundant genetic variant found in vertebrates and invertebrates. SNP discovery has become a highly automated, robust and relatively inexpensive process allowing the identification of many thousands of mutations for model and non-model organisms. Annotating large numbers of SNPs can be a difficult and complex process. Many tools available are optimised for use with organisms densely sampled for SNPs, such as humans. There are currently few tools available that are species non-specific or support non-model organism data. Results Here we present SNPdat, a high throughput analysis tool that can provide a comprehensive annotation of both novel and known SNPs for any organism with a draft sequence and annotation. Using a dataset of 4,566 SNPs identified in cattle using high-throughput DNA sequencing we demonstrate the annotations performed and the statistics that can be generated by SNPdat. Conclusions SNPdat provides users with a simple tool for annotation of genomes that are either not supported by other tools or have a small number of annotated SNPs available. SNPdat can also be used to analyse datasets from organisms which are densely sampled for SNPs. As a command line tool it can easily be incorporated into existing SNP discovery pipelines and fills a niche for analyses involving non-model organisms that are not supported by many available SNP annotation tools. SNPdat will be of great interest to scientists involved in SNP discovery and analysis projects, particularly those with limited bioinformatics experience.

  13. Continuing Education Workshops in Bioinformatics Positively Impact Research and Careers.

    Science.gov (United States)

    Brazas, Michelle D; Ouellette, B F Francis

    2016-06-01

    Bioinformatics.ca has been hosting continuing education programs in introductory and advanced bioinformatics topics in Canada since 1999 and has trained more than 2,000 participants to date. These workshops have been adapted over the years to keep pace with advances in both science and technology as well as the changing landscape in available learning modalities and the bioinformatics training needs of our audience. Post-workshop surveys have been a mandatory component of each workshop and are used to ensure appropriate adjustments are made to workshops to maximize learning. However, neither bioinformatics.ca nor others offering similar training programs have explored the long-term impact of bioinformatics continuing education training. Bioinformatics.ca recently initiated a look back on the impact its workshops have had on the career trajectories, research outcomes, publications, and collaborations of its participants. Using an anonymous online survey, bioinformatics.ca analyzed responses from those surveyed and discovered its workshops have had a positive impact on collaborations, research, publications, and career progression.

  14. Using "Arabidopsis" Genetic Sequences to Teach Bioinformatics

    Science.gov (United States)

    Zhang, Xiaorong

    2009-01-01

    This article describes a new approach to teaching bioinformatics using "Arabidopsis" genetic sequences. Several open-ended and inquiry-based laboratory exercises have been designed to help students grasp key concepts and gain practical skills in bioinformatics, using "Arabidopsis" leucine-rich repeat receptor-like kinase (LRR…

  15. Fuzzy Logic in Medicine and Bioinformatics

    Directory of Open Access Journals (Sweden)

    Angela Torres

    2006-01-01

    Full Text Available 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.

  16. Functionality and Evolutionary History of the Chaperonins in Thermophilic Archaea. A Bioinformatical Perspective

    Science.gov (United States)

    Karlin, Samuel

    2004-01-01

    We used bioinformatics methods to study phylogenetic relations and differentiation patterns of the archaeal chaperonin 60 kDa heat-shock protein (HSP60) genes in support of the study of differential expression patterns of the three chaperonin genes encoded in Sulfolobus shibatae.

  17. Online Bioinformatics Tutorials | Office of Cancer Genomics

    Science.gov (United States)

    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.

  18. Decades of Discovery

    Science.gov (United States)

    2011-06-01

    For the past two-and-a-half decades, the Office of Science at the U.S. Department of Energy has been at the forefront of scientific discovery. Over 100 important discoveries supported by the Office of Science are represented in this document.

  19. The development and application of bioinformatics core competencies to improve bioinformatics training and education.

    Science.gov (United States)

    Mulder, Nicola; Schwartz, Russell; Brazas, Michelle D; Brooksbank, Cath; Gaeta, Bruno; Morgan, Sarah L; Pauley, Mark A; Rosenwald, Anne; Rustici, Gabriella; Sierk, Michael; Warnow, Tandy; Welch, Lonnie

    2018-02-01

    Bioinformatics is recognized as part of the essential knowledge base of numerous career paths in biomedical research and healthcare. However, there is little agreement in the field over what that knowledge entails or how best to provide it. These disagreements are compounded by the wide range of populations in need of bioinformatics training, with divergent prior backgrounds and intended application areas. The Curriculum Task Force of the International Society of Computational Biology (ISCB) Education Committee has sought to provide a framework for training needs and curricula in terms of a set of bioinformatics core competencies that cut across many user personas and training programs. The initial competencies developed based on surveys of employers and training programs have since been refined through a multiyear process of community engagement. This report describes the current status of the competencies and presents a series of use cases illustrating how they are being applied in diverse training contexts. These use cases are intended to demonstrate how others can make use of the competencies and engage in the process of their continuing refinement and application. The report concludes with a consideration of remaining challenges and future plans.

  20. The development and application of bioinformatics core competencies to improve bioinformatics training and education

    Science.gov (United States)

    Brooksbank, Cath; Morgan, Sarah L.; Rosenwald, Anne; Warnow, Tandy; Welch, Lonnie

    2018-01-01

    Bioinformatics is recognized as part of the essential knowledge base of numerous career paths in biomedical research and healthcare. However, there is little agreement in the field over what that knowledge entails or how best to provide it. These disagreements are compounded by the wide range of populations in need of bioinformatics training, with divergent prior backgrounds and intended application areas. The Curriculum Task Force of the International Society of Computational Biology (ISCB) Education Committee has sought to provide a framework for training needs and curricula in terms of a set of bioinformatics core competencies that cut across many user personas and training programs. The initial competencies developed based on surveys of employers and training programs have since been refined through a multiyear process of community engagement. This report describes the current status of the competencies and presents a series of use cases illustrating how they are being applied in diverse training contexts. These use cases are intended to demonstrate how others can make use of the competencies and engage in the process of their continuing refinement and application. The report concludes with a consideration of remaining challenges and future plans. PMID:29390004

  1. 4273π: bioinformatics education on low cost ARM hardware.

    Science.gov (United States)

    Barker, Daniel; Ferrier, David Ek; Holland, Peter Wh; Mitchell, John Bo; Plaisier, Heleen; Ritchie, Michael G; Smart, Steven D

    2013-08-12

    Teaching bioinformatics at universities is complicated by typical computer classroom settings. As well as running software locally and online, students should gain experience of systems administration. For a future career in biology or bioinformatics, the installation of software is a useful skill. We propose that this may be taught by running the course on GNU/Linux running on inexpensive Raspberry Pi computer hardware, for which students may be granted full administrator access. We release 4273π, an operating system image for Raspberry Pi based on Raspbian Linux. This includes minor customisations for classroom use and includes our Open Access bioinformatics course, 4273π Bioinformatics for Biologists. This is based on the final-year undergraduate module BL4273, run on Raspberry Pi computers at the University of St Andrews, Semester 1, academic year 2012-2013. 4273π is a means to teach bioinformatics, including systems administration tasks, to undergraduates at low cost.

  2. OpenHelix: bioinformatics education outside of a different box.

    Science.gov (United States)

    Williams, Jennifer M; Mangan, Mary E; Perreault-Micale, Cynthia; Lathe, Scott; Sirohi, Neeraj; Lathe, Warren C

    2010-11-01

    The amount of biological data is increasing rapidly, and will continue to increase as new rapid technologies are developed. Professionals in every area of bioscience will have data management needs that require publicly available bioinformatics resources. Not all scientists desire a formal bioinformatics education but would benefit from more informal educational sources of learning. Effective bioinformatics education formats will address a broad range of scientific needs, will be aimed at a variety of user skill levels, and will be delivered in a number of different formats to address different learning styles. Informal sources of bioinformatics education that are effective are available, and will be explored in this review.

  3. Performance Evaluation of Frequent Subgraph Discovery Techniques

    Directory of Open Access Journals (Sweden)

    Saif Ur Rehman

    2014-01-01

    Full Text Available Due to rapid development of the Internet technology and new scientific advances, the number of applications that model the data as graphs increases, because graphs have highly expressive power to model a complicated structure. Graph mining is a well-explored area of research which is gaining popularity in the data mining community. A graph is a general model to represent data and has been used in many domains such as cheminformatics, web information management system, computer network, and bioinformatics, to name a few. In graph mining the frequent subgraph discovery is a challenging task. Frequent subgraph mining is concerned with discovery of those subgraphs from graph dataset which have frequent or multiple instances within the given graph dataset. In the literature a large number of frequent subgraph mining algorithms have been proposed; these included FSG, AGM, gSpan, CloseGraph, SPIN, Gaston, and Mofa. The objective of this research work is to perform quantitative comparison of the above listed techniques. The performances of these techniques have been evaluated through a number of experiments based on three different state-of-the-art graph datasets. This novel work will provide base for anyone who is working to design a new frequent subgraph discovery technique.

  4. Footprints: A Visual Search Tool that Supports Discovery and Coverage Tracking.

    Science.gov (United States)

    Isaacs, Ellen; Domico, Kelly; Ahern, Shane; Bart, Eugene; Singhal, Mudita

    2014-12-01

    Searching a large document collection to learn about a broad subject involves the iterative process of figuring out what to ask, filtering the results, identifying useful documents, and deciding when one has covered enough material to stop searching. We are calling this activity "discoverage," discovery of relevant material and tracking coverage of that material. We built a visual analytic tool called Footprints that uses multiple coordinated visualizations to help users navigate through the discoverage process. To support discovery, Footprints displays topics extracted from documents that provide an overview of the search space and are used to construct searches visuospatially. Footprints allows users to triage their search results by assigning a status to each document (To Read, Read, Useful), and those status markings are shown on interactive histograms depicting the user's coverage through the documents across dates, sources, and topics. Coverage histograms help users notice biases in their search and fill any gaps in their analytic process. To create Footprints, we used a highly iterative, user-centered approach in which we conducted many evaluations during both the design and implementation stages and continually modified the design in response to feedback.

  5. A Survey on Evolutionary Algorithm Based Hybrid Intelligence in Bioinformatics

    Directory of Open Access Journals (Sweden)

    Shan Li

    2014-01-01

    Full Text Available With the rapid advance in genomics, proteomics, metabolomics, and other types of omics technologies during the past decades, a tremendous amount of data related to molecular biology has been produced. It is becoming a big challenge for the bioinformatists to analyze and interpret these data with conventional intelligent techniques, for example, support vector machines. Recently, the hybrid intelligent methods, which integrate several standard intelligent approaches, are becoming more and more popular due to their robustness and efficiency. Specifically, the hybrid intelligent approaches based on evolutionary algorithms (EAs are widely used in various fields due to the efficiency and robustness of EAs. In this review, we give an introduction about the applications of hybrid intelligent methods, in particular those based on evolutionary algorithm, in bioinformatics. In particular, we focus on their applications to three common problems that arise in bioinformatics, that is, feature selection, parameter estimation, and reconstruction of biological networks.

  6. Extending Asia Pacific bioinformatics into new realms in the "-omics" era.

    Science.gov (United States)

    Ranganathan, Shoba; Eisenhaber, Frank; Tong, Joo Chuan; Tan, Tin Wee

    2009-12-03

    The 2009 annual conference of the Asia Pacific Bioinformatics Network (APBioNet), Asia's oldest bioinformatics organisation dating back to 1998, was organized as the 8th International Conference on Bioinformatics (InCoB), Sept. 7-11, 2009 at Biopolis, Singapore. Besides bringing together scientists from the field of bioinformatics in this region, InCoB has actively engaged clinicians and researchers from the area of systems biology, to facilitate greater synergy between these two groups. InCoB2009 followed on from a series of successful annual events in Bangkok (Thailand), Penang (Malaysia), Auckland (New Zealand), Busan (South Korea), New Delhi (India), Hong Kong and Taipei (Taiwan), with InCoB2010 scheduled to be held in Tokyo, Japan, Sept. 26-28, 2010. The Workshop on Education in Bioinformatics and Computational Biology (WEBCB) and symposia on Clinical Bioinformatics (CBAS), the Singapore Symposium on Computational Biology (SYMBIO) and training tutorials were scheduled prior to the scientific meeting, and provided ample opportunity for in-depth learning and special interest meetings for educators, clinicians and students. We provide a brief overview of the peer-reviewed bioinformatics manuscripts accepted for publication in this supplement, grouped into thematic areas. In order to facilitate scientific reproducibility and accountability, we have, for the first time, introduced minimum information criteria for our pubilcations, including compliance to a Minimum Information about a Bioinformatics Investigation (MIABi). As the regional research expertise in bioinformatics matures, we have delineated a minimum set of bioinformatics skills required for addressing the computational challenges of the "-omics" era.

  7. Concepts and introduction to RNA bioinformatics

    DEFF Research Database (Denmark)

    Gorodkin, Jan; Hofacker, Ivo L.; Ruzzo, Walter L.

    2014-01-01

    RNA bioinformatics and computational RNA biology have emerged from implementing methods for predicting the secondary structure of single sequences. The field has evolved to exploit multiple sequences to take evolutionary information into account, such as compensating (and structure preserving) base...... for interactions between RNA and proteins.Here, we introduce the basic concepts of predicting RNA secondary structure relevant to the further analyses of RNA sequences. We also provide pointers to methods addressing various aspects of RNA bioinformatics and computational RNA biology....

  8. Adapting bioinformatics curricula for big data

    Science.gov (United States)

    Greene, Anna C.; Giffin, Kristine A.; Greene, Casey S.

    2016-01-01

    Modern technologies are capable of generating enormous amounts of data that measure complex biological systems. Computational biologists and bioinformatics scientists are increasingly being asked to use these data to reveal key systems-level properties. We review the extent to which curricula are changing in the era of big data. We identify key competencies that scientists dealing with big data are expected to possess across fields, and we use this information to propose courses to meet these growing needs. While bioinformatics programs have traditionally trained students in data-intensive science, we identify areas of particular biological, computational and statistical emphasis important for this era that can be incorporated into existing curricula. For each area, we propose a course structured around these topics, which can be adapted in whole or in parts into existing curricula. In summary, specific challenges associated with big data provide an important opportunity to update existing curricula, but we do not foresee a wholesale redesign of bioinformatics training programs. PMID:25829469

  9. Improvement of the banana "Musa acuminata" reference sequence using NGS data and semi-automated bioinformatics methods

    Czech Academy of Sciences Publication Activity Database

    Martin, G.; Baurens, F.C.; Droc, G.; Rouard, M.; Cenci, A.; Kilian, A.; Hastie, A.; Doležel, Jaroslav; Aury, J. M.; Alberti, A.; Carreel, F.; D'Hont, A.

    2016-01-01

    Roč. 17, MAR 16 (2016), s. 243 ISSN 1471-2164 Institutional support: RVO:61389030 Keywords : Musa acuminata * Genome assembly * Bioinformatics tool Subject RIV: EB - Genetics ; Molecular Biology Impact factor: 3.729, year: 2016

  10. The discovery of the periodic table as a case of simultaneous discovery.

    Science.gov (United States)

    Scerri, Eric

    2015-03-13

    The article examines the question of priority and simultaneous discovery in the context of the discovery of the periodic system. It is argued that rather than being anomalous, simultaneous discovery is the rule. Moreover, I argue that the discovery of the periodic system by at least six authors in over a period of 7 years represents one of the best examples of a multiple discovery. This notion is supported by a new view of the evolutionary development of science through a mechanism that is dubbed Sci-Gaia by analogy with Lovelock's Gaia hypothesis. © 2015 The Author(s) Published by the Royal Society. All rights reserved.

  11. Concepts Of Bioinformatics And Its Application In Veterinary ...

    African Journals Online (AJOL)

    Bioinformatics has advanced the course of research and future veterinary vaccines development because it has provided new tools for identification of vaccine targets from sequenced biological data of organisms. In Nigeria, there is lack of bioinformatics training in the universities, expect for short training courses in which ...

  12. Nanoinformatics: an emerging area of information technology at the intersection of bioinformatics, computational chemistry and nanobiotechnology

    Directory of Open Access Journals (Sweden)

    Fernando González-Nilo

    2011-01-01

    Full Text Available After the progress made during the genomics era, bioinformatics was tasked with supporting the flow of information generated by nanobiotechnology efforts. This challenge requires adapting classical bioinformatic and computational chemistry tools to store, standardize, analyze, and visualize nanobiotechnological information. Thus, old and new bioinformatic and computational chemistry tools have been merged into a new sub-discipline: nanoinformatics. This review takes a second look at the development of this new and exciting area as seen from the perspective of the evolution of nanobiotechnology applied to the life sciences. The knowledge obtained at the nano-scale level implies answers to new questions and the development of new concepts in different fields. The rapid convergence of technologies around nanobiotechnologies has spun off collaborative networks and web platforms created for sharing and discussing the knowledge generated in nanobiotechnology. The implementation of new database schemes suitable for storage, processing and integrating physical, chemical, and biological properties of nanoparticles will be a key element in achieving the promises in this convergent field. In this work, we will review some applications of nanobiotechnology to life sciences in generating new requirements for diverse scientific fields, such as bioinformatics and computational chemistry.

  13. Vertical and Horizontal Integration of Bioinformatics Education: A Modular, Interdisciplinary Approach

    Science.gov (United States)

    Furge, Laura Lowe; Stevens-Truss, Regina; Moore, D. Blaine; Langeland, James A.

    2009-01-01

    Bioinformatics education for undergraduates has been approached primarily in two ways: introduction of new courses with largely bioinformatics focus or introduction of bioinformatics experiences into existing courses. For small colleges such as Kalamazoo, creation of new courses within an already resource-stretched setting has not been an option.…

  14. Adapting bioinformatics curricula for big data.

    Science.gov (United States)

    Greene, Anna C; Giffin, Kristine A; Greene, Casey S; Moore, Jason H

    2016-01-01

    Modern technologies are capable of generating enormous amounts of data that measure complex biological systems. Computational biologists and bioinformatics scientists are increasingly being asked to use these data to reveal key systems-level properties. We review the extent to which curricula are changing in the era of big data. We identify key competencies that scientists dealing with big data are expected to possess across fields, and we use this information to propose courses to meet these growing needs. While bioinformatics programs have traditionally trained students in data-intensive science, we identify areas of particular biological, computational and statistical emphasis important for this era that can be incorporated into existing curricula. For each area, we propose a course structured around these topics, which can be adapted in whole or in parts into existing curricula. In summary, specific challenges associated with big data provide an important opportunity to update existing curricula, but we do not foresee a wholesale redesign of bioinformatics training programs. © The Author 2015. Published by Oxford University Press.

  15. Application of Bioinformatics in Chronobiology Research

    Directory of Open Access Journals (Sweden)

    Robson da Silva Lopes

    2013-01-01

    Full Text Available Bioinformatics and other well-established sciences, such as molecular biology, genetics, and biochemistry, provide a scientific approach for the analysis of data generated through “omics” projects that may be used in studies of chronobiology. The results of studies that apply these techniques demonstrate how they significantly aided the understanding of chronobiology. However, bioinformatics tools alone cannot eliminate the need for an understanding of the field of research or the data to be considered, nor can such tools replace analysts and researchers. It is often necessary to conduct an evaluation of the results of a data mining effort to determine the degree of reliability. To this end, familiarity with the field of investigation is necessary. It is evident that the knowledge that has been accumulated through chronobiology and the use of tools derived from bioinformatics has contributed to the recognition and understanding of the patterns and biological rhythms found in living organisms. The current work aims to develop new and important applications in the near future through chronobiology research.

  16. Computational Lipidomics and Lipid Bioinformatics: Filling In the Blanks.

    Science.gov (United States)

    Pauling, Josch; Klipp, Edda

    2016-12-22

    Lipids are highly diverse metabolites of pronounced importance in health and disease. While metabolomics is a broad field under the omics umbrella that may also relate to lipids, lipidomics is an emerging field which specializes in the identification, quantification and functional interpretation of complex lipidomes. Today, it is possible to identify and distinguish lipids in a high-resolution, high-throughput manner and simultaneously with a lot of structural detail. However, doing so may produce thousands of mass spectra in a single experiment which has created a high demand for specialized computational support to analyze these spectral libraries. The computational biology and bioinformatics community has so far established methodology in genomics, transcriptomics and proteomics but there are many (combinatorial) challenges when it comes to structural diversity of lipids and their identification, quantification and interpretation. This review gives an overview and outlook on lipidomics research and illustrates ongoing computational and bioinformatics efforts. These efforts are important and necessary steps to advance the lipidomics field alongside analytic, biochemistry, biomedical and biology communities and to close the gap in available computational methodology between lipidomics and other omics sub-branches.

  17. Interinstitutional collaboration for end-user bioinformatics training: Cytoscape as a case study

    Directory of Open Access Journals (Sweden)

    Marci D. Brandenburg, MS, MSI

    2017-04-01

    Conclusions: This collaboration furthered the U-M bioinformationist’s role in the field as an expert in Cytoscape instruction, while also establishing the CWML as a leader in providing support for analyzing and visualizing molecular data at Yale University. The authors found this collaboration to be a successful way for librarians to fill end-user training gaps in rapidly changing fields such as bioinformatics.

  18. Skate Genome Project: Cyber-Enabled Bioinformatics Collaboration

    Science.gov (United States)

    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.

  19. 5th HUPO BPP Bioinformatics Meeting at the European Bioinformatics Institute in Hinxton, UK--Setting the analysis frame.

    Science.gov (United States)

    Stephan, Christian; Hamacher, Michael; Blüggel, Martin; Körting, Gerhard; Chamrad, Daniel; Scheer, Christian; Marcus, Katrin; Reidegeld, Kai A; Lohaus, Christiane; Schäfer, Heike; Martens, Lennart; Jones, Philip; Müller, Michael; Auyeung, Kevin; Taylor, Chris; Binz, Pierre-Alain; Thiele, Herbert; Parkinson, David; Meyer, Helmut E; Apweiler, Rolf

    2005-09-01

    The Bioinformatics Committee of the HUPO Brain Proteome Project (HUPO BPP) meets regularly to execute the post-lab analyses of the data produced in the HUPO BPP pilot studies. On July 7, 2005 the members came together for the 5th time at the European Bioinformatics Institute (EBI) in Hinxton, UK, hosted by Rolf Apweiler. As a main result, the parameter set of the semi-automated data re-analysis of MS/MS spectra has been elaborated and the subsequent work steps have been defined.

  20. Evaluating an Inquiry-Based Bioinformatics Course Using Q Methodology

    Science.gov (United States)

    Ramlo, Susan E.; McConnell, David; Duan, Zhong-Hui; Moore, Francisco B.

    2008-01-01

    Faculty at a Midwestern metropolitan public university recently developed a course on bioinformatics that emphasized collaboration and inquiry. Bioinformatics, essentially the application of computational tools to biological data, is inherently interdisciplinary. Thus part of the challenge of creating this course was serving the needs and…

  1. Report on the EMBER Project--A European Multimedia Bioinformatics Educational Resource

    Science.gov (United States)

    Attwood, Terri K.; Selimas, Ioannis; Buis, Rob; Altenburg, Ruud; Herzog, Robert; Ledent, Valerie; Ghita, Viorica; Fernandes, Pedro; Marques, Isabel; Brugman, Marc

    2005-01-01

    EMBER was a European project aiming to develop bioinformatics teaching materials on the Web and CD-ROM to help address the recognised skills shortage in bioinformatics. The project grew out of pilot work on the development of an interactive web-based bioinformatics tutorial and the desire to repackage that resource with the help of a professional…

  2. An Overview of Bioinformatics Tools and Resources in Allergy.

    Science.gov (United States)

    Fu, Zhiyan; Lin, Jing

    2017-01-01

    The rapidly increasing number of characterized allergens has created huge demands for advanced information storage, retrieval, and analysis. Bioinformatics and machine learning approaches provide useful tools for the study of allergens and epitopes prediction, which greatly complement traditional laboratory techniques. The specific applications mainly include identification of B- and T-cell epitopes, and assessment of allergenicity and cross-reactivity. In order to facilitate the work of clinical and basic researchers who are not familiar with bioinformatics, we review in this chapter the most important databases, bioinformatic tools, and methods with relevance to the study of allergens.

  3. RNA Editing and Drug Discovery for Cancer Therapy

    Directory of Open Access Journals (Sweden)

    Wei-Hsuan Huang

    2013-01-01

    Full Text Available RNA editing is vital to provide the RNA and protein complexity to regulate the gene expression. Correct RNA editing maintains the cell function and organism development. Imbalance of the RNA editing machinery may lead to diseases and cancers. Recently, RNA editing has been recognized as a target for drug discovery although few studies targeting RNA editing for disease and cancer therapy were reported in the field of natural products. Therefore, RNA editing may be a potential target for therapeutic natural products. In this review, we provide a literature overview of the biological functions of RNA editing on gene expression, diseases, cancers, and drugs. The bioinformatics resources of RNA editing were also summarized.

  4. Current status and future perspectives of bioinformatics in Tanzania ...

    African Journals Online (AJOL)

    The main bottleneck in advancing genomics in present times is the lack of expertise in using bioinformatics tools and approaches for data mining in raw DNA sequences generated by modern high throughput technologies such as next generation sequencing. Although bioinformatics has been making major progress and ...

  5. Buying in to bioinformatics: an introduction to commercial sequence analysis software.

    Science.gov (United States)

    Smith, David Roy

    2015-07-01

    Advancements in high-throughput nucleotide sequencing techniques have brought with them state-of-the-art bioinformatics programs and software packages. Given the importance of molecular sequence data in contemporary life science research, these software suites are becoming an essential component of many labs and classrooms, and as such are frequently designed for non-computer specialists and marketed as one-stop bioinformatics toolkits. Although beautifully designed and powerful, user-friendly bioinformatics packages can be expensive and, as more arrive on the market each year, it can be difficult for researchers, teachers and students to choose the right software for their needs, especially if they do not have a bioinformatics background. This review highlights some of the currently available and most popular commercial bioinformatics packages, discussing their prices, usability, features and suitability for teaching. Although several commercial bioinformatics programs are arguably overpriced and overhyped, many are well designed, sophisticated and, in my opinion, worth the investment. If you are just beginning your foray into molecular sequence analysis or an experienced genomicist, I encourage you to explore proprietary software bundles. They have the potential to streamline your research, increase your productivity, energize your classroom and, if anything, add a bit of zest to the often dry detached world of bioinformatics. © The Author 2014. Published by Oxford University Press.

  6. Tools and data services registry: a community effort to document bioinformatics resources

    NARCIS (Netherlands)

    Ison, J.; Rapacki, K.; Menager, H.; Kalas, M.; Rydza, E.; Chmura, P.; Anthon, C.; Beard, N.; Berka, K.; Bolser, D.; Booth, T.; Bretaudeau, A.; Brezovsky, J.; Casadio, R.; Cesareni, G.; Coppens, F.; Cornell, M.; Cuccuru, G.; Davidsen, K.; Vedova, G.D.; Dogan, T.; Doppelt-Azeroual, O.; Emery, L.; Gasteiger, E.; Gatter, T.; Goldberg, T.; Grosjean, M.; Gruning, B.; Helmer-Citterich, M.; Ienasescu, H.; Ioannidis, V.; Jespersen, M.C.; Jimenez, R.; Juty, N.; Juvan, P.; Koch, M.; Laibe, C.; Li, J.W.; Licata, L.; Mareuil, F.; Micetic, I.; Friborg, R.M.; Moretti, S.; Morris, C.; Moller, S.; Nenadic, A.; Peterson, H.; Profiti, G.; Rice, P.; Romano, P.; Roncaglia, P.; Saidi, R.; Schafferhans, A.; Schwammle, V.; Smith, C.; Sperotto, M.M.; Stockinger, H.; Varekova, R.S.; Tosatto, S.C.; Torre, V.; Uva, P.; Via, A.; Yachdav, G.; Zambelli, F.; Vriend, G.; Rost, B.; Parkinson, H.; Longreen, P.; Brunak, S.

    2016-01-01

    Life sciences are yielding huge data sets that underpin scientific discoveries fundamental to improvement in human health, agriculture and the environment. In support of these discoveries, a plethora of databases and tools are deployed, in technically complex and diverse implementations, across a

  7. Mathematics and evolutionary biology make bioinformatics education comprehensible

    Science.gov (United States)

    Weisstein, Anton E.

    2013-01-01

    The patterns of variation within a molecular sequence data set result from the interplay between population genetic, molecular evolutionary and macroevolutionary processes—the standard purview of evolutionary biologists. Elucidating these patterns, particularly for large data sets, requires an understanding of the structure, assumptions and limitations of the algorithms used by bioinformatics software—the domain of mathematicians and computer scientists. As a result, bioinformatics often suffers a ‘two-culture’ problem because of the lack of broad overlapping expertise between these two groups. Collaboration among specialists in different fields has greatly mitigated this problem among active bioinformaticians. However, science education researchers report that much of bioinformatics education does little to bridge the cultural divide, the curriculum too focused on solving narrow problems (e.g. interpreting pre-built phylogenetic trees) rather than on exploring broader ones (e.g. exploring alternative phylogenetic strategies for different kinds of data sets). Herein, we present an introduction to the mathematics of tree enumeration, tree construction, split decomposition and sequence alignment. We also introduce off-line downloadable software tools developed by the BioQUEST Curriculum Consortium to help students learn how to interpret and critically evaluate the results of standard bioinformatics analyses. PMID:23821621

  8. Mathematics and evolutionary biology make bioinformatics education comprehensible.

    Science.gov (United States)

    Jungck, John R; Weisstein, Anton E

    2013-09-01

    The patterns of variation within a molecular sequence data set result from the interplay between population genetic, molecular evolutionary and macroevolutionary processes-the standard purview of evolutionary biologists. Elucidating these patterns, particularly for large data sets, requires an understanding of the structure, assumptions and limitations of the algorithms used by bioinformatics software-the domain of mathematicians and computer scientists. As a result, bioinformatics often suffers a 'two-culture' problem because of the lack of broad overlapping expertise between these two groups. Collaboration among specialists in different fields has greatly mitigated this problem among active bioinformaticians. However, science education researchers report that much of bioinformatics education does little to bridge the cultural divide, the curriculum too focused on solving narrow problems (e.g. interpreting pre-built phylogenetic trees) rather than on exploring broader ones (e.g. exploring alternative phylogenetic strategies for different kinds of data sets). Herein, we present an introduction to the mathematics of tree enumeration, tree construction, split decomposition and sequence alignment. We also introduce off-line downloadable software tools developed by the BioQUEST Curriculum Consortium to help students learn how to interpret and critically evaluate the results of standard bioinformatics analyses.

  9. Bioinformatics of cardiovascular miRNA biology.

    Science.gov (United States)

    Kunz, Meik; Xiao, Ke; Liang, Chunguang; Viereck, Janika; Pachel, Christina; Frantz, Stefan; Thum, Thomas; Dandekar, Thomas

    2015-12-01

    MicroRNAs (miRNAs) are small ~22 nucleotide non-coding RNAs and are highly conserved among species. Moreover, miRNAs regulate gene expression of a large number of genes associated with important biological functions and signaling pathways. Recently, several miRNAs have been found to be associated with cardiovascular diseases. Thus, investigating the complex regulatory effect of miRNAs may lead to a better understanding of their functional role in the heart. To achieve this, bioinformatics approaches have to be coupled with validation and screening experiments to understand the complex interactions of miRNAs with the genome. This will boost the subsequent development of diagnostic markers and our understanding of the physiological and therapeutic role of miRNAs in cardiac remodeling. In this review, we focus on and explain different bioinformatics strategies and algorithms for the identification and analysis of miRNAs and their regulatory elements to better understand cardiac miRNA biology. Starting with the biogenesis of miRNAs, we present approaches such as LocARNA and miRBase for combining sequence and structure analysis including phylogenetic comparisons as well as detailed analysis of RNA folding patterns, functional target prediction, signaling pathway as well as functional analysis. We also show how far bioinformatics helps to tackle the unprecedented level of complexity and systemic effects by miRNA, underlining the strong therapeutic potential of miRNA and miRNA target structures in cardiovascular disease. In addition, we discuss drawbacks and limitations of bioinformatics algorithms and the necessity of experimental approaches for miRNA target identification. This article is part of a Special Issue entitled 'Non-coding RNAs'. Copyright © 2014 Elsevier Ltd. All rights reserved.

  10. An innovative approach for testing bioinformatics programs using metamorphic testing

    Directory of Open Access Journals (Sweden)

    Liu Huai

    2009-01-01

    Full Text Available Abstract Background Recent advances in experimental and computational technologies have fueled the development of many sophisticated bioinformatics programs. The correctness of such programs is crucial as incorrectly computed results may lead to wrong biological conclusion or misguide downstream experimentation. Common software testing procedures involve executing the target program with a set of test inputs and then verifying the correctness of the test outputs. However, due to the complexity of many bioinformatics programs, it is often difficult to verify the correctness of the test outputs. Therefore our ability to perform systematic software testing is greatly hindered. Results We propose to use a novel software testing technique, metamorphic testing (MT, to test a range of bioinformatics programs. Instead of requiring a mechanism to verify whether an individual test output is correct, the MT technique verifies whether a pair of test outputs conform to a set of domain specific properties, called metamorphic relations (MRs, thus greatly increases the number and variety of test cases that can be applied. To demonstrate how MT is used in practice, we applied MT to test two open-source bioinformatics programs, namely GNLab and SeqMap. In particular we show that MT is simple to implement, and is effective in detecting faults in a real-life program and some artificially fault-seeded programs. Further, we discuss how MT can be applied to test programs from various domains of bioinformatics. Conclusion This paper describes the application of a simple, effective and automated technique to systematically test a range of bioinformatics programs. We show how MT can be implemented in practice through two real-life case studies. Since many bioinformatics programs, particularly those for large scale simulation and data analysis, are hard to test systematically, their developers may benefit from using MT as part of the testing strategy. Therefore our work

  11. Assessment of a Bioinformatics across Life Science Curricula Initiative

    Science.gov (United States)

    Howard, David R.; Miskowski, Jennifer A.; Grunwald, Sandra K.; Abler, Michael L.

    2007-01-01

    At the University of Wisconsin-La Crosse, we have undertaken a program to integrate the study of bioinformatics across the undergraduate life science curricula. Our efforts have included incorporating bioinformatics exercises into courses in the biology, microbiology, and chemistry departments, as well as coordinating the efforts of faculty within…

  12. EDAM: an ontology of bioinformatics operations, types of data and identifiers, topics and formats

    Science.gov (United States)

    Ison, Jon; Kalaš, Matúš; Jonassen, Inge; Bolser, Dan; Uludag, Mahmut; McWilliam, Hamish; Malone, James; Lopez, Rodrigo; Pettifer, Steve; Rice, Peter

    2013-01-01

    Motivation: Advancing the search, publication and integration of bioinformatics tools and resources demands consistent machine-understandable descriptions. A comprehensive ontology allowing such descriptions is therefore required. Results: EDAM is an ontology of bioinformatics operations (tool or workflow functions), types of data and identifiers, application domains and data formats. EDAM supports semantic annotation of diverse entities such as Web services, databases, programmatic libraries, standalone tools, interactive applications, data schemas, datasets and publications within bioinformatics. EDAM applies to organizing and finding suitable tools and data and to automating their integration into complex applications or workflows. It includes over 2200 defined concepts and has successfully been used for annotations and implementations. Availability: The latest stable version of EDAM is available in OWL format from http://edamontology.org/EDAM.owl and in OBO format from http://edamontology.org/EDAM.obo. It can be viewed online at the NCBO BioPortal and the EBI Ontology Lookup Service. For documentation and license please refer to http://edamontology.org. This article describes version 1.2 available at http://edamontology.org/EDAM_1.2.owl. Contact: jison@ebi.ac.uk PMID:23479348

  13. A collaborative filtering-based approach to biomedical knowledge discovery.

    Science.gov (United States)

    Lever, Jake; Gakkhar, Sitanshu; Gottlieb, Michael; Rashnavadi, Tahereh; Lin, Santina; Siu, Celia; Smith, Maia; Jones, Martin R; Krzywinski, Martin; Jones, Steven J M; Wren, Jonathan

    2018-02-15

    The increase in publication rates makes it challenging for an individual researcher to stay abreast of all relevant research in order to find novel research hypotheses. Literature-based discovery methods make use of knowledge graphs built using text mining and can infer future associations between biomedical concepts that will likely occur in new publications. These predictions are a valuable resource for researchers to explore a research topic. Current methods for prediction are based on the local structure of the knowledge graph. A method that uses global knowledge from across the knowledge graph needs to be developed in order to make knowledge discovery a frequently used tool by researchers. We propose an approach based on the singular value decomposition (SVD) that is able to combine data from across the knowledge graph through a reduced representation. Using cooccurrence data extracted from published literature, we show that SVD performs better than the leading methods for scoring discoveries. We also show the diminishing predictive power of knowledge discovery as we compare our predictions with real associations that appear further into the future. Finally, we examine the strengths and weaknesses of the SVD approach against another well-performing system using several predicted associations. All code and results files for this analysis can be accessed at https://github.com/jakelever/knowledgediscovery. sjones@bcgsc.ca. Supplementary data are available at Bioinformatics online. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com

  14. The Semantic Automated Discovery and Integration (SADI Web service Design-Pattern, API and Reference Implementation

    Directory of Open Access Journals (Sweden)

    Wilkinson Mark D

    2011-10-01

    Full Text Available Abstract Background The complexity and inter-related nature of biological data poses a difficult challenge for data and tool integration. There has been a proliferation of interoperability standards and projects over the past decade, none of which has been widely adopted by the bioinformatics community. Recent attempts have focused on the use of semantics to assist integration, and Semantic Web technologies are being welcomed by this community. Description SADI - Semantic Automated Discovery and Integration - is a lightweight set of fully standards-compliant Semantic Web service design patterns that simplify the publication of services of the type commonly found in bioinformatics and other scientific domains. Using Semantic Web technologies at every level of the Web services "stack", SADI services consume and produce instances of OWL Classes following a small number of very straightforward best-practices. In addition, we provide codebases that support these best-practices, and plug-in tools to popular developer and client software that dramatically simplify deployment of services by providers, and the discovery and utilization of those services by their consumers. Conclusions SADI Services are fully compliant with, and utilize only foundational Web standards; are simple to create and maintain for service providers; and can be discovered and utilized in a very intuitive way by biologist end-users. In addition, the SADI design patterns significantly improve the ability of software to automatically discover appropriate services based on user-needs, and automatically chain these into complex analytical workflows. We show that, when resources are exposed through SADI, data compliant with a given ontological model can be automatically gathered, or generated, from these distributed, non-coordinating resources - a behaviour we have not observed in any other Semantic system. Finally, we show that, using SADI, data dynamically generated from Web services

  15. The Semantic Automated Discovery and Integration (SADI) Web service Design-Pattern, API and Reference Implementation

    Science.gov (United States)

    2011-01-01

    Background The complexity and inter-related nature of biological data poses a difficult challenge for data and tool integration. There has been a proliferation of interoperability standards and projects over the past decade, none of which has been widely adopted by the bioinformatics community. Recent attempts have focused on the use of semantics to assist integration, and Semantic Web technologies are being welcomed by this community. Description SADI - Semantic Automated Discovery and Integration - is a lightweight set of fully standards-compliant Semantic Web service design patterns that simplify the publication of services of the type commonly found in bioinformatics and other scientific domains. Using Semantic Web technologies at every level of the Web services "stack", SADI services consume and produce instances of OWL Classes following a small number of very straightforward best-practices. In addition, we provide codebases that support these best-practices, and plug-in tools to popular developer and client software that dramatically simplify deployment of services by providers, and the discovery and utilization of those services by their consumers. Conclusions SADI Services are fully compliant with, and utilize only foundational Web standards; are simple to create and maintain for service providers; and can be discovered and utilized in a very intuitive way by biologist end-users. In addition, the SADI design patterns significantly improve the ability of software to automatically discover appropriate services based on user-needs, and automatically chain these into complex analytical workflows. We show that, when resources are exposed through SADI, data compliant with a given ontological model can be automatically gathered, or generated, from these distributed, non-coordinating resources - a behaviour we have not observed in any other Semantic system. Finally, we show that, using SADI, data dynamically generated from Web services can be explored in a manner

  16. The Semantic Automated Discovery and Integration (SADI) Web service Design-Pattern, API and Reference Implementation.

    Science.gov (United States)

    Wilkinson, Mark D; Vandervalk, Benjamin; McCarthy, Luke

    2011-10-24

    The complexity and inter-related nature of biological data poses a difficult challenge for data and tool integration. There has been a proliferation of interoperability standards and projects over the past decade, none of which has been widely adopted by the bioinformatics community. Recent attempts have focused on the use of semantics to assist integration, and Semantic Web technologies are being welcomed by this community. SADI - Semantic Automated Discovery and Integration - is a lightweight set of fully standards-compliant Semantic Web service design patterns that simplify the publication of services of the type commonly found in bioinformatics and other scientific domains. Using Semantic Web technologies at every level of the Web services "stack", SADI services consume and produce instances of OWL Classes following a small number of very straightforward best-practices. In addition, we provide codebases that support these best-practices, and plug-in tools to popular developer and client software that dramatically simplify deployment of services by providers, and the discovery and utilization of those services by their consumers. SADI Services are fully compliant with, and utilize only foundational Web standards; are simple to create and maintain for service providers; and can be discovered and utilized in a very intuitive way by biologist end-users. In addition, the SADI design patterns significantly improve the ability of software to automatically discover appropriate services based on user-needs, and automatically chain these into complex analytical workflows. We show that, when resources are exposed through SADI, data compliant with a given ontological model can be automatically gathered, or generated, from these distributed, non-coordinating resources - a behaviour we have not observed in any other Semantic system. Finally, we show that, using SADI, data dynamically generated from Web services can be explored in a manner very similar to data housed in

  17. AuScope research infrastructure - supporting Australian mineral discovery

    Science.gov (United States)

    McInnes, B.; Rawling, T.

    2016-12-01

    issue for pinpointing where the next major mineral deposits are. Having solid baseline data will help improve targeting, which in turn reduces the costs associated with exploration and supports new discovery.

  18. Effective Online Group Discovery in Trajectory Databases

    DEFF Research Database (Denmark)

    Li, Xiaohui; Ceikute, Vaida; Jensen, Christian S.

    2013-01-01

    GPS-enabled devices are pervasive nowadays. Finding movement patterns in trajectory data stream is gaining in importance. We propose a group discovery framework that aims to efficiently support the online discovery of moving objects that travel together. The framework adopts a sampling-independen......GPS-enabled devices are pervasive nowadays. Finding movement patterns in trajectory data stream is gaining in importance. We propose a group discovery framework that aims to efficiently support the online discovery of moving objects that travel together. The framework adopts a sampling......-independent approach that makes no assumptions about when positions are sampled, gives no special importance to sampling points, and naturally supports the use of approximate trajectories. The framework's algorithms exploit state-of-the-art, density-based clustering (DBScan) to identify groups. The groups are scored...

  19. Comprehensive decision tree models in bioinformatics.

    Directory of Open Access Journals (Sweden)

    Gregor Stiglic

    Full Text Available PURPOSE: Classification is an important and widely used machine learning technique in bioinformatics. Researchers and other end-users of machine learning software often prefer to work with comprehensible models where knowledge extraction and explanation of reasoning behind the classification model are possible. METHODS: This paper presents an extension to an existing machine learning environment and a study on visual tuning of decision tree classifiers. The motivation for this research comes from the need to build effective and easily interpretable decision tree models by so called one-button data mining approach where no parameter tuning is needed. To avoid bias in classification, no classification performance measure is used during the tuning of the model that is constrained exclusively by the dimensions of the produced decision tree. RESULTS: The proposed visual tuning of decision trees was evaluated on 40 datasets containing classical machine learning problems and 31 datasets from the field of bioinformatics. Although we did not expected significant differences in classification performance, the results demonstrate a significant increase of accuracy in less complex visually tuned decision trees. In contrast to classical machine learning benchmarking datasets, we observe higher accuracy gains in bioinformatics datasets. Additionally, a user study was carried out to confirm the assumption that the tree tuning times are significantly lower for the proposed method in comparison to manual tuning of the decision tree. CONCLUSIONS: The empirical results demonstrate that by building simple models constrained by predefined visual boundaries, one not only achieves good comprehensibility, but also very good classification performance that does not differ from usually more complex models built using default settings of the classical decision tree algorithm. In addition, our study demonstrates the suitability of visually tuned decision trees for datasets

  20. Comprehensive decision tree models in bioinformatics.

    Science.gov (United States)

    Stiglic, Gregor; Kocbek, Simon; Pernek, Igor; Kokol, Peter

    2012-01-01

    Classification is an important and widely used machine learning technique in bioinformatics. Researchers and other end-users of machine learning software often prefer to work with comprehensible models where knowledge extraction and explanation of reasoning behind the classification model are possible. This paper presents an extension to an existing machine learning environment and a study on visual tuning of decision tree classifiers. The motivation for this research comes from the need to build effective and easily interpretable decision tree models by so called one-button data mining approach where no parameter tuning is needed. To avoid bias in classification, no classification performance measure is used during the tuning of the model that is constrained exclusively by the dimensions of the produced decision tree. The proposed visual tuning of decision trees was evaluated on 40 datasets containing classical machine learning problems and 31 datasets from the field of bioinformatics. Although we did not expected significant differences in classification performance, the results demonstrate a significant increase of accuracy in less complex visually tuned decision trees. In contrast to classical machine learning benchmarking datasets, we observe higher accuracy gains in bioinformatics datasets. Additionally, a user study was carried out to confirm the assumption that the tree tuning times are significantly lower for the proposed method in comparison to manual tuning of the decision tree. The empirical results demonstrate that by building simple models constrained by predefined visual boundaries, one not only achieves good comprehensibility, but also very good classification performance that does not differ from usually more complex models built using default settings of the classical decision tree algorithm. In addition, our study demonstrates the suitability of visually tuned decision trees for datasets with binary class attributes and a high number of possibly

  1. When process mining meets bioinformatics

    NARCIS (Netherlands)

    Jagadeesh Chandra Bose, R.P.; Aalst, van der W.M.P.; Nurcan, S.

    2011-01-01

    Process mining techniques can be used to extract non-trivial process related knowledge and thus generate interesting insights from event logs. Similarly, bioinformatics aims at increasing the understanding of biological processes through the analysis of information associated with biological

  2. 9th International Conference on Practical Applications of Computational Biology and Bioinformatics

    CERN Document Server

    Rocha, Miguel; Fdez-Riverola, Florentino; Paz, Juan

    2015-01-01

    This proceedings presents recent practical applications of Computational Biology and  Bioinformatics. It contains the proceedings of the 9th International Conference on Practical Applications of Computational Biology & Bioinformatics held at University of Salamanca, Spain, at June 3rd-5th, 2015. The International Conference on Practical Applications of Computational Biology & Bioinformatics (PACBB) is an annual international meeting dedicated to emerging and challenging applied research in Bioinformatics and Computational Biology. Biological and biomedical research are increasingly driven by experimental techniques that challenge our ability to analyse, process and extract meaningful knowledge from the underlying data. The impressive capabilities of next generation sequencing technologies, together with novel and ever evolving distinct types of omics data technologies, have put an increasingly complex set of challenges for the growing fields of Bioinformatics and Computational Biology. The analysis o...

  3. Bioconductor: open software development for computational biology and bioinformatics

    DEFF Research Database (Denmark)

    Gentleman, R.C.; Carey, V.J.; Bates, D.M.

    2004-01-01

    The Bioconductor project is an initiative for the collaborative creation of extensible software for computational biology and bioinformatics. The goals of the project include: fostering collaborative development and widespread use of innovative software, reducing barriers to entry into interdisci......The Bioconductor project is an initiative for the collaborative creation of extensible software for computational biology and bioinformatics. The goals of the project include: fostering collaborative development and widespread use of innovative software, reducing barriers to entry...... into interdisciplinary scientific research, and promoting the achievement of remote reproducibility of research results. We describe details of our aims and methods, identify current challenges, compare Bioconductor to other open bioinformatics projects, and provide working examples....

  4. Peer Mentoring for Bioinformatics presentation

    OpenAIRE

    Budd, Aidan

    2014-01-01

    A handout used in a HUB (Heidelberg Unseminars in Bioinformatics) meeting focused on career development for bioinformaticians. It describes an activity for use to help introduce the idea of peer mentoring, potnetially acting as an opportunity to create peer-mentoring groups.

  5. PubData: search engine for bioinformatics databases worldwide

    OpenAIRE

    Vand, Kasra; Wahlestedt, Thor; Khomtchouk, Kelly; Sayed, Mohammed; Wahlestedt, Claes; Khomtchouk, Bohdan

    2016-01-01

    We propose a search engine and file retrieval system for all bioinformatics databases worldwide. PubData searches biomedical data in a user-friendly fashion similar to how PubMed searches biomedical literature. PubData is built on novel network programming, natural language processing, and artificial intelligence algorithms that can patch into the file transfer protocol servers of any user-specified bioinformatics database, query its contents, retrieve files for download, and adapt to the use...

  6. Bioinformatics and its application in animal health: a review | Soetan ...

    African Journals Online (AJOL)

    Bioinformatics is an interdisciplinary subject, which uses computer application, statistics, mathematics and engineering for the analysis and management of biological information. It has become an important tool for basic and applied research in veterinary sciences. Bioinformatics has brought about advancements into ...

  7. Assessment of Data Reliability of Wireless Sensor Network for Bioinformatics

    Directory of Open Access Journals (Sweden)

    Ting Dong

    2017-09-01

    Full Text Available As a focal point of biotechnology, bioinformatics integrates knowledge from biology, mathematics, physics, chemistry, computer science and information science. It generally deals with genome informatics, protein structure and drug design. However, the data or information thus acquired from the main areas of bioinformatics may not be effective. Some researchers combined bioinformatics with wireless sensor network (WSN into biosensor and other tools, and applied them to such areas as fermentation, environmental monitoring, food engineering, clinical medicine and military. In the combination, the WSN is used to collect data and information. The reliability of the WSN in bioinformatics is the prerequisite to effective utilization of information. It is greatly influenced by factors like quality, benefits, service, timeliness and stability, some of them are qualitative and some are quantitative. Hence, it is necessary to develop a method that can handle both qualitative and quantitative assessment of information. A viable option is the fuzzy linguistic method, especially 2-tuple linguistic model, which has been extensively used to cope with such issues. As a result, this paper introduces 2-tuple linguistic representation to assist experts in giving their opinions on different WSNs in bioinformatics that involve multiple factors. Moreover, the author proposes a novel way to determine attribute weights and uses the method to weigh the relative importance of different influencing factors which can be considered as attributes in the assessment of the WSN in bioinformatics. Finally, an illustrative example is given to provide a reasonable solution for the assessment.

  8. Reproducible Bioinformatics Research for Biologists

    Science.gov (United States)

    This book chapter describes the current Big Data problem in Bioinformatics and the resulting issues with performing reproducible computational research. The core of the chapter provides guidelines and summaries of current tools/techniques that a noncomputational researcher would need to learn to pe...

  9. Bioinformatics of genomic association mapping

    NARCIS (Netherlands)

    Vaez Barzani, Ahmad

    2015-01-01

    In this thesis we present an overview of bioinformatics-based approaches for genomic association mapping, with emphasis on human quantitative traits and their contribution to complex diseases. We aim to provide a comprehensive walk-through of the classic steps of genomic association mapping

  10. Bioinformatic tools for PCR Primer design

    African Journals Online (AJOL)

    ES

    Bioinformatics is an emerging scientific discipline that uses information ... complex biological questions. ... and computer programs for various purposes of primer ..... polymerase chain reaction: Human Immunodeficiency Virus 1 model studies.

  11. Generative Topic Modeling in Image Data Mining and Bioinformatics Studies

    Science.gov (United States)

    Chen, Xin

    2012-01-01

    Probabilistic topic models have been developed for applications in various domains such as text mining, information retrieval and computer vision and bioinformatics domain. In this thesis, we focus on developing novel probabilistic topic models for image mining and bioinformatics studies. Specifically, a probabilistic topic-connection (PTC) model…

  12. Taking Bioinformatics to Systems Medicine

    NARCIS (Netherlands)

    van Kampen, Antoine H. C.; Moerland, Perry D.

    2016-01-01

    Systems medicine promotes a range of approaches and strategies to study human health and disease at a systems level with the aim of improving the overall well-being of (healthy) individuals, and preventing, diagnosing, or curing disease. In this chapter we discuss how bioinformatics critically

  13. Metagenomics and Bioinformatics in Microbial Ecology: Current Status and Beyond.

    Science.gov (United States)

    Hiraoka, Satoshi; Yang, Ching-Chia; Iwasaki, Wataru

    2016-09-29

    Metagenomic approaches are now commonly used in microbial ecology to study microbial communities in more detail, including many strains that cannot be cultivated in the laboratory. Bioinformatic analyses make it possible to mine huge metagenomic datasets and discover general patterns that govern microbial ecosystems. However, the findings of typical metagenomic and bioinformatic analyses still do not completely describe the ecology and evolution of microbes in their environments. Most analyses still depend on straightforward sequence similarity searches against reference databases. We herein review the current state of metagenomics and bioinformatics in microbial ecology and discuss future directions for the field. New techniques will allow us to go beyond routine analyses and broaden our knowledge of microbial ecosystems. We need to enrich reference databases, promote platforms that enable meta- or comprehensive analyses of diverse metagenomic datasets, devise methods that utilize long-read sequence information, and develop more powerful bioinformatic methods to analyze data from diverse perspectives.

  14. Best practices in bioinformatics training for life scientists

    DEFF Research Database (Denmark)

    Via, Allegra; Blicher, Thomas; Bongcam-Rudloff, Erik

    2013-01-01

    their data efficiently, and progress their research, is a challenge across the globe. Delivering good training goes beyond traditional lectures and resource-centric demos, using interactivity, problem-solving exercises and cooperative learning to substantially enhance training quality and learning outcomes...... to environmental researchers, a common theme is the need not just to use, and gain familiarity with, bioinformatics tools and resources but also to understand their underlying fundamental theoretical and practical concepts. Providing bioinformatics training to empower life scientists to handle and analyse...

  15. Teaching Bioinformatics and Neuroinformatics by Using Free Web-Based Tools

    Science.gov (United States)

    Grisham, William; Schottler, Natalie A.; Valli-Marill, Joanne; Beck, Lisa; Beatty, Jackson

    2010-01-01

    This completely computer-based module's purpose is to introduce students to bioinformatics resources. We present an easy-to-adopt module that weaves together several important bioinformatic tools so students can grasp how these tools are used in answering research questions. Students integrate information gathered from websites dealing with…

  16. Bioinformatics and the Undergraduate Curriculum

    Science.gov (United States)

    Maloney, Mark; Parker, Jeffrey; LeBlanc, Mark; Woodard, Craig T.; Glackin, Mary; Hanrahan, Michael

    2010-01-01

    Recent advances involving high-throughput techniques for data generation and analysis have made familiarity with basic bioinformatics concepts and programs a necessity in the biological sciences. Undergraduate students increasingly need training in methods related to finding and retrieving information stored in vast databases. The rapid rise of…

  17. Bringing Web 2.0 to bioinformatics.

    Science.gov (United States)

    Zhang, Zhang; Cheung, Kei-Hoi; Townsend, Jeffrey P

    2009-01-01

    Enabling deft data integration from numerous, voluminous and heterogeneous data sources is a major bioinformatic challenge. Several approaches have been proposed to address this challenge, including data warehousing and federated databasing. Yet despite the rise of these approaches, integration of data from multiple sources remains problematic and toilsome. These two approaches follow a user-to-computer communication model for data exchange, and do not facilitate a broader concept of data sharing or collaboration among users. In this report, we discuss the potential of Web 2.0 technologies to transcend this model and enhance bioinformatics research. We propose a Web 2.0-based Scientific Social Community (SSC) model for the implementation of these technologies. By establishing a social, collective and collaborative platform for data creation, sharing and integration, we promote a web services-based pipeline featuring web services for computer-to-computer data exchange as users add value. This pipeline aims to simplify data integration and creation, to realize automatic analysis, and to facilitate reuse and sharing of data. SSC can foster collaboration and harness collective intelligence to create and discover new knowledge. In addition to its research potential, we also describe its potential role as an e-learning platform in education. We discuss lessons from information technology, predict the next generation of Web (Web 3.0), and describe its potential impact on the future of bioinformatics studies.

  18. Shared Bioinformatics Databases within the Unipro UGENE Platform

    Directory of Open Access Journals (Sweden)

    Protsyuk Ivan V.

    2015-03-01

    Full Text Available Unipro UGENE is an open-source bioinformatics toolkit that integrates popular tools along with original instruments for molecular biologists within a unified user interface. Nowadays, most bioinformatics desktop applications, including UGENE, make use of a local data model while processing different types of data. Such an approach causes an inconvenience for scientists working cooperatively and relying on the same data. This refers to the need of making multiple copies of certain files for every workplace and maintaining synchronization between them in case of modifications. Therefore, we focused on delivering a collaborative work into the UGENE user experience. Currently, several UGENE installations can be connected to a designated shared database and users can interact with it simultaneously. Such databases can be created by UGENE users and be used at their discretion. Objects of each data type, supported by UGENE such as sequences, annotations, multiple alignments, etc., can now be easily imported from or exported to a remote storage. One of the main advantages of this system, compared to existing ones, is the almost simultaneous access of client applications to shared data regardless of their volume. Moreover, the system is capable of storing millions of objects. The storage itself is a regular database server so even an inexpert user is able to deploy it. Thus, UGENE may provide access to shared data for users located, for example, in the same laboratory or institution. UGENE is available at: http://ugene.net/download.html.

  19. Cloud Storage and Bioinformatics in a private cloud deployment: Lessons for Data Intensive research

    OpenAIRE

    Chang, Victor; Walters, Robert John; Wills, Gary

    2013-01-01

    This paper describes service portability for a private cloud deployment, including a detailed case study about Cloud Storage and bioinformatics services developed as part of the Cloud Computing Adoption Framework (CCAF). Our Cloud Storage design and deployment is based on Storage Area Network (SAN) technologies, details of which include functionalities, technical implementation, architecture and user support. Experiments for data services (backup automation, data recovery and data migration) ...

  20. Bioinformatics on the Cloud Computing Platform Azure

    Science.gov (United States)

    Shanahan, Hugh P.; Owen, Anne M.; Harrison, Andrew P.

    2014-01-01

    We discuss the applicability of the Microsoft cloud computing platform, Azure, for bioinformatics. We focus on the usability of the resource rather than its performance. We provide an example of how R can be used on Azure to analyse a large amount of microarray expression data deposited at the public database ArrayExpress. We provide a walk through to demonstrate explicitly how Azure can be used to perform these analyses in Appendix S1 and we offer a comparison with a local computation. We note that the use of the Platform as a Service (PaaS) offering of Azure can represent a steep learning curve for bioinformatics developers who will usually have a Linux and scripting language background. On the other hand, the presence of an additional set of libraries makes it easier to deploy software in a parallel (scalable) fashion and explicitly manage such a production run with only a few hundred lines of code, most of which can be incorporated from a template. We propose that this environment is best suited for running stable bioinformatics software by users not involved with its development. PMID:25050811

  1. A bioinformatics roadmap for the human vaccines project.

    Science.gov (United States)

    Scheuermann, Richard H; Sinkovits, Robert S; Schenkelberg, Theodore; Koff, Wayne C

    2017-06-01

    Biomedical research has become a data intensive science in which high throughput experimentation is producing comprehensive data about biological systems at an ever-increasing pace. The Human Vaccines Project is a new public-private partnership, with the goal of accelerating development of improved vaccines and immunotherapies for global infectious diseases and cancers by decoding the human immune system. To achieve its mission, the Project is developing a Bioinformatics Hub as an open-source, multidisciplinary effort with the overarching goal of providing an enabling infrastructure to support the data processing, analysis and knowledge extraction procedures required to translate high throughput, high complexity human immunology research data into biomedical knowledge, to determine the core principles driving specific and durable protective immune responses.

  2. Fundamentals of bioinformatics and computational biology methods and exercises in matlab

    CERN Document Server

    Singh, Gautam B

    2015-01-01

    This book offers comprehensive coverage of all the core topics of bioinformatics, and includes practical examples completed using the MATLAB bioinformatics toolbox™. It is primarily intended as a textbook for engineering and computer science students attending advanced undergraduate and graduate courses in bioinformatics and computational biology. The book develops bioinformatics concepts from the ground up, starting with an introductory chapter on molecular biology and genetics. This chapter will enable physical science students to fully understand and appreciate the ultimate goals of applying the principles of information technology to challenges in biological data management, sequence analysis, and systems biology. The first part of the book also includes a survey of existing biological databases, tools that have become essential in today’s biotechnology research. The second part of the book covers methodologies for retrieving biological information, including fundamental algorithms for sequence compar...

  3. BioRuby: bioinformatics software for the Ruby programming language.

    Science.gov (United States)

    Goto, Naohisa; Prins, Pjotr; Nakao, Mitsuteru; Bonnal, Raoul; Aerts, Jan; Katayama, Toshiaki

    2010-10-15

    The BioRuby software toolkit contains a comprehensive set of free development tools and libraries for bioinformatics and molecular biology, written in the Ruby programming language. BioRuby has components for sequence analysis, pathway analysis, protein modelling and phylogenetic analysis; it supports many widely used data formats and provides easy access to databases, external programs and public web services, including BLAST, KEGG, GenBank, MEDLINE and GO. BioRuby comes with a tutorial, documentation and an interactive environment, which can be used in the shell, and in the web browser. BioRuby is free and open source software, made available under the Ruby license. BioRuby runs on all platforms that support Ruby, including Linux, Mac OS X and Windows. And, with JRuby, BioRuby runs on the Java Virtual Machine. The source code is available from http://www.bioruby.org/. katayama@bioruby.org

  4. Bioinformatics Methods for Interpreting Toxicogenomics Data: The Role of Text-Mining

    NARCIS (Netherlands)

    Hettne, K.M.; Kleinjans, J.; Stierum, R.H.; Boorsma, A.; Kors, J.A.

    2014-01-01

    This chapter concerns the application of bioinformatics methods to the analysis of toxicogenomics data. The chapter starts with an introduction covering how bioinformatics has been applied in toxicogenomics data analysis, and continues with a description of the foundations of a specific

  5. BioStar: an online question & answer resource for the bioinformatics community

    Science.gov (United States)

    Although the era of big data has produced many bioinformatics tools and databases, using them effectively often requires specialized knowledge. Many groups lack bioinformatics expertise, and frequently find that software documentation is inadequate and local colleagues may be overburdened or unfamil...

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

    Science.gov (United States)

    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…

  7. Systems Bioinformatics: increasing precision of computational diagnostics and therapeutics through network-based approaches.

    Science.gov (United States)

    Oulas, Anastasis; Minadakis, George; Zachariou, Margarita; Sokratous, Kleitos; Bourdakou, Marilena M; Spyrou, George M

    2017-11-27

    Systems Bioinformatics is a relatively new approach, which lies in the intersection of systems biology and classical bioinformatics. It focuses on integrating information across different levels using a bottom-up approach as in systems biology with a data-driven top-down approach as in bioinformatics. The advent of omics technologies has provided the stepping-stone for the emergence of Systems Bioinformatics. These technologies provide a spectrum of information ranging from genomics, transcriptomics and proteomics to epigenomics, pharmacogenomics, metagenomics and metabolomics. Systems Bioinformatics is the framework in which systems approaches are applied to such data, setting the level of resolution as well as the boundary of the system of interest and studying the emerging properties of the system as a whole rather than the sum of the properties derived from the system's individual components. A key approach in Systems Bioinformatics is the construction of multiple networks representing each level of the omics spectrum and their integration in a layered network that exchanges information within and between layers. Here, we provide evidence on how Systems Bioinformatics enhances computational therapeutics and diagnostics, hence paving the way to precision medicine. The aim of this review is to familiarize the reader with the emerging field of Systems Bioinformatics and to provide a comprehensive overview of its current state-of-the-art methods and technologies. Moreover, we provide examples of success stories and case studies that utilize such methods and tools to significantly advance research in the fields of systems biology and systems medicine. © The Author 2017. Published by Oxford University Press.

  8. Ergatis: a web interface and scalable software system for bioinformatics workflows

    Science.gov (United States)

    Orvis, Joshua; Crabtree, Jonathan; Galens, Kevin; Gussman, Aaron; Inman, Jason M.; Lee, Eduardo; Nampally, Sreenath; Riley, David; Sundaram, Jaideep P.; Felix, Victor; Whitty, Brett; Mahurkar, Anup; Wortman, Jennifer; White, Owen; Angiuoli, Samuel V.

    2010-01-01

    Motivation: The growth of sequence data has been accompanied by an increasing need to analyze data on distributed computer clusters. The use of these systems for routine analysis requires scalable and robust software for data management of large datasets. Software is also needed to simplify data management and make large-scale bioinformatics analysis accessible and reproducible to a wide class of target users. Results: We have developed a workflow management system named Ergatis that enables users to build, execute and monitor pipelines for computational analysis of genomics data. Ergatis contains preconfigured components and template pipelines for a number of common bioinformatics tasks such as prokaryotic genome annotation and genome comparisons. Outputs from many of these components can be loaded into a Chado relational database. Ergatis was designed to be accessible to a broad class of users and provides a user friendly, web-based interface. Ergatis supports high-throughput batch processing on distributed compute clusters and has been used for data management in a number of genome annotation and comparative genomics projects. Availability: Ergatis is an open-source project and is freely available at http://ergatis.sourceforge.net Contact: jorvis@users.sourceforge.net PMID:20413634

  9. clubber: removing the bioinformatics bottleneck in big data analyses

    Science.gov (United States)

    Miller, Maximilian; Zhu, Chengsheng; Bromberg, Yana

    2018-01-01

    With the advent of modern day high-throughput technologies, the bottleneck in biological discovery has shifted from the cost of doing experiments to that of analyzing results. clubber is our automated cluster-load balancing system developed for optimizing these “big data” analyses. Its plug-and-play framework encourages re-use of existing solutions for bioinformatics problems. clubber’s goals are to reduce computation times and to facilitate use of cluster computing. The first goal is achieved by automating the balance of parallel submissions across available high performance computing (HPC) resources. Notably, the latter can be added on demand, including cloud-based resources, and/or featuring heterogeneous environments. The second goal of making HPCs user-friendly is facilitated by an interactive web interface and a RESTful API, allowing for job monitoring and result retrieval. We used clubber to speed up our pipeline for annotating molecular functionality of metagenomes. Here, we analyzed the Deepwater Horizon oil-spill study data to quantitatively show that the beach sands have not yet entirely recovered. Further, our analysis of the CAMI-challenge data revealed that microbiome taxonomic shifts do not necessarily correlate with functional shifts. These examples (21 metagenomes processed in 172 min) clearly illustrate the importance of clubber in the everyday computational biology environment. PMID:28609295

  10. clubber: removing the bioinformatics bottleneck in big data analyses.

    Science.gov (United States)

    Miller, Maximilian; Zhu, Chengsheng; Bromberg, Yana

    2017-06-13

    With the advent of modern day high-throughput technologies, the bottleneck in biological discovery has shifted from the cost of doing experiments to that of analyzing results. clubber is our automated cluster-load balancing system developed for optimizing these "big data" analyses. Its plug-and-play framework encourages re-use of existing solutions for bioinformatics problems. clubber's goals are to reduce computation times and to facilitate use of cluster computing. The first goal is achieved by automating the balance of parallel submissions across available high performance computing (HPC) resources. Notably, the latter can be added on demand, including cloud-based resources, and/or featuring heterogeneous environments. The second goal of making HPCs user-friendly is facilitated by an interactive web interface and a RESTful API, allowing for job monitoring and result retrieval. We used clubber to speed up our pipeline for annotating molecular functionality of metagenomes. Here, we analyzed the Deepwater Horizon oil-spill study data to quantitatively show that the beach sands have not yet entirely recovered. Further, our analysis of the CAMI-challenge data revealed that microbiome taxonomic shifts do not necessarily correlate with functional shifts. These examples (21 metagenomes processed in 172 min) clearly illustrate the importance of clubber in the everyday computational biology environment.

  11. clubber: removing the bioinformatics bottleneck in big data analyses

    Directory of Open Access Journals (Sweden)

    Miller Maximilian

    2017-06-01

    Full Text Available With the advent of modern day high-throughput technologies, the bottleneck in biological discovery has shifted from the cost of doing experiments to that of analyzing results. clubber is our automated cluster-load balancing system developed for optimizing these “big data” analyses. Its plug-and-play framework encourages re-use of existing solutions for bioinformatics problems. clubber’s goals are to reduce computation times and to facilitate use of cluster computing. The first goal is achieved by automating the balance of parallel submissions across available high performance computing (HPC resources. Notably, the latter can be added on demand, including cloud-based resources, and/or featuring heterogeneous environments. The second goal of making HPCs user-friendly is facilitated by an interactive web interface and a RESTful API, allowing for job monitoring and result retrieval. We used clubber to speed up our pipeline for annotating molecular functionality of metagenomes. Here, we analyzed the Deepwater Horizon oil-spill study data to quantitatively show that the beach sands have not yet entirely recovered. Further, our analysis of the CAMI-challenge data revealed that microbiome taxonomic shifts do not necessarily correlate with functional shifts. These examples (21 metagenomes processed in 172 min clearly illustrate the importance of clubber in the everyday computational biology environment.

  12. Discovery of novel algae-degrading enzymes from marine bacteria

    DEFF Research Database (Denmark)

    Schultz-Johansen, Mikkel; Bech, Pernille Kjersgaard; Hennessy, Rosanna Catherine

    Algal cell wall polysaccharides, and their derived oligosaccharides, display a range of health beneficial bioactive properties. Enzymes capable of degrading algal polysaccharides into oligosaccharides may be used to produce biomolecules with new functionalities for the food and pharma industry....... Some marine bacteria are specialized in degrading algal biomass and secrete enzymes that can decompose the complex algal cell wall polysaccharides. In order to identify such bacteria and enzymatic activities, we have used a combination of traditional cultivation and isolation methods, bioinformatics...... and functional screening. This resulted in the discovery of a novel marine bacterium which displays a large enzymatic potential for degradation of red algal polysaccharides e.g. agar and carrageenan. In addition, we searched metagenome sequence data and identified new enzyme candidates for degradation...

  13. The growing need for microservices in bioinformatics

    Directory of Open Access Journals (Sweden)

    Christopher L Williams

    2016-01-01

    Full Text Available Objective: Within the information technology (IT industry, best practices and standards are constantly evolving and being refined. In contrast, computer technology utilized within the healthcare industry often evolves at a glacial pace, with reduced opportunities for justified innovation. Although the use of timely technology refreshes within an enterprise′s overall technology stack can be costly, thoughtful adoption of select technologies with a demonstrated return on investment can be very effective in increasing productivity and at the same time, reducing the burden of maintenance often associated with older and legacy systems. In this brief technical communication, we introduce the concept of microservices as applied to the ecosystem of data analysis pipelines. Microservice architecture is a framework for dividing complex systems into easily managed parts. Each individual service is limited in functional scope, thereby conferring a higher measure of functional isolation and reliability to the collective solution. Moreover, maintenance challenges are greatly simplified by virtue of the reduced architectural complexity of each constitutive module. This fact notwithstanding, rendered overall solutions utilizing a microservices-based approach provide equal or greater levels of functionality as compared to conventional programming approaches. Bioinformatics, with its ever-increasing demand for performance and new testing algorithms, is the perfect use-case for such a solution. Moreover, if promulgated within the greater development community as an open-source solution, such an approach holds potential to be transformative to current bioinformatics software development. Context: Bioinformatics relies on nimble IT framework which can adapt to changing requirements. Aims: To present a well-established software design and deployment strategy as a solution for current challenges within bioinformatics Conclusions: Use of the microservices framework

  14. The growing need for microservices in bioinformatics.

    Science.gov (United States)

    Williams, Christopher L; Sica, Jeffrey C; Killen, Robert T; Balis, Ulysses G J

    2016-01-01

    Within the information technology (IT) industry, best practices and standards are constantly evolving and being refined. In contrast, computer technology utilized within the healthcare industry often evolves at a glacial pace, with reduced opportunities for justified innovation. Although the use of timely technology refreshes within an enterprise's overall technology stack can be costly, thoughtful adoption of select technologies with a demonstrated return on investment can be very effective in increasing productivity and at the same time, reducing the burden of maintenance often associated with older and legacy systems. In this brief technical communication, we introduce the concept of microservices as applied to the ecosystem of data analysis pipelines. Microservice architecture is a framework for dividing complex systems into easily managed parts. Each individual service is limited in functional scope, thereby conferring a higher measure of functional isolation and reliability to the collective solution. Moreover, maintenance challenges are greatly simplified by virtue of the reduced architectural complexity of each constitutive module. This fact notwithstanding, rendered overall solutions utilizing a microservices-based approach provide equal or greater levels of functionality as compared to conventional programming approaches. Bioinformatics, with its ever-increasing demand for performance and new testing algorithms, is the perfect use-case for such a solution. Moreover, if promulgated within the greater development community as an open-source solution, such an approach holds potential to be transformative to current bioinformatics software development. Bioinformatics relies on nimble IT framework which can adapt to changing requirements. To present a well-established software design and deployment strategy as a solution for current challenges within bioinformatics. Use of the microservices framework is an effective methodology for the fabrication and

  15. The growing need for microservices in bioinformatics

    Science.gov (United States)

    Williams, Christopher L.; Sica, Jeffrey C.; Killen, Robert T.; Balis, Ulysses G. J.

    2016-01-01

    Objective: Within the information technology (IT) industry, best practices and standards are constantly evolving and being refined. In contrast, computer technology utilized within the healthcare industry often evolves at a glacial pace, with reduced opportunities for justified innovation. Although the use of timely technology refreshes within an enterprise's overall technology stack can be costly, thoughtful adoption of select technologies with a demonstrated return on investment can be very effective in increasing productivity and at the same time, reducing the burden of maintenance often associated with older and legacy systems. In this brief technical communication, we introduce the concept of microservices as applied to the ecosystem of data analysis pipelines. Microservice architecture is a framework for dividing complex systems into easily managed parts. Each individual service is limited in functional scope, thereby conferring a higher measure of functional isolation and reliability to the collective solution. Moreover, maintenance challenges are greatly simplified by virtue of the reduced architectural complexity of each constitutive module. This fact notwithstanding, rendered overall solutions utilizing a microservices-based approach provide equal or greater levels of functionality as compared to conventional programming approaches. Bioinformatics, with its ever-increasing demand for performance and new testing algorithms, is the perfect use-case for such a solution. Moreover, if promulgated within the greater development community as an open-source solution, such an approach holds potential to be transformative to current bioinformatics software development. Context: Bioinformatics relies on nimble IT framework which can adapt to changing requirements. Aims: To present a well-established software design and deployment strategy as a solution for current challenges within bioinformatics Conclusions: Use of the microservices framework is an effective

  16. ZBIT Bioinformatics Toolbox: A Web-Platform for Systems Biology and Expression Data Analysis.

    Science.gov (United States)

    Römer, Michael; Eichner, Johannes; Dräger, Andreas; Wrzodek, Clemens; Wrzodek, Finja; Zell, Andreas

    2016-01-01

    Bioinformatics analysis has become an integral part of research in biology. However, installation and use of scientific software can be difficult and often requires technical expert knowledge. Reasons are dependencies on certain operating systems or required third-party libraries, missing graphical user interfaces and documentation, or nonstandard input and output formats. In order to make bioinformatics software easily accessible to researchers, we here present a web-based platform. The Center for Bioinformatics Tuebingen (ZBIT) Bioinformatics Toolbox provides web-based access to a collection of bioinformatics tools developed for systems biology, protein sequence annotation, and expression data analysis. Currently, the collection encompasses software for conversion and processing of community standards SBML and BioPAX, transcription factor analysis, and analysis of microarray data from transcriptomics and proteomics studies. All tools are hosted on a customized Galaxy instance and run on a dedicated computation cluster. Users only need a web browser and an active internet connection in order to benefit from this service. The web platform is designed to facilitate the usage of the bioinformatics tools for researchers without advanced technical background. Users can combine tools for complex analyses or use predefined, customizable workflows. All results are stored persistently and reproducible. For each tool, we provide documentation, tutorials, and example data to maximize usability. The ZBIT Bioinformatics Toolbox is freely available at https://webservices.cs.uni-tuebingen.de/.

  17. Model-driven user interfaces for bioinformatics data resources: regenerating the wheel as an alternative to reinventing it

    Directory of Open Access Journals (Sweden)

    Swainston Neil

    2006-12-01

    Full Text Available Abstract Background The proliferation of data repositories in bioinformatics has resulted in the development of numerous interfaces that allow scientists to browse, search and analyse the data that they contain. Interfaces typically support repository access by means of web pages, but other means are also used, such as desktop applications and command line tools. Interfaces often duplicate functionality amongst each other, and this implies that associated development activities are repeated in different laboratories. Interfaces developed by public laboratories are often created with limited developer resources. In such environments, reducing the time spent on creating user interfaces allows for a better deployment of resources for specialised tasks, such as data integration or analysis. Laboratories maintaining data resources are challenged to reconcile requirements for software that is reliable, functional and flexible with limitations on software development resources. Results This paper proposes a model-driven approach for the partial generation of user interfaces for searching and browsing bioinformatics data repositories. Inspired by the Model Driven Architecture (MDA of the Object Management Group (OMG, we have developed a system that generates interfaces designed for use with bioinformatics resources. This approach helps laboratory domain experts decrease the amount of time they have to spend dealing with the repetitive aspects of user interface development. As a result, the amount of time they can spend on gathering requirements and helping develop specialised features increases. The resulting system is known as Pierre, and has been validated through its application to use cases in the life sciences, including the PEDRoDB proteomics database and the e-Fungi data warehouse. Conclusion MDAs focus on generating software from models that describe aspects of service capabilities, and can be applied to support rapid development of repository

  18. BioXSD: the common data-exchange format for everyday bioinformatics web services

    Science.gov (United States)

    Kalaš, Matúš; Puntervoll, Pæl; Joseph, Alexandre; Bartaševičiūtė, Edita; Töpfer, Armin; Venkataraman, Prabakar; Pettifer, Steve; Bryne, Jan Christian; Ison, Jon; Blanchet, Christophe; Rapacki, Kristoffer; Jonassen, Inge

    2010-01-01

    Motivation: The world-wide community of life scientists has access to a large number of public bioinformatics databases and tools, which are developed and deployed using diverse technologies and designs. More and more of the resources offer programmatic web-service interface. However, efficient use of the resources is hampered by the lack of widely used, standard data-exchange formats for the basic, everyday bioinformatics data types. Results: BioXSD has been developed as a candidate for standard, canonical exchange format for basic bioinformatics data. BioXSD is represented by a dedicated XML Schema and defines syntax for biological sequences, sequence annotations, alignments and references to resources. We have adapted a set of web services to use BioXSD as the input and output format, and implemented a test-case workflow. This demonstrates that the approach is feasible and provides smooth interoperability. Semantics for BioXSD is provided by annotation with the EDAM ontology. We discuss in a separate section how BioXSD relates to other initiatives and approaches, including existing standards and the Semantic Web. Availability: The BioXSD 1.0 XML Schema is freely available at http://www.bioxsd.org/BioXSD-1.0.xsd under the Creative Commons BY-ND 3.0 license. The http://bioxsd.org web page offers documentation, examples of data in BioXSD format, example workflows with source codes in common programming languages, an updated list of compatible web services and tools and a repository of feature requests from the community. Contact: matus.kalas@bccs.uib.no; developers@bioxsd.org; support@bioxsd.org PMID:20823319

  19. A Portable Bioinformatics Course for Upper-Division Undergraduate Curriculum in Sciences

    Science.gov (United States)

    Floraino, Wely B.

    2008-01-01

    This article discusses the challenges that bioinformatics education is facing and describes a bioinformatics course that is successfully taught at the California State Polytechnic University, Pomona, to the fourth year undergraduate students in biological sciences, chemistry, and computer science. Information on lecture and computer practice…

  20. Computer Programming and Biomolecular Structure Studies: A Step beyond Internet Bioinformatics

    Science.gov (United States)

    Likic, Vladimir A.

    2006-01-01

    This article describes the experience of teaching structural bioinformatics to third year undergraduate students in a subject titled "Biomolecular Structure and Bioinformatics." Students were introduced to computer programming and used this knowledge in a practical application as an alternative to the well established Internet bioinformatics…

  1. Chapter 16: text mining for translational bioinformatics.

    Science.gov (United States)

    Cohen, K Bretonnel; Hunter, Lawrence E

    2013-04-01

    Text mining for translational bioinformatics is a new field with tremendous research potential. It is a subfield of biomedical natural language processing that concerns itself directly with the problem of relating basic biomedical research to clinical practice, and vice versa. Applications of text mining fall both into the category of T1 translational research-translating basic science results into new interventions-and T2 translational research, or translational research for public health. Potential use cases include better phenotyping of research subjects, and pharmacogenomic research. A variety of methods for evaluating text mining applications exist, including corpora, structured test suites, and post hoc judging. Two basic principles of linguistic structure are relevant for building text mining applications. One is that linguistic structure consists of multiple levels. The other is that every level of linguistic structure is characterized by ambiguity. There are two basic approaches to text mining: rule-based, also known as knowledge-based; and machine-learning-based, also known as statistical. Many systems are hybrids of the two approaches. Shared tasks have had a strong effect on the direction of the field. Like all translational bioinformatics software, text mining software for translational bioinformatics can be considered health-critical and should be subject to the strictest standards of quality assurance and software testing.

  2. Hermes: Seamless delivery of containerized bioinformatics workflows in hybrid cloud (HTC) environments

    Science.gov (United States)

    Kintsakis, Athanassios M.; Psomopoulos, Fotis E.; Symeonidis, Andreas L.; Mitkas, Pericles A.

    Hermes introduces a new "describe once, run anywhere" paradigm for the execution of bioinformatics workflows in hybrid cloud environments. It combines the traditional features of parallelization-enabled workflow management systems and of distributed computing platforms in a container-based approach. It offers seamless deployment, overcoming the burden of setting up and configuring the software and network requirements. Most importantly, Hermes fosters the reproducibility of scientific workflows by supporting standardization of the software execution environment, thus leading to consistent scientific workflow results and accelerating scientific output.

  3. Automated cell type discovery and classification through knowledge transfer

    Science.gov (United States)

    Lee, Hao-Chih; Kosoy, Roman; Becker, Christine E.

    2017-01-01

    Abstract Motivation: Recent advances in mass cytometry allow simultaneous measurements of up to 50 markers at single-cell resolution. However, the high dimensionality of mass cytometry data introduces computational challenges for automated data analysis and hinders translation of new biological understanding into clinical applications. Previous studies have applied machine learning to facilitate processing of mass cytometry data. However, manual inspection is still inevitable and becoming the barrier to reliable large-scale analysis. Results: We present a new algorithm called Automated Cell-type Discovery and Classification (ACDC) that fully automates the classification of canonical cell populations and highlights novel cell types in mass cytometry data. Evaluations on real-world data show ACDC provides accurate and reliable estimations compared to manual gating results. Additionally, ACDC automatically classifies previously ambiguous cell types to facilitate discovery. Our findings suggest that ACDC substantially improves both reliability and interpretability of results obtained from high-dimensional mass cytometry profiling data. Availability and Implementation: A Python package (Python 3) and analysis scripts for reproducing the results are availability on https://bitbucket.org/dudleylab/acdc. Contact: brian.kidd@mssm.edu or joel.dudley@mssm.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:28158442

  4. Discovery of the leinamycin family of natural products by mining actinobacterial genomes.

    Science.gov (United States)

    Pan, Guohui; Xu, Zhengren; Guo, Zhikai; Hindra; Ma, Ming; Yang, Dong; Zhou, Hao; Gansemans, Yannick; Zhu, Xiangcheng; Huang, Yong; Zhao, Li-Xing; Jiang, Yi; Cheng, Jinhua; Van Nieuwerburgh, Filip; Suh, Joo-Won; Duan, Yanwen; Shen, Ben

    2017-12-26

    Nature's ability to generate diverse natural products from simple building blocks has inspired combinatorial biosynthesis. The knowledge-based approach to combinatorial biosynthesis has allowed the production of designer analogs by rational metabolic pathway engineering. While successful, structural alterations are limited, with designer analogs often produced in compromised titers. The discovery-based approach to combinatorial biosynthesis complements the knowledge-based approach by exploring the vast combinatorial biosynthesis repertoire found in Nature. Here we showcase the discovery-based approach to combinatorial biosynthesis by targeting the domain of unknown function and cysteine lyase domain (DUF-SH) didomain, specific for sulfur incorporation from the leinamycin (LNM) biosynthetic machinery, to discover the LNM family of natural products. By mining bacterial genomes from public databases and the actinomycetes strain collection at The Scripps Research Institute, we discovered 49 potential producers that could be grouped into 18 distinct clades based on phylogenetic analysis of the DUF-SH didomains. Further analysis of the representative genomes from each of the clades identified 28 lnm -type gene clusters. Structural diversities encoded by the LNM-type biosynthetic machineries were predicted based on bioinformatics and confirmed by in vitro characterization of selected adenylation proteins and isolation and structural elucidation of the guangnanmycins and weishanmycins. These findings demonstrate the power of the discovery-based approach to combinatorial biosynthesis for natural product discovery and structural diversity and highlight Nature's rich biosynthetic repertoire. Comparative analysis of the LNM-type biosynthetic machineries provides outstanding opportunities to dissect Nature's biosynthetic strategies and apply these findings to combinatorial biosynthesis for natural product discovery and structural diversity.

  5. A decade of Web Server updates at the Bioinformatics Links Directory: 2003-2012.

    Science.gov (United States)

    Brazas, Michelle D; Yim, David; Yeung, Winston; Ouellette, B F Francis

    2012-07-01

    The 2012 Bioinformatics Links Directory update marks the 10th special Web Server issue from Nucleic Acids Research. Beginning with content from their 2003 publication, the Bioinformatics Links Directory in collaboration with Nucleic Acids Research has compiled and published a comprehensive list of freely accessible, online tools, databases and resource materials for the bioinformatics and life science research communities. The past decade has exhibited significant growth and change in the types of tools, databases and resources being put forth, reflecting both technology changes and the nature of research over that time. With the addition of 90 web server tools and 12 updates from the July 2012 Web Server issue of Nucleic Acids Research, the Bioinformatics Links Directory at http://bioinformatics.ca/links_directory/ now contains an impressive 134 resources, 455 databases and 1205 web server tools, mirroring the continued activity and efforts of our field.

  6. BOWS (bioinformatics open web services) to centralize bioinformatics tools in web services.

    Science.gov (United States)

    Velloso, Henrique; Vialle, Ricardo A; Ortega, J Miguel

    2015-06-02

    Bioinformaticians face a range of difficulties to get locally-installed tools running and producing results; they would greatly benefit from a system that could centralize most of the tools, using an easy interface for input and output. Web services, due to their universal nature and widely known interface, constitute a very good option to achieve this goal. Bioinformatics open web services (BOWS) is a system based on generic web services produced to allow programmatic access to applications running on high-performance computing (HPC) clusters. BOWS intermediates the access to registered tools by providing front-end and back-end web services. Programmers can install applications in HPC clusters in any programming language and use the back-end service to check for new jobs and their parameters, and then to send the results to BOWS. Programs running in simple computers consume the BOWS front-end service to submit new processes and read results. BOWS compiles Java clients, which encapsulate the front-end web service requisitions, and automatically creates a web page that disposes the registered applications and clients. Bioinformatics open web services registered applications can be accessed from virtually any programming language through web services, or using standard java clients. The back-end can run in HPC clusters, allowing bioinformaticians to remotely run high-processing demand applications directly from their machines.

  7. SPECIES DATABASES AND THE BIOINFORMATICS REVOLUTION.

    Science.gov (United States)

    Biological databases are having a growth spurt. Much of this results from research in genetics and biodiversity, coupled with fast-paced developments in information technology. The revolution in bioinformatics, defined by Sugden and Pennisi (2000) as the "tools and techniques for...

  8. BioSmalltalk: a pure object system and library for bioinformatics.

    Science.gov (United States)

    Morales, Hernán F; Giovambattista, Guillermo

    2013-09-15

    We have developed BioSmalltalk, a new environment system for pure object-oriented bioinformatics programming. Adaptive end-user programming systems tend to become more important for discovering biological knowledge, as is demonstrated by the emergence of open-source programming toolkits for bioinformatics in the past years. Our software is intended to bridge the gap between bioscientists and rapid software prototyping while preserving the possibility of scaling to whole-system biology applications. BioSmalltalk performs better in terms of execution time and memory usage than Biopython and BioPerl for some classical situations. BioSmalltalk is cross-platform and freely available (MIT license) through the Google Project Hosting at http://code.google.com/p/biosmalltalk hernan.morales@gmail.com Supplementary data are available at Bioinformatics online.

  9. Bioinformatics analysis of transcriptome dynamics during growth in angus cattle longissimus muscle.

    Science.gov (United States)

    Moisá, Sonia J; Shike, Daniel W; Graugnard, Daniel E; Rodriguez-Zas, Sandra L; Everts, Robin E; Lewin, Harris A; Faulkner, Dan B; Berger, Larry L; Loor, Juan J

    2013-01-01

    Transcriptome dynamics in the longissimus muscle (LM) of young Angus cattle were evaluated at 0, 60, 120, and 220 days from early-weaning. Bioinformatic analysis was performed using the dynamic impact approach (DIA) by means of Kyoto Encyclopedia of Genes and Genomes (KEGG) and Database for Annotation, Visualization and Integrated Discovery (DAVID) databases. Between 0 to 120 days (growing phase) most of the highly-impacted pathways (eg, ascorbate and aldarate metabolism, drug metabolism, cytochrome P450 and Retinol metabolism) were inhibited. The phase between 120 to 220 days (finishing phase) was characterized by the most striking differences with 3,784 differentially expressed genes (DEGs). Analysis of those DEGs revealed that the most impacted KEGG canonical pathway was glycosylphosphatidylinositol (GPI)-anchor biosynthesis, which was inhibited. Furthermore, inhibition of calpastatin and activation of tyrosine aminotransferase ubiquitination at 220 days promotes proteasomal degradation, while the concurrent activation of ribosomal proteins promotes protein synthesis. Therefore, the balance of these processes likely results in a steady-state of protein turnover during the finishing phase. Results underscore the importance of transcriptome dynamics in LM during growth.

  10. Knowledge Discovery in Biological Databases for Revealing Candidate Genes Linked to Complex Phenotypes.

    Science.gov (United States)

    Hassani-Pak, Keywan; Rawlings, Christopher

    2017-06-13

    Genetics and "omics" studies designed to uncover genotype to phenotype relationships often identify large numbers of potential candidate genes, among which the causal genes are hidden. Scientists generally lack the time and technical expertise to review all relevant information available from the literature, from key model species and from a potentially wide range of related biological databases in a variety of data formats with variable quality and coverage. Computational tools are needed for the integration and evaluation of heterogeneous information in order to prioritise candidate genes and components of interaction networks that, if perturbed through potential interventions, have a positive impact on the biological outcome in the whole organism without producing negative side effects. Here we review several bioinformatics tools and databases that play an important role in biological knowledge discovery and candidate gene prioritization. We conclude with several key challenges that need to be addressed in order to facilitate biological knowledge discovery in the future.

  11. DASS: efficient discovery and p-value calculation of substructures in unordered data.

    Science.gov (United States)

    Hollunder, Jens; Friedel, Maik; Beyer, Andreas; Workman, Christopher T; Wilhelm, Thomas

    2007-01-01

    Pattern identification in biological sequence data is one of the main objectives of bioinformatics research. However, few methods are available for detecting patterns (substructures) in unordered datasets. Data mining algorithms mainly developed outside the realm of bioinformatics have been adapted for that purpose, but typically do not determine the statistical significance of the identified patterns. Moreover, these algorithms do not exploit the often modular structure of biological data. We present the algorithm DASS (Discovery of All Significant Substructures) that first identifies all substructures in unordered data (DASS(Sub)) in a manner that is especially efficient for modular data. In addition, DASS calculates the statistical significance of the identified substructures, for sets with at most one element of each type (DASS(P(set))), or for sets with multiple occurrence of elements (DASS(P(mset))). The power and versatility of DASS is demonstrated by four examples: combinations of protein domains in multi-domain proteins, combinations of proteins in protein complexes (protein subcomplexes), combinations of transcription factor target sites in promoter regions and evolutionarily conserved protein interaction subnetworks. The program code and additional data are available at http://www.fli-leibniz.de/tsb/DASS

  12. Bioinformatics programs are 31-fold over-represented among the highest impact scientific papers of the past two decades.

    Science.gov (United States)

    Wren, Jonathan D

    2016-09-01

    To analyze the relative proportion of bioinformatics papers and their non-bioinformatics counterparts in the top 20 most cited papers annually for the past two decades. When defining bioinformatics papers as encompassing both those that provide software for data analysis or methods underlying data analysis software, we find that over the past two decades, more than a third (34%) of the most cited papers in science were bioinformatics papers, which is approximately a 31-fold enrichment relative to the total number of bioinformatics papers published. More than half of the most cited papers during this span were bioinformatics papers. Yet, the average 5-year JIF of top 20 bioinformatics papers was 7.7, whereas the average JIF for top 20 non-bioinformatics papers was 25.8, significantly higher (P papers, bioinformatics journals tended to have higher Gini coefficients, suggesting that development of novel bioinformatics resources may be somewhat 'hit or miss'. That is, relative to other fields, bioinformatics produces some programs that are extremely widely adopted and cited, yet there are fewer of intermediate success. jdwren@gmail.com Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

  13. Knowledge-based analysis of microarrays for the discovery of transcriptional regulation relationships.

    Science.gov (United States)

    Seok, Junhee; Kaushal, Amit; Davis, Ronald W; Xiao, Wenzhong

    2010-01-18

    The large amount of high-throughput genomic data has facilitated the discovery of the regulatory relationships between transcription factors and their target genes. While early methods for discovery of transcriptional regulation relationships from microarray data often focused on the high-throughput experimental data alone, more recent approaches have explored the integration of external knowledge bases of gene interactions. In this work, we develop an algorithm that provides improved performance in the prediction of transcriptional regulatory relationships by supplementing the analysis of microarray data with a new method of integrating information from an existing knowledge base. Using a well-known dataset of yeast microarrays and the Yeast Proteome Database, a comprehensive collection of known information of yeast genes, we show that knowledge-based predictions demonstrate better sensitivity and specificity in inferring new transcriptional interactions than predictions from microarray data alone. We also show that comprehensive, direct and high-quality knowledge bases provide better prediction performance. Comparison of our results with ChIP-chip data and growth fitness data suggests that our predicted genome-wide regulatory pairs in yeast are reasonable candidates for follow-up biological verification. High quality, comprehensive, and direct knowledge bases, when combined with appropriate bioinformatic algorithms, can significantly improve the discovery of gene regulatory relationships from high throughput gene expression data.

  14. Hermes: Seamless delivery of containerized bioinformatics workflows in hybrid cloud (HTC environments

    Directory of Open Access Journals (Sweden)

    Athanassios M. Kintsakis

    2017-01-01

    Full Text Available Hermes introduces a new “describe once, run anywhere” paradigm for the execution of bioinformatics workflows in hybrid cloud environments. It combines the traditional features of parallelization-enabled workflow management systems and of distributed computing platforms in a container-based approach. It offers seamless deployment, overcoming the burden of setting up and configuring the software and network requirements. Most importantly, Hermes fosters the reproducibility of scientific workflows by supporting standardization of the software execution environment, thus leading to consistent scientific workflow results and accelerating scientific output.

  15. Agonist Binding to Chemosensory Receptors: A Systematic Bioinformatics Analysis

    Directory of Open Access Journals (Sweden)

    Fabrizio Fierro

    2017-09-01

    Full Text Available Human G-protein coupled receptors (hGPCRs constitute a large and highly pharmaceutically relevant membrane receptor superfamily. About half of the hGPCRs' family members are chemosensory receptors, involved in bitter taste and olfaction, along with a variety of other physiological processes. Hence these receptors constitute promising targets for pharmaceutical intervention. Molecular modeling has been so far the most important tool to get insights on agonist binding and receptor activation. Here we investigate both aspects by bioinformatics-based predictions across all bitter taste and odorant receptors for which site-directed mutagenesis data are available. First, we observe that state-of-the-art homology modeling combined with previously used docking procedures turned out to reproduce only a limited fraction of ligand/receptor interactions inferred by experiments. This is most probably caused by the low sequence identity with available structural templates, which limits the accuracy of the protein model and in particular of the side-chains' orientations. Methods which transcend the limited sampling of the conformational space of docking may improve the predictions. As an example corroborating this, we review here multi-scale simulations from our lab and show that, for the three complexes studied so far, they significantly enhance the predictive power of the computational approach. Second, our bioinformatics analysis provides support to previous claims that several residues, including those at positions 1.50, 2.50, and 7.52, are involved in receptor activation.

  16. BIRCH: A user-oriented, locally-customizable, bioinformatics system

    Science.gov (United States)

    Fristensky, Brian

    2007-01-01

    Background Molecular biologists need sophisticated analytical tools which often demand extensive computational resources. While finding, installing, and using these tools can be challenging, pipelining data from one program to the next is particularly awkward, especially when using web-based programs. At the same time, system administrators tasked with maintaining these tools do not always appreciate the needs of research biologists. Results BIRCH (Biological Research Computing Hierarchy) is an organizational framework for delivering bioinformatics resources to a user group, scaling from a single lab to a large institution. The BIRCH core distribution includes many popular bioinformatics programs, unified within the GDE (Genetic Data Environment) graphic interface. Of equal importance, BIRCH provides the system administrator with tools that simplify the job of managing a multiuser bioinformatics system across different platforms and operating systems. These include tools for integrating locally-installed programs and databases into BIRCH, and for customizing the local BIRCH system to meet the needs of the user base. BIRCH can also act as a front end to provide a unified view of already-existing collections of bioinformatics software. Documentation for the BIRCH and locally-added programs is merged in a hierarchical set of web pages. In addition to manual pages for individual programs, BIRCH tutorials employ step by step examples, with screen shots and sample files, to illustrate both the important theoretical and practical considerations behind complex analytical tasks. Conclusion BIRCH provides a versatile organizational framework for managing software and databases, and making these accessible to a user base. Because of its network-centric design, BIRCH makes it possible for any user to do any task from anywhere. PMID:17291351

  17. BIRCH: A user-oriented, locally-customizable, bioinformatics system

    Directory of Open Access Journals (Sweden)

    Fristensky Brian

    2007-02-01

    Full Text Available Abstract Background Molecular biologists need sophisticated analytical tools which often demand extensive computational resources. While finding, installing, and using these tools can be challenging, pipelining data from one program to the next is particularly awkward, especially when using web-based programs. At the same time, system administrators tasked with maintaining these tools do not always appreciate the needs of research biologists. Results BIRCH (Biological Research Computing Hierarchy is an organizational framework for delivering bioinformatics resources to a user group, scaling from a single lab to a large institution. The BIRCH core distribution includes many popular bioinformatics programs, unified within the GDE (Genetic Data Environment graphic interface. Of equal importance, BIRCH provides the system administrator with tools that simplify the job of managing a multiuser bioinformatics system across different platforms and operating systems. These include tools for integrating locally-installed programs and databases into BIRCH, and for customizing the local BIRCH system to meet the needs of the user base. BIRCH can also act as a front end to provide a unified view of already-existing collections of bioinformatics software. Documentation for the BIRCH and locally-added programs is merged in a hierarchical set of web pages. In addition to manual pages for individual programs, BIRCH tutorials employ step by step examples, with screen shots and sample files, to illustrate both the important theoretical and practical considerations behind complex analytical tasks. Conclusion BIRCH provides a versatile organizational framework for managing software and databases, and making these accessible to a user base. Because of its network-centric design, BIRCH makes it possible for any user to do any task from anywhere.

  18. mORCA: sailing bioinformatics world with mobile devices.

    Science.gov (United States)

    Díaz-Del-Pino, Sergio; Falgueras, Juan; Perez-Wohlfeil, Esteban; Trelles, Oswaldo

    2018-03-01

    Nearly 10 years have passed since the first mobile apps appeared. Given the fact that bioinformatics is a web-based world and that mobile devices are endowed with web-browsers, it seemed natural that bioinformatics would transit from personal computers to mobile devices but nothing could be further from the truth. The transition demands new paradigms, designs and novel implementations. Throughout an in-depth analysis of requirements of existing bioinformatics applications we designed and deployed an easy-to-use web-based lightweight mobile client. Such client is able to browse, select, compose automatically interface parameters, invoke services and monitor the execution of Web Services using the service's metadata stored in catalogs or repositories. mORCA is available at http://bitlab-es.com/morca/app as a web-app. It is also available in the App store by Apple and Play Store by Google. The software will be available for at least 2 years. ortrelles@uma.es. Source code, final web-app, training material and documentation is available at http://bitlab-es.com/morca. © The Author(s) 2017. Published by Oxford University Press.

  19. p3d--Python module for structural bioinformatics.

    Science.gov (United States)

    Fufezan, Christian; Specht, Michael

    2009-08-21

    High-throughput bioinformatic analysis tools are needed to mine the large amount of structural data via knowledge based approaches. The development of such tools requires a robust interface to access the structural data in an easy way. For this the Python scripting language is the optimal choice since its philosophy is to write an understandable source code. p3d is an object oriented Python module that adds a simple yet powerful interface to the Python interpreter to process and analyse three dimensional protein structure files (PDB files). p3d's strength arises from the combination of a) very fast spatial access to the structural data due to the implementation of a binary space partitioning (BSP) tree, b) set theory and c) functions that allow to combine a and b and that use human readable language in the search queries rather than complex computer language. All these factors combined facilitate the rapid development of bioinformatic tools that can perform quick and complex analyses of protein structures. p3d is the perfect tool to quickly develop tools for structural bioinformatics using the Python scripting language.

  20. Best practices in bioinformatics training for life scientists.

    KAUST Repository

    Via, Allegra

    2013-06-25

    The mountains of data thrusting from the new landscape of modern high-throughput biology are irrevocably changing biomedical research and creating a near-insatiable demand for training in data management and manipulation and data mining and analysis. Among life scientists, from clinicians to environmental researchers, a common theme is the need not just to use, and gain familiarity with, bioinformatics tools and resources but also to understand their underlying fundamental theoretical and practical concepts. Providing bioinformatics training to empower life scientists to handle and analyse their data efficiently, and progress their research, is a challenge across the globe. Delivering good training goes beyond traditional lectures and resource-centric demos, using interactivity, problem-solving exercises and cooperative learning to substantially enhance training quality and learning outcomes. In this context, this article discusses various pragmatic criteria for identifying training needs and learning objectives, for selecting suitable trainees and trainers, for developing and maintaining training skills and evaluating training quality. Adherence to these criteria may help not only to guide course organizers and trainers on the path towards bioinformatics training excellence but, importantly, also to improve the training experience for life scientists.

  1. A global perspective on evolving bioinformatics and data science training needs.

    Science.gov (United States)

    Attwood, Teresa K; Blackford, Sarah; Brazas, Michelle D; Davies, Angela; Schneider, Maria Victoria

    2017-08-29

    Bioinformatics is now intrinsic to life science research, but the past decade has witnessed a continuing deficiency in this essential expertise. Basic data stewardship is still taught relatively rarely in life science education programmes, creating a chasm between theory and practice, and fuelling demand for bioinformatics training across all educational levels and career roles. Concerned by this, surveys have been conducted in recent years to monitor bioinformatics and computational training needs worldwide. This article briefly reviews the principal findings of a number of these studies. We see that there is still a strong appetite for short courses to improve expertise and confidence in data analysis and interpretation; strikingly, however, the most urgent appeal is for bioinformatics to be woven into the fabric of life science degree programmes. Satisfying the relentless training needs of current and future generations of life scientists will require a concerted response from stakeholders across the globe, who need to deliver sustainable solutions capable of both transforming education curricula and cultivating a new cadre of trainer scientists. © The Author 2017. Published by Oxford University Press.

  2. Bioinformatic tools for PCR Primer design

    African Journals Online (AJOL)

    ES

    reaction (PCR), oligo hybridization and DNA sequencing. Proper primer design is actually one of the most important factors/steps in successful DNA sequencing. Various bioinformatics programs are available for selection of primer pairs from a template sequence. The plethora programs for PCR primer design reflects the.

  3. Introductory Bioinformatics Exercises Utilizing Hemoglobin and Chymotrypsin to Reinforce the Protein Sequence-Structure-Function Relationship

    Science.gov (United States)

    Inlow, Jennifer K.; Miller, Paige; Pittman, Bethany

    2007-01-01

    We describe two bioinformatics exercises intended for use in a computer laboratory setting in an upper-level undergraduate biochemistry course. To introduce students to bioinformatics, the exercises incorporate several commonly used bioinformatics tools, including BLAST, that are freely available online. The exercises build upon the students'…

  4. Advance in structural bioinformatics

    CERN Document Server

    Wei, Dongqing; Zhao, Tangzhen; Dai, Hao

    2014-01-01

    This text examines in detail mathematical and physical modeling, computational methods and systems for obtaining and analyzing biological structures, using pioneering research cases as examples. As such, it emphasizes programming and problem-solving skills. It provides information on structure bioinformatics at various levels, with individual chapters covering introductory to advanced aspects, from fundamental methods and guidelines on acquiring and analyzing genomics and proteomics sequences, the structures of protein, DNA and RNA, to the basics of physical simulations and methods for conform

  5. What is bioinformatics? A proposed definition and overview of the field.

    Science.gov (United States)

    Luscombe, N M; Greenbaum, D; Gerstein, M

    2001-01-01

    The recent flood of data from genome sequences and functional genomics has given rise to new field, bioinformatics, which combines elements of biology and computer science. Here we propose a definition for this new field and review some of the research that is being pursued, particularly in relation to transcriptional regulatory systems. Our definition is as follows: Bioinformatics is conceptualizing biology in terms of macromolecules (in the sense of physical-chemistry) and then applying "informatics" techniques (derived from disciplines such as applied maths, computer science, and statistics) to understand and organize the information associated with these molecules, on a large-scale. Analyses in bioinformatics predominantly focus on three types of large datasets available in molecular biology: macromolecular structures, genome sequences, and the results of functional genomics experiments (e.g. expression data). Additional information includes the text of scientific papers and "relationship data" from metabolic pathways, taxonomy trees, and protein-protein interaction networks. Bioinformatics employs a wide range of computational techniques including sequence and structural alignment, database design and data mining, macromolecular geometry, phylogenetic tree construction, prediction of protein structure and function, gene finding, and expression data clustering. The emphasis is on approaches integrating a variety of computational methods and heterogeneous data sources. Finally, bioinformatics is a practical discipline. We survey some representative applications, such as finding homologues, designing drugs, and performing large-scale censuses. Additional information pertinent to the review is available over the web at http://bioinfo.mbb.yale.edu/what-is-it.

  6. An overview of topic modeling and its current applications in bioinformatics.

    Science.gov (United States)

    Liu, Lin; Tang, Lin; Dong, Wen; Yao, Shaowen; Zhou, Wei

    2016-01-01

    With the rapid accumulation of biological datasets, machine learning methods designed to automate data analysis are urgently needed. In recent years, so-called topic models that originated from the field of natural language processing have been receiving much attention in bioinformatics because of their interpretability. Our aim was to review the application and development of topic models for bioinformatics. This paper starts with the description of a topic model, with a focus on the understanding of topic modeling. A general outline is provided on how to build an application in a topic model and how to develop a topic model. Meanwhile, the literature on application of topic models to biological data was searched and analyzed in depth. According to the types of models and the analogy between the concept of document-topic-word and a biological object (as well as the tasks of a topic model), we categorized the related studies and provided an outlook on the use of topic models for the development of bioinformatics applications. Topic modeling is a useful method (in contrast to the traditional means of data reduction in bioinformatics) and enhances researchers' ability to interpret biological information. Nevertheless, due to the lack of topic models optimized for specific biological data, the studies on topic modeling in biological data still have a long and challenging road ahead. We believe that topic models are a promising method for various applications in bioinformatics research.

  7. "Extreme Programming" in a Bioinformatics Class

    Science.gov (United States)

    Kelley, Scott; Alger, Christianna; Deutschman, Douglas

    2009-01-01

    The importance of Bioinformatics tools and methodology in modern biological research underscores the need for robust and effective courses at the college level. This paper describes such a course designed on the principles of cooperative learning based on a computer software industry production model called "Extreme Programming" (EP).…

  8. Bioinformatics in Undergraduate Education: Practical Examples

    Science.gov (United States)

    Boyle, John A.

    2004-01-01

    Bioinformatics has emerged as an important research tool in recent years. The ability to mine large databases for relevant information has become increasingly central to many different aspects of biochemistry and molecular biology. It is important that undergraduates be introduced to the available information and methodologies. We present a…

  9. Supporting Formulary Decisions: The Discovery of New Facts or Constructed Evidence?

    Directory of Open Access Journals (Sweden)

    Paul C Langley

    2016-07-01

    Full Text Available A critical question, given the growing importance of more targeted therapies to support personalized and precision medicine, is the credibility of the evidence base to support formulary decisions and pricing. On the one hand, for those who subscribe to the reference case model of the National Institute of Health and Care Excellence (NICE in the UK, the decision rests upon the creation of modeled or simulated imaginary worlds and the application of threshold willingness-to-pay cost-per-QALY thresholds. On the other hand, for those who subscribe to the standards of normal science, the decision rests upon the ability to evaluate competing claims, both clinical and cost-effective, in a timeframe that is meaningful to a formulary committee. If we subscribe to the scientific method where the focus is on the discovery of new facts, untestable claims for clinical benefit and cost-effectiveness, such as created claims for lifetime cost per-quality-adjusted discounted life years (QALYs, are properly relegated to the category of pseudoscience. We have no idea, and will never know, whether the claims are right or even if they are wrong. If formulary decisions are to respect the standards of normal science then there has to be a commitment to claims evaluation. A willingness to accept new products provisionally, subject to an agreed protocol to support the evaluation of clinical and cost-effectiveness claims. This dichotomy between the standards of normal science and pseudoscience is explored in the context of published claims for cost-effectiveness and recommendations for product pricing in the US.   Type: Commentary

  10. The Bioinformatics of Integrative Medical Insights: Proposals for an International Psycho-Social and Cultural Bioinformatics Project

    Directory of Open Access Journals (Sweden)

    Ernest Rossi

    2006-01-01

    Full Text Available We propose the formation of an International Psycho-Social and Cultural Bioinformatics Project (IPCBP to explore the research foundations of Integrative Medical Insights (IMI on all levels from the molecular-genomic to the psychological, cultural, social, and spiritual. Just as The Human Genome Project identified the molecular foundations of modern medicine with the new technology of sequencing DNA during the past decade, the IPCBP would extend and integrate this neuroscience knowledge base with the technology of gene expression via DNA/proteomic microarray research and brain imaging in development, stress, healing, rehabilitation, and the psychotherapeutic facilitation of existentional wellness. We anticipate that the IPCBP will require a unique international collaboration of, academic institutions, researchers, and clinical practioners for the creation of a new neuroscience of mind-body communication, brain plasticity, memory, learning, and creative processing during optimal experiential states of art, beauty, and truth. We illustrate this emerging integration of bioinformatics with medicine with a videotape of the classical 4-stage creative process in a neuroscience approach to psychotherapy.

  11. The Bioinformatics of Integrative Medical Insights: Proposals for an International PsychoSocial and Cultural Bioinformatics Project

    Directory of Open Access Journals (Sweden)

    Ernest Rossi

    2006-01-01

    Full Text Available We propose the formation of an International PsychoSocial and Cultural Bioinformatics Project (IPCBP to explore the research foundations of Integrative Medical Insights (IMI on all levels from the molecular-genomic to the psychological, cultural, social, and spiritual. Just as The Human Genome Project identified the molecular foundations of modern medicine with the new technology of sequencing DNA during the past decade, the IPCBP would extend and integrate this neuroscience knowledge base with the technology of gene expression via DNA/proteomic microarray research and brain imaging in development, stress, healing, rehabilitation, and the psychotherapeutic facilitation of existentional wellness. We anticipate that the IPCBP will require a unique international collaboration of, academic institutions, researchers, and clinical practioners for the creation of a new neuroscience of mind-body communication, brain plasticity, memory, learning, and creative processing during optimal experiential states of art, beauty, and truth. We illustrate this emerging integration of bioinformatics with medicine with a videotape of the classical 4-stage creative process in a neuroscience approach to psychotherapy.

  12. Incorporating a Collaborative Web-Based Virtual Laboratory in an Undergraduate Bioinformatics Course

    Science.gov (United States)

    Weisman, David

    2010-01-01

    Face-to-face bioinformatics courses commonly include a weekly, in-person computer lab to facilitate active learning, reinforce conceptual material, and teach practical skills. Similarly, fully-online bioinformatics courses employ hands-on exercises to achieve these outcomes, although students typically perform this work offsite. Combining a…

  13. A Summer Program Designed to Educate College Students for Careers in Bioinformatics

    Science.gov (United States)

    Krilowicz, Beverly; Johnston, Wendie; Sharp, Sandra B.; Warter-Perez, Nancy; Momand, Jamil

    2007-01-01

    A summer program was created for undergraduates and graduate students that teaches bioinformatics concepts, offers skills in professional development, and provides research opportunities in academic and industrial institutions. We estimate that 34 of 38 graduates (89%) are in a career trajectory that will use bioinformatics. Evidence from…

  14. Relax with CouchDB - Into the non-relational DBMS era of Bioinformatics

    Science.gov (United States)

    Manyam, Ganiraju; Payton, Michelle A.; Roth, Jack A.; Abruzzo, Lynne V.; Coombes, Kevin R.

    2012-01-01

    With the proliferation of high-throughput technologies, genome-level data analysis has become common in molecular biology. Bioinformaticians are developing extensive resources to annotate and mine biological features from high-throughput data. The underlying database management systems for most bioinformatics software are based on a relational model. Modern non-relational databases offer an alternative that has flexibility, scalability, and a non-rigid design schema. Moreover, with an accelerated development pace, non-relational databases like CouchDB can be ideal tools to construct bioinformatics utilities. We describe CouchDB by presenting three new bioinformatics resources: (a) geneSmash, which collates data from bioinformatics resources and provides automated gene-centric annotations, (b) drugBase, a database of drug-target interactions with a web interface powered by geneSmash, and (c) HapMap-CN, which provides a web interface to query copy number variations from three SNP-chip HapMap datasets. In addition to the web sites, all three systems can be accessed programmatically via web services. PMID:22609849

  15. Rediscovering Don Swanson: The Past, Present and Future of Literature-based Discovery

    Directory of Open Access Journals (Sweden)

    Neil R. Smalheiser

    2017-12-01

    Full Text Available Purpose: The late Don R. Swanson was well appreciated during his lifetime as Dean of the Graduate Library School at University of Chicago, as winner of the American Society for Information Science Award of Merit for 2000, and as author of many seminal articles. In this informal essay, I will give my personal perspective on Don’s contributions to science, and outline some current and future directions in literature-based discovery that are rooted in concepts that he developed. Design/methodology/approach: Personal recollections and literature review. Findings: The Swanson A-B-C model of literature-based discovery has been successfully used by laboratory investigators analyzing their findings and hypotheses. It continues to be a fertile area of research in a wide range of application areas including text mining, drug repurposing, studies of scientific innovation, knowledge discovery in databases, and bioinformatics. Recently, additional modes of discovery that do not follow the A-B-C model have also been proposed and explored (e.g. so-called storytelling, gaps, analogies, link prediction, negative consensus, outliers, and revival of neglected or discarded research questions. Research limitations: This paper reflects the opinions of the author and is not a comprehensive nor technically based review of literature-based discovery. Practical implications: The general scientific public is still not aware of the availability of tools for literature-based discovery. Our Arrowsmith project site maintains a suite of discovery tools that are free and open to the public (http://arrowsmith.psych.uic.edu, as does BITOLA which is maintained by Dmitar Hristovski (http:// http://ibmi.mf.uni-lj.si/bitola, and Epiphanet which is maintained by Trevor Cohen (http://epiphanet.uth.tmc.edu/. Bringing user-friendly tools to the public should be a high priority, since even more than advancing basic research in informatics, it is vital that we ensure that scientists

  16. Integrating GIS components with knowledge discovery technology for environmental health decision support.

    Science.gov (United States)

    Bédard, Yvan; Gosselin, Pierre; Rivest, Sonia; Proulx, Marie-Josée; Nadeau, Martin; Lebel, Germain; Gagnon, Marie-France

    2003-04-01

    This paper presents a new category of decision-support tools that builds on today's Geographic Information Systems (GIS) and On-Line Analytical Processing (OLAP) technologies to facilitate Geographic Knowledge Discovery (GKD). This new category, named Spatial OLAP (SOLAP), has been an R&D topic for about 5 years in a few university labs and is now being implemented by early adopters in different fields, including public health where it provides numerous advantages. In this paper, we present an example of a SOLAP application in the field of environmental health: the ICEM-SE project. After having presented this example, we describe the design of this system and explain how it provides fast and easy access to the detailed and aggregated data that are needed for GKD and decision-making in public health. The SOLAP concept is also described and a comparison is made with traditional GIS applications.

  17. promoting self directed learning in simulation based discovery learning environments through intelligent support.

    NARCIS (Netherlands)

    Veermans, K.H.; de Jong, Anthonius J.M.; van Joolingen, Wouter

    2000-01-01

    Providing learners with computer-generated feedback on their learning process in simulationbased discovery environments cannot be based on a detailed model of the learning process due to the “open” character of discovery learning. This paper describes a method for generating adaptive feedback for

  18. A Quick Guide for Building a Successful Bioinformatics Community

    Science.gov (United States)

    Budd, Aidan; Corpas, Manuel; Brazas, Michelle D.; Fuller, Jonathan C.; Goecks, Jeremy; Mulder, Nicola J.; Michaut, Magali; Ouellette, B. F. Francis; Pawlik, Aleksandra; Blomberg, Niklas

    2015-01-01

    “Scientific community” refers to a group of people collaborating together on scientific-research-related activities who also share common goals, interests, and values. Such communities play a key role in many bioinformatics activities. Communities may be linked to a specific location or institute, or involve people working at many different institutions and locations. Education and training is typically an important component of these communities, providing a valuable context in which to develop skills and expertise, while also strengthening links and relationships within the community. Scientific communities facilitate: (i) the exchange and development of ideas and expertise; (ii) career development; (iii) coordinated funding activities; (iv) interactions and engagement with professionals from other fields; and (v) other activities beneficial to individual participants, communities, and the scientific field as a whole. It is thus beneficial at many different levels to understand the general features of successful, high-impact bioinformatics communities; how individual participants can contribute to the success of these communities; and the role of education and training within these communities. We present here a quick guide to building and maintaining a successful, high-impact bioinformatics community, along with an overview of the general benefits of participating in such communities. This article grew out of contributions made by organizers, presenters, panelists, and other participants of the ISMB/ECCB 2013 workshop “The ‘How To Guide’ for Establishing a Successful Bioinformatics Network” at the 21st Annual International Conference on Intelligent Systems for Molecular Biology (ISMB) and the 12th European Conference on Computational Biology (ECCB). PMID:25654371

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

    Science.gov (United States)

    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…

  20. Genomics and bioinformatics resources for translational science in Rosaceae.

    Science.gov (United States)

    Jung, Sook; Main, Dorrie

    2014-01-01

    Recent technological advances in biology promise unprecedented opportunities for rapid and sustainable advancement of crop quality. Following this trend, the Rosaceae research community continues to generate large amounts of genomic, genetic and breeding data. These include annotated whole genome sequences, transcriptome and expression data, proteomic and metabolomic data, genotypic and phenotypic data, and genetic and physical maps. Analysis, storage, integration and dissemination of these data using bioinformatics tools and databases are essential to provide utility of the data for basic, translational and applied research. This review discusses the currently available genomics and bioinformatics resources for the Rosaceae family.

  1. Implementing bioinformatic workflows within the bioextract server

    Science.gov (United States)

    Computational workflows in bioinformatics are becoming increasingly important in the achievement of scientific advances. These workflows typically require the integrated use of multiple, distributed data sources and analytic tools. The BioExtract Server (http://bioextract.org) is a distributed servi...

  2. Bioinformatics in Middle East Program Curricula--A Focus on the Arabian Gulf

    Science.gov (United States)

    Loucif, Samia

    2014-01-01

    The purpose of this paper is to investigate the inclusion of bioinformatics in program curricula in the Middle East, focusing on educational institutions in the Arabian Gulf. Bioinformatics is a multidisciplinary field which has emerged in response to the need for efficient data storage and retrieval, and accurate and fast computational and…

  3. Lowering industry firewalls: pre-competitive informatics initiatives in drug discovery.

    Science.gov (United States)

    Barnes, Michael R; Harland, Lee; Foord, Steven M; Hall, Matthew D; Dix, Ian; Thomas, Scott; Williams-Jones, Bryn I; Brouwer, Cory R

    2009-09-01

    Pharmaceutical research and development is facing substantial challenges that have prompted the industry to shift funding from early- to late-stage projects. Among the effects is a major change in the attitude of many companies to their internal bioinformatics resources: the focus has moved from the vigorous pursuit of intellectual property towards exploration of pre-competitive cross-industry collaborations and engagement with the public domain. High-quality, open and accessible data are the foundation of pre-competitive research, and strong public-private partnerships have considerable potential to enhance public data resources, which would benefit everyone engaged in drug discovery. In this article, we discuss the background to these changes and propose new areas of collaboration in computational biology and chemistry between the public domain and the pharmaceutical industry.

  4. Combining medical informatics and bioinformatics toward tools for personalized medicine.

    Science.gov (United States)

    Sarachan, B D; Simmons, M K; Subramanian, P; Temkin, J M

    2003-01-01

    Key bioinformatics and medical informatics research areas need to be identified to advance knowledge and understanding of disease risk factors and molecular disease pathology in the 21 st century toward new diagnoses, prognoses, and treatments. Three high-impact informatics areas are identified: predictive medicine (to identify significant correlations within clinical data using statistical and artificial intelligence methods), along with pathway informatics and cellular simulations (that combine biological knowledge with advanced informatics to elucidate molecular disease pathology). Initial predictive models have been developed for a pilot study in Huntington's disease. An initial bioinformatics platform has been developed for the reconstruction and analysis of pathways, and work has begun on pathway simulation. A bioinformatics research program has been established at GE Global Research Center as an important technology toward next generation medical diagnostics. We anticipate that 21 st century medical research will be a combination of informatics tools with traditional biology wet lab research, and that this will translate to increased use of informatics techniques in the clinic.

  5. GOBLET: the Global Organisation for Bioinformatics Learning, Education and Training.

    Science.gov (United States)

    Attwood, Teresa K; Atwood, Teresa K; Bongcam-Rudloff, Erik; Brazas, Michelle E; Corpas, Manuel; Gaudet, Pascale; Lewitter, Fran; Mulder, Nicola; Palagi, Patricia M; Schneider, Maria Victoria; van Gelder, Celia W G

    2015-04-01

    In recent years, high-throughput technologies have brought big data to the life sciences. The march of progress has been rapid, leaving in its wake a demand for courses in data analysis, data stewardship, computing fundamentals, etc., a need that universities have not yet been able to satisfy--paradoxically, many are actually closing "niche" bioinformatics courses at a time of critical need. The impact of this is being felt across continents, as many students and early-stage researchers are being left without appropriate skills to manage, analyse, and interpret their data with confidence. This situation has galvanised a group of scientists to address the problems on an international scale. For the first time, bioinformatics educators and trainers across the globe have come together to address common needs, rising above institutional and international boundaries to cooperate in sharing bioinformatics training expertise, experience, and resources, aiming to put ad hoc training practices on a more professional footing for the benefit of all.

  6. GOBLET: The Global Organisation for Bioinformatics Learning, Education and Training

    Science.gov (United States)

    Atwood, Teresa K.; Bongcam-Rudloff, Erik; Brazas, Michelle E.; Corpas, Manuel; Gaudet, Pascale; Lewitter, Fran; Mulder, Nicola; Palagi, Patricia M.; Schneider, Maria Victoria; van Gelder, Celia W. G.

    2015-01-01

    In recent years, high-throughput technologies have brought big data to the life sciences. The march of progress has been rapid, leaving in its wake a demand for courses in data analysis, data stewardship, computing fundamentals, etc., a need that universities have not yet been able to satisfy—paradoxically, many are actually closing “niche” bioinformatics courses at a time of critical need. The impact of this is being felt across continents, as many students and early-stage researchers are being left without appropriate skills to manage, analyse, and interpret their data with confidence. This situation has galvanised a group of scientists to address the problems on an international scale. For the first time, bioinformatics educators and trainers across the globe have come together to address common needs, rising above institutional and international boundaries to cooperate in sharing bioinformatics training expertise, experience, and resources, aiming to put ad hoc training practices on a more professional footing for the benefit of all. PMID:25856076

  7. Community annotation and bioinformatics workforce development in concert--Little Skate Genome Annotation Workshops and Jamborees.

    Science.gov (United States)

    Wang, Qinghua; Arighi, Cecilia N; King, Benjamin L; Polson, Shawn W; Vincent, James; Chen, Chuming; Huang, Hongzhan; Kingham, Brewster F; Page, Shallee T; Rendino, Marc Farnum; Thomas, William Kelley; Udwary, Daniel W; Wu, Cathy H

    2012-01-01

    Recent advances in high-throughput DNA sequencing technologies have equipped biologists with a powerful new set of tools for advancing research goals. The resulting flood of sequence data has made it critically important to train the next generation of scientists to handle the inherent bioinformatic challenges. The North East Bioinformatics Collaborative (NEBC) is undertaking the genome sequencing and annotation of the little skate (Leucoraja erinacea) to promote advancement of bioinformatics infrastructure in our region, with an emphasis on practical education to create a critical mass of informatically savvy life scientists. In support of the Little Skate Genome Project, the NEBC members have developed several annotation workshops and jamborees to provide training in genome sequencing, annotation and analysis. Acting as a nexus for both curation activities and dissemination of project data, a project web portal, SkateBase (http://skatebase.org) has been developed. As a case study to illustrate effective coupling of community annotation with workforce development, we report the results of the Mitochondrial Genome Annotation Jamborees organized to annotate the first completely assembled element of the Little Skate Genome Project, as a culminating experience for participants from our three prior annotation workshops. We are applying the physical/virtual infrastructure and lessons learned from these activities to enhance and streamline the genome annotation workflow, as we look toward our continuing efforts for larger-scale functional and structural community annotation of the L. erinacea genome.

  8. Community annotation and bioinformatics workforce development in concert—Little Skate Genome Annotation Workshops and Jamborees

    Science.gov (United States)

    Wang, Qinghua; Arighi, Cecilia N.; King, Benjamin L.; Polson, Shawn W.; Vincent, James; Chen, Chuming; Huang, Hongzhan; Kingham, Brewster F.; Page, Shallee T.; Farnum Rendino, Marc; Thomas, William Kelley; Udwary, Daniel W.; Wu, Cathy H.

    2012-01-01

    Recent advances in high-throughput DNA sequencing technologies have equipped biologists with a powerful new set of tools for advancing research goals. The resulting flood of sequence data has made it critically important to train the next generation of scientists to handle the inherent bioinformatic challenges. The North East Bioinformatics Collaborative (NEBC) is undertaking the genome sequencing and annotation of the little skate (Leucoraja erinacea) to promote advancement of bioinformatics infrastructure in our region, with an emphasis on practical education to create a critical mass of informatically savvy life scientists. In support of the Little Skate Genome Project, the NEBC members have developed several annotation workshops and jamborees to provide training in genome sequencing, annotation and analysis. Acting as a nexus for both curation activities and dissemination of project data, a project web portal, SkateBase (http://skatebase.org) has been developed. As a case study to illustrate effective coupling of community annotation with workforce development, we report the results of the Mitochondrial Genome Annotation Jamborees organized to annotate the first completely assembled element of the Little Skate Genome Project, as a culminating experience for participants from our three prior annotation workshops. We are applying the physical/virtual infrastructure and lessons learned from these activities to enhance and streamline the genome annotation workflow, as we look toward our continuing efforts for larger-scale functional and structural community annotation of the L. erinacea genome. PMID:22434832

  9. A Survey of Bioinformatics Database and Software Usage through Mining the Literature.

    Directory of Open Access Journals (Sweden)

    Geraint Duck

    Full Text Available Computer-based resources are central to much, if not most, biological and medical research. However, while there is an ever expanding choice of bioinformatics resources to use, described within the biomedical literature, little work to date has provided an evaluation of the full range of availability or levels of usage of database and software resources. Here we use text mining to process the PubMed Central full-text corpus, identifying mentions of databases or software within the scientific literature. We provide an audit of the resources contained within the biomedical literature, and a comparison of their relative usage, both over time and between the sub-disciplines of bioinformatics, biology and medicine. We find that trends in resource usage differs between these domains. The bioinformatics literature emphasises novel resource development, while database and software usage within biology and medicine is more stable and conservative. Many resources are only mentioned in the bioinformatics literature, with a relatively small number making it out into general biology, and fewer still into the medical literature. In addition, many resources are seeing a steady decline in their usage (e.g., BLAST, SWISS-PROT, though some are instead seeing rapid growth (e.g., the GO, R. We find a striking imbalance in resource usage with the top 5% of resource names (133 names accounting for 47% of total usage, and over 70% of resources extracted being only mentioned once each. While these results highlight the dynamic and creative nature of bioinformatics research they raise questions about software reuse, choice and the sharing of bioinformatics practice. Is it acceptable that so many resources are apparently never reused? Finally, our work is a step towards automated extraction of scientific method from text. We make the dataset generated by our study available under the CC0 license here: http://dx.doi.org/10.6084/m9.figshare.1281371.

  10. Relax with CouchDB--into the non-relational DBMS era of bioinformatics.

    Science.gov (United States)

    Manyam, Ganiraju; Payton, Michelle A; Roth, Jack A; Abruzzo, Lynne V; Coombes, Kevin R

    2012-07-01

    With the proliferation of high-throughput technologies, genome-level data analysis has become common in molecular biology. Bioinformaticians are developing extensive resources to annotate and mine biological features from high-throughput data. The underlying database management systems for most bioinformatics software are based on a relational model. Modern non-relational databases offer an alternative that has flexibility, scalability, and a non-rigid design schema. Moreover, with an accelerated development pace, non-relational databases like CouchDB can be ideal tools to construct bioinformatics utilities. We describe CouchDB by presenting three new bioinformatics resources: (a) geneSmash, which collates data from bioinformatics resources and provides automated gene-centric annotations, (b) drugBase, a database of drug-target interactions with a web interface powered by geneSmash, and (c) HapMap-CN, which provides a web interface to query copy number variations from three SNP-chip HapMap datasets. In addition to the web sites, all three systems can be accessed programmatically via web services. Copyright © 2012 Elsevier Inc. All rights reserved.

  11. Using registries to integrate bioinformatics tools and services into workbench environments

    DEFF Research Database (Denmark)

    Ménager, Hervé; Kalaš, Matúš; Rapacki, Kristoffer

    2016-01-01

    The diversity and complexity of bioinformatics resources presents significant challenges to their localisation, deployment and use, creating a need for reliable systems that address these issues. Meanwhile, users demand increasingly usable and integrated ways to access and analyse data, especially......, a software component that will ease the integration of bioinformatics resources in a workbench environment, using their description provided by the existing ELIXIR Tools and Data Services Registry....

  12. Cloud-based bioinformatics workflow platform for large-scale next-generation sequencing analyses.

    Science.gov (United States)

    Liu, Bo; Madduri, Ravi K; Sotomayor, Borja; Chard, Kyle; Lacinski, Lukasz; Dave, Utpal J; Li, Jianqiang; Liu, Chunchen; Foster, Ian T

    2014-06-01

    Due to the upcoming data deluge of genome data, the need for storing and processing large-scale genome data, easy access to biomedical analyses tools, efficient data sharing and retrieval has presented significant challenges. The variability in data volume results in variable computing and storage requirements, therefore biomedical researchers are pursuing more reliable, dynamic and convenient methods for conducting sequencing analyses. This paper proposes a Cloud-based bioinformatics workflow platform for large-scale next-generation sequencing analyses, which enables reliable and highly scalable execution of sequencing analyses workflows in a fully automated manner. Our platform extends the existing Galaxy workflow system by adding data management capabilities for transferring large quantities of data efficiently and reliably (via Globus Transfer), domain-specific analyses tools preconfigured for immediate use by researchers (via user-specific tools integration), automatic deployment on Cloud for on-demand resource allocation and pay-as-you-go pricing (via Globus Provision), a Cloud provisioning tool for auto-scaling (via HTCondor scheduler), and the support for validating the correctness of workflows (via semantic verification tools). Two bioinformatics workflow use cases as well as performance evaluation are presented to validate the feasibility of the proposed approach. Copyright © 2014 Elsevier Inc. All rights reserved.

  13. Accurate Prediction of Coronary Artery Disease Using Bioinformatics Algorithms

    Directory of Open Access Journals (Sweden)

    Hajar Shafiee

    2016-06-01

    Full Text Available Background and Objectives: Cardiovascular disease is one of the main causes of death in developed and Third World countries. According to the statement of the World Health Organization, it is predicted that death due to heart disease will rise to 23 million by 2030. According to the latest statistics reported by Iran’s Minister of health, 3.39% of all deaths are attributed to cardiovascular diseases and 19.5% are related to myocardial infarction. The aim of this study was to predict coronary artery disease using data mining algorithms. Methods: In this study, various bioinformatics algorithms, such as decision trees, neural networks, support vector machines, clustering, etc., were used to predict coronary heart disease. The data used in this study was taken from several valid databases (including 14 data. Results: In this research, data mining techniques can be effectively used to diagnose different diseases, including coronary artery disease. Also, for the first time, a prediction system based on support vector machine with the best possible accuracy was introduced. Conclusion: The results showed that among the features, thallium scan variable is the most important feature in the diagnosis of heart disease. Designation of machine prediction models, such as support vector machine learning algorithm can differentiate between sick and healthy individuals with 100% accuracy.

  14. pocketZebra: a web-server for automated selection and classification of subfamily-specific binding sites by bioinformatic analysis of diverse protein families.

    Science.gov (United States)

    Suplatov, Dmitry; Kirilin, Eugeny; Arbatsky, Mikhail; Takhaveev, Vakil; Svedas, Vytas

    2014-07-01

    The new web-server pocketZebra implements the power of bioinformatics and geometry-based structural approaches to identify and rank subfamily-specific binding sites in proteins by functional significance, and select particular positions in the structure that determine selective accommodation of ligands. A new scoring function has been developed to annotate binding sites by the presence of the subfamily-specific positions in diverse protein families. pocketZebra web-server has multiple input modes to meet the needs of users with different experience in bioinformatics. The server provides on-site visualization of the results as well as off-line version of the output in annotated text format and as PyMol sessions ready for structural analysis. pocketZebra can be used to study structure-function relationship and regulation in large protein superfamilies, classify functionally important binding sites and annotate proteins with unknown function. The server can be used to engineer ligand-binding sites and allosteric regulation of enzymes, or implemented in a drug discovery process to search for potential molecular targets and novel selective inhibitors/effectors. The server, documentation and examples are freely available at http://biokinet.belozersky.msu.ru/pocketzebra and there are no login requirements. © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.

  15. Molecular property diagnostic suite (MPDS): Development of disease-specific open source web portals for drug discovery.

    Science.gov (United States)

    Nagamani, S; Gaur, A S; Tanneeru, K; Muneeswaran, G; Madugula, S S; Consortium, Mpds; Druzhilovskiy, D; Poroikov, V V; Sastry, G N

    2017-11-01

    Molecular property diagnostic suite (MPDS) is a Galaxy-based open source drug discovery and development platform. MPDS web portals are designed for several diseases, such as tuberculosis, diabetes mellitus, and other metabolic disorders, specifically aimed to evaluate and estimate the drug-likeness of a given molecule. MPDS consists of three modules, namely data libraries, data processing, and data analysis tools which are configured and interconnected to assist drug discovery for specific diseases. The data library module encompasses vast information on chemical space, wherein the MPDS compound library comprises 110.31 million unique molecules generated from public domain databases. Every molecule is assigned with a unique ID and card, which provides complete information for the molecule. Some of the modules in the MPDS are specific to the diseases, while others are non-specific. Importantly, a suitably altered protocol can be effectively generated for another disease-specific MPDS web portal by modifying some of the modules. Thus, the MPDS suite of web portals shows great promise to emerge as disease-specific portals of great value, integrating chemoinformatics, bioinformatics, molecular modelling, and structure- and analogue-based drug discovery approaches.

  16. p3d – Python module for structural bioinformatics

    Directory of Open Access Journals (Sweden)

    Fufezan Christian

    2009-08-01

    Full Text Available Abstract Background High-throughput bioinformatic analysis tools are needed to mine the large amount of structural data via knowledge based approaches. The development of such tools requires a robust interface to access the structural data in an easy way. For this the Python scripting language is the optimal choice since its philosophy is to write an understandable source code. Results p3d is an object oriented Python module that adds a simple yet powerful interface to the Python interpreter to process and analyse three dimensional protein structure files (PDB files. p3d's strength arises from the combination of a very fast spatial access to the structural data due to the implementation of a binary space partitioning (BSP tree, b set theory and c functions that allow to combine a and b and that use human readable language in the search queries rather than complex computer language. All these factors combined facilitate the rapid development of bioinformatic tools that can perform quick and complex analyses of protein structures. Conclusion p3d is the perfect tool to quickly develop tools for structural bioinformatics using the Python scripting language.

  17. A comparison of common programming languages used in bioinformatics.

    Science.gov (United States)

    Fourment, Mathieu; Gillings, Michael R

    2008-02-05

    The performance of different programming languages has previously been benchmarked using abstract mathematical algorithms, but not using standard bioinformatics algorithms. We compared the memory usage and speed of execution for three standard bioinformatics methods, implemented in programs using one of six different programming languages. Programs for the Sellers algorithm, the Neighbor-Joining tree construction algorithm and an algorithm for parsing BLAST file outputs were implemented in C, C++, C#, Java, Perl and Python. Implementations in C and C++ were fastest and used the least memory. Programs in these languages generally contained more lines of code. Java and C# appeared to be a compromise between the flexibility of Perl and Python and the fast performance of C and C++. The relative performance of the tested languages did not change from Windows to Linux and no clear evidence of a faster operating system was found. Source code and additional information are available from http://www.bioinformatics.org/benchmark/. This benchmark provides a comparison of six commonly used programming languages under two different operating systems. The overall comparison shows that a developer should choose an appropriate language carefully, taking into account the performance expected and the library availability for each language.

  18. Bioinformatics process management: information flow via a computational journal

    Directory of Open Access Journals (Sweden)

    Lushington Gerald

    2007-12-01

    Full Text Available Abstract This paper presents the Bioinformatics Computational Journal (BCJ, a framework for conducting and managing computational experiments in bioinformatics and computational biology. These experiments often involve series of computations, data searches, filters, and annotations which can benefit from a structured environment. Systems to manage computational experiments exist, ranging from libraries with standard data models to elaborate schemes to chain together input and output between applications. Yet, although such frameworks are available, their use is not widespread–ad hoc scripts are often required to bind applications together. The BCJ explores another solution to this problem through a computer based environment suitable for on-site use, which builds on the traditional laboratory notebook paradigm. It provides an intuitive, extensible paradigm designed for expressive composition of applications. Extensive features facilitate sharing data, computational methods, and entire experiments. By focusing on the bioinformatics and computational biology domain, the scope of the computational framework was narrowed, permitting us to implement a capable set of features for this domain. This report discusses the features determined critical by our system and other projects, along with design issues. We illustrate the use of our implementation of the BCJ on two domain-specific examples.

  19. The eBioKit, a stand-alone educational platform for bioinformatics.

    Science.gov (United States)

    Hernández-de-Diego, Rafael; de Villiers, Etienne P; Klingström, Tomas; Gourlé, Hadrien; Conesa, Ana; Bongcam-Rudloff, Erik

    2017-09-01

    Bioinformatics skills have become essential for many research areas; however, the availability of qualified researchers is usually lower than the demand and training to increase the number of able bioinformaticians is an important task for the bioinformatics community. When conducting training or hands-on tutorials, the lack of control over the analysis tools and repositories often results in undesirable situations during training, as unavailable online tools or version conflicts may delay, complicate, or even prevent the successful completion of a training event. The eBioKit is a stand-alone educational platform that hosts numerous tools and databases for bioinformatics research and allows training to take place in a controlled environment. A key advantage of the eBioKit over other existing teaching solutions is that all the required software and databases are locally installed on the system, significantly reducing the dependence on the internet. Furthermore, the architecture of the eBioKit has demonstrated itself to be an excellent balance between portability and performance, not only making the eBioKit an exceptional educational tool but also providing small research groups with a platform to incorporate bioinformatics analysis in their research. As a result, the eBioKit has formed an integral part of training and research performed by a wide variety of universities and organizations such as the Pan African Bioinformatics Network (H3ABioNet) as part of the initiative Human Heredity and Health in Africa (H3Africa), the Southern Africa Network for Biosciences (SAnBio) initiative, the Biosciences eastern and central Africa (BecA) hub, and the International Glossina Genome Initiative.

  20. The structural bioinformatics library: modeling in biomolecular science and beyond.

    Science.gov (United States)

    Cazals, Frédéric; Dreyfus, Tom

    2017-04-01

    Software in structural bioinformatics has mainly been application driven. To favor practitioners seeking off-the-shelf applications, but also developers seeking advanced building blocks to develop novel applications, we undertook the design of the Structural Bioinformatics Library ( SBL , http://sbl.inria.fr ), a generic C ++/python cross-platform software library targeting complex problems in structural bioinformatics. Its tenet is based on a modular design offering a rich and versatile framework allowing the development of novel applications requiring well specified complex operations, without compromising robustness and performances. The SBL involves four software components (1-4 thereafter). For end-users, the SBL provides ready to use, state-of-the-art (1) applications to handle molecular models defined by unions of balls, to deal with molecular flexibility, to model macro-molecular assemblies. These applications can also be combined to tackle integrated analysis problems. For developers, the SBL provides a broad C ++ toolbox with modular design, involving core (2) algorithms , (3) biophysical models and (4) modules , the latter being especially suited to develop novel applications. The SBL comes with a thorough documentation consisting of user and reference manuals, and a bugzilla platform to handle community feedback. The SBL is available from http://sbl.inria.fr. Frederic.Cazals@inria.fr. Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

  1. The SIB Swiss Institute of Bioinformatics' resources: focus on curated databases

    OpenAIRE

    Bultet, Lisandra Aguilar; Aguilar Rodriguez, Jose; Ahrens, Christian H; Ahrne, Erik Lennart; Ai, Ni; Aimo, Lucila; Akalin, Altuna; Aleksiev, Tyanko; Alocci, Davide; Altenhoff, Adrian; Alves, Isabel; Ambrosini, Giovanna; Pedone, Pascale Anderle; Angelina, Paolo; Anisimova, Maria

    2016-01-01

    The SIB Swiss Institute of Bioinformatics (www.isb-sib.ch) provides world-class bioinformatics databases, software tools, services and training to the international life science community in academia and industry. These solutions allow life scientists to turn the exponentially growing amount of data into knowledge. Here, we provide an overview of SIB's resources and competence areas, with a strong focus on curated databases and SIB's most popular and widely used resources. In particular, SIB'...

  2. Green Fluorescent Protein-Focused Bioinformatics Laboratory Experiment Suitable for Undergraduates in Biochemistry Courses

    Science.gov (United States)

    Rowe, Laura

    2017-01-01

    An introductory bioinformatics laboratory experiment focused on protein analysis has been developed that is suitable for undergraduate students in introductory biochemistry courses. The laboratory experiment is designed to be potentially used as a "stand-alone" activity in which students are introduced to basic bioinformatics tools and…

  3. Rough-fuzzy pattern recognition applications in bioinformatics and medical imaging

    CERN Document Server

    Maji, Pradipta

    2012-01-01

    Learn how to apply rough-fuzzy computing techniques to solve problems in bioinformatics and medical image processing Emphasizing applications in bioinformatics and medical image processing, this text offers a clear framework that enables readers to take advantage of the latest rough-fuzzy computing techniques to build working pattern recognition models. The authors explain step by step how to integrate rough sets with fuzzy sets in order to best manage the uncertainties in mining large data sets. Chapters are logically organized according to the major phases of pattern recognition systems dev

  4. Bioinformatics and moonlighting proteins

    Directory of Open Access Journals (Sweden)

    Sergio eHernández

    2015-06-01

    Full Text Available 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 analyse 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, 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 have 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.

  5. Best practices in bioinformatics training for life scientists.

    KAUST Repository

    Via, Allegra; Blicher, Thomas; Bongcam-Rudloff, Erik; Brazas, Michelle D; Brooksbank, Cath; Budd, Aidan; De Las Rivas, Javier; Dreyer, Jacqueline; Fernandes, Pedro L; van Gelder, Celia; Jacob, Joachim; Jimenez, Rafael C; Loveland, Jane; Moran, Federico; Mulder, Nicola; Nyrö nen, Tommi; Rother, Kristian; Schneider, Maria Victoria; Attwood, Teresa K

    2013-01-01

    concepts. Providing bioinformatics training to empower life scientists to handle and analyse their data efficiently, and progress their research, is a challenge across the globe. Delivering good training goes beyond traditional lectures and resource

  6. Privacy Preserving PCA on Distributed Bioinformatics Datasets

    Science.gov (United States)

    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…

  7. Engaging Students in a Bioinformatics Activity to Introduce Gene Structure and Function

    Directory of Open Access Journals (Sweden)

    Barbara J. May

    2013-02-01

    Full Text Available Bioinformatics spans many fields of biological research and plays a vital role in mining and analyzing data. Therefore, there is an ever-increasing need for students to understand not only what can be learned from this data, but also how to use basic bioinformatics tools.  This activity is designed to provide secondary and undergraduate biology students to a hands-on activity meant to explore and understand gene structure with the use of basic bioinformatic tools.  Students are provided an “unknown” sequence from which they are asked to use a free online gene finder program to identify the gene. Students then predict the putative function of this gene with the use of additional online databases.

  8. Rise and demise of bioinformatics? Promise and progress.

    Directory of Open Access Journals (Sweden)

    Christos A Ouzounis

    Full Text Available The field of bioinformatics and computational biology has gone through a number of transformations during the past 15 years, establishing itself as a key component of new biology. This spectacular growth has been challenged by a number of disruptive changes in science and technology. Despite the apparent fatigue of the linguistic use of the term itself, bioinformatics has grown perhaps to a point beyond recognition. We explore both historical aspects and future trends and argue that as the field expands, key questions remain unanswered and acquire new meaning while at the same time the range of applications is widening to cover an ever increasing number of biological disciplines. These trends appear to be pointing to a redefinition of certain objectives, milestones, and possibly the field itself.

  9. Meeting review: 2002 O'Reilly Bioinformatics Technology Conference.

    Science.gov (United States)

    Counsell, Damian

    2002-01-01

    At the end of January I travelled to the States to speak at and attend the first O'Reilly Bioinformatics Technology Conference. It was a large, well-organized and diverse meeting with an interesting history. Although the meeting was not a typical academic conference, its style will, I am sure, become more typical of meetings in both biological and computational sciences.Speakers at the event included prominent bioinformatics researchers such as Ewan Birney, Terry Gaasterland and Lincoln Stein; authors and leaders in the open source programming community like Damian Conway and Nat Torkington; and representatives from several publishing companies including the Nature Publishing Group, Current Science Group and the President of O'Reilly himself, Tim O'Reilly. There were presentations, tutorials, debates, quizzes and even a 'jam session' for musical bioinformaticists.

  10. Can Full Duplex reduce the discovery time in D2D Communication?

    DEFF Research Database (Denmark)

    Gatnau, Marta; Berardinelli, Gilberto; Mahmood, Nurul Huda

    2016-01-01

    Device-to-device (D2D) communication is considered as one of the key technologies to support new types of services, such as public safety and proximity-based applications. D2D communication requires a discovery phase, i.e., the node awareness procedure prior to the communication phase. Conventional...... half duplex transmission may not be sufficient to provide fast discovery and cope with the strict latency targets of future 5G services. On the other hand, in-band full duplex, by allowing simultaneous transmission and reception, may complete the discovery phase faster. In this paper, the potential...... of full duplex in providing fast discovery for the next 5th generation (5G) system supporting D2D communication is investigated. A design for such system is presented and evaluated via simulations, showing that full duplex can accelerate the discovery phase by supporting a higher transmission probability...

  11. The Computer Revolution in Science: Steps towards the realization of computer-supported discovery environments

    NARCIS (Netherlands)

    de Jong, Hidde; Rip, Arie

    1997-01-01

    The tools that scientists use in their search processes together form so-called discovery environments. The promise of artificial intelligence and other branches of computer science is to radically transform conventional discovery environments by equipping scientists with a range of powerful

  12. A lightweight, flow-based toolkit for parallel and distributed bioinformatics pipelines

    Directory of Open Access Journals (Sweden)

    Cieślik Marcin

    2011-02-01

    Full Text Available Abstract Background Bioinformatic analyses typically proceed as chains of data-processing tasks. A pipeline, or 'workflow', is a well-defined protocol, with a specific structure defined by the topology of data-flow interdependencies, and a particular functionality arising from the data transformations applied at each step. In computer science, the dataflow programming (DFP paradigm defines software systems constructed in this manner, as networks of message-passing components. Thus, bioinformatic workflows can be naturally mapped onto DFP concepts. Results To enable the flexible creation and execution of bioinformatics dataflows, we have written a modular framework for parallel pipelines in Python ('PaPy'. A PaPy workflow is created from re-usable components connected by data-pipes into a directed acyclic graph, which together define nested higher-order map functions. The successive functional transformations of input data are evaluated on flexibly pooled compute resources, either local or remote. Input items are processed in batches of adjustable size, all flowing one to tune the trade-off between parallelism and lazy-evaluation (memory consumption. An add-on module ('NuBio' facilitates the creation of bioinformatics workflows by providing domain specific data-containers (e.g., for biomolecular sequences, alignments, structures and functionality (e.g., to parse/write standard file formats. Conclusions PaPy offers a modular framework for the creation and deployment of parallel and distributed data-processing workflows. Pipelines derive their functionality from user-written, data-coupled components, so PaPy also can be viewed as a lightweight toolkit for extensible, flow-based bioinformatics data-processing. The simplicity and flexibility of distributed PaPy pipelines may help users bridge the gap between traditional desktop/workstation and grid computing. PaPy is freely distributed as open-source Python code at http://muralab.org/PaPy, and

  13. RISE OF BIOINFORMATICS AND COMPUTATIONAL BIOLOGY IN INDIA: A LOOK THROUGH PUBLICATIONS

    Directory of Open Access Journals (Sweden)

    Anjali Srivastava

    2017-09-01

    Full Text Available Computational biology and bioinformatics have been part and parcel of biomedical research for few decades now. However, the institutionalization of bioinformatics research took place with the establishment of Distributed Information Centres (DISCs in the research institutions of repute in various disciplines by the Department of Biotechnology, Government of India. Though, at initial stages, this endeavor was mainly focused on providing infrastructure for using information technology and internet based communication and tools for carrying out computational biology and in-silico assisted research in varied arena of research starting from disease biology to agricultural crops, spices, veterinary science and many more, the natural outcome of establishment of such facilities resulted into new experiments with bioinformatics tools. Thus, Biotechnology Information Systems (BTIS grew into a solid movement and a large number of publications started coming out of these centres. In the end of last century, bioinformatics started developing like a full-fledged research subject. In the last decade, a need was felt to actually make a factual estimation of the result of this endeavor of DBT which had, by then, established about two hundred centres in almost all disciplines of biomedical research. In a bid to evaluate the efforts and outcome of these centres, BTIS Centre at CSIR-CDRI, Lucknow was entrusted with collecting and collating the publications of these centres. However, when the full data was compiled, the DBT task force felt that the study must include Non-BTIS centres also so as to expand the report to have a glimpse of bioinformatics publications from the country.

  14. Bioinformatics: A History of Evolution "In Silico"

    Science.gov (United States)

    Ondrej, Vladan; Dvorak, Petr

    2012-01-01

    Bioinformatics, biological databases, and the worldwide use of computers have accelerated biological research in many fields, such as evolutionary biology. Here, we describe a primer of nucleotide sequence management and the construction of a phylogenetic tree with two examples; the two selected are from completely different groups of organisms:…

  15. Protein raftophilicity. How bioinformatics can help membranologists

    DEFF Research Database (Denmark)

    Nielsen, Henrik; Sperotto, Maria Maddalena

    )-based bioinformatics approach. The ANN was trained to recognize feature-based patterns in proteins that are considered to be associated with lipid rafts. The trained ANN was then used to predict protein raftophilicity. We found that, in the case of α-helical membrane proteins, their hydrophobic length does not affect...

  16. Development and implementation of a bioinformatics online ...

    African Journals Online (AJOL)

    Thus, there is the need for appropriate strategies of introducing the basic components of this emerging scientific field to part of the African populace through the development of an online distance education learning tool. This study involved the design of a bioinformatics online distance educative tool an implementation of ...

  17. H3ABioNet, a sustainable pan-African bioinformatics network for human heredity and health in Africa

    Science.gov (United States)

    Mulder, Nicola J.; Adebiyi, Ezekiel; Alami, Raouf; Benkahla, Alia; Brandful, James; Doumbia, Seydou; Everett, Dean; Fadlelmola, Faisal M.; Gaboun, Fatima; Gaseitsiwe, Simani; Ghazal, Hassan; Hazelhurst, Scott; Hide, Winston; Ibrahimi, Azeddine; Jaufeerally Fakim, Yasmina; Jongeneel, C. Victor; Joubert, Fourie; Kassim, Samar; Kayondo, Jonathan; Kumuthini, Judit; Lyantagaye, Sylvester; Makani, Julie; Mansour Alzohairy, Ahmed; Masiga, Daniel; Moussa, Ahmed; Nash, Oyekanmi; Ouwe Missi Oukem-Boyer, Odile; Owusu-Dabo, Ellis; Panji, Sumir; Patterton, Hugh; Radouani, Fouzia; Sadki, Khalid; Seghrouchni, Fouad; Tastan Bishop, Özlem; Tiffin, Nicki; Ulenga, Nzovu

    2016-01-01

    The application of genomics technologies to medicine and biomedical research is increasing in popularity, made possible by new high-throughput genotyping and sequencing technologies and improved data analysis capabilities. Some of the greatest genetic diversity among humans, animals, plants, and microbiota occurs in Africa, yet genomic research outputs from the continent are limited. The Human Heredity and Health in Africa (H3Africa) initiative was established to drive the development of genomic research for human health in Africa, and through recognition of the critical role of bioinformatics in this process, spurred the establishment of H3ABioNet, a pan-African bioinformatics network for H3Africa. The limitations in bioinformatics capacity on the continent have been a major contributory factor to the lack of notable outputs in high-throughput biology research. Although pockets of high-quality bioinformatics teams have existed previously, the majority of research institutions lack experienced faculty who can train and supervise bioinformatics students. H3ABioNet aims to address this dire need, specifically in the area of human genetics and genomics, but knock-on effects are ensuring this extends to other areas of bioinformatics. Here, we describe the emergence of genomics research and the development of bioinformatics in Africa through H3ABioNet. PMID:26627985

  18. Analysis of requirements for teaching materials based on the course bioinformatics for plant metabolism

    Science.gov (United States)

    Balqis, Widodo, Lukiati, Betty; Amin, Mohamad

    2017-05-01

    A way to improve the quality of learning in the course of Plant Metabolism in the Department of Biology, State University of Malang, is to develop teaching materials. This research evaluates the needs of bioinformatics-based teaching material in the course Plant Metabolism by the Analyze, Design, Develop, Implement, and Evaluate (ADDIE) development model. Data were collected through questionnaires distributed to the students in the Plant Metabolism course of the Department of Biology, University of Malang, and analysis of the plan of lectures semester (RPS). Learning gains of this course show that it is not yet integrated into the field of bioinformatics. All respondents stated that plant metabolism books do not include bioinformatics and fail to explain the metabolism of a chemical compound of a local plant in Indonesia. Respondents thought that bioinformatics can explain examples and metabolism of a secondary metabolite analysis techniques and discuss potential medicinal compounds from local plants. As many as 65% of the respondents said that the existing metabolism book could not be used to understand secondary metabolism in lectures of plant metabolism. Therefore, the development of teaching materials including plant metabolism-based bioinformatics is important to improve the understanding of the lecture material in plant metabolism.

  19. SegMine workflows for semantic microarray data analysis in Orange4WS

    Directory of Open Access Journals (Sweden)

    Kulovesi Kimmo

    2011-10-01

    Full Text Available Abstract Background In experimental data analysis, bioinformatics researchers increasingly rely on tools that enable the composition and reuse of scientific workflows. The utility of current bioinformatics workflow environments can be significantly increased by offering advanced data mining services as workflow components. Such services can support, for instance, knowledge discovery from diverse distributed data and knowledge sources (such as GO, KEGG, PubMed, and experimental databases. Specifically, cutting-edge data analysis approaches, such as semantic data mining, link discovery, and visualization, have not yet been made available to researchers investigating complex biological datasets. Results We present a new methodology, SegMine, for semantic analysis of microarray data by exploiting general biological knowledge, and a new workflow environment, Orange4WS, with integrated support for web services in which the SegMine methodology is implemented. The SegMine methodology consists of two main steps. First, the semantic subgroup discovery algorithm is used to construct elaborate rules that identify enriched gene sets. Then, a link discovery service is used for the creation and visualization of new biological hypotheses. The utility of SegMine, implemented as a set of workflows in Orange4WS, is demonstrated in two microarray data analysis applications. In the analysis of senescence in human stem cells, the use of SegMine resulted in three novel research hypotheses that could improve understanding of the underlying mechanisms of senescence and identification of candidate marker genes. Conclusions Compared to the available data analysis systems, SegMine offers improved hypothesis generation and data interpretation for bioinformatics in an easy-to-use integrated workflow environment.

  20. A BIOINFORMATIC STRATEGY TO RAPIDLY CHARACTERIZE CDNA LIBRARIES

    Science.gov (United States)

    A Bioinformatic Strategy to Rapidly Characterize cDNA LibrariesG. Charles Ostermeier1, David J. Dix2 and Stephen A. Krawetz1.1Departments of Obstetrics and Gynecology, Center for Molecular Medicine and Genetics, & Institute for Scientific Computing, Wayne State Univer...

  1. The Critical Role of Organic Chemistry in Drug Discovery.

    Science.gov (United States)

    Rotella, David P

    2016-10-19

    Small molecules remain the backbone for modern drug discovery. They are conceived and synthesized by medicinal chemists, many of whom were originally trained as organic chemists. Support from government and industry to provide training and personnel for continued development of this critical skill set has been declining for many years. This Viewpoint highlights the value of organic chemistry and organic medicinal chemists in the complex journey of drug discovery as a reminder that basic science support must be restored.

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

    Science.gov (United States)

    El-Kalioby, Mohamed; Abouelhoda, Mohamed; Krüger, Jan; Giegerich, Robert; Sczyrba, Alexander; Wall, Dennis P; Tonellato, Peter

    2012-01-01

    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. 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. 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.

  3. Exploring Cystic Fibrosis Using Bioinformatics Tools: A Module Designed for the Freshman Biology Course

    Science.gov (United States)

    Zhang, Xiaorong

    2011-01-01

    We incorporated a bioinformatics component into the freshman biology course that allows students to explore cystic fibrosis (CF), a common genetic disorder, using bioinformatics tools and skills. Students learn about CF through searching genetic databases, analyzing genetic sequences, and observing the three-dimensional structures of proteins…

  4. 2nd Colombian Congress on Computational Biology and Bioinformatics

    CERN Document Server

    Cristancho, Marco; Isaza, Gustavo; Pinzón, Andrés; Rodríguez, Juan

    2014-01-01

    This volume compiles accepted contributions for the 2nd Edition of the Colombian Computational Biology and Bioinformatics Congress CCBCOL, after a rigorous review process in which 54 papers were accepted for publication from 119 submitted contributions. Bioinformatics and Computational Biology are areas of knowledge that have emerged due to advances that have taken place in the Biological Sciences and its integration with Information Sciences. The expansion of projects involving the study of genomes has led the way in the production of vast amounts of sequence data which needs to be organized, analyzed and stored to understand phenomena associated with living organisms related to their evolution, behavior in different ecosystems, and the development of applications that can be derived from this analysis.  .

  5. BEAM web server: a tool for structural RNA motif discovery.

    Science.gov (United States)

    Pietrosanto, Marco; Adinolfi, Marta; Casula, Riccardo; Ausiello, Gabriele; Ferrè, Fabrizio; Helmer-Citterich, Manuela

    2018-03-15

    RNA structural motif finding is a relevant problem that becomes computationally hard when working on high-throughput data (e.g. eCLIP, PAR-CLIP), often represented by thousands of RNA molecules. Currently, the BEAM server is the only web tool capable to handle tens of thousands of RNA in input with a motif discovery procedure that is only limited by the current secondary structure prediction accuracies. The recently developed method BEAM (BEAr Motifs finder) can analyze tens of thousands of RNA molecules and identify RNA secondary structure motifs associated to a measure of their statistical significance. BEAM is extremely fast thanks to the BEAR encoding that transforms each RNA secondary structure in a string of characters. BEAM also exploits the evolutionary knowledge contained in a substitution matrix of secondary structure elements, extracted from the RFAM database of families of homologous RNAs. The BEAM web server has been designed to streamline data pre-processing by automatically handling folding and encoding of RNA sequences, giving users a choice for the preferred folding program. The server provides an intuitive and informative results page with the list of secondary structure motifs identified, the logo of each motif, its significance, graphic representation and information about its position in the RNA molecules sharing it. The web server is freely available at http://beam.uniroma2.it/ and it is implemented in NodeJS and Python with all major browsers supported. marco.pietrosanto@uniroma2.it. Supplementary data are available at Bioinformatics online.

  6. KBWS: an EMBOSS associated package for accessing bioinformatics web services.

    Science.gov (United States)

    Oshita, Kazuki; Arakawa, Kazuharu; Tomita, Masaru

    2011-04-29

    The availability of bioinformatics web-based services is rapidly proliferating, for their interoperability and ease of use. The next challenge is in the integration of these services in the form of workflows, and several projects are already underway, standardizing the syntax, semantics, and user interfaces. In order to deploy the advantages of web services with locally installed tools, here we describe a collection of proxy client tools for 42 major bioinformatics web services in the form of European Molecular Biology Open Software Suite (EMBOSS) UNIX command-line tools. EMBOSS provides sophisticated means for discoverability and interoperability for hundreds of tools, and our package, named the Keio Bioinformatics Web Service (KBWS), adds functionalities of local and multiple alignment of sequences, phylogenetic analyses, and prediction of cellular localization of proteins and RNA secondary structures. This software implemented in C is available under GPL from http://www.g-language.org/kbws/ and GitHub repository http://github.com/cory-ko/KBWS. Users can utilize the SOAP services implemented in Perl directly via WSDL file at http://soap.g-language.org/kbws.wsdl (RPC Encoded) and http://soap.g-language.org/kbws_dl.wsdl (Document/literal).

  7. KBWS: an EMBOSS associated package for accessing bioinformatics web services

    Directory of Open Access Journals (Sweden)

    Tomita Masaru

    2011-04-01

    Full Text Available Abstract The availability of bioinformatics web-based services is rapidly proliferating, for their interoperability and ease of use. The next challenge is in the integration of these services in the form of workflows, and several projects are already underway, standardizing the syntax, semantics, and user interfaces. In order to deploy the advantages of web services with locally installed tools, here we describe a collection of proxy client tools for 42 major bioinformatics web services in the form of European Molecular Biology Open Software Suite (EMBOSS UNIX command-line tools. EMBOSS provides sophisticated means for discoverability and interoperability for hundreds of tools, and our package, named the Keio Bioinformatics Web Service (KBWS, adds functionalities of local and multiple alignment of sequences, phylogenetic analyses, and prediction of cellular localization of proteins and RNA secondary structures. This software implemented in C is available under GPL from http://www.g-language.org/kbws/ and GitHub repository http://github.com/cory-ko/KBWS. Users can utilize the SOAP services implemented in Perl directly via WSDL file at http://soap.g-language.org/kbws.wsdl (RPC Encoded and http://soap.g-language.org/kbws_dl.wsdl (Document/literal.

  8. Implementing a Web-Based Introductory Bioinformatics Course for Non-Bioinformaticians That Incorporates Practical Exercises

    Science.gov (United States)

    Vincent, Antony T.; Bourbonnais, Yves; Brouard, Jean-Simon; Deveau, Hélène; Droit, Arnaud; Gagné, Stéphane M.; Guertin, Michel; Lemieux, Claude; Rathier, Louis; Charette, Steve J.; Lagüe, Patrick

    2018-01-01

    A recent scientific discipline, bioinformatics, defined as using informatics for the study of biological problems, is now a requirement for the study of biological sciences. Bioinformatics has become such a powerful and popular discipline that several academic institutions have created programs in this field, allowing students to become…

  9. Statistical modelling in biostatistics and bioinformatics selected papers

    CERN Document Server

    Peng, Defen

    2014-01-01

    This book presents selected papers on statistical model development related mainly to the fields of Biostatistics and Bioinformatics. The coverage of the material falls squarely into the following categories: (a) Survival analysis and multivariate survival analysis, (b) Time series and longitudinal data analysis, (c) Statistical model development and (d) Applied statistical modelling. Innovations in statistical modelling are presented throughout each of the four areas, with some intriguing new ideas on hierarchical generalized non-linear models and on frailty models with structural dispersion, just to mention two examples. The contributors include distinguished international statisticians such as Philip Hougaard, John Hinde, Il Do Ha, Roger Payne and Alessandra Durio, among others, as well as promising newcomers. Some of the contributions have come from researchers working in the BIO-SI research programme on Biostatistics and Bioinformatics, centred on the Universities of Limerick and Galway in Ireland and fu...

  10. Naturally selecting solutions: the use of genetic algorithms in bioinformatics.

    Science.gov (United States)

    Manning, Timmy; Sleator, Roy D; Walsh, Paul

    2013-01-01

    For decades, computer scientists have looked to nature for biologically inspired solutions to computational problems; ranging from robotic control to scheduling optimization. Paradoxically, as we move deeper into the post-genomics era, the reverse is occurring, as biologists and bioinformaticians look to computational techniques, to solve a variety of biological problems. One of the most common biologically inspired techniques are genetic algorithms (GAs), which take the Darwinian concept of natural selection as the driving force behind systems for solving real world problems, including those in the bioinformatics domain. Herein, we provide an overview of genetic algorithms and survey some of the most recent applications of this approach to bioinformatics based problems.

  11. Data integration strategies for bioinformatics with applications in biomarker and network discovery

    NARCIS (Netherlands)

    Hulsman, M.

    2014-01-01

    Nowadays, with large amounts of data becoming available, solving biological quests is becoming more and more a data-driven activity. To support this, there is a need for tools that enable the integration of the many sources of data. This thesis presents several avenues that can be taken, showing how

  12. Providing data science support for systems pharmacology and its implications to drug discovery.

    Science.gov (United States)

    Hart, Thomas; Xie, Lei

    2016-01-01

    The conventional one-drug-one-target-one-disease drug discovery process has been less successful in tracking multi-genic, multi-faceted complex diseases. Systems pharmacology has emerged as a new discipline to tackle the current challenges in drug discovery. The goal of systems pharmacology is to transform huge, heterogeneous, and dynamic biological and clinical data into interpretable and actionable mechanistic models for decision making in drug discovery and patient treatment. Thus, big data technology and data science will play an essential role in systems pharmacology. This paper critically reviews the impact of three fundamental concepts of data science on systems pharmacology: similarity inference, overfitting avoidance, and disentangling causality from correlation. The authors then discuss recent advances and future directions in applying the three concepts of data science to drug discovery, with a focus on proteome-wide context-specific quantitative drug target deconvolution and personalized adverse drug reaction prediction. Data science will facilitate reducing the complexity of systems pharmacology modeling, detecting hidden correlations between complex data sets, and distinguishing causation from correlation. The power of data science can only be fully realized when integrated with mechanism-based multi-scale modeling that explicitly takes into account the hierarchical organization of biological systems from nucleic acid to proteins, to molecular interaction networks, to cells, to tissues, to patients, and to populations.

  13. CLIMB (the Cloud Infrastructure for Microbial Bioinformatics): an online resource for the medical microbiology community.

    Science.gov (United States)

    Connor, Thomas R; Loman, Nicholas J; Thompson, Simon; Smith, Andy; Southgate, Joel; Poplawski, Radoslaw; Bull, Matthew J; Richardson, Emily; Ismail, Matthew; Thompson, Simon Elwood-; Kitchen, Christine; Guest, Martyn; Bakke, Marius; Sheppard, Samuel K; Pallen, Mark J

    2016-09-01

    The increasing availability and decreasing cost of high-throughput sequencing has transformed academic medical microbiology, delivering an explosion in available genomes while also driving advances in bioinformatics. However, many microbiologists are unable to exploit the resulting large genomics datasets because they do not have access to relevant computational resources and to an appropriate bioinformatics infrastructure. Here, we present the Cloud Infrastructure for Microbial Bioinformatics (CLIMB) facility, a shared computing infrastructure that has been designed from the ground up to provide an environment where microbiologists can share and reuse methods and data.

  14. Bioboxes: standardised containers for interchangeable bioinformatics software.

    Science.gov (United States)

    Belmann, Peter; Dröge, Johannes; Bremges, Andreas; McHardy, Alice C; Sczyrba, Alexander; Barton, Michael D

    2015-01-01

    Software is now both central and essential to modern biology, yet lack of availability, difficult installations, and complex user interfaces make software hard to obtain and use. Containerisation, as exemplified by the Docker platform, has the potential to solve the problems associated with sharing software. We propose bioboxes: containers with standardised interfaces to make bioinformatics software interchangeable.

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

    Science.gov (United States)

    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…

  16. Comparative Proteome Bioinformatics: Identification of Phosphotyrosine Signaling Proteins in the Unicellular Protozoan Ciliate Tetrahymena

    DEFF Research Database (Denmark)

    Gammeltoft, Steen; Christensen, Søren Tvorup; Joachimiak, Marcin

    2005-01-01

    Tetrahymena, bioinformatics, cilia, evolution, signaling, TtPTK1, PTK, Grb2, SH-PTP 2, Plcy, Src, PTP, PI3K, SH2, SH3, PH......Tetrahymena, bioinformatics, cilia, evolution, signaling, TtPTK1, PTK, Grb2, SH-PTP 2, Plcy, Src, PTP, PI3K, SH2, SH3, PH...

  17. A New Universe of Discoveries

    Science.gov (United States)

    Córdova, France A.

    2016-01-01

    The convergence of emerging advances in astronomical instruments, computational capabilities and talented practitioners (both professional and civilian) is creating an extraordinary new environment for making numerous fundamental discoveries in astronomy, ranging from the nature of exoplanets to understanding the evolution of solar systems and galaxies. The National Science Foundation is playing a critical role in supporting, stimulating, and shaping these advances. NSF is more than an agency of government or a funding mechanism for the infrastructure of science. The work of NSF is a sacred trust that every generation of Americans makes to those of the next generation, that we will build on the body of knowledge we inherit and continue to push forward the frontiers of science. We never lose sight of NSF's obligation to "explore the unexplored" and inspire all of humanity with the wonders of discovery. As the only Federal agency dedicated to the support of basic research and education in all fields of science and engineering, NSF has empowered discoveries across a broad spectrum of scientific inquiry for more than six decades. The result is fundamental scientific research that has had a profound impact on our nation's innovation ecosystem and kept our nation at the very forefront of the world's science-and-engineering enterprise.

  18. Facilitating the use of large-scale biological data and tools in the era of translational bioinformatics

    DEFF Research Database (Denmark)

    Kouskoumvekaki, Irene; Shublaq, Nour; Brunak, Søren

    2014-01-01

    As both the amount of generated biological data and the processing compute power increase, computational experimentation is no longer the exclusivity of bioinformaticians, but it is moving across all biomedical domains. For bioinformatics to realize its translational potential, domain experts need...... access to user-friendly solutions to navigate, integrate and extract information out of biological databases, as well as to combine tools and data resources in bioinformatics workflows. In this review, we present services that assist biomedical scientists in incorporating bioinformatics tools...... into their research.We review recent applications of Cytoscape, BioGPS and DAVID for data visualization, integration and functional enrichment. Moreover, we illustrate the use of Taverna, Kepler, GenePattern, and Galaxy as open-access workbenches for bioinformatics workflows. Finally, we mention services...

  19. Recent development in software and automation tools for high-throughput discovery bioanalysis.

    Science.gov (United States)

    Shou, Wilson Z; Zhang, Jun

    2012-05-01

    Bioanalysis with LC-MS/MS has been established as the method of choice for quantitative determination of drug candidates in biological matrices in drug discovery and development. The LC-MS/MS bioanalytical support for drug discovery, especially for early discovery, often requires high-throughput (HT) analysis of large numbers of samples (hundreds to thousands per day) generated from many structurally diverse compounds (tens to hundreds per day) with a very quick turnaround time, in order to provide important activity and liability data to move discovery projects forward. Another important consideration for discovery bioanalysis is its fit-for-purpose quality requirement depending on the particular experiments being conducted at this stage, and it is usually not as stringent as those required in bioanalysis supporting drug development. These aforementioned attributes of HT discovery bioanalysis made it an ideal candidate for using software and automation tools to eliminate manual steps, remove bottlenecks, improve efficiency and reduce turnaround time while maintaining adequate quality. In this article we will review various recent developments that facilitate automation of individual bioanalytical procedures, such as sample preparation, MS/MS method development, sample analysis and data review, as well as fully integrated software tools that manage the entire bioanalytical workflow in HT discovery bioanalysis. In addition, software tools supporting the emerging high-resolution accurate MS bioanalytical approach are also discussed.

  20. Insights into Integrated Lead Generation and Target Identification in Malaria and Tuberculosis Drug Discovery.

    Science.gov (United States)

    Okombo, John; Chibale, Kelly

    2017-07-18

    New, safe and effective drugs are urgently needed to treat and control malaria and tuberculosis, which affect millions of people annually. However, financial return on investment in the poor settings where these diseases are mostly prevalent is very minimal to support market-driven drug discovery and development. Moreover, the imminent loss of therapeutic lifespan of existing therapies due to evolution and spread of drug resistance further compounds the urgency to identify novel effective drugs. However, the advent of new public-private partnerships focused on tropical diseases and the recent release of large data sets by pharmaceutical companies on antimalarial and antituberculosis compounds derived from phenotypic whole cell high throughput screening have spurred renewed interest and opened new frontiers in malaria and tuberculosis drug discovery. This Account recaps the existing challenges facing antimalarial and antituberculosis drug discovery, including limitations associated with experimental animal models as well as biological complexities intrinsic to the causative pathogens. We enlist various highlights from a body of work within our research group aimed at identifying and characterizing new chemical leads, and navigating these challenges to contribute toward the global drug discovery and development pipeline in malaria and tuberculosis. We describe a catalogue of in-house efforts toward deriving safe and efficacious preclinical drug development candidates via cell-based medicinal chemistry optimization of phenotypic whole-cell medium and high throughput screening hits sourced from various small molecule chemical libraries. We also provide an appraisal of target-based screening, as invoked in our laboratory for mechanistic evaluation of the hits generated, with particular focus on the enzymes within the de novo pyrimidine biosynthetic and hemoglobin degradation pathways, the latter constituting a heme detoxification process and an associated cysteine

  1. Workflows in bioinformatics: meta-analysis and prototype implementation of a workflow generator

    Directory of Open Access Journals (Sweden)

    Thoraval Samuel

    2005-04-01

    Full Text Available Abstract Background Computational methods for problem solving need to interleave information access and algorithm execution in a problem-specific workflow. The structures of these workflows are defined by a scaffold of syntactic, semantic and algebraic objects capable of representing them. Despite the proliferation of GUIs (Graphic User Interfaces in bioinformatics, only some of them provide workflow capabilities; surprisingly, no meta-analysis of workflow operators and components in bioinformatics has been reported. Results We present a set of syntactic components and algebraic operators capable of representing analytical workflows in bioinformatics. Iteration, recursion, the use of conditional statements, and management of suspend/resume tasks have traditionally been implemented on an ad hoc basis and hard-coded; by having these operators properly defined it is possible to use and parameterize them as generic re-usable components. To illustrate how these operations can be orchestrated, we present GPIPE, a prototype graphic pipeline generator for PISE that allows the definition of a pipeline, parameterization of its component methods, and storage of metadata in XML formats. This implementation goes beyond the macro capacities currently in PISE. As the entire analysis protocol is defined in XML, a complete bioinformatic experiment (linked sets of methods, parameters and results can be reproduced or shared among users. Availability: http://if-web1.imb.uq.edu.au/Pise/5.a/gpipe.html (interactive, ftp://ftp.pasteur.fr/pub/GenSoft/unix/misc/Pise/ (download. Conclusion From our meta-analysis we have identified syntactic structures and algebraic operators common to many workflows in bioinformatics. The workflow components and algebraic operators can be assimilated into re-usable software components. GPIPE, a prototype implementation of this framework, provides a GUI builder to facilitate the generation of workflows and integration of heterogeneous

  2. Analyzing the field of bioinformatics with the multi-faceted topic modeling technique.

    Science.gov (United States)

    Heo, Go Eun; Kang, Keun Young; Song, Min; Lee, Jeong-Hoon

    2017-05-31

    Bioinformatics is an interdisciplinary field at the intersection of molecular biology and computing technology. To characterize the field as convergent domain, researchers have used bibliometrics, augmented with text-mining techniques for content analysis. In previous studies, Latent Dirichlet Allocation (LDA) was the most representative topic modeling technique for identifying topic structure of subject areas. However, as opposed to revealing the topic structure in relation to metadata such as authors, publication date, and journals, LDA only displays the simple topic structure. In this paper, we adopt the Tang et al.'s Author-Conference-Topic (ACT) model to study the field of bioinformatics from the perspective of keyphrases, authors, and journals. The ACT model is capable of incorporating the paper, author, and conference into the topic distribution simultaneously. To obtain more meaningful results, we use journals and keyphrases instead of conferences and bag-of-words.. For analysis, we use PubMed to collected forty-six bioinformatics journals from the MEDLINE database. We conducted time series topic analysis over four periods from 1996 to 2015 to further examine the interdisciplinary nature of bioinformatics. We analyze the ACT Model results in each period. Additionally, for further integrated analysis, we conduct a time series analysis among the top-ranked keyphrases, journals, and authors according to their frequency. We also examine the patterns in the top journals by simultaneously identifying the topical probability in each period, as well as the top authors and keyphrases. The results indicate that in recent years diversified topics have become more prevalent and convergent topics have become more clearly represented. The results of our analysis implies that overtime the field of bioinformatics becomes more interdisciplinary where there is a steady increase in peripheral fields such as conceptual, mathematical, and system biology. These results are

  3. libcov: A C++ bioinformatic library to manipulate protein structures, sequence alignments and phylogeny

    OpenAIRE

    Butt, Davin; Roger, Andrew J; Blouin, Christian

    2005-01-01

    Background An increasing number of bioinformatics methods are considering the phylogenetic relationships between biological sequences. Implementing new methodologies using the maximum likelihood phylogenetic framework can be a time consuming task. Results The bioinformatics library libcov is a collection of C++ classes that provides a high and low-level interface to maximum likelihood phylogenetics, sequence analysis and a data structure for structural biological methods. libcov can be used ...

  4. Bioinformatics for whole-genome shotgun sequencing of microbial communities.

    Directory of Open Access Journals (Sweden)

    Kevin Chen

    2005-07-01

    Full Text Available The application of whole-genome shotgun sequencing to microbial communities represents a major development in metagenomics, the study of uncultured microbes via the tools of modern genomic analysis. In the past year, whole-genome shotgun sequencing projects of prokaryotic communities from an acid mine biofilm, the Sargasso Sea, Minnesota farm soil, three deep-sea whale falls, and deep-sea sediments have been reported, adding to previously published work on viral communities from marine and fecal samples. The interpretation of this new kind of data poses a wide variety of exciting and difficult bioinformatics problems. The aim of this review is to introduce the bioinformatics community to this emerging field by surveying existing techniques and promising new approaches for several of the most interesting of these computational problems.

  5. Promoting synergistic research and education in genomics and bioinformatics.

    Science.gov (United States)

    Yang, Jack Y; Yang, Mary Qu; Zhu, Mengxia Michelle; Arabnia, Hamid R; Deng, Youping

    2008-01-01

    Bioinformatics and Genomics are closely related disciplines that hold great promises for the advancement of research and development in complex biomedical systems, as well as public health, drug design, comparative genomics, personalized medicine and so on. Research and development in these two important areas are impacting the science and technology.High throughput sequencing and molecular imaging technologies marked the beginning of a new era for modern translational medicine and personalized healthcare. The impact of having the human sequence and personalized digital images in hand has also created tremendous demands of developing powerful supercomputing, statistical learning and artificial intelligence approaches to handle the massive bioinformatics and personalized healthcare data, which will obviously have a profound effect on how biomedical research will be conducted toward the improvement of human health and prolonging of human life in the future. The International Society of Intelligent Biological Medicine (http://www.isibm.org) and its official journals, the International Journal of Functional Informatics and Personalized Medicine (http://www.inderscience.com/ijfipm) and the International Journal of Computational Biology and Drug Design (http://www.inderscience.com/ijcbdd) in collaboration with International Conference on Bioinformatics and Computational Biology (Biocomp), touch tomorrow's bioinformatics and personalized medicine throughout today's efforts in promoting the research, education and awareness of the upcoming integrated inter/multidisciplinary field. The 2007 international conference on Bioinformatics and Computational Biology (BIOCOMP07) was held in Las Vegas, the United States of American on June 25-28, 2007. The conference attracted over 400 papers, covering broad research areas in the genomics, biomedicine and bioinformatics. The Biocomp 2007 provides a common platform for the cross fertilization of ideas, and to help shape knowledge and

  6. Bioinformatics and Microarray Data Analysis on the Cloud.

    Science.gov (United States)

    Calabrese, Barbara; Cannataro, Mario

    2016-01-01

    High-throughput platforms such as microarray, mass spectrometry, and next-generation sequencing are producing an increasing volume of omics data that needs large data storage and computing power. Cloud computing offers massive scalable computing and storage, data sharing, on-demand anytime and anywhere access to resources and applications, and thus, it may represent the key technology for facing those issues. In fact, in the recent years it has been adopted for the deployment of different bioinformatics solutions and services both in academia and in the industry. Although this, cloud computing presents several issues regarding the security and privacy of data, that are particularly important when analyzing patients data, such as in personalized medicine. This chapter reviews main academic and industrial cloud-based bioinformatics solutions; with a special focus on microarray data analysis solutions and underlines main issues and problems related to the use of such platforms for the storage and analysis of patients data.

  7. Protecting innovation in bioinformatics and in-silico biology.

    Science.gov (United States)

    Harrison, Robert

    2003-01-01

    Commercial success or failure of innovation in bioinformatics and in-silico biology requires the appropriate use of legal tools for protecting and exploiting intellectual property. These tools include patents, copyrights, trademarks, design rights, and limiting information in the form of 'trade secrets'. Potentially patentable components of bioinformatics programmes include lines of code, algorithms, data content, data structure and user interfaces. In both the US and the European Union, copyright protection is granted for software as a literary work, and most other major industrial countries have adopted similar rules. Nonetheless, the grant of software patents remains controversial and is being challenged in some countries. Current debate extends to aspects such as whether patents can claim not only the apparatus and methods but also the data signals and/or products, such as a CD-ROM, on which the programme is stored. The patentability of substances discovered using in-silico methods is a separate debate that is unlikely to be resolved in the near future.

  8. Computer-aided vaccine designing approach against fish pathogens Edwardsiella tarda and Flavobacterium columnare using bioinformatics softwares

    Directory of Open Access Journals (Sweden)

    Mahendran R

    2016-05-01

    Full Text Available Radha Mahendran,1 Suganya Jeyabaskar,1 Gayathri Sitharaman,1 Rajamani Dinakaran Michael,2 Agnal Vincent Paul1 1Department of Bioinformatics, 2Centre for Fish Immunology, School of Life Sciences, Vels University, Pallavaram, Chennai, Tamil Nadu, India Abstract: Edwardsiella tarda and Flavobacterium columnare are two important intracellular pathogenic bacteria that cause the infectious diseases edwardsiellosis and columnaris in wild and cultured fish. Prediction of major histocompatibility complex (MHC binding is an important issue in T-cell epitope prediction. In a healthy immune system, the T-cells must recognize epitopes and induce the immune response. In this study, T-cell epitopes were predicted by using in silico immunoinformatics approach with the help of bioinformatics tools that are less expensive and are not time consuming. Such identification of binding interaction between peptides and MHC alleles aids in the discovery of new peptide vaccines. We have reported the potential peptides chosen from the outer membrane proteins (OMPs of E. tarda and F. columnare, which interact well with MHC class I alleles. OMPs from E. tarda and F. columnare were selected and analyzed based on their antigenic and immunogenic properties. The OMPs of the genes TolC and FCOL_04620, respectively, from E. tarda and F. columnare were taken for study. Finally, two epitopes from the OMP of E. tarda exhibited excellent protein–peptide interaction when docked with MHC class I alleles. Five epitopes from the OMP of F. columnare had good protein–peptide interaction when docked with MHC class I alleles. Further in vitro studies can aid in the development of potential peptide vaccines using the predicted peptides. Keywords: E. tarda, F. columnare, edwardsiellosis, columnaris, T-cell epitopes, MHC class I, peptide vaccine, outer membrane proteins 

  9. Nispero: a cloud-computing based Scala tool specially suited for bioinformatics data processing

    OpenAIRE

    Evdokim Kovach; Alexey Alekhin; Eduardo Pareja Tobes; Raquel Tobes; Eduardo Pareja; Marina Manrique

    2014-01-01

    Nowadays it is widely accepted that the bioinformatics data analysis is a real bottleneck in many research activities related to life sciences. High-throughput technologies like Next Generation Sequencing (NGS) have completely reshaped the biology and bioinformatics landscape. Undoubtedly NGS has allowed important progress in many life-sciences related fields but has also presented interesting challenges in terms of computation capabilities and algorithms. Many kinds of tasks related with NGS...

  10. An Adaptive Hybrid Multiprocessor technique for bioinformatics sequence alignment

    KAUST Repository

    Bonny, Talal; Salama, Khaled N.; Zidan, Mohammed A.

    2012-01-01

    Sequence alignment algorithms such as the Smith-Waterman algorithm are among the most important applications in the development of bioinformatics. Sequence alignment algorithms must process large amounts of data which may take a long time. Here, we

  11. Adaptation of a Bioinformatics Microarray Analysis Workflow for a Toxicogenomic Study in Rainbow Trout.

    Directory of Open Access Journals (Sweden)

    Sophie Depiereux

    Full Text Available Sex steroids play a key role in triggering sex differentiation in fish, the use of exogenous hormone treatment leading to partial or complete sex reversal. This phenomenon has attracted attention since the discovery that even low environmental doses of exogenous steroids can adversely affect gonad morphology (ovotestis development and induce reproductive failure. Modern genomic-based technologies have enhanced opportunities to find out mechanisms of actions (MOA and identify biomarkers related to the toxic action of a compound. However, high throughput data interpretation relies on statistical analysis, species genomic resources, and bioinformatics tools. The goals of this study are to improve the knowledge of feminisation in fish, by the analysis of molecular responses in the gonads of rainbow trout fry after chronic exposure to several doses (0.01, 0.1, 1 and 10 μg/L of ethynylestradiol (EE2 and to offer target genes as potential biomarkers of ovotestis development. We successfully adapted a bioinformatics microarray analysis workflow elaborated on human data to a toxicogenomic study using rainbow trout, a fish species lacking accurate functional annotation and genomic resources. The workflow allowed to obtain lists of genes supposed to be enriched in true positive differentially expressed genes (DEGs, which were subjected to over-representation analysis methods (ORA. Several pathways and ontologies, mostly related to cell division and metabolism, sexual reproduction and steroid production, were found significantly enriched in our analyses. Moreover, two sets of potential ovotestis biomarkers were selected using several criteria. The first group displayed specific potential biomarkers belonging to pathways/ontologies highlighted in the experiment. Among them, the early ovarian differentiation gene foxl2a was overexpressed. The second group, which was highly sensitive but not specific, included the DEGs presenting the highest fold change and

  12. 'Students-as-partners' scheme enhances postgraduate students' employability skills while addressing gaps in bioinformatics education.

    Science.gov (United States)

    Mello, Luciane V; Tregilgas, Luke; Cowley, Gwen; Gupta, Anshul; Makki, Fatima; Jhutty, Anjeet; Shanmugasundram, Achchuthan

    2017-01-01

    Teaching bioinformatics is a longstanding challenge for educators who need to demonstrate to students how skills developed in the classroom may be applied to real world research. This study employed an action research methodology which utilised student-staff partnership and peer-learning. It was centred on the experiences of peer-facilitators, students who had previously taken a postgraduate bioinformatics module, and had applied knowledge and skills gained from it to their own research. It aimed to demonstrate to peer-receivers, current students, how bioinformatics could be used in their own research while developing peer-facilitators' teaching and mentoring skills. This student-centred approach was well received by the peer-receivers, who claimed to have gained improved understanding of bioinformatics and its relevance to research. Equally, peer-facilitators also developed a better understanding of the subject and appreciated that the activity was a rare and invaluable opportunity to develop their teaching and mentoring skills, enhancing their employability.

  13. A bioinformatics-based overview of protein Lys-Ne-acetylation

    Science.gov (United States)

    Among posttranslational modifications, there are some conceptual similarities between Lys-N'-acetylation and Ser/Thr/Tyr O-phosphorylation. Herein we present a bioinformatics-based overview of reversible protein Lys-acetylation, including some comparisons with reversible protein phosphorylation. T...

  14. Missing "Links" in Bioinformatics Education: Expanding Students' Conceptions of Bioinformatics Using a Biodiversity Database of Living and Fossil Reef Corals

    Science.gov (United States)

    Nehm, Ross H.; Budd, Ann F.

    2006-01-01

    NMITA is a reef coral biodiversity database that we use to introduce students to the expansive realm of bioinformatics beyond genetics. We introduce a series of lessons that have students use this database, thereby accessing real data that can be used to test hypotheses about biodiversity and evolution while targeting the "National Science …

  15. BioMaS: a modular pipeline for Bioinformatic analysis of Metagenomic AmpliconS.

    Science.gov (United States)

    Fosso, Bruno; Santamaria, Monica; Marzano, Marinella; Alonso-Alemany, Daniel; Valiente, Gabriel; Donvito, Giacinto; Monaco, Alfonso; Notarangelo, Pasquale; Pesole, Graziano

    2015-07-01

    Substantial advances in microbiology, molecular evolution and biodiversity have been carried out in recent years thanks to Metagenomics, which allows to unveil the composition and functions of mixed microbial communities in any environmental niche. If the investigation is aimed only at the microbiome taxonomic structure, a target-based metagenomic approach, here also referred as Meta-barcoding, is generally applied. This approach commonly involves the selective amplification of a species-specific genetic marker (DNA meta-barcode) in the whole taxonomic range of interest and the exploration of its taxon-related variants through High-Throughput Sequencing (HTS) technologies. The accessibility to proper computational systems for the large-scale bioinformatic analysis of HTS data represents, currently, one of the major challenges in advanced Meta-barcoding projects. BioMaS (Bioinformatic analysis of Metagenomic AmpliconS) is a new bioinformatic pipeline designed to support biomolecular researchers involved in taxonomic studies of environmental microbial communities by a completely automated workflow, comprehensive of all the fundamental steps, from raw sequence data upload and cleaning to final taxonomic identification, that are absolutely required in an appropriately designed Meta-barcoding HTS-based experiment. In its current version, BioMaS allows the analysis of both bacterial and fungal environments starting directly from the raw sequencing data from either Roche 454 or Illumina HTS platforms, following two alternative paths, respectively. BioMaS is implemented into a public web service available at https://recasgateway.ba.infn.it/ and is also available in Galaxy at http://galaxy.cloud.ba.infn.it:8080 (only for Illumina data). BioMaS is a friendly pipeline for Meta-barcoding HTS data analysis specifically designed for users without particular computing skills. A comparative benchmark, carried out by using a simulated dataset suitably designed to broadly represent

  16. Evaluating the inverse reasoning account of object discovery.

    Science.gov (United States)

    Carroll, Christopher D; Kemp, Charles

    2015-06-01

    People routinely make inferences about unobserved objects. A hotel guest with welts on his arms, for example, will often worry about bed bugs. The discovery of unobserved objects almost always involves a backward inference from some observed effects (e.g., welts) to unobserved causes (e.g., bed bugs). The inverse reasoning account, which is typically formalized as Bayesian inference, posits that the strength of a backward inference is closely connected to the strength of the corresponding forward inference from the unobserved causes to the observed effects. We evaluated the inverse reasoning account of object discovery in three experiments where participants were asked to discover the unobserved "attractors" and "repellers" that controlled a "particle" moving within an arena. Experiments 1 and 2 showed that participants often failed to provide the best explanations for various particle motions, even when the best explanations were simple and when participants enthusiastically endorsed these explanations when presented with them. This failure demonstrates that object discovery is critically dependent on the processes that support hypothesis generation-processes that the inverse reasoning account does not explain. Experiment 3 demonstrated that people sometimes generate explanations that are invalid even according to their own forward inferences, suggesting that the psychological processes that support forward and backward inference are less intertwined than the inverse reasoning account suggests. The experimental findings support an alternative account of object discovery in which people rely on heuristics to generate possible explanations. Copyright © 2015 Elsevier B.V. All rights reserved.

  17. Penalized feature selection and classification in bioinformatics

    OpenAIRE

    Ma, Shuangge; Huang, Jian

    2008-01-01

    In bioinformatics studies, supervised classification with high-dimensional input variables is frequently encountered. Examples routinely arise in genomic, epigenetic and proteomic studies. Feature selection can be employed along with classifier construction to avoid over-fitting, to generate more reliable classifier and to provide more insights into the underlying causal relationships. In this article, we provide a review of several recently developed penalized feature selection and classific...

  18. The discovery of Halictivirus resolves the Sinaivirus phylogeny.

    Science.gov (United States)

    Bigot, Diane; Dalmon, Anne; Roy, Bronwen; Hou, Chunsheng; Germain, Michèle; Romary, Manon; Deng, Shuai; Diao, Qingyun; Weinert, Lucy A; Cook, James M; Herniou, Elisabeth A; Gayral, Philippe

    2017-11-01

    By providing pollination services, bees are among the most important insects, both in ecological and economical terms. Combined next-generation and classical sequencing approaches were applied to discover and study new insect viruses potentially harmful to bees. A bioinformatics virus discovery pipeline was used on individual Illumina transcriptomes of 13 wild bees from three species from the genus Halictus and 30 ants from six species of the genera Messor and Aphaenogaster. This allowed the discovery and description of three sequences of a new virus termed Halictus scabiosae Adlikon virus (HsAV). Phylogenetic analyses of ORF1, RNA-dependent RNA-polymerase (RdRp) and capsid genes showed that HsAV is closely related to (+)ssRNA viruses of the unassigned Sinaivirus genus but distant enough to belong to a different new genus we called Halictivirus. In addition, our study of ant transcriptomes revealed the first four sinaivirus sequences from ants (Messor barbarus, M. capitatus and M. concolor). Maximum likelihood phylogenetic analyses were performed on a 594 nt fragment of the ORF1/RdRp region from 84 sinaivirus sequences, including 31 new Lake Sinai viruses (LSVs) from honey bees collected in five countries across the globe and the four ant viral sequences. The phylogeny revealed four main clades potentially representing different viral species infecting honey bees. Moreover, the ant viruses belonged to the LSV4 clade, suggesting a possible cross-species transmission between bees and ants. Lastly, wide honey bee screening showed that all four LSV clades have worldwide distributions with no obvious geographical segregation.

  19. Translational medicine and drug discovery

    National Research Council Canada - National Science Library

    Littman, Bruce H; Krishna, Rajesh

    2011-01-01

    ..., and examples of their application to real-life drug discovery and development. The latest thinking is presented by researchers from many of the world's leading pharmaceutical companies, including Pfizer, Merck, Eli Lilly, Abbott, and Novartis, as well as from academic institutions and public- private partnerships that support translational research...

  20. Bioenergy Knowledge Discovery Framework Fact Sheet

    Energy Technology Data Exchange (ETDEWEB)

    None

    2017-07-01

    The Bioenergy Knowledge Discovery Framework (KDF) supports the development of a sustainable bioenergy industry by providing access to a variety of data sets, publications, and collaboration and mapping tools that support bioenergy research, analysis, and decision making. In the KDF, users can search for information, contribute data, and use the tools and map interface to synthesize, analyze, and visualize information in a spatially integrated manner.

  1. Architecture exploration of FPGA based accelerators for bioinformatics applications

    CERN Document Server

    Varma, B Sharat Chandra; Balakrishnan, M

    2016-01-01

    This book presents an evaluation methodology to design future FPGA fabrics incorporating hard embedded blocks (HEBs) to accelerate applications. This methodology will be useful for selection of blocks to be embedded into the fabric and for evaluating the performance gain that can be achieved by such an embedding. The authors illustrate the use of their methodology by studying the impact of HEBs on two important bioinformatics applications: protein docking and genome assembly. The book also explains how the respective HEBs are designed and how hardware implementation of the application is done using these HEBs. It shows that significant speedups can be achieved over pure software implementations by using such FPGA-based accelerators. The methodology presented in this book may also be used for designing HEBs for accelerating software implementations in other domains besides bioinformatics. This book will prove useful to students, researchers, and practicing engineers alike.

  2. Discovery of novel xylosides in co-culture of basidiomycetes Trametes versicolor and Ganoderma applanatum by integrated metabolomics and bioinformatics

    Science.gov (United States)

    Yao, Lu; Zhu, Li-Ping; Xu, Xiao-Yan; Tan, Ling-Ling; Sadilek, Martin; Fan, Huan; Hu, Bo; Shen, Xiao-Ting; Yang, Jie; Qiao, Bin; Yang, Song

    2016-09-01

    Transcriptomic analysis of cultured fungi suggests that many genes for secondary metabolite synthesis are presumably silent under standard laboratory condition. In order to investigate the expression of silent genes in symbiotic systems, 136 fungi-fungi symbiotic systems were built up by co-culturing seventeen basidiomycetes, among which the co-culture of Trametes versicolor and Ganoderma applanatum demonstrated the strongest coloration of confrontation zones. Metabolomics study of this co-culture discovered that sixty-two features were either newly synthesized or highly produced in the co-culture compared with individual cultures. Molecular network analysis highlighted a subnetwork including two novel xylosides (compounds 2 and 3). Compound 2 was further identified as N-(4-methoxyphenyl)formamide 2-O-β-D-xyloside and was revealed to have the potential to enhance the cell viability of human immortalized bronchial epithelial cell line of Beas-2B. Moreover, bioinformatics and transcriptional analysis of T. versicolor revealed a potential candidate gene (GI: 636605689) encoding xylosyltransferases for xylosylation. Additionally, 3-phenyllactic acid and orsellinic acid were detected for the first time in G. applanatum, which may be ascribed to response against T.versicolor stress. In general, the described co-culture platform provides a powerful tool to discover novel metabolites and help gain insights into the mechanism of silent gene activation in fungal defense.

  3. Staff Scientist - RNA Bioinformatics | Center for Cancer Research

    Science.gov (United States)

    The newly established RNA Biology Laboratory (RBL) at the Center for Cancer Research (CCR), National Cancer Institute (NCI), National Institutes of Health (NIH) in Frederick, Maryland is recruiting a Staff Scientist with strong expertise in RNA bioinformatics to join the Intramural Research Program’s mission of high impact, high reward science. The RBL is the equivalent of an

  4. Integrated quantitative and qualitative workflow for in vivo bioanalytical support in drug discovery using hybrid Q-TOF-MS.

    Science.gov (United States)

    Ranasinghe, Asoka; Ramanathan, Ragu; Jemal, Mohammed; D'Arienzo, Celia J; Humphreys, W Griffith; Olah, Timothy V

    2012-03-01

    UHPLC coupled with orthogonal acceleration hybrid quadrupole-TOF (Q-TOF)-MS is an emerging technique offering new strategies for the efficient screening of new chemical entities and related molecules at the early discovery stage within the pharmaceutical industry. In the first part of this article, we examine the main instrumental parameters that are critical for the integration of UHPLC-Q-TOF technology to existing bioanalytical workflows, in order to provide simultaneous quantitative and qualitative bioanalysis of samples generated following in vivo studies. Three modern Q-TOF mass spectrometers, including Bruker maXis™, Agilent 6540 and Sciex TripleTOF™ 5600, all interfaced with UHPLC systems, are evaluated in the second part of the article. The scope of this work is to demonstrate the potential of Q-TOF for the analysis of typical small molecules, therapeutic peptides (molecular weight <6000 Da), and enzymatically (i.e., trypsin, chymotrypsin and pepsin) cleaved peptides from larger proteins. This work focuses mainly on full-scan TOF data obtained under ESI conditions, the major mode of TOF operation in discovery bioanalytical research, where the compounds are selected based on their pharmacokinetic/pharmacodynamic behaviors using animal models prior to selecting a few desirable candidates for further development. Finally, important emerging TOF technologies that could potentially benefit bioanalytical research in the semi-quantification of metabolites without synthesized standards are discussed. Particularly, the utility of captive spray ionization coupled with TripleTOF 5600 was evaluated for improving sensitivity and providing normalized MS response for drugs and their metabolites. The workflow proposed compromises neither the efficiency, nor the quality of pharmacokinetic data in support of early drug discovery programs.

  5. Expanding Role of Data Science and Bioinformatics in Drug Discovery and Development.

    Science.gov (United States)

    Fingert, Howard J

    2018-01-01

    Numerous barriers have been identified which detract from successful applications of clinical trial data and platforms. Despite the challenges, opportunities are growing to advance compliance, quality, and practical applications through top-down establishment of guiding principles, coupled with bottom-up approaches to promote data science competencies among data producers. Recent examples of successful applications include modern treatments for hematologic malignancies, developed with support from public-private partnerships, guiding principles for data-sharing, standards for protocol designs and data management, digital technologies, and quality analytics. © 2017 American Society for Clinical Pharmacology and Therapeutics.

  6. Systems-based biological concordance and predictive reproducibility of gene set discovery methods in cardiovascular disease.

    Science.gov (United States)

    Azuaje, Francisco; Zheng, Huiru; Camargo, Anyela; Wang, Haiying

    2011-08-01

    The discovery of novel disease biomarkers is a crucial challenge for translational bioinformatics. Demonstration of both their classification power and reproducibility across independent datasets are essential requirements to assess their potential clinical relevance. Small datasets and multiplicity of putative biomarker sets may explain lack of predictive reproducibility. Studies based on pathway-driven discovery approaches have suggested that, despite such discrepancies, the resulting putative biomarkers tend to be implicated in common biological processes. Investigations of this problem have been mainly focused on datasets derived from cancer research. We investigated the predictive and functional concordance of five methods for discovering putative biomarkers in four independently-generated datasets from the cardiovascular disease domain. A diversity of biosignatures was identified by the different methods. However, we found strong biological process concordance between them, especially in the case of methods based on gene set analysis. With a few exceptions, we observed lack of classification reproducibility using independent datasets. Partial overlaps between our putative sets of biomarkers and the primary studies exist. Despite the observed limitations, pathway-driven or gene set analysis can predict potentially novel biomarkers and can jointly point to biomedically-relevant underlying molecular mechanisms. Copyright © 2011 Elsevier Inc. All rights reserved.

  7. ‘Students-as-partners’ scheme enhances postgraduate students’ employability skills while addressing gaps in bioinformatics education

    Science.gov (United States)

    Mello, Luciane V.; Tregilgas, Luke; Cowley, Gwen; Gupta, Anshul; Makki, Fatima; Jhutty, Anjeet; Shanmugasundram, Achchuthan

    2017-01-01

    Abstract Teaching bioinformatics is a longstanding challenge for educators who need to demonstrate to students how skills developed in the classroom may be applied to real world research. This study employed an action research methodology which utilised student–staff partnership and peer-learning. It was centred on the experiences of peer-facilitators, students who had previously taken a postgraduate bioinformatics module, and had applied knowledge and skills gained from it to their own research. It aimed to demonstrate to peer-receivers, current students, how bioinformatics could be used in their own research while developing peer-facilitators’ teaching and mentoring skills. This student-centred approach was well received by the peer-receivers, who claimed to have gained improved understanding of bioinformatics and its relevance to research. Equally, peer-facilitators also developed a better understanding of the subject and appreciated that the activity was a rare and invaluable opportunity to develop their teaching and mentoring skills, enhancing their employability. PMID:29098185

  8. Bioinformatics tools for development of fast and cost effective simple ...

    African Journals Online (AJOL)

    Bioinformatics tools for development of fast and cost effective simple sequence repeat ... comparative mapping and exploration of functional genetic diversity in the ... Already, a number of computer programs have been implemented that aim at ...

  9. Virginia Bioinformatics Institute to expand cyberinfrastructure education and outreach project

    OpenAIRE

    Whyte, Barry James

    2008-01-01

    The National Science Foundation has awarded the Virginia Bioinformatics Institute at Virginia Tech $918,000 to expand its education and outreach program in Cyberinfrastructure - Training, Education, Advancement and Mentoring, commonly known as the CI-TEAM.

  10. 6th International Conference on Practical Applications of Computational Biology & Bioinformatics

    CERN Document Server

    Luscombe, Nicholas; Fdez-Riverola, Florentino; Rodríguez, Juan; Practical Applications of Computational Biology & Bioinformatics

    2012-01-01

    The growth in the Bioinformatics and Computational Biology fields over the last few years has been remarkable.. The analysis of the datasets of Next Generation Sequencing needs new algorithms and approaches from fields such as Databases, Statistics, Data Mining, Machine Learning, Optimization, Computer Science and Artificial Intelligence. Also Systems Biology has also been emerging as an alternative to the reductionist view that dominated biological research in the last decades. This book presents the results of the  6th International Conference on Practical Applications of Computational Biology & Bioinformatics held at University of Salamanca, Spain, 28-30th March, 2012 which brought together interdisciplinary scientists that have a strong background in the biological and computational sciences.

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

    Science.gov (United States)

    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…

  12. Development of traditional Chinese medicine clinical data warehouse for medical knowledge discovery and decision support.

    Science.gov (United States)

    Zhou, Xuezhong; Chen, Shibo; Liu, Baoyan; Zhang, Runsun; Wang, Yinghui; Li, Ping; Guo, Yufeng; Zhang, Hua; Gao, Zhuye; Yan, Xiufeng

    2010-01-01

    Traditional Chinese medicine (TCM) is a scientific discipline, which develops the related theories from the long-term clinical practices. The large-scale clinical data are the core empirical knowledge source for TCM research. This paper introduces a clinical data warehouse (CDW) system, which incorporates the structured electronic medical record (SEMR) data for medical knowledge discovery and TCM clinical decision support (CDS). We have developed the clinical reference information model (RIM) and physical data model to manage the various information entities and their relationships in TCM clinical data. An extraction-transformation-loading (ETL) tool is implemented to integrate and normalize the clinical data from different operational data sources. The CDW includes online analytical processing (OLAP) and complex network analysis (CNA) components to explore the various clinical relationships. Furthermore, the data mining and CNA methods are used to discover the valuable clinical knowledge from the data. The CDW has integrated 20,000 TCM inpatient data and 20,000 outpatient data, which contains manifestations (e.g. symptoms, physical examinations and laboratory test results), diagnoses and prescriptions as the main information components. We propose a practical solution to accomplish the large-scale clinical data integration and preprocessing tasks. Meanwhile, we have developed over 400 OLAP reports to enable the multidimensional analysis of clinical data and the case-based CDS. We have successfully conducted several interesting data mining applications. Particularly, we use various classification methods, namely support vector machine, decision tree and Bayesian network, to discover the knowledge of syndrome differentiation. Furthermore, we have applied association rule and CNA to extract the useful acupuncture point and herb combination patterns from the clinical prescriptions. A CDW system consisting of TCM clinical RIM, ETL, OLAP and data mining as the core

  13. Volatility Discovery

    DEFF Research Database (Denmark)

    Dias, Gustavo Fruet; Scherrer, Cristina; Papailias, Fotis

    The price discovery literature investigates how homogenous securities traded on different markets incorporate information into prices. We take this literature one step further and investigate how these markets contribute to stochastic volatility (volatility discovery). We formally show...... that the realized measures from homogenous securities share a fractional stochastic trend, which is a combination of the price and volatility discovery measures. Furthermore, we show that volatility discovery is associated with the way that market participants process information arrival (market sensitivity......). Finally, we compute volatility discovery for 30 actively traded stocks in the U.S. and report that Nyse and Arca dominate Nasdaq....

  14. Bioinformatics for Undergraduates: Steps toward a Quantitative Bioscience Curriculum

    Science.gov (United States)

    Chapman, Barbara S.; Christmann, James L.; Thatcher, Eileen F.

    2006-01-01

    We describe an innovative bioinformatics course developed under grants from the National Science Foundation and the California State University Program in Research and Education in Biotechnology for undergraduate biology students. The project has been part of a continuing effort to offer students classroom experiences focused on principles and…

  15. Bioinformatic tools and guideline for PCR primer design | Abd ...

    African Journals Online (AJOL)

    Bioinformatics has become an essential tool not only for basic research but also for applied research in biotechnology and biomedical sciences. Optimal primer sequence and appropriate primer concentration are essential for maximal specificity and efficiency of PCR. A poorly designed primer can result in little or no ...

  16. Discovery of antimicrobial lipodepsipeptides produced by a Serratia sp. within mosquito microbiomes.

    Science.gov (United States)

    Ganley, Jack; Carr, Gavin; Ioerger, Thomas; Sacchettini, James; Clardy, Jon; Derbyshire, Emily

    2018-04-26

    The Anopheles mosquito that harbors the Plasmodium parasite contains a microbiota that can influence both the vector and parasite. In recent years, insect-associated microbes have highlighted the untapped potential of exploiting interspecies interactions to discover bioactive compounds. In this study, we report the discovery of nonribosomal lipodepsipeptides that are produced by a Serratia sp. within the midgut and salivary glands of A. stephensi mosquitoes. The lipodepsipeptides, stephensiolides A-K, have antibiotic activity and facilitate bacterial surface motility. Bioinformatic analyses indicate that the stephensiolides are ubiquitous in nature and are likely important for Serratia spp. colonization within mosquitoes, humans, and other ecological niches. Our results demonstrate the usefulness of probing insect-microbiome interactions, enhance our understanding of the chemical ecology within Anopheles mosquitoes, and provide a secondary metabolite scaffold to further investigate this complex relationship. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  17. Bioinformatics analysis and detection of gelatinase encoded gene in Lysinibacillussphaericus

    Science.gov (United States)

    Repin, Rul Aisyah Mat; Mutalib, Sahilah Abdul; Shahimi, Safiyyah; Khalid, Rozida Mohd.; Ayob, Mohd. Khan; Bakar, Mohd. Faizal Abu; Isa, Mohd Noor Mat

    2016-11-01

    In this study, we performed bioinformatics analysis toward genome sequence of Lysinibacillussphaericus (L. sphaericus) to determine gene encoded for gelatinase. L. sphaericus was isolated from soil and gelatinase species-specific bacterium to porcine and bovine gelatin. This bacterium offers the possibility of enzymes production which is specific to both species of meat, respectively. The main focus of this research is to identify the gelatinase encoded gene within the bacteria of L. Sphaericus using bioinformatics analysis of partially sequence genome. From the research study, three candidate gene were identified which was, gelatinase candidate gene 1 (P1), NODE_71_length_93919_cov_158.931839_21 which containing 1563 base pair (bp) in size with 520 amino acids sequence; Secondly, gelatinase candidate gene 2 (P2), NODE_23_length_52851_cov_190.061386_17 which containing 1776 bp in size with 591 amino acids sequence; and Thirdly, gelatinase candidate gene 3 (P3), NODE_106_length_32943_cov_169.147919_8 containing 1701 bp in size with 566 amino acids sequence. Three pairs of oligonucleotide primers were designed and namely as, F1, R1, F2, R2, F3 and R3 were targeted short sequences of cDNA by PCR. The amplicons were reliably results in 1563 bp in size for candidate gene P1 and 1701 bp in size for candidate gene P3. Therefore, the results of bioinformatics analysis of L. Sphaericus resulting in gene encoded gelatinase were identified.

  18. In silico cloning and bioinformatic analysis of PEPCK gene in ...

    African Journals Online (AJOL)

    Phosphoenolpyruvate carboxykinase (PEPCK), a critical gluconeogenic enzyme, catalyzes the first committed step in the diversion of tricarboxylic acid cycle intermediates toward gluconeogenesis. According to the relative conservation of homologous gene, a bioinformatics strategy was applied to clone Fusarium ...

  19. mockrobiota: a Public Resource for Microbiome Bioinformatics Benchmarking.

    Science.gov (United States)

    Bokulich, Nicholas A; Rideout, Jai Ram; Mercurio, William G; Shiffer, Arron; Wolfe, Benjamin; Maurice, Corinne F; Dutton, Rachel J; Turnbaugh, Peter J; Knight, Rob; Caporaso, J Gregory

    2016-01-01

    Mock communities are an important tool for validating, optimizing, and comparing bioinformatics methods for microbial community analysis. We present mockrobiota, a public resource for sharing, validating, and documenting mock community data resources, available at http://caporaso-lab.github.io/mockrobiota/. The materials contained in mockrobiota include data set and sample metadata, expected composition data (taxonomy or gene annotations or reference sequences for mock community members), and links to raw data (e.g., raw sequence data) for each mock community data set. mockrobiota does not supply physical sample materials directly, but the data set metadata included for each mock community indicate whether physical sample materials are available. At the time of this writing, mockrobiota contains 11 mock community data sets with known species compositions, including bacterial, archaeal, and eukaryotic mock communities, analyzed by high-throughput marker gene sequencing. IMPORTANCE The availability of standard and public mock community data will facilitate ongoing method optimizations, comparisons across studies that share source data, and greater transparency and access and eliminate redundancy. These are also valuable resources for bioinformatics teaching and training. This dynamic resource is intended to expand and evolve to meet the changing needs of the omics community.

  20. The Revolution in Viral Genomics as Exemplified by the Bioinformatic Analysis of Human Adenoviruses

    Directory of Open Access Journals (Sweden)

    Sarah Torres

    2010-06-01

    Full Text Available Over the past 30 years, genomic and bioinformatic analysis of human adenoviruses has been achieved using a variety of DNA sequencing methods; initially with the use of restriction enzymes and more currently with the use of the GS FLX pyrosequencing technology. Following the conception of DNA sequencing in the 1970s, analysis of adenoviruses has evolved from 100 base pair mRNA fragments to entire genomes. Comparative genomics of adenoviruses made its debut in 1984 when nucleotides and amino acids of coding sequences within the hexon genes of two human adenoviruses (HAdV, HAdV–C2 and HAdV–C5, were compared and analyzed. It was determined that there were three different zones (1-393, 394-1410, 1411-2910 within the hexon gene, of which HAdV–C2 and HAdV–C5 shared zones 1 and 3 with 95% and 89.5% nucleotide identity, respectively. In 1992, HAdV-C5 became the first adenovirus genome to be fully sequenced using the Sanger method. Over the next seven years, whole genome analysis and characterization was completed using bioinformatic tools such as blastn, tblastx, ClustalV and FASTA, in order to determine key proteins in species HAdV-A through HAdV-F. The bioinformatic revolution was initiated with the introduction of a novel species, HAdV-G, that was typed and named by the use of whole genome sequencing and phylogenetics as opposed to traditional serology. HAdV bioinformatics will continue to advance as the latest sequencing technology enables scientists to add to and expand the resource databases. As a result of these advancements, how novel HAdVs are typed has changed. Bioinformatic analysis has become the revolutionary tool that has significantly accelerated the in-depth study of HAdV microevolution through comparative genomics.

  1. Bioinformatics in the Netherlands : The value of a nationwide community

    NARCIS (Netherlands)

    van Gelder, Celia W.G.; Hooft, Rob; van Rijswijk, Merlijn; van den Berg, Linda; Kok, Ruben; Reinders, M.J.T.; Mons, Barend; Heringa, Jaap

    2017-01-01

    This review provides a historical overview of the inception and development of bioinformatics research in the Netherlands. Rooted in theoretical biology by foundational figures such as Paulien Hogeweg (at Utrecht University since the 1970s), the developments leading to organizational structures

  2. Bioinformatics Identification of Modules of Transcription Factor Binding Sites in Alzheimer's Disease-Related Genes by In Silico Promoter Analysis and Microarrays

    Directory of Open Access Journals (Sweden)

    Regina Augustin

    2011-01-01

    Full Text Available The molecular mechanisms and genetic risk factors underlying Alzheimer's disease (AD pathogenesis are only partly understood. To identify new factors, which may contribute to AD, different approaches are taken including proteomics, genetics, and functional genomics. Here, we used a bioinformatics approach and found that distinct AD-related genes share modules of transcription factor binding sites, suggesting a transcriptional coregulation. To detect additional coregulated genes, which may potentially contribute to AD, we established a new bioinformatics workflow with known multivariate methods like support vector machines, biclustering, and predicted transcription factor binding site modules by using in silico analysis and over 400 expression arrays from human and mouse. Two significant modules are composed of three transcription factor families: CTCF, SP1F, and EGRF/ZBPF, which are conserved between human and mouse APP promoter sequences. The specific combination of in silico promoter and multivariate analysis can identify regulation mechanisms of genes involved in multifactorial diseases.

  3. An overview of the Hadoop/MapReduce/HBase framework and its current applications in bioinformatics

    International Nuclear Information System (INIS)

    Taylor, Ronald C.

    2010-01-01

    Bioinformatics researchers are increasingly confronted with analysis of ultra large-scale data sets, a problem that will only increase at an alarming rate in coming years. Recent developments in open source software, that is, the Hadoop project and associated software, provide a foundation for scaling to petabyte scale data warehouses on Linux clusters, providing fault-tolerant parallelized analysis on such data using a programming style named MapReduce. An overview is given of the current usage within the bioinformatics community of Hadoop, a top-level Apache Software Foundation project, and of associated open source software projects. The concepts behind Hadoop and the associated HBase project are defined, and current bioinformatics software that employ Hadoop is described. The focus is on next-generation sequencing, as the leading application area to date.

  4. Thoughtflow: Standards and Tools for Provenance Capture and Workflow Definition to Support Model-Informed Drug Discovery and Development.

    Science.gov (United States)

    Wilkins, J J; Chan, Pls; Chard, J; Smith, G; Smith, M K; Beer, M; Dunn, A; Flandorfer, C; Franklin, C; Gomeni, R; Harnisch, L; Kaye, R; Moodie, S; Sardu, M L; Wang, E; Watson, E; Wolstencroft, K; Cheung, Sya

    2017-05-01

    Pharmacometric analyses are complex and multifactorial. It is essential to check, track, and document the vast amounts of data and metadata that are generated during these analyses (and the relationships between them) in order to comply with regulations, support quality control, auditing, and reporting. It is, however, challenging, tedious, error-prone, and time-consuming, and diverts pharmacometricians from the more useful business of doing science. Automating this process would save time, reduce transcriptional errors, support the retention and transfer of knowledge, encourage good practice, and help ensure that pharmacometric analyses appropriately impact decisions. The ability to document, communicate, and reconstruct a complete pharmacometric analysis using an open standard would have considerable benefits. In this article, the Innovative Medicines Initiative (IMI) Drug Disease Model Resources (DDMoRe) consortium proposes a set of standards to facilitate the capture, storage, and reporting of knowledge (including assumptions and decisions) in the context of model-informed drug discovery and development (MID3), as well as to support reproducibility: "Thoughtflow." A prototype software implementation is provided. © 2017 The Authors CPT: Pharmacometrics & Systems Pharmacology published by Wiley Periodicals, Inc. on behalf of American Society for Clinical Pharmacology and Therapeutics.

  5. Learning Genetics through an Authentic Research Simulation in Bioinformatics

    Science.gov (United States)

    Gelbart, Hadas; Yarden, Anat

    2006-01-01

    Following the rationale that learning is an active process of knowledge construction as well as enculturation into a community of experts, we developed a novel web-based learning environment in bioinformatics for high-school biology majors in Israel. The learning environment enables the learners to actively participate in a guided inquiry process…

  6. Atlas – a data warehouse for integrative bioinformatics

    Directory of Open Access Journals (Sweden)

    Yuen Macaire MS

    2005-02-01

    Full Text Available Abstract Background We present a biological data warehouse called Atlas that locally stores and integrates biological sequences, molecular interactions, homology information, functional annotations of genes, and biological ontologies. The goal of the system is to provide data, as well as a software infrastructure for bioinformatics research and development. Description The Atlas system is based on relational data models that we developed for each of the source data types. Data stored within these relational models are managed through Structured Query Language (SQL calls that are implemented in a set of Application Programming Interfaces (APIs. The APIs include three languages: C++, Java, and Perl. The methods in these API libraries are used to construct a set of loader applications, which parse and load the source datasets into the Atlas database, and a set of toolbox applications which facilitate data retrieval. Atlas stores and integrates local instances of GenBank, RefSeq, UniProt, Human Protein Reference Database (HPRD, Biomolecular Interaction Network Database (BIND, Database of Interacting Proteins (DIP, Molecular Interactions Database (MINT, IntAct, NCBI Taxonomy, Gene Ontology (GO, Online Mendelian Inheritance in Man (OMIM, LocusLink, Entrez Gene and HomoloGene. The retrieval APIs and toolbox applications are critical components that offer end-users flexible, easy, integrated access to this data. We present use cases that use Atlas to integrate these sources for genome annotation, inference of molecular interactions across species, and gene-disease associations. Conclusion The Atlas biological data warehouse serves as data infrastructure for bioinformatics research and development. It forms the backbone of the research activities in our laboratory and facilitates the integration of disparate, heterogeneous biological sources of data enabling new scientific inferences. Atlas achieves integration of diverse data sets at two levels. First

  7. XCluSim: a visual analytics tool for interactively comparing multiple clustering results of bioinformatics data

    Science.gov (United States)

    2015-01-01

    Background Though cluster analysis has become a routine analytic task for bioinformatics research, it is still arduous for researchers to assess the quality of a clustering result. To select the best clustering method and its parameters for a dataset, researchers have to run multiple clustering algorithms and compare them. However, such a comparison task with multiple clustering results is cognitively demanding and laborious. Results In this paper, we present XCluSim, a visual analytics tool that enables users to interactively compare multiple clustering results based on the Visual Information Seeking Mantra. We build a taxonomy for categorizing existing techniques of clustering results visualization in terms of the Gestalt principles of grouping. Using the taxonomy, we choose the most appropriate interactive visualizations for presenting individual clustering results from different types of clustering algorithms. The efficacy of XCluSim is shown through case studies with a bioinformatician. Conclusions Compared to other relevant tools, XCluSim enables users to compare multiple clustering results in a more scalable manner. Moreover, XCluSim supports diverse clustering algorithms and dedicated visualizations and interactions for different types of clustering results, allowing more effective exploration of details on demand. Through case studies with a bioinformatics researcher, we received positive feedback on the functionalities of XCluSim, including its ability to help identify stably clustered items across multiple clustering results. PMID:26328893

  8. PyPedia: using the wiki paradigm as crowd sourcing environment for bioinformatics protocols.

    Science.gov (United States)

    Kanterakis, Alexandros; Kuiper, Joël; Potamias, George; Swertz, Morris A

    2015-01-01

    Today researchers can choose from many bioinformatics protocols for all types of life sciences research, computational environments and coding languages. Although the majority of these are open source, few of them possess all virtues to maximize reuse and promote reproducible science. Wikipedia has proven a great tool to disseminate information and enhance collaboration between users with varying expertise and background to author qualitative content via crowdsourcing. However, it remains an open question whether the wiki paradigm can be applied to bioinformatics protocols. We piloted PyPedia, a wiki where each article is both implementation and documentation of a bioinformatics computational protocol in the python language. Hyperlinks within the wiki can be used to compose complex workflows and induce reuse. A RESTful API enables code execution outside the wiki. Initial content of PyPedia contains articles for population statistics, bioinformatics format conversions and genotype imputation. Use of the easy to learn wiki syntax effectively lowers the barriers to bring expert programmers and less computer savvy researchers on the same page. PyPedia demonstrates how wiki can provide a collaborative development, sharing and even execution environment for biologists and bioinformaticians that complement existing resources, useful for local and multi-center research teams. PyPedia is available online at: http://www.pypedia.com. The source code and installation instructions are available at: https://github.com/kantale/PyPedia_server. The PyPedia python library is available at: https://github.com/kantale/pypedia. PyPedia is open-source, available under the BSD 2-Clause License.

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

    Science.gov (United States)

    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…

  10. Providing Fast Discovery in D2D Communication with Full Duplex Technology

    DEFF Research Database (Denmark)

    Gatnau, Marta; Berardinelli, Gilberto; Mahmood, Nurul Huda

    2016-01-01

    technology to provide D2D fast discovery. Such framework provides an algorithm to estimate the number of neighbor devices and to dynamically decide the transmission probability, for adapting to network changes and meeting the 10 milliseconds target. Finally, a signaling scheme is proposed to reduce......In Direct Device-to-Device (D2D), the device awareness procedure known as the discovery phase is required prior to the exchange of data. This work considers autonomous devices where the infrastructure is not involved in the discovery procedure. Commonly, the transmission of the discovery message...... the network interference. Results show that our framework performs better than a static approach, reducing the time it takes to complete the discovery phase. In addition, supporting full duplex allows to further reduce the discovery time compared to half duplex transmission mode....

  11. SupportNet: a novel incremental learning framework through deep learning and support data

    KAUST Repository

    Li, Yu; Li, Zhongxiao; Ding, Lizhong; Hu, Yuhui; Chen, Wei; Gao, Xin

    2018-01-01

    Motivation: In most biological data sets, the amount of data is regularly growing and the number of classes is continuously increasing. To deal with the new data from the new classes, one approach is to train a classification model, e.g., a deep learning model, from scratch based on both old and new data. This approach is highly computationally costly and the extracted features are likely very different from the ones extracted by the model trained on the old data alone, which leads to poor model robustness. Another approach is to fine tune the trained model from the old data on the new data. However, this approach often does not have the ability to learn new knowledge without forgetting the previously learned knowledge, which is known as the catastrophic forgetting problem. To our knowledge, this problem has not been studied in the field of bioinformatics despite its existence in many bioinformatic problems. Results: Here we propose a novel method, SupportNet, to solve the catastrophic forgetting problem efficiently and effectively. SupportNet combines the strength of deep learning and support vector machine (SVM), where SVM is used to identify the support data from the old data, which are fed to the deep learning model together with the new data for further training so that the model can review the essential information of the old data when learning the new information. Two powerful consolidation regularizers are applied to ensure the robustness of the learned model. Comprehensive experiments on various tasks, including enzyme function prediction, subcellular structure classification and breast tumor classification, show that SupportNet drastically outperforms the state-of-the-art incremental learning methods and reaches similar performance as the deep learning model trained from scratch on both old and new data. Availability: Our program is accessible at: \\url{https://github.com/lykaust15/SupportNet}.

  12. SupportNet: a novel incremental learning framework through deep learning and support data

    KAUST Repository

    Li, Yu

    2018-05-08

    Motivation: In most biological data sets, the amount of data is regularly growing and the number of classes is continuously increasing. To deal with the new data from the new classes, one approach is to train a classification model, e.g., a deep learning model, from scratch based on both old and new data. This approach is highly computationally costly and the extracted features are likely very different from the ones extracted by the model trained on the old data alone, which leads to poor model robustness. Another approach is to fine tune the trained model from the old data on the new data. However, this approach often does not have the ability to learn new knowledge without forgetting the previously learned knowledge, which is known as the catastrophic forgetting problem. To our knowledge, this problem has not been studied in the field of bioinformatics despite its existence in many bioinformatic problems. Results: Here we propose a novel method, SupportNet, to solve the catastrophic forgetting problem efficiently and effectively. SupportNet combines the strength of deep learning and support vector machine (SVM), where SVM is used to identify the support data from the old data, which are fed to the deep learning model together with the new data for further training so that the model can review the essential information of the old data when learning the new information. Two powerful consolidation regularizers are applied to ensure the robustness of the learned model. Comprehensive experiments on various tasks, including enzyme function prediction, subcellular structure classification and breast tumor classification, show that SupportNet drastically outperforms the state-of-the-art incremental learning methods and reaches similar performance as the deep learning model trained from scratch on both old and new data. Availability: Our program is accessible at: \\\\url{https://github.com/lykaust15/SupportNet}.

  13. A Metadata Schema for Geospatial Resource Discovery Use Cases

    Directory of Open Access Journals (Sweden)

    Darren Hardy

    2014-07-01

    Full Text Available We introduce a metadata schema that focuses on GIS discovery use cases for patrons in a research library setting. Text search, faceted refinement, and spatial search and relevancy are among GeoBlacklight's primary use cases for federated geospatial holdings. The schema supports a variety of GIS data types and enables contextual, collection-oriented discovery applications as well as traditional portal applications. One key limitation of GIS resource discovery is the general lack of normative metadata practices, which has led to a proliferation of metadata schemas and duplicate records. The ISO 19115/19139 and FGDC standards specify metadata formats, but are intricate, lengthy, and not focused on discovery. Moreover, they require sophisticated authoring environments and cataloging expertise. Geographic metadata standards target preservation and quality measure use cases, but they do not provide for simple inter-institutional sharing of metadata for discovery use cases. To this end, our schema reuses elements from Dublin Core and GeoRSS to leverage their normative semantics, community best practices, open-source software implementations, and extensive examples already deployed in discovery contexts such as web search and mapping. Finally, we discuss a Solr implementation of the schema using a "geo" extension to MODS.

  14. Learning with Support Vector Machines

    CERN Document Server

    Campbell, Colin

    2010-01-01

    Support Vectors Machines have become a well established tool within machine learning. They work well in practice and have now been used across a wide range of applications from recognizing hand-written digits, to face identification, text categorisation, bioinformatics, and database marketing. In this book we give an introductory overview of this subject. We start with a simple Support Vector Machine for performing binary classification before considering multi-class classification and learning in the presence of noise. We show that this framework can be extended to many other scenarios such a

  15. Rapid cloning and bioinformatic analysis of spinach Y chromosome ...

    Indian Academy of Sciences (India)

    Rapid cloning and bioinformatic analysis of spinach Y chromosome- specific EST sequences. Chuan-Liang Deng, Wei-Li Zhang, Ying Cao, Shao-Jing Wang, ... Arabidopsis thaliana mRNA for mitochondrial half-ABC transporter (STA1 gene). 389 2.31E-13. 98.96. SP3−12. Betula pendula histidine kinase 3 (HK3) mRNA, ...

  16. Automatic generation of bioinformatics tools for predicting protein-ligand binding sites.

    Science.gov (United States)

    Komiyama, Yusuke; Banno, Masaki; Ueki, Kokoro; Saad, Gul; Shimizu, Kentaro

    2016-03-15

    Predictive tools that model protein-ligand binding on demand are needed to promote ligand research in an innovative drug-design environment. However, it takes considerable time and effort to develop predictive tools that can be applied to individual ligands. An automated production pipeline that can rapidly and efficiently develop user-friendly protein-ligand binding predictive tools would be useful. We developed a system for automatically generating protein-ligand binding predictions. Implementation of this system in a pipeline of Semantic Web technique-based web tools will allow users to specify a ligand and receive the tool within 0.5-1 day. We demonstrated high prediction accuracy for three machine learning algorithms and eight ligands. The source code and web application are freely available for download at http://utprot.net They are implemented in Python and supported on Linux. shimizu@bi.a.u-tokyo.ac.jp Supplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press.

  17. Publication, discovery and interoperability of Clinical Decision Support Systems: A Linked Data approach.

    Science.gov (United States)

    Marco-Ruiz, Luis; Pedrinaci, Carlos; Maldonado, J A; Panziera, Luca; Chen, Rong; Bellika, J Gustav

    2016-08-01

    The high costs involved in the development of Clinical Decision Support Systems (CDSS) make it necessary to share their functionality across different systems and organizations. Service Oriented Architectures (SOA) have been proposed to allow reusing CDSS by encapsulating them in a Web service. However, strong barriers in sharing CDS functionality are still present as a consequence of lack of expressiveness of services' interfaces. Linked Services are the evolution of the Semantic Web Services paradigm to process Linked Data. They aim to provide semantic descriptions over SOA implementations to overcome the limitations derived from the syntactic nature of Web services technologies. To facilitate the publication, discovery and interoperability of CDS services by evolving them into Linked Services that expose their interfaces as Linked Data. We developed methods and models to enhance CDS SOA as Linked Services that define a rich semantic layer based on machine interpretable ontologies that powers their interoperability and reuse. These ontologies provided unambiguous descriptions of CDS services properties to expose them to the Web of Data. We developed models compliant with Linked Data principles to create a semantic representation of the components that compose CDS services. To evaluate our approach we implemented a set of CDS Linked Services using a Web service definition ontology. The definitions of Web services were linked to the models developed in order to attach unambiguous semantics to the service components. All models were bound to SNOMED-CT and public ontologies (e.g. Dublin Core) in order to count on a lingua franca to explore them. Discovery and analysis of CDS services based on machine interpretable models was performed reasoning over the ontologies built. Linked Services can be used effectively to expose CDS services to the Web of Data by building on current CDS standards. This allows building shared Linked Knowledge Bases to provide machine

  18. Novel approaches for bioinformatic analysis of salivary RNA sequencing data for development.

    Science.gov (United States)

    Kaczor-Urbanowicz, Karolina Elzbieta; Kim, Yong; Li, Feng; Galeev, Timur; Kitchen, Rob R; Gerstein, Mark; Koyano, Kikuye; Jeong, Sung-Hee; Wang, Xiaoyan; Elashoff, David; Kang, So Young; Kim, Su Mi; Kim, Kyoung; Kim, Sung; Chia, David; Xiao, Xinshu; Rozowsky, Joel; Wong, David T W

    2018-01-01

    Analysis of RNA sequencing (RNA-Seq) data in human saliva is challenging. Lack of standardization and unification of the bioinformatic procedures undermines saliva's diagnostic potential. Thus, it motivated us to perform this study. We applied principal pipelines for bioinformatic analysis of small RNA-Seq data of saliva of 98 healthy Korean volunteers including either direct or indirect mapping of the reads to the human genome using Bowtie1. Analysis of alignments to exogenous genomes by another pipeline revealed that almost all of the reads map to bacterial genomes. Thus, salivary exRNA has fundamental properties that warrant the design of unique additional steps while performing the bioinformatic analysis. Our pipelines can serve as potential guidelines for processing of RNA-Seq data of human saliva. Processing and analysis results of the experimental data generated by the exceRpt (v4.6.3) small RNA-seq pipeline (github.gersteinlab.org/exceRpt) are available from exRNA atlas (exrna-atlas.org). Alignment to exogenous genomes and their quantification results were used in this paper for the analyses of small RNAs of exogenous origin. dtww@ucla.edu. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com

  19. CROSSWORK for Glycans: Glycan Identificatin Through Mass Spectrometry and Bioinformatics

    DEFF Research Database (Denmark)

    Rasmussen, Morten; Thaysen-Andersen, Morten; Højrup, Peter

      We have developed "GLYCANthrope " - CROSSWORKS for glycans:  a bioinformatics tool, which assists in identifying N-linked glycosylated peptides as well as their glycan moieties from MS2 data of enzymatically digested glycoproteins. The program runs either as a stand-alone application or as a plug...

  20. Hidden in the Middle: Culture, Value and Reward in Bioinformatics

    Science.gov (United States)

    Lewis, Jamie; Bartlett, Andrew; Atkinson, Paul

    2016-01-01

    Bioinformatics--the so-called shotgun marriage between biology and computer science--is an interdiscipline. Despite interdisciplinarity being seen as a virtue, for having the capacity to solve complex problems and foster innovation, it has the potential to place projects and people in anomalous categories. For example, valorised…

  1. A middleware-based platform for the integration of bioinformatic services

    Directory of Open Access Journals (Sweden)

    Guzmán Llambías

    2015-08-01

    Full Text Available Performing Bioinformatic´s experiments involve an intensive access to distributed services and information resources through Internet. Although existing tools facilitate the implementation of workflow-oriented applications, they lack of capabilities to integrate services beyond low-scale applications, particularly integrating services with heterogeneous interaction patterns and in a larger scale. This is particularly required to enable a large-scale distributed processing of biological data generated by massive sequencing technologies. On the other hand, such integration mechanisms are provided by middleware products like Enterprise Service Buses (ESB, which enable to integrate distributed systems following a Service Oriented Architecture. This paper proposes an integration platform, based on enterprise middleware, to integrate Bioinformatics services. It presents a multi-level reference architecture and focuses on ESB-based mechanisms to provide asynchronous communications, event-based interactions and data transformation capabilities. The paper presents a formal specification of the platform using the Event-B model.

  2. Introducing bioinformatics, the biosciences' genomic revolution

    CERN Document Server

    Zanella, Paolo

    1999-01-01

    The general audience for these lectures is mainly physicists, computer scientists, engineers or the general public wanting to know more about what’s going on in the biosciences. What’s bioinformatics and why is all this fuss being made about it ? What’s this revolution triggered by the human genome project ? Are there any results yet ? What are the problems ? What new avenues of research have been opened up ? What about the technology ? These new developments will be compared with what happened at CERN earlier in its evolution, and it is hoped that the similiraties and contrasts will stimulate new curiosity and provoke new thoughts.

  3. Directional genomic hybridization for chromosomal inversion discovery and detection.

    Science.gov (United States)

    Ray, F Andrew; Zimmerman, Erin; Robinson, Bruce; Cornforth, Michael N; Bedford, Joel S; Goodwin, Edwin H; Bailey, Susan M

    2013-04-01

    Chromosomal rearrangements are a source of structural variation within the genome that figure prominently in human disease, where the importance of translocations and deletions is well recognized. In principle, inversions-reversals in the orientation of DNA sequences within a chromosome-should have similar detrimental potential. However, the study of inversions has been hampered by traditional approaches used for their detection, which are not particularly robust. Even with significant advances in whole genome approaches, changes in the absolute orientation of DNA remain difficult to detect routinely. Consequently, our understanding of inversions is still surprisingly limited, as is our appreciation for their frequency and involvement in human disease. Here, we introduce the directional genomic hybridization methodology of chromatid painting-a whole new way of looking at structural features of the genome-that can be employed with high resolution on a cell-by-cell basis, and demonstrate its basic capabilities for genome-wide discovery and targeted detection of inversions. Bioinformatics enabled development of sequence- and strand-specific directional probe sets, which when coupled with single-stranded hybridization, greatly improved the resolution and ease of inversion detection. We highlight examples of the far-ranging applicability of this cytogenomics-based approach, which include confirmation of the alignment of the human genome database and evidence that individuals themselves share similar sequence directionality, as well as use in comparative and evolutionary studies for any species whose genome has been sequenced. In addition to applications related to basic mechanistic studies, the information obtainable with strand-specific hybridization strategies may ultimately enable novel gene discovery, thereby benefitting the diagnosis and treatment of a variety of human disease states and disorders including cancer, autism, and idiopathic infertility.

  4. Emergent Computation Emphasizing Bioinformatics

    CERN Document Server

    Simon, Matthew

    2005-01-01

    Emergent Computation is concerned with recent applications of Mathematical Linguistics or Automata Theory. This subject has a primary focus upon "Bioinformatics" (the Genome and arising interest in the Proteome), but the closing chapter also examines applications in Biology, Medicine, Anthropology, etc. The book is composed of an organized examination of DNA, RNA, and the assembly of amino acids into proteins. Rather than examine these areas from a purely mathematical viewpoint (that excludes much of the biochemical reality), the author uses scientific papers written mostly by biochemists based upon their laboratory observations. Thus while DNA may exist in its double stranded form, triple stranded forms are not excluded. Similarly, while bases exist in Watson-Crick complements, mismatched bases and abasic pairs are not excluded, nor are Hoogsteen bonds. Just as there are four bases naturally found in DNA, the existence of additional bases is not ignored, nor amino acids in addition to the usual complement of...

  5. Evaluating the Effectiveness of a Practical Inquiry-Based Learning Bioinformatics Module on Undergraduate Student Engagement and Applied Skills

    Science.gov (United States)

    Brown, James A. L.

    2016-01-01

    A pedagogic intervention, in the form of an inquiry-based peer-assisted learning project (as a practical student-led bioinformatics module), was assessed for its ability to increase students' engagement, practical bioinformatic skills and process-specific knowledge. Elements assessed were process-specific knowledge following module completion,…

  6. Neonatal Informatics: Transforming Neonatal Care Through Translational Bioinformatics

    Science.gov (United States)

    Palma, Jonathan P.; Benitz, William E.; Tarczy-Hornoch, Peter; Butte, Atul J.; Longhurst, Christopher A.

    2012-01-01

    The future of neonatal informatics will be driven by the availability of increasingly vast amounts of clinical and genetic data. The field of translational bioinformatics is concerned with linking and learning from these data and applying new findings to clinical care to transform the data into proactive, predictive, preventive, and participatory health. As a result of advances in translational informatics, the care of neonates will become more data driven, evidence based, and personalized. PMID:22924023

  7. Search strategy has influenced the discovery rate of human viruses.

    Science.gov (United States)

    Rosenberg, Ronald; Johansson, Michael A; Powers, Ann M; Miller, Barry R

    2013-08-20

    A widely held concern is that the pace of infectious disease emergence has been increasing. We have analyzed the rate of discovery of pathogenic viruses, the preeminent source of newly discovered causes of human disease, from 1897 through 2010. The rate was highest during 1950-1969, after which it moderated. This general picture masks two distinct trends: for arthropod-borne viruses, which comprised 39% of pathogenic viruses, the discovery rate peaked at three per year during 1960-1969, but subsequently fell nearly to zero by 1980; however, the rate of discovery of nonarboviruses remained stable at about two per year from 1950 through 2010. The period of highest arbovirus discovery coincided with a comprehensive program supported by The Rockefeller Foundation of isolating viruses from humans, animals, and arthropod vectors at field stations in Latin America, Africa, and India. The productivity of this strategy illustrates the importance of location, approach, long-term commitment, and sponsorship in the discovery of emerging pathogens.

  8. Drug Discovery in an Academic Setting: Playing to the Strengths

    OpenAIRE

    Huryn, Donna M.

    2013-01-01

    Drug discovery and medicinal chemistry initiatives in academia provide an opportunity to create a unique environment that is distinct from the traditional industrial model. Two characteristics of a university setting that are not usually associated with pharma are the ability to pursue high-risk projects and a depth of expertise, infrastructure, and capabilities in focused areas. Encouraging, supporting, and fostering drug discovery efforts that take advantage of these an...

  9. Cloud BioLinux: pre-configured and on-demand bioinformatics computing for the genomics community.

    Science.gov (United States)

    Krampis, Konstantinos; Booth, Tim; Chapman, Brad; Tiwari, Bela; Bicak, Mesude; Field, Dawn; Nelson, Karen E

    2012-03-19

    A steep drop in the cost of next-generation sequencing during recent years has made the technology affordable to the majority of researchers, but downstream bioinformatic analysis still poses a resource bottleneck for smaller laboratories and institutes that do not have access to substantial computational resources. Sequencing instruments are typically bundled with only the minimal processing and storage capacity required for data capture during sequencing runs. Given the scale of sequence datasets, scientific value cannot be obtained from acquiring a sequencer unless it is accompanied by an equal investment in informatics infrastructure. Cloud BioLinux is a publicly accessible Virtual Machine (VM) that enables scientists to quickly provision on-demand infrastructures for high-performance bioinformatics computing using cloud platforms. Users have instant access to a range of pre-configured command line and graphical software applications, including a full-featured desktop interface, documentation and over 135 bioinformatics packages for applications including sequence alignment, clustering, assembly, display, editing, and phylogeny. Each tool's functionality is fully described in the documentation directly accessible from the graphical interface of the VM. Besides the Amazon EC2 cloud, we have started instances of Cloud BioLinux on a private Eucalyptus cloud installed at the J. Craig Venter Institute, and demonstrated access to the bioinformatic tools interface through a remote connection to EC2 instances from a local desktop computer. Documentation for using Cloud BioLinux on EC2 is available from our project website, while a Eucalyptus cloud image and VirtualBox Appliance is also publicly available for download and use by researchers with access to private clouds. Cloud BioLinux provides a platform for developing bioinformatics infrastructures on the cloud. An automated and configurable process builds Virtual Machines, allowing the development of highly

  10. Cloud BioLinux: pre-configured and on-demand bioinformatics computing for the genomics community

    Science.gov (United States)

    2012-01-01

    Background A steep drop in the cost of next-generation sequencing during recent years has made the technology affordable to the majority of researchers, but downstream bioinformatic analysis still poses a resource bottleneck for smaller laboratories and institutes that do not have access to substantial computational resources. Sequencing instruments are typically bundled with only the minimal processing and storage capacity required for data capture during sequencing runs. Given the scale of sequence datasets, scientific value cannot be obtained from acquiring a sequencer unless it is accompanied by an equal investment in informatics infrastructure. Results Cloud BioLinux is a publicly accessible Virtual Machine (VM) that enables scientists to quickly provision on-demand infrastructures for high-performance bioinformatics computing using cloud platforms. Users have instant access to a range of pre-configured command line and graphical software applications, including a full-featured desktop interface, documentation and over 135 bioinformatics packages for applications including sequence alignment, clustering, assembly, display, editing, and phylogeny. Each tool's functionality is fully described in the documentation directly accessible from the graphical interface of the VM. Besides the Amazon EC2 cloud, we have started instances of Cloud BioLinux on a private Eucalyptus cloud installed at the J. Craig Venter Institute, and demonstrated access to the bioinformatic tools interface through a remote connection to EC2 instances from a local desktop computer. Documentation for using Cloud BioLinux on EC2 is available from our project website, while a Eucalyptus cloud image and VirtualBox Appliance is also publicly available for download and use by researchers with access to private clouds. Conclusions Cloud BioLinux provides a platform for developing bioinformatics infrastructures on the cloud. An automated and configurable process builds Virtual Machines, allowing the

  11. Applying Hierarchical Task Analysis Method to Discovery Layer Evaluation

    Directory of Open Access Journals (Sweden)

    Marlen Promann

    2015-03-01

    Full Text Available Libraries are implementing discovery layers to offer better user experiences. While usability tests have been helpful in evaluating the success or failure of implementing discovery layers in the library context, the focus has remained on its relative interface benefits over the traditional federated search. The informal site- and context specific usability tests have offered little to test the rigor of the discovery layers against the user goals, motivations and workflow they have been designed to support. This study proposes hierarchical task analysis (HTA as an important complementary evaluation method to usability testing of discovery layers. Relevant literature is reviewed for the discovery layers and the HTA method. As no previous application of HTA to the evaluation of discovery layers was found, this paper presents the application of HTA as an expert based and workflow centered (e.g. retrieving a relevant book or a journal article method to evaluating discovery layers. Purdue University’s Primo by Ex Libris was used to map eleven use cases as HTA charts. Nielsen’s Goal Composition theory was used as an analytical framework to evaluate the goal carts from two perspectives: a users’ physical interactions (i.e. clicks, and b user’s cognitive steps (i.e. decision points for what to do next. A brief comparison of HTA and usability test findings is offered as a way of conclusion.

  12. Rough – Granular Computing knowledge discovery models

    Directory of Open Access Journals (Sweden)

    Mohammed M. Eissa

    2016-11-01

    Full Text Available Medical domain has become one of the most important areas of research in order to richness huge amounts of medical information about the symptoms of diseases and how to distinguish between them to diagnose it correctly. Knowledge discovery models play vital role in refinement and mining of medical indicators to help medical experts to settle treatment decisions. This paper introduces four hybrid Rough – Granular Computing knowledge discovery models based on Rough Sets Theory, Artificial Neural Networks, Genetic Algorithm and Rough Mereology Theory. A comparative analysis of various knowledge discovery models that use different knowledge discovery techniques for data pre-processing, reduction, and data mining supports medical experts to extract the main medical indicators, to reduce the misdiagnosis rates and to improve decision-making for medical diagnosis and treatment. The proposed models utilized two medical datasets: Coronary Heart Disease dataset and Hepatitis C Virus dataset. The main purpose of this paper was to explore and evaluate the proposed models based on Granular Computing methodology for knowledge extraction according to different evaluation criteria for classification of medical datasets. Another purpose is to make enhancement in the frame of KDD processes for supervised learning using Granular Computing methodology.

  13. Multiobjective optimization in bioinformatics and computational biology.

    Science.gov (United States)

    Handl, Julia; Kell, Douglas B; Knowles, Joshua

    2007-01-01

    This paper reviews the application of multiobjective optimization in the fields of bioinformatics and computational biology. A survey of existing work, organized by application area, forms the main body of the review, following an introduction to the key concepts in multiobjective optimization. An original contribution of the review is the identification of five distinct "contexts," giving rise to multiple objectives: These are used to explain the reasons behind the use of multiobjective optimization in each application area and also to point the way to potential future uses of the technique.

  14. A Discovery of Strong Metal-Support Bonding in Nanoengineered Au-Fe3O4 Dumbbell-like Nanoparticles by in Situ Transmission Electron Microscopy.

    Science.gov (United States)

    Han, Chang Wan; Choksi, Tej; Milligan, Cory; Majumdar, Paulami; Manto, Michael; Cui, Yanran; Sang, Xiahan; Unocic, Raymond R; Zemlyanov, Dmitry; Wang, Chao; Ribeiro, Fabio H; Greeley, Jeffrey; Ortalan, Volkan

    2017-08-09

    The strength of metal-support bonding in heterogeneous catalysts determines their thermal stability, therefore, a tremendous amount of effort has been expended to understand metal-support interactions. Herein, we report the discovery of an anomalous "strong metal-support bonding" between gold nanoparticles and "nano-engineered" Fe 3 O 4 substrates by in situ microscopy. During in situ vacuum annealing of Au-Fe 3 O 4 dumbbell-like nanoparticles, synthesized by the epitaxial growth of nano-Fe 3 O 4 on Au nanoparticles, the gold nanoparticles transform into the gold thin films and wet the surface of nano-Fe 3 O 4 , as the surface reduction of nano-Fe 3 O 4 proceeds. This phenomenon results from a unique coupling of the size-and shape-dependent high surface reducibility of nano-Fe 3 O 4 and the extremely strong adhesion between Au and the reduced Fe 3 O 4 . This strong metal-support bonding reveals the significance of controlling the metal oxide support size and morphology for optimizing metal-support bonding and ultimately for the development of improved catalysts and functional nanostructures.

  15. An internet-based bioinformatics toolkit for plant biosecurity diagnosis and surveillance of viruses and viroids.

    Science.gov (United States)

    Barrero, Roberto A; Napier, Kathryn R; Cunnington, James; Liefting, Lia; Keenan, Sandi; Frampton, Rebekah A; Szabo, Tamas; Bulman, Simon; Hunter, Adam; Ward, Lisa; Whattam, Mark; Bellgard, Matthew I

    2017-01-11

    Detection and preventing entry of exotic viruses and viroids at the border is critical for protecting plant industries trade worldwide. Existing post entry quarantine screening protocols rely on time-consuming biological indicators and/or molecular assays that require knowledge of infecting viral pathogens. Plants have developed the ability to recognise and respond to viral infections through Dicer-like enzymes that cleave viral sequences into specific small RNA products. Many studies reported the use of a broad range of small RNAs encompassing the product sizes of several Dicer enzymes involved in distinct biological pathways. Here we optimise the assembly of viral sequences by using specific small RNA subsets. We sequenced the small RNA fractions of 21 plants held at quarantine glasshouse facilities in Australia and New Zealand. Benchmarking of several de novo assembler tools yielded SPAdes using a kmer of 19 to produce the best assembly outcomes. We also found that de novo assembly using 21-25 nt small RNAs can result in chimeric assemblies of viral sequences and plant host sequences. Such non-specific assemblies can be resolved by using 21-22 nt or 24 nt small RNAs subsets. Among the 21 selected samples, we identified contigs with sequence similarity to 18 viruses and 3 viroids in 13 samples. Most of the viruses were assembled using only 21-22 nt long virus-derived siRNAs (viRNAs), except for one Citrus endogenous pararetrovirus that was more efficiently assembled using 24 nt long viRNAs. All three viroids found in this study were fully assembled using either 21-22 nt or 24 nt viRNAs. Optimised analysis workflows were customised within the Yabi web-based analytical environment. We present a fully automated viral surveillance and diagnosis web-based bioinformatics toolkit that provides a flexible, user-friendly, robust and scalable interface for the discovery and diagnosis of viral pathogens. We have implemented an automated viral surveillance and

  16. A review of bioinformatic methods for forensic DNA analyses.

    Science.gov (United States)

    Liu, Yao-Yuan; Harbison, SallyAnn

    2018-03-01

    Short tandem repeats, single nucleotide polymorphisms, and whole mitochondrial analyses are three classes of markers which will play an important role in the future of forensic DNA typing. The arrival of massively parallel sequencing platforms in forensic science reveals new information such as insights into the complexity and variability of the markers that were previously unseen, along with amounts of data too immense for analyses by manual means. Along with the sequencing chemistries employed, bioinformatic methods are required to process and interpret this new and extensive data. As more is learnt about the use of these new technologies for forensic applications, development and standardization of efficient, favourable tools for each stage of data processing is being carried out, and faster, more accurate methods that improve on the original approaches have been developed. As forensic laboratories search for the optimal pipeline of tools, sequencer manufacturers have incorporated pipelines into sequencer software to make analyses convenient. This review explores the current state of bioinformatic methods and tools used for the analyses of forensic markers sequenced on the massively parallel sequencing (MPS) platforms currently most widely used. Copyright © 2017 Elsevier B.V. All rights reserved.

  17. A generally applicable lightweight method for calculating a value structure for tools and services in bioinformatics infrastructure projects.

    Science.gov (United States)

    Mayer, Gerhard; Quast, Christian; Felden, Janine; Lange, Matthias; Prinz, Manuel; Pühler, Alfred; Lawerenz, Chris; Scholz, Uwe; Glöckner, Frank Oliver; Müller, Wolfgang; Marcus, Katrin; Eisenacher, Martin

    2017-10-30

    Sustainable noncommercial bioinformatics infrastructures are a prerequisite to use and take advantage of the potential of big data analysis for research and economy. Consequently, funders, universities and institutes as well as users ask for a transparent value model for the tools and services offered. In this article, a generally applicable lightweight method is described by which bioinformatics infrastructure projects can estimate the value of tools and services offered without determining exactly the total costs of ownership. Five representative scenarios for value estimation from a rough estimation to a detailed breakdown of costs are presented. To account for the diversity in bioinformatics applications and services, the notion of service-specific 'service provision units' is introduced together with the factors influencing them and the main underlying assumptions for these 'value influencing factors'. Special attention is given on how to handle personnel costs and indirect costs such as electricity. Four examples are presented for the calculation of the value of tools and services provided by the German Network for Bioinformatics Infrastructure (de.NBI): one for tool usage, one for (Web-based) database analyses, one for consulting services and one for bioinformatics training events. Finally, from the discussed values, the costs of direct funding and the costs of payment of services by funded projects are calculated and compared. © The Author 2017. Published by Oxford University Press.

  18. Kubernetes as an approach for solving bioinformatic problems.

    OpenAIRE

    Markstedt, Olof

    2017-01-01

    The cluster orchestration tool Kubernetes enables easy deployment and reproducibility of life science research by utilizing the advantages of the container technology. The container technology allows for easy tool creation, sharing and runs on any Linux system once it has been built. The applicability of Kubernetes as an approach to run bioinformatic workflows was evaluated and resulted in some examples of how Kubernetes and containers could be used within the field of life science and how th...

  19. Using Bioinformatics to Develop and Test Hypotheses: E. coli-Specific Virulence Determinants

    Directory of Open Access Journals (Sweden)

    Joanna R. Klein

    2012-09-01

    Full Text Available Bioinformatics, the use of computer resources to understand biological information, is an important tool in research, and can be easily integrated into the curriculum of undergraduate courses. Such an example is provided in this series of four activities that introduces students to the field of bioinformatics as they design PCR based tests for pathogenic E. coli strains. A variety of computer tools are used including BLAST searches at NCBI, bacterial genome searches at the Integrated Microbial Genomes (IMG database, protein analysis at Pfam and literature research at PubMed. In the process, students also learn about virulence factors, enzyme function and horizontal gene transfer. Some or all of the four activities can be incorporated into microbiology or general biology courses taken by students at a variety of levels, ranging from high school through college. The activities build on one another as they teach and reinforce knowledge and skills, promote critical thinking, and provide for student collaboration and presentation. The computer-based activities can be done either in class or outside of class, thus are appropriate for inclusion in online or blended learning formats. Assessment data showed that students learned general microbiology concepts related to pathogenesis and enzyme function, gained skills in using tools of bioinformatics and molecular biology, and successfully developed and tested a scientific hypothesis.

  20. Scientific workflows as productivity tools for drug discovery.

    Science.gov (United States)

    Shon, John; Ohkawa, Hitomi; Hammer, Juergen

    2008-05-01

    Large pharmaceutical companies annually invest tens to hundreds of millions of US dollars in research informatics to support their early drug discovery processes. Traditionally, most of these investments are designed to increase the efficiency of drug discovery. The introduction of do-it-yourself scientific workflow platforms has enabled research informatics organizations to shift their efforts toward scientific innovation, ultimately resulting in a possible increase in return on their investments. Unlike the handling of most scientific data and application integration approaches, researchers apply scientific workflows to in silico experimentation and exploration, leading to scientific discoveries that lie beyond automation and integration. This review highlights some key requirements for scientific workflow environments in the pharmaceutical industry that are necessary for increasing research productivity. Examples of the application of scientific workflows in research and a summary of recent platform advances are also provided.

  1. Bioinformatics study of the mangrove actin genes

    Science.gov (United States)

    Basyuni, M.; Wasilah, M.; Sumardi

    2017-01-01

    This study describes the bioinformatics methods to analyze eight actin genes from mangrove plants on DDBJ/EMBL/GenBank as well as predicted the structure, composition, subcellular localization, similarity, and phylogenetic. The physical and chemical properties of eight mangroves showed variation among the genes. The percentage of the secondary structure of eight mangrove actin genes followed the order of a helix > random coil > extended chain structure for BgActl, KcActl, RsActl, and A. corniculatum Act. In contrast to this observation, the remaining actin genes were random coil > extended chain structure > a helix. This study, therefore, shown the prediction of secondary structure was performed for necessary structural information. The values of chloroplast or signal peptide or mitochondrial target were too small, indicated that no chloroplast or mitochondrial transit peptide or signal peptide of secretion pathway in mangrove actin genes. These results suggested the importance of understanding the diversity and functional of properties of the different amino acids in mangrove actin genes. To clarify the relationship among the mangrove actin gene, a phylogenetic tree was constructed. Three groups of mangrove actin genes were formed, the first group contains B. gymnorrhiza BgAct and R. stylosa RsActl. The second cluster which consists of 5 actin genes the largest group, and the last branch consist of one gene, B. sexagula Act. The present study, therefore, supported the previous results that plant actin genes form distinct clusters in the tree.

  2. Data mining in bioinformatics using Weka.

    Science.gov (United States)

    Frank, Eibe; Hall, Mark; Trigg, Len; Holmes, Geoffrey; Witten, Ian H

    2004-10-12

    The Weka machine learning workbench provides a general-purpose environment for automatic classification, regression, clustering and feature selection-common data mining problems in bioinformatics research. It contains an extensive collection of machine learning algorithms and data pre-processing methods complemented by graphical user interfaces for data exploration and the experimental comparison of different machine learning techniques on the same problem. Weka can process data given in the form of a single relational table. Its main objectives are to (a) assist users in extracting useful information from data and (b) enable them to easily identify a suitable algorithm for generating an accurate predictive model from it. http://www.cs.waikato.ac.nz/ml/weka.

  3. Topology Discovery Using Cisco Discovery Protocol

    OpenAIRE

    Rodriguez, Sergio R.

    2009-01-01

    In this paper we address the problem of discovering network topology in proprietary networks. Namely, we investigate topology discovery in Cisco-based networks. Cisco devices run Cisco Discovery Protocol (CDP) which holds information about these devices. We first compare properties of topologies that can be obtained from networks deploying CDP versus Spanning Tree Protocol (STP) and Management Information Base (MIB) Forwarding Database (FDB). Then we describe a method of discovering topology ...

  4. Video Bioinformatics Analysis of Human Embryonic Stem Cell Colony Growth

    Science.gov (United States)

    Lin, Sabrina; Fonteno, Shawn; Satish, Shruthi; Bhanu, Bir; Talbot, Prue

    2010-01-01

    Because video data are complex and are comprised of many images, mining information from video material is difficult to do without the aid of computer software. Video bioinformatics is a powerful quantitative approach for extracting spatio-temporal data from video images using computer software to perform dating mining and analysis. In this article, we introduce a video bioinformatics method for quantifying the growth of human embryonic stem cells (hESC) by analyzing time-lapse videos collected in a Nikon BioStation CT incubator equipped with a camera for video imaging. In our experiments, hESC colonies that were attached to Matrigel were filmed for 48 hours in the BioStation CT. To determine the rate of growth of these colonies, recipes were developed using CL-Quant software which enables users to extract various types of data from video images. To accurately evaluate colony growth, three recipes were created. The first segmented the image into the colony and background, the second enhanced the image to define colonies throughout the video sequence accurately, and the third measured the number of pixels in the colony over time. The three recipes were run in sequence on video data collected in a BioStation CT to analyze the rate of growth of individual hESC colonies over 48 hours. To verify the truthfulness of the CL-Quant recipes, the same data were analyzed manually using Adobe Photoshop software. When the data obtained using the CL-Quant recipes and Photoshop were compared, results were virtually identical, indicating the CL-Quant recipes were truthful. The method described here could be applied to any video data to measure growth rates of hESC or other cells that grow in colonies. In addition, other video bioinformatics recipes can be developed in the future for other cell processes such as migration, apoptosis, and cell adhesion. PMID:20495527

  5. iSyTE 2.0: a database for expression-based gene discovery in the eye

    Science.gov (United States)

    Kakrana, Atul; Yang, Andrian; Anand, Deepti; Djordjevic, Djordje; Ramachandruni, Deepti; Singh, Abhyudai; Huang, Hongzhan

    2018-01-01

    Abstract Although successful in identifying new cataract-linked genes, the previous version of the database iSyTE (integrated Systems Tool for Eye gene discovery) was based on expression information on just three mouse lens stages and was functionally limited to visualization by only UCSC-Genome Browser tracks. To increase its efficacy, here we provide an enhanced iSyTE version 2.0 (URL: http://research.bioinformatics.udel.edu/iSyTE) based on well-curated, comprehensive genome-level lens expression data as a one-stop portal for the effective visualization and analysis of candidate genes in lens development and disease. iSyTE 2.0 includes all publicly available lens Affymetrix and Illumina microarray datasets representing a broad range of embryonic and postnatal stages from wild-type and specific gene-perturbation mouse mutants with eye defects. Further, we developed a new user-friendly web interface for direct access and cogent visualization of the curated expression data, which supports convenient searches and a range of downstream analyses. The utility of these new iSyTE 2.0 features is illustrated through examples of established genes associated with lens development and pathobiology, which serve as tutorials for its application by the end-user. iSyTE 2.0 will facilitate the prioritization of eye development and disease-linked candidate genes in studies involving transcriptomics or next-generation sequencing data, linkage analysis and GWAS approaches. PMID:29036527

  6. Bioinformatics and structural characterization of a hypothetical protein from Streptococcus mutans

    DEFF Research Database (Denmark)

    Nan, Jie; Brostromer, Erik; Liu, Xiang-Yu

    2009-01-01

    . From the interlinking structural and bioinformatics studies, we have concluded that SMU.440 could be involved in polyketide-like antibiotic resistance, providing a better understanding of this hypothetical protein. Besides, the combination of multiple methods in this study can be used as a general...

  7. Databases and Associated Bioinformatic Tools in Studies of Food Allergens, Epitopes and Haptens – a Review

    Directory of Open Access Journals (Sweden)

    Bucholska Justyna

    2018-06-01

    Full Text Available Allergies and/or food intolerances are a growing problem of the modern world. Diffi culties associated with the correct diagnosis of food allergies result in the need to classify the factors causing allergies and allergens themselves. Therefore, internet databases and other bioinformatic tools play a special role in deepening knowledge of biologically-important compounds. Internet repositories, as a source of information on different chemical compounds, including those related to allergy and intolerance, are increasingly being used by scientists. Bioinformatic methods play a signifi cant role in biological and medical sciences, and their importance in food science is increasing. This study aimed at presenting selected databases and tools of bioinformatic analysis useful in research on food allergies, allergens (11 databases, epitopes (7 databases, and haptens (2 databases. It also presents examples of the application of computer methods in studies related to allergies.

  8. Bioinformatics prediction of swine MHC class I epitopes from Porcine Reproductive and Respiratory Syndrome Virus

    DEFF Research Database (Denmark)

    Welner, Simon; Nielsen, Morten; Lund, Ole

    an effective CTL response against PRRSV, we have taken a bioinformatics approach to identify common PRRSV epitopes predicted to react broadly with predominant swine MHC (SLA) alleles. First, the genomic integrity and sequencing method was examined for 334 available complete PRRSV type 2 genomes leaving 104...... by the PopCover algorithm, providing a final list of 54 epitopes prioritized according to maximum coverage of PRRSV strains and SLA alleles. This bioinformatics approach provides a rational strategy for selecting peptides for a CTL-activating vaccine with broad coverage of both virus and swine diversity...

  9. Pharmacological screening technologies for venom peptide discovery.

    Science.gov (United States)

    Prashanth, Jutty Rajan; Hasaballah, Nojod; Vetter, Irina

    2017-12-01

    Venomous animals occupy one of the most successful evolutionary niches and occur on nearly every continent. They deliver venoms via biting and stinging apparatuses with the aim to rapidly incapacitate prey and deter predators. This has led to the evolution of venom components that act at a number of biological targets - including ion channels, G-protein coupled receptors, transporters and enzymes - with exquisite selectivity and potency, making venom-derived components attractive pharmacological tool compounds and drug leads. In recent years, plate-based pharmacological screening approaches have been introduced to accelerate venom-derived drug discovery. A range of assays are amenable to this purpose, including high-throughput electrophysiology, fluorescence-based functional and binding assays. However, despite these technological advances, the traditional activity-guided fractionation approach is time-consuming and resource-intensive. The combination of screening techniques suitable for miniaturization with sequence-based discovery approaches - supported by advanced proteomics, mass spectrometry, chromatography as well as synthesis and expression techniques - promises to further improve venom peptide discovery. Here, we discuss practical aspects of establishing a pipeline for venom peptide drug discovery with a particular emphasis on pharmacology and pharmacological screening approaches. This article is part of the Special Issue entitled 'Venom-derived Peptides as Pharmacological Tools.' Copyright © 2017 Elsevier Ltd. All rights reserved.

  10. Designing a course model for distance-based online bioinformatics training in Africa: The H3ABioNet experience

    Science.gov (United States)

    Panji, Sumir; Fernandes, Pedro L.; Judge, David P.; Ghouila, Amel; Salifu, Samson P.; Ahmed, Rehab; Kayondo, Jonathan; Ssemwanga, Deogratius

    2017-01-01

    Africa is not unique in its need for basic bioinformatics training for individuals from a diverse range of academic backgrounds. However, particular logistical challenges in Africa, most notably access to bioinformatics expertise and internet stability, must be addressed in order to meet this need on the continent. H3ABioNet (www.h3abionet.org), the Pan African Bioinformatics Network for H3Africa, has therefore developed an innovative, free-of-charge “Introduction to Bioinformatics” course, taking these challenges into account as part of its educational efforts to provide on-site training and develop local expertise inside its network. A multiple-delivery–mode learning model was selected for this 3-month course in order to increase access to (mostly) African, expert bioinformatics trainers. The content of the course was developed to include a range of fundamental bioinformatics topics at the introductory level. For the first iteration of the course (2016), classrooms with a total of 364 enrolled participants were hosted at 20 institutions across 10 African countries. To ensure that classroom success did not depend on stable internet, trainers pre-recorded their lectures, and classrooms downloaded and watched these locally during biweekly contact sessions. The trainers were available via video conferencing to take questions during contact sessions, as well as via online “question and discussion” forums outside of contact session time. This learning model, developed for a resource-limited setting, could easily be adapted to other settings. PMID:28981516

  11. GeneDig: a web application for accessing genomic and bioinformatics knowledge.

    Science.gov (United States)

    Suciu, Radu M; Aydin, Emir; Chen, Brian E

    2015-02-28

    With the exponential increase and widespread availability of genomic, transcriptomic, and proteomic data, accessing these '-omics' data is becoming increasingly difficult. The current resources for accessing and analyzing these data have been created to perform highly specific functions intended for specialists, and thus typically emphasize functionality over user experience. We have developed a web-based application, GeneDig.org, that allows any general user access to genomic information with ease and efficiency. GeneDig allows for searching and browsing genes and genomes, while a dynamic navigator displays genomic, RNA, and protein information simultaneously for co-navigation. We demonstrate that our application allows more than five times faster and efficient access to genomic information than any currently available methods. We have developed GeneDig as a platform for bioinformatics integration focused on usability as its central design. This platform will introduce genomic navigation to broader audiences while aiding the bioinformatics analyses performed in everyday biology research.

  12. Host-parasite interactions and ecology of the malaria parasite-a bioinformatics approach.

    Science.gov (United States)

    Izak, Dariusz; Klim, Joanna; Kaczanowski, Szymon

    2018-04-25

    Malaria remains one of the highest mortality infectious diseases. Malaria is caused by parasites from the genus Plasmodium. Most deaths are caused by infections involving Plasmodium falciparum, which has a complex life cycle. Malaria parasites are extremely well adapted for interactions with their host and their host's immune system and are able to suppress the human immune system, erase immunological memory and rapidly alter exposed antigens. Owing to this rapid evolution, parasites develop drug resistance and express novel forms of antigenic proteins that are not recognized by the host immune system. There is an emerging need for novel interventions, including novel drugs and vaccines. Designing novel therapies requires knowledge about host-parasite interactions, which is still limited. However, significant progress has recently been achieved in this field through the application of bioinformatics analysis of parasite genome sequences. In this review, we describe the main achievements in 'malarial' bioinformatics and provide examples of successful applications of protein sequence analysis. These examples include the prediction of protein functions based on homology and the prediction of protein surface localization via domain and motif analysis. Additionally, we describe PlasmoDB, a database that stores accumulated experimental data. This tool allows data mining of the stored information and will play an important role in the development of malaria science. Finally, we illustrate the application of bioinformatics in the development of population genetics research on malaria parasites, an approach referred to as reverse ecology.

  13. BioXSD: the common data-exchange format for everyday bioinformatics web services.

    Science.gov (United States)

    Kalas, Matús; Puntervoll, Pål; Joseph, Alexandre; Bartaseviciūte, Edita; Töpfer, Armin; Venkataraman, Prabakar; Pettifer, Steve; Bryne, Jan Christian; Ison, Jon; Blanchet, Christophe; Rapacki, Kristoffer; Jonassen, Inge

    2010-09-15

    The world-wide community of life scientists has access to a large number of public bioinformatics databases and tools, which are developed and deployed using diverse technologies and designs. More and more of the resources offer programmatic web-service interface. However, efficient use of the resources is hampered by the lack of widely used, standard data-exchange formats for the basic, everyday bioinformatics data types. BioXSD has been developed as a candidate for standard, canonical exchange format for basic bioinformatics data. BioXSD is represented by a dedicated XML Schema and defines syntax for biological sequences, sequence annotations, alignments and references to resources. We have adapted a set of web services to use BioXSD as the input and output format, and implemented a test-case workflow. This demonstrates that the approach is feasible and provides smooth interoperability. Semantics for BioXSD is provided by annotation with the EDAM ontology. We discuss in a separate section how BioXSD relates to other initiatives and approaches, including existing standards and the Semantic Web. The BioXSD 1.0 XML Schema is freely available at http://www.bioxsd.org/BioXSD-1.0.xsd under the Creative Commons BY-ND 3.0 license. The http://bioxsd.org web page offers documentation, examples of data in BioXSD format, example workflows with source codes in common programming languages, an updated list of compatible web services and tools and a repository of feature requests from the community.

  14. MicroRNA from tuberculosis RNA: A bioinformatics study

    OpenAIRE

    Wiwanitkit, Somsri; Wiwanitkit, Viroj

    2012-01-01

    The role of microRNA in the pathogenesis of pulmonary tuberculosis is the interesting topic in chest medicine at present. Recently, it was proposed that the microRNA can be a useful biomarker for monitoring of pulmonary tuberculosis and might be the important part in pathogenesis of disease. Here, the authors perform a bioinformatics study to assess the microRNA within known tuberculosis RNA. The microRNA part can be detected and this can be important key information in further study of the p...

  15. Scientific Prediction and Prophetic Patenting in Drug Discovery.

    Science.gov (United States)

    Curry, Stephen H; Schneiderman, Anne M

    2015-01-01

    Pharmaceutical patenting involves writing claims based on both discoveries already made, and on prophesy of future developments in an ongoing project. This is necessitated by the very different timelines involved in the drug discovery and product development process on the one hand, and successful patenting on the other. If patents are sought too early there is a risk that patent examiners will disallow claims because of lack of enablement. If patenting is delayed, claims are at risk of being denied on the basis of existence of prior art, because the body of relevant known science will have developed significantly while the project was being pursued. This review examines the role of prophetic patenting in relation to the essential predictability of many aspects of drug discovery science, promoting the concepts of discipline-related and project-related prediction. This is especially directed towards patenting activities supporting commercialization of academia-based discoveries, where long project timelines occur, and where experience, and resources to pay for patenting, are limited. The need for improved collaborative understanding among project scientists, technology transfer professionals in, for example, universities, patent attorneys, and patent examiners is emphasized.

  16. 14 CFR 406.143 - Discovery.

    Science.gov (United States)

    2010-01-01

    ... 14 Aeronautics and Space 4 2010-01-01 2010-01-01 false Discovery. 406.143 Section 406.143... Transportation Adjudications § 406.143 Discovery. (a) Initiation of discovery. Any party may initiate discovery... after a complaint has been filed. (b) Methods of discovery. The following methods of discovery are...

  17. FungiDB: An Integrated Bioinformatic Resource for Fungi and Oomycetes

    Directory of Open Access Journals (Sweden)

    Evelina Y. Basenko

    2018-03-01

    Full Text Available FungiDB (fungidb.org is a free online resource for data mining and functional genomics analysis for fungal and oomycete species. FungiDB is part of the Eukaryotic Pathogen Genomics Database Resource (EuPathDB, eupathdb.org platform that integrates genomic, transcriptomic, proteomic, and phenotypic datasets, and other types of data for pathogenic and nonpathogenic, free-living and parasitic organisms. FungiDB is one of the largest EuPathDB databases containing nearly 100 genomes obtained from GenBank, Aspergillus Genome Database (AspGD, The Broad Institute, Joint Genome Institute (JGI, Ensembl, and other sources. FungiDB offers a user-friendly web interface with embedded bioinformatics tools that support custom in silico experiments that leverage FungiDB-integrated data. In addition, a Galaxy-based workspace enables users to generate custom pipelines for large-scale data analysis (e.g., RNA-Seq, variant calling, etc.. This review provides an introduction to the FungiDB resources and focuses on available features, tools, and queries and how they can be used to mine data across a diverse range of integrated FungiDB datasets and records.

  18. Bioinformatics for Next Generation Sequencing Data

    Directory of Open Access Journals (Sweden)

    Alberto Magi

    2010-09-01

    Full Text Available The emergence of next-generation sequencing (NGS platforms imposes increasing demands on statistical methods and bioinformatic tools for the analysis and the management of the huge amounts of data generated by these technologies. Even at the early stages of their commercial availability, a large number of softwares already exist for analyzing NGS data. These tools can be fit into many general categories including alignment of sequence reads to a reference, base-calling and/or polymorphism detection, de novo assembly from paired or unpaired reads, structural variant detection and genome browsing. This manuscript aims to guide readers in the choice of the available computational tools that can be used to face the several steps of the data analysis workflow.

  19. Clinical decision support systems for improving diagnostic accuracy and achieving precision medicine.

    Science.gov (United States)

    Castaneda, Christian; Nalley, Kip; Mannion, Ciaran; Bhattacharyya, Pritish; Blake, Patrick; Pecora, Andrew; Goy, Andre; Suh, K Stephen

    2015-01-01

    As research laboratories and clinics collaborate to achieve precision medicine, both communities are required to understand mandated electronic health/medical record (EHR/EMR) initiatives that will be fully implemented in all clinics in the United States by 2015. Stakeholders will need to evaluate current record keeping practices and optimize and standardize methodologies to capture nearly all information in digital format. Collaborative efforts from academic and industry sectors are crucial to achieving higher efficacy in patient care while minimizing costs. Currently existing digitized data and information are present in multiple formats and are largely unstructured. In the absence of a universally accepted management system, departments and institutions continue to generate silos of information. As a result, invaluable and newly discovered knowledge is difficult to access. To accelerate biomedical research and reduce healthcare costs, clinical and bioinformatics systems must employ common data elements to create structured annotation forms enabling laboratories and clinics to capture sharable data in real time. Conversion of these datasets to knowable information should be a routine institutionalized process. New scientific knowledge and clinical discoveries can be shared via integrated knowledge environments defined by flexible data models and extensive use of standards, ontologies, vocabularies, and thesauri. In the clinical setting, aggregated knowledge must be displayed in user-friendly formats so that physicians, non-technical laboratory personnel, nurses, data/research coordinators, and end-users can enter data, access information, and understand the output. The effort to connect astronomical numbers of data points, including '-omics'-based molecular data, individual genome sequences, experimental data, patient clinical phenotypes, and follow-up data is a monumental task. Roadblocks to this vision of integration and interoperability include ethical, legal

  20. Application of lean manufacturing concepts to drug discovery: rapid analogue library synthesis.

    Science.gov (United States)

    Weller, Harold N; Nirschl, David S; Petrillo, Edward W; Poss, Michael A; Andres, Charles J; Cavallaro, Cullen L; Echols, Martin M; Grant-Young, Katherine A; Houston, John G; Miller, Arthur V; Swann, R Thomas

    2006-01-01

    The application of parallel synthesis to lead optimization programs in drug discovery has been an ongoing challenge since the first reports of library synthesis. A number of approaches to the application of parallel array synthesis to lead optimization have been attempted over the years, ranging from widespread deployment by (and support of) individual medicinal chemists to centralization as a service by an expert core team. This manuscript describes our experience with the latter approach, which was undertaken as part of a larger initiative to optimize drug discovery. In particular, we highlight how concepts taken from the manufacturing sector can be applied to drug discovery and parallel synthesis to improve the timeliness and thus the impact of arrays on drug discovery.

  1. Reinventing Discovery Learning: A Field-Wide Research Program

    Science.gov (United States)

    Abrahamson, Dor; Kapur, Manu

    2018-01-01

    Whereas some educational designers believe that students should learn new concepts through explorative problem solving within dedicated environments that constrain key parameters of their search and then support their progressive appropriation of empowering disciplinary forms, others are critical of the ultimate efficacy of this discovery-based…

  2. Higgs Discovery

    DEFF Research Database (Denmark)

    Sannino, Francesco

    2013-01-01

    has been challenged by the discovery of a not-so-heavy Higgs-like state. I will therefore review the recent discovery \\cite{Foadi:2012bb} that the standard model top-induced radiative corrections naturally reduce the intrinsic non-perturbative mass of the composite Higgs state towards the desired...... via first principle lattice simulations with encouraging results. The new findings show that the recent naive claims made about new strong dynamics at the electroweak scale being disfavoured by the discovery of a not-so-heavy composite Higgs are unwarranted. I will then introduce the more speculative......I discuss the impact of the discovery of a Higgs-like state on composite dynamics starting by critically examining the reasons in favour of either an elementary or composite nature of this state. Accepting the standard model interpretation I re-address the standard model vacuum stability within...

  3. Reporting Astronomical Discoveries: Past, Now, and Future

    Science.gov (United States)

    Yamaoka, Hitoshi; Green, Daniel W. E.; Samus, Nikolai N.; West, Richard

    2015-08-01

    Many new astronomical objects have been discovered over the years by amateur astronomers, and this continues to be the case. They have traditionally reported them (as have professional astronomers) to the Central Bureau for Astronomical Telegrams (CBAT), which was established in the 19th century. This procedure has worked very well throughout the 20th century, moving under the umbrella of the newly established IAU in 1920. The discoverers have been honored by the formal announcement of their discoveries in the publications of the CBAT.In recent years, some professional research groups have established other ways of announcing their discoveries of explosive objects such as novae and supernovae; some do not now report their discoveries or spectroscopic confirmations of the transients to the CBAT, including often spectroscopic reports of objects posted to the CBAT "Transient Objects Confirmation Page" -- the highly successful TOCP webpage, which assigns official positional designations to new transients posted there by approved, registered users. This leads to a delay in formal announcements of discoveries by amateur astronomers in many cases, as well as inconsistent designations being put into use by individual groups. Amateur astronomers are feeling frustrated about this situation, and they hope that the IAU will help to settle the situation.We have proposed the new IAU commission NC-52, which will treat these phenomena in a continuation of Commission 6, through the CBAT. We hope to continuously support the reporting of the discoveries by amateur astronomers, as well as professional astronomers, who all deserve and desire proper recognition. Our strategy will maintain the firm trust between the amateur and professional astronomers, which is necessary for true collaboration. The plan is for the CBAT to work with collaborators to assure that discoveries posted on the TOCP are promptly designated and announced by the CBAT, even when confirmations are made elsewhere

  4. [Artificial Intelligence in Drug Discovery].

    Science.gov (United States)

    Fujiwara, Takeshi; Kamada, Mayumi; Okuno, Yasushi

    2018-04-01

    According to the increase of data generated from analytical instruments, application of artificial intelligence(AI)technology in medical field is indispensable. In particular, practical application of AI technology is strongly required in "genomic medicine" and "genomic drug discovery" that conduct medical practice and novel drug development based on individual genomic information. In our laboratory, we have been developing a database to integrate genome data and clinical information obtained by clinical genome analysis and a computational support system for clinical interpretation of variants using AI. In addition, with the aim of creating new therapeutic targets in genomic drug discovery, we have been also working on the development of a binding affinity prediction system for mutated proteins and drugs by molecular dynamics simulation using supercomputer "Kei". We also have tackled for problems in a drug virtual screening. Our developed AI technology has successfully generated virtual compound library, and deep learning method has enabled us to predict interaction between compound and target protein.

  5. Assessing computational genomics skills: Our experience in the H3ABioNet African bioinformatics network.

    Science.gov (United States)

    Jongeneel, C Victor; Achinike-Oduaran, Ovokeraye; Adebiyi, Ezekiel; Adebiyi, Marion; Adeyemi, Seun; Akanle, Bola; Aron, Shaun; Ashano, Efejiro; Bendou, Hocine; Botha, Gerrit; Chimusa, Emile; Choudhury, Ananyo; Donthu, Ravikiran; Drnevich, Jenny; Falola, Oluwadamila; Fields, Christopher J; Hazelhurst, Scott; Hendry, Liesl; Isewon, Itunuoluwa; Khetani, Radhika S; Kumuthini, Judit; Kimuda, Magambo Phillip; Magosi, Lerato; Mainzer, Liudmila Sergeevna; Maslamoney, Suresh; Mbiyavanga, Mamana; Meintjes, Ayton; Mugutso, Danny; Mpangase, Phelelani; Munthali, Richard; Nembaware, Victoria; Ndhlovu, Andrew; Odia, Trust; Okafor, Adaobi; Oladipo, Olaleye; Panji, Sumir; Pillay, Venesa; Rendon, Gloria; Sengupta, Dhriti; Mulder, Nicola

    2017-06-01

    The H3ABioNet pan-African bioinformatics network, which is funded to support the Human Heredity and Health in Africa (H3Africa) program, has developed node-assessment exercises to gauge the ability of its participating research and service groups to analyze typical genome-wide datasets being generated by H3Africa research groups. We describe a framework for the assessment of computational genomics analysis skills, which includes standard operating procedures, training and test datasets, and a process for administering the exercise. We present the experiences of 3 research groups that have taken the exercise and the impact on their ability to manage complex projects. Finally, we discuss the reasons why many H3ABioNet nodes have declined so far to participate and potential strategies to encourage them to do so.

  6. Specification and Validation of an Edge Router Discovery Protocol for Mobile Ad Hoc Networks

    DEFF Research Database (Denmark)

    Kristensen, Lars Michael; Jensen, Kurt

    2004-01-01

    We present an industrial project at Ericsson Telebit A/S where Coloured Petri Nets (CP-nets or CPNs) have been used for the design and specification of an edge router discovery protocol for mobile ad-hoc networks. The Edge Router Discovery Protocol (ERDP) supports an edge router in a stationary...

  7. Robust Bioinformatics Recognition with VLSI Biochip Microsystem

    Science.gov (United States)

    Lue, Jaw-Chyng L.; Fang, Wai-Chi

    2006-01-01

    A microsystem architecture for real-time, on-site, robust bioinformatic patterns recognition and analysis has been proposed. This system is compatible with on-chip DNA analysis means such as polymerase chain reaction (PCR)amplification. A corresponding novel artificial neural network (ANN) learning algorithm using new sigmoid-logarithmic transfer function based on error backpropagation (EBP) algorithm is invented. Our results show the trained new ANN can recognize low fluorescence patterns better than the conventional sigmoidal ANN does. A differential logarithmic imaging chip is designed for calculating logarithm of relative intensities of fluorescence signals. The single-rail logarithmic circuit and a prototype ANN chip are designed, fabricated and characterized.

  8. The University of New Mexico Center for Molecular Discovery

    Science.gov (United States)

    Edwards, Bruce S.; Gouveia, Kristine; Oprea, Tudor I.; Sklar, Larry A.

    2015-01-01

    The University of New Mexico Center for Molecular Discovery (UNMCMD) is an academic research center that specializes in discovery using high throughput flow cytometry (HTFC) integrated with virtual screening, as well as knowledge mining and drug informatics. With a primary focus on identifying small molecules that can be used as chemical probes and as leads for drug discovery, it is a central core resource for research and translational activities at UNM that supports implementation and management of funded screening projects as well as “up-front” services such as consulting for project design and implementation, assistance in assay development and generation of preliminary data for pilot projects in support of competitive grant applications. The HTFC platform in current use represents advanced, proprietary technology developed at UNM that is now routinely capable of processing bioassays arrayed in 96-, 384- and 1536-well formats at throughputs of 60,000 or more wells per day. Key programs at UNMCMD include screening of research targets submitted by the international community through NIH’s Molecular Libraries Program; a multi-year effort involving translational partnerships at UNM directed towards drug repurposing - identifying new uses for clinically approved drugs; and a recently established personalized medicine initiative for advancing cancer therapy by the application of “smart” oncology drugs in selected patients based on response patterns of their cancer cells in vitro. UNMCMD discoveries, innovation, and translation have contributed to a wealth of inventions, patents, licenses and publications, as well as startup companies, clinical trials and a multiplicity of domestic and international collaborative partnerships to further the research enterprise. PMID:24409953

  9. Microbial bioinformatics 2020.

    Science.gov (United States)

    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! © 2016 The Author. Microbial Biotechnology published by John Wiley & Sons Ltd and Society for Applied Microbiology.

  10. Tissue damage in organic rainbow trout muscle investigated by proteomics and bioinformatics

    DEFF Research Database (Denmark)

    Wulff, Tune; Silva, T.; Nielsen, Michael Engelbrecht

    2013-01-01

    and magnitude of the cellular response, in the context of a regenerative process. Using a bioinformatics approach, the main biological function of these proteins were assigned, showing the regulation of proteins involved in processes like apoptosis, iron homeostasis and regulation of muscular structure...

  11. User Driven Development of Software Tools for Open Data Discovery and Exploration

    Science.gov (United States)

    Schlobinski, Sascha; Keppel, Frank; Dihe, Pascal; Boot, Gerben; Falkenroth, Esa

    2016-04-01

    The use of open data in research faces challenges not restricted to inherent properties such as data quality, resolution of open data sets. Often Open data is catalogued insufficiently or fragmented. Software tools that support the effective discovery including the assessment of the data's appropriateness for research have shortcomings such as the lack of essential functionalities like support for data provenance. We believe that one of the reasons is the neglect of real end users requirements in the development process of aforementioned software tools. In the context of the FP7 Switch-On project we have pro-actively engaged the relevant user user community to collaboratively develop a means to publish, find and bind open data relevant for hydrologic research. Implementing key concepts of data discovery and exploration we have used state of the art web technologies to provide an interactive software tool that is easy to use yet powerful enough to satisfy the data discovery and access requirements of the hydrological research community.

  12. Beyond Discovery

    DEFF Research Database (Denmark)

    Korsgaard, Steffen; Sassmannshausen, Sean Patrick

    2017-01-01

    In this chapter we explore four alternatives to the dominant discovery view of entrepreneurship; the development view, the construction view, the evolutionary view, and the Neo-Austrian view. We outline the main critique points of the discovery presented in these four alternatives, as well...

  13. Why Choose This One? Factors in Scientists' Selection of Bioinformatics Tools

    Science.gov (United States)

    Bartlett, Joan C.; Ishimura, Yusuke; Kloda, Lorie A.

    2011-01-01

    Purpose: The objective was to identify and understand the factors involved in scientists' selection of preferred bioinformatics tools, such as databases of gene or protein sequence information (e.g., GenBank) or programs that manipulate and analyse biological data (e.g., BLAST). Methods: Eight scientists maintained research diaries for a two-week…

  14. Adding biological meaning to human protein-protein interactions identified by yeast two-hybrid screenings: A guide through bioinformatics tools.

    Science.gov (United States)

    Felgueiras, Juliana; Silva, Joana Vieira; Fardilha, Margarida

    2018-01-16

    "A man is known by the company he keeps" is a popular expression that perfectly fits proteins. A common approach to characterize the function of a target protein is to identify its interacting partners and thus infer its roles based on the known functions of the interactors. Protein-protein interaction networks (PPINs) have been created for several organisms, including humans, primarily as results of high-throughput screenings, such as yeast two-hybrid (Y2H). Their unequivocal use to understand events underlying human pathophysiology is promising in identifying genes and proteins associated with diseases. Therefore, numerous opportunities have emerged for PPINs as tools for clinical management of diseases: network-based disease classification systems, discovery of biomarkers and identification of therapeutic targets. Despite the great advantages of PPINs, their use is still unrecognised by several researchers who generate high-throughput data to generally characterize interactions in a certain model or to select an interaction to study in detail. We strongly believe that both approaches are not exclusive and that we can use PPINs as a complementary methodology and rich-source of information to the initial study proposal. Here, we suggest a pipeline to deal with Y2H results using bioinformatics tools freely available for academics. Yeast two-hybrid is widely-used to identify protein-protein interactions. Conventionally, the positive clones that result from a yeast two-hybrid screening are sequenced to identify the interactors of the protein of interest (also known as bait protein), and few interactions, thought as potentially relevant for the model in study, are selected for further validation using biochemical methods (e.g. co-immunoprecipitation and co-localization). The huge amount of data that is potentially lost during this conservative approach motivated us to write this tutorial-like review, so that researchers feel encouraged to take advantage of

  15. "Eureka, Eureka!" Discoveries in Science

    Science.gov (United States)

    Agarwal, Pankaj

    2011-01-01

    Accidental discoveries have been of significant value in the progress of science. Although accidental discoveries are more common in pharmacology and chemistry, other branches of science have also benefited from such discoveries. While most discoveries are the result of persistent research, famous accidental discoveries provide a fascinating…

  16. 30 CFR 44.24 - Discovery.

    Science.gov (United States)

    2010-07-01

    ... 30 Mineral Resources 1 2010-07-01 2010-07-01 false Discovery. 44.24 Section 44.24 Mineral... Discovery. Parties shall be governed in their conduct of discovery by appropriate provisions of the Federal... discovery. Alternative periods of time for discovery may be prescribed by the presiding administrative law...

  17. 19 CFR 356.20 - Discovery.

    Science.gov (United States)

    2010-04-01

    ... 19 Customs Duties 3 2010-04-01 2010-04-01 false Discovery. 356.20 Section 356.20 Customs Duties... § 356.20 Discovery. (a) Voluntary discovery. All parties are encouraged to engage in voluntary discovery... sanctions proceeding. (b) Limitations on discovery. The administrative law judge shall place such limits...

  18. Chemical Discovery

    Science.gov (United States)

    Brown, Herbert C.

    1974-01-01

    The role of discovery in the advance of the science of chemistry and the factors that are currently operating to handicap that function are considered. Examples are drawn from the author's work with boranes. The thesis that exploratory research and discovery should be encouraged is stressed. (DT)

  19. Enhancing knowledge discovery from cancer genomics data with Galaxy.

    Science.gov (United States)

    Albuquerque, Marco A; Grande, Bruno M; Ritch, Elie J; Pararajalingam, Prasath; Jessa, Selin; Krzywinski, Martin; Grewal, Jasleen K; Shah, Sohrab P; Boutros, Paul C; Morin, Ryan D

    2017-05-01

    The field of cancer genomics has demonstrated the power of massively parallel sequencing techniques to inform on the genes and specific alterations that drive tumor onset and progression. Although large comprehensive sequence data sets continue to be made increasingly available, data analysis remains an ongoing challenge, particularly for laboratories lacking dedicated resources and bioinformatics expertise. To address this, we have produced a collection of Galaxy tools that represent many popular algorithms for detecting somatic genetic alterations from cancer genome and exome data. We developed new methods for parallelization of these tools within Galaxy to accelerate runtime and have demonstrated their usability and summarized their runtimes on multiple cloud service providers. Some tools represent extensions or refinement of existing toolkits to yield visualizations suited to cohort-wide cancer genomic analysis. For example, we present Oncocircos and Oncoprintplus, which generate data-rich summaries of exome-derived somatic mutation. Workflows that integrate these to achieve data integration and visualizations are demonstrated on a cohort of 96 diffuse large B-cell lymphomas and enabled the discovery of multiple candidate lymphoma-related genes. Our toolkit is available from our GitHub repository as Galaxy tool and dependency definitions and has been deployed using virtualization on multiple platforms including Docker. © The Author 2017. Published by Oxford University Press.

  20. Bioinformatic analysis of functional differences between the immunoproteasome and the constitutive proteasome

    DEFF Research Database (Denmark)

    Kesmir, Can; van Noort, V.; de Boer, R.J.

    2003-01-01

    not yet been quantified how different the specificity of two forms of the proteasome are. The main question, which still lacks direct evidence, is whether the immunoproteasome generates more MHC ligands. Here we use bioinformatics tools to quantify these differences and show that the immunoproteasome...

  1. In-depth analysis of the adipocyte proteome by mass spectrometry and bioinformatics

    DEFF Research Database (Denmark)

    Adachi, Jun; Kumar, Chanchal; Zhang, Yanling

    2007-01-01

    , mitochondria, membrane, and cytosol of 3T3-L1 adipocytes. We identified 3,287 proteins while essentially eliminating false positives, making this one of the largest high confidence proteomes reported to date. Comprehensive bioinformatics analysis revealed that the adipocyte proteome, despite its specialized...

  2. Bioinformatics analysis of Brucella vaccines and vaccine targets using VIOLIN.

    Science.gov (United States)

    He, Yongqun; Xiang, Zuoshuang

    2010-09-27

    Brucella spp. are Gram-negative, facultative intracellular bacteria that cause brucellosis, one of the commonest zoonotic diseases found worldwide in humans and a variety of animal species. While several animal vaccines are available, there is no effective and safe vaccine for prevention of brucellosis in humans. VIOLIN (http://www.violinet.org) is a web-based vaccine database and analysis system that curates, stores, and analyzes published data of commercialized vaccines, and vaccines in clinical trials or in research. VIOLIN contains information for 454 vaccines or vaccine candidates for 73 pathogens. VIOLIN also contains many bioinformatics tools for vaccine data analysis, data integration, and vaccine target prediction. To demonstrate the applicability of VIOLIN for vaccine research, VIOLIN was used for bioinformatics analysis of existing Brucella vaccines and prediction of new Brucella vaccine targets. VIOLIN contains many literature mining programs (e.g., Vaxmesh) that provide in-depth analysis of Brucella vaccine literature. As a result of manual literature curation, VIOLIN contains information for 38 Brucella vaccines or vaccine candidates, 14 protective Brucella antigens, and 68 host response studies to Brucella vaccines from 97 peer-reviewed articles. These Brucella vaccines are classified in the Vaccine Ontology (VO) system and used for different ontological applications. The web-based VIOLIN vaccine target prediction program Vaxign was used to predict new Brucella vaccine targets. Vaxign identified 14 outer membrane proteins that are conserved in six virulent strains from B. abortus, B. melitensis, and B. suis that are pathogenic in humans. Of the 14 membrane proteins, two proteins (Omp2b and Omp31-1) are not present in B. ovis, a Brucella species that is not pathogenic in humans. Brucella vaccine data stored in VIOLIN were compared and analyzed using the VIOLIN query system. Bioinformatics curation and ontological representation of Brucella vaccines

  3. 24 CFR 180.500 - Discovery.

    Science.gov (United States)

    2010-04-01

    ... 24 Housing and Urban Development 1 2010-04-01 2010-04-01 false Discovery. 180.500 Section 180.500... OPPORTUNITY CONSOLIDATED HUD HEARING PROCEDURES FOR CIVIL RIGHTS MATTERS Discovery § 180.500 Discovery. (a) In general. This subpart governs discovery in aid of administrative proceedings under this part. Discovery in...

  4. 22 CFR 224.21 - Discovery.

    Science.gov (United States)

    2010-04-01

    ... 22 Foreign Relations 1 2010-04-01 2010-04-01 false Discovery. 224.21 Section 224.21 Foreign....21 Discovery. (a) The following types of discovery are authorized: (1) Requests for production of... parties, discovery is available only as ordered by the ALJ. The ALJ shall regulate the timing of discovery...

  5. Bioinformatics: Cheap and robust method to explore biomaterial from Indonesia biodiversity

    Science.gov (United States)

    Widodo

    2015-02-01

    Indonesia has a huge amount of biodiversity, which may contain many biomaterials for pharmaceutical application. These resources potency should be explored to discover new drugs for human wealth. However, the bioactive screening using conventional methods is very expensive and time-consuming. Therefore, we developed a methodology for screening the potential of natural resources based on bioinformatics. The method is developed based on the fact that organisms in the same taxon will have similar genes, metabolism and secondary metabolites product. Then we employ bioinformatics to explore the potency of biomaterial from Indonesia biodiversity by comparing species with the well-known taxon containing the active compound through published paper or chemical database. Then we analyze drug-likeness, bioactivity and the target proteins of the active compound based on their molecular structure. The target protein was examined their interaction with other proteins in the cell to determine action mechanism of the active compounds in the cellular level, as well as to predict its side effects and toxicity. By using this method, we succeeded to screen anti-cancer, immunomodulators and anti-inflammation from Indonesia biodiversity. For example, we found anticancer from marine invertebrate by employing the method. The anti-cancer was explore based on the isolated compounds of marine invertebrate from published article and database, and then identified the protein target, followed by molecular pathway analysis. The data suggested that the active compound of the invertebrate able to kill cancer cell. Further, we collect and extract the active compound from the invertebrate, and then examined the activity on cancer cell (MCF7). The MTT result showed that the methanol extract of marine invertebrate was highly potent in killing MCF7 cells. Therefore, we concluded that bioinformatics is cheap and robust way to explore bioactive from Indonesia biodiversity for source of drug and another

  6. 19 CFR 207.109 - Discovery.

    Science.gov (United States)

    2010-04-01

    ... 19 Customs Duties 3 2010-04-01 2010-04-01 false Discovery. 207.109 Section 207.109 Customs Duties... and Committee Proceedings § 207.109 Discovery. (a) Discovery methods. All parties may obtain discovery under such terms and limitations as the administrative law judge may order. Discovery may be by one or...

  7. 15 CFR 25.21 - Discovery.

    Science.gov (United States)

    2010-01-01

    ... 15 Commerce and Foreign Trade 1 2010-01-01 2010-01-01 false Discovery. 25.21 Section 25.21... Discovery. (a) The following types of discovery are authorized: (1) Requests for production of documents for..., discovery is available only as ordered by the ALJ. The ALJ shall regulate the timing of discovery. (d...

  8. Drug discovery in an academic setting: playing to the strengths.

    Science.gov (United States)

    Huryn, Donna M

    2013-03-14

    Drug discovery and medicinal chemistry initiatives in academia provide an opportunity to create a unique environment that is distinct from the traditional industrial model. Two characteristics of a university setting that are not usually associated with pharma are the ability to pursue high-risk projects and a depth of expertise, infrastructure, and capabilities in focused areas. Encouraging, supporting, and fostering drug discovery efforts that take advantage of these and other distinguishing characteristics of an academic setting can lead to novel and innovative therapies that might not be discovered otherwise.

  9. OralCard: a bioinformatic tool for the study of oral proteome.

    Science.gov (United States)

    Arrais, Joel P; Rosa, Nuno; Melo, José; Coelho, Edgar D; Amaral, Diana; Correia, Maria José; Barros, Marlene; Oliveira, José Luís

    2013-07-01

    The molecular complexity of the human oral cavity can only be clarified through identification of components that participate within it. However current proteomic techniques produce high volumes of information that are dispersed over several online databases. Collecting all of this data and using an integrative approach capable of identifying unknown associations is still an unsolved problem. This is the main motivation for this work. We present the online bioinformatic tool OralCard, which comprises results from 55 manually curated articles reflecting the oral molecular ecosystem (OralPhysiOme). It comprises experimental information available from the oral proteome both of human (OralOme) and microbial origin (MicroOralOme) structured in protein, disease and organism. This tool is a key resource for researchers to understand the molecular foundations implicated in biology and disease mechanisms of the oral cavity. The usefulness of this tool is illustrated with the analysis of the oral proteome associated with diabetes melitus type 2. OralCard is available at http://bioinformatics.ua.pt/oralcard. Copyright © 2013 Elsevier Ltd. All rights reserved.

  10. Efficient Feature Selection and Classification of Protein Sequence Data in Bioinformatics

    Science.gov (United States)

    Faye, Ibrahima; Samir, Brahim Belhaouari; Md Said, Abas

    2014-01-01

    Bioinformatics has been an emerging area of research for the last three decades. The ultimate aims of bioinformatics were to store and manage the biological data, and develop and analyze computational tools to enhance their understanding. The size of data accumulated under various sequencing projects is increasing exponentially, which presents difficulties for the experimental methods. To reduce the gap between newly sequenced protein and proteins with known functions, many computational techniques involving classification and clustering algorithms were proposed in the past. The classification of protein sequences into existing superfamilies is helpful in predicting the structure and function of large amount of newly discovered proteins. The existing classification results are unsatisfactory due to a huge size of features obtained through various feature encoding methods. In this work, a statistical metric-based feature selection technique has been proposed in order to reduce the size of the extracted feature vector. The proposed method of protein classification shows significant improvement in terms of performance measure metrics: accuracy, sensitivity, specificity, recall, F-measure, and so forth. PMID:25045727

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

    Directory of Open Access Journals (Sweden)

    Thomas K. Karikari

    2015-06-01

    Full Text Available 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.

  12. 39 CFR 963.14 - Discovery.

    Science.gov (United States)

    2010-07-01

    ... 39 Postal Service 1 2010-07-01 2010-07-01 false Discovery. 963.14 Section 963.14 Postal Service... PANDERING ADVERTISEMENTS STATUTE, 39 U.S.C. 3008 § 963.14 Discovery. Discovery is to be conducted on a... such discovery as he or she deems reasonable and necessary. Discovery may include one or more of the...

  13. Single-Cell Transcriptomics Bioinformatics and Computational Challenges

    Directory of Open Access Journals (Sweden)

    Lana Garmire

    2016-09-01

    Full Text Available The emerging single-cell RNA-Seq (scRNA-Seq technology holds the promise to revolutionize our understanding of diseases and associated biological processes at an unprecedented resolution. It opens the door to reveal the intercellular heterogeneity and has been employed to a variety of applications, ranging from characterizing cancer cells subpopulations to elucidating tumor resistance mechanisms. Parallel to improving experimental protocols to deal with technological issues, deriving new analytical methods to reveal the complexity in scRNA-Seq data is just as challenging. Here we review the current state-of-the-art bioinformatics tools and methods for scRNA-Seq analysis, as well as addressing some critical analytical challenges that the field faces.

  14. Schizophrenia genomics and proteomics: are we any closer to biomarker discovery?

    Directory of Open Access Journals (Sweden)

    Kramer Alon

    2009-01-01

    Full Text Available Abstract The field of proteomics has made leaps and bounds in the last 10 years particularly in the fields of oncology and cardiovascular medicine. In comparison, neuroproteomics is still playing catch up mainly due to the relative complexity of neurological disorders. Schizophrenia is one such disorder, believed to be the results of multiple factors both genetic and environmental. Affecting over 2 million people in the US alone, it has become a major clinical and public health concern worldwide. This paper gives an update of schizophrenia biomarker research as reviewed by Lakhan in 2006 and gives us a rundown of the progress made during the last two years. Several studies demonstrate the potential of cerebrospinal fluid as a source of neuro-specific biomarkers. Genetic association studies are making headway in identifying candidate genes for schizophrenia. In addition, metabonomics, bioinformatics, and neuroimaging techniques are aiming to complete the picture by filling in knowledge gaps. International cooperation in the form of genomics and protein databases and brain banks is facilitating research efforts. While none of the recent developments described here in qualifies as biomarker discovery, many are likely to be stepping stones towards that goal.

  15. Assessing computational genomics skills: Our experience in the H3ABioNet African bioinformatics network.

    Directory of Open Access Journals (Sweden)

    C Victor Jongeneel

    2017-06-01

    Full Text Available The H3ABioNet pan-African bioinformatics network, which is funded to support the Human Heredity and Health in Africa (H3Africa program, has developed node-assessment exercises to gauge the ability of its participating research and service groups to analyze typical genome-wide datasets being generated by H3Africa research groups. We describe a framework for the assessment of computational genomics analysis skills, which includes standard operating procedures, training and test datasets, and a process for administering the exercise. We present the experiences of 3 research groups that have taken the exercise and the impact on their ability to manage complex projects. Finally, we discuss the reasons why many H3ABioNet nodes have declined so far to participate and potential strategies to encourage them to do so.

  16. Synergy between Medical Informatics and Bioinformatics: Facilitating Genomic Medicine for Future Health Care

    Czech Academy of Sciences Publication Activity Database

    Martin-Sanchez, F.; Iakovidis, I.; Norager, S.; Maojo, V.; de Groen, P.; Van der Lei, J.; Jones, T.; Abraham-Fuchs, K.; Apweiler, R.; Babic, A.; Baud, R.; Breton, V.; Cinquin, P.; Doupi, P.; Dugas, M.; Eils, R.; Engelbrecht, R.; Ghazal, P.; Jehenson, P.; Kulikowski, C.; Lampe, K.; De Moor, G.; Orphanoudakis, S.; Rossing, N.; Sarachan, B.; Sousa, A.; Spekowius, G.; Thireos, G.; Zahlmann, G.; Zvárová, Jana; Hermosilla, I.; Vicente, F. J.

    2004-01-01

    Roč. 37, - (2004), s. 30-42 ISSN 1532-0464 Institutional research plan: CEZ:AV0Z1030915 Keywords : bioinformatics * medical informatics * genomics * genomic medicine * biomedical informatics Subject RIV: BD - Theory of Information Impact factor: 1.013, year: 2004

  17. Molecular bioinformatics: algorithms and applications

    National Research Council Canada - National Science Library

    Schulze-Kremer, S

    1996-01-01

    ... on molecular biology, especially D N A sequence analysis and protein structure prediction. These two issues are also central to this book. Other application areas covered here are: interpretation of spectroscopic data and discovery of structure-function relationships in D N A and proteins. Figure 1 depicts the interdependence of computer science,...

  18. Bioinformatics analysis identifies several intrinsically disordered human E3 ubiquitin-protein ligases

    DEFF Research Database (Denmark)

    Boomsma, Wouter Krogh; Nielsen, Sofie Vincents; Lindorff-Larsen, Kresten

    2016-01-01

    conduct a bioinformatics analysis to examine >600 human and S. cerevisiae E3 ligases to identify enzymes that are similar to San1 in terms of function and/or mechanism of substrate recognition. An initial sequence-based database search was found to detect candidates primarily based on the homology...

  19. Strategies for Using Peer-Assisted Learning Effectively in an Undergraduate Bioinformatics Course

    Science.gov (United States)

    Shapiro, Casey; Ayon, Carlos; Moberg-Parker, Jordan; Levis-Fitzgerald, Marc; Sanders, Erin R.

    2013-01-01

    This study used a mixed methods approach to evaluate hybrid peer-assisted learning approaches incorporated into a bioinformatics tutorial for a genome annotation research project. Quantitative and qualitative data were collected from undergraduates who enrolled in a research-based laboratory course during two different academic terms at UCLA.…

  20. Bioinformatics Mining and Modeling Methods for the Identification of Disease Mechanisms in Neurodegenerative Disorders

    Directory of Open Access Journals (Sweden)

    Martin Hofmann-Apitius

    2015-12-01

    Full Text Available Since the decoding of the Human Genome, techniques from bioinformatics, statistics, and machine learning have been instrumental in uncovering patterns in increasing amounts and types of different data produced by technical profiling technologies applied to clinical samples, animal models, and cellular systems. Yet, progress on unravelling biological mechanisms, causally driving diseases, has been limited, in part due to the inherent complexity of biological systems. Whereas we have witnessed progress in the areas of cancer, cardiovascular and metabolic diseases, the area of neurodegenerative diseases has proved to be very challenging. This is in part because the aetiology of neurodegenerative diseases such as Alzheimer´s disease or Parkinson´s disease is unknown, rendering it very difficult to discern early causal events. Here we describe a panel of bioinformatics and modeling approaches that have recently been developed to identify candidate mechanisms of neurodegenerative diseases based on publicly available data and knowledge. We identify two complementary strategies—data mining techniques using genetic data as a starting point to be further enriched using other data-types, or alternatively to encode prior knowledge about disease mechanisms in a model based framework supporting reasoning and enrichment analysis. Our review illustrates the challenges entailed in integrating heterogeneous, multiscale and multimodal information in the area of neurology in general and neurodegeneration in particular. We conclude, that progress would be accelerated by increasing efforts on performing systematic collection of multiple data-types over time from each individual suffering from neurodegenerative disease. The work presented here has been driven by project AETIONOMY; a project funded in the course of the Innovative Medicines Initiative (IMI; which is a public-private partnership of the European Federation of Pharmaceutical Industry Associations

  1. GENEASE: Real time bioinformatics tool for multi-omics and disease ontology exploration, analysis and visualization.

    Science.gov (United States)

    Ghandikota, Sudhir; Hershey, Gurjit K Khurana; Mersha, Tesfaye B

    2018-03-24

    Advances in high-throughput sequencing technologies have made it possible to generate multiple omics data at an unprecedented rate and scale. The accumulation of these omics data far outpaces the rate at which biologists can mine and generate new hypothesis to test experimentally. There is an urgent need to develop a myriad of powerful tools to efficiently and effectively search and filter these resources to address specific post-GWAS functional genomics questions. However, to date, these resources are scattered across several databases and often lack a unified portal for data annotation and analytics. In addition, existing tools to analyze and visualize these databases are highly fragmented, resulting researchers to access multiple applications and manual interventions for each gene or variant in an ad hoc fashion until all the questions are answered. In this study, we present GENEASE, a web-based one-stop bioinformatics tool designed to not only query and explore multi-omics and phenotype databases (e.g., GTEx, ClinVar, dbGaP, GWAS Catalog, ENCODE, Roadmap Epigenomics, KEGG, Reactome, Gene and Phenotype Ontology) in a single web interface but also to perform seamless post genome-wide association downstream functional and overlap analysis for non-coding regulatory variants. GENEASE accesses over 50 different databases in public domain including model organism-specific databases to facilitate gene/variant and disease exploration, enrichment and overlap analysis in real time. It is a user-friendly tool with point-and-click interface containing links for support information including user manual and examples. GENEASE can be accessed freely at http://research.cchmc.org/mershalab/genease_new/login.html. Tesfaye.Mersha@cchmc.org, Sudhir.Ghandikota@cchmc.org. Supplementary data are available at Bioinformatics online.

  2. Usability of Discovery Portals

    OpenAIRE

    Bulens, J.D.; Vullings, L.A.E.; Houtkamp, J.M.; Vanmeulebrouk, B.

    2013-01-01

    As INSPIRE progresses to be implemented in the EU, many new discovery portals are built to facilitate finding spatial data. Currently the structure of the discovery portals is determined by the way spatial data experts like to work. However, we argue that the main target group for discovery portals are not spatial data experts but professionals with limited spatial knowledge, and a focus outside the spatial domain. An exploratory usability experiment was carried out in which three discovery p...

  3. Sea Level Rise Data Discovery

    Science.gov (United States)

    Quach, N.; Huang, T.; Boening, C.; Gill, K. M.

    2016-12-01

    Research related to sea level rise crosses multiple disciplines from sea ice to land hydrology. The NASA Sea Level Change Portal (SLCP) is a one-stop source for current sea level change information and data, including interactive tools for accessing and viewing regional data, a virtual dashboard of sea level indicators, and ongoing updates through a suite of editorial products that include content articles, graphics, videos, and animations. The architecture behind the SLCP makes it possible to integrate web content and data relevant to sea level change that are archived across various data centers as well as new data generated by sea level change principal investigators. The Extensible Data Gateway Environment (EDGE) is incorporated into the SLCP architecture to provide a unified platform for web content and science data discovery. EDGE is a data integration platform designed to facilitate high-performance geospatial data discovery and access with the ability to support multi-metadata standard specifications. EDGE has the capability to retrieve data from one or more sources and package the resulting sets into a single response to the requestor. With this unified endpoint, the Data Analysis Tool that is available on the SLCP can retrieve dataset and granule level metadata as well as perform geospatial search on the data. This talk focuses on the architecture that makes it possible to seamlessly integrate and enable discovery of disparate data relevant to sea level rise.

  4. Computational Discovery of Materials Using the Firefly Algorithm

    Science.gov (United States)

    Avendaño-Franco, Guillermo; Romero, Aldo

    Our current ability to model physical phenomena accurately, the increase computational power and better algorithms are the driving forces behind the computational discovery and design of novel materials, allowing for virtual characterization before their realization in the laboratory. We present the implementation of a novel firefly algorithm, a population-based algorithm for global optimization for searching the structure/composition space. This novel computation-intensive approach naturally take advantage of concurrency, targeted exploration and still keeping enough diversity. We apply the new method in both periodic and non-periodic structures and we present the implementation challenges and solutions to improve efficiency. The implementation makes use of computational materials databases and network analysis to optimize the search and get insights about the geometric structure of local minima on the energy landscape. The method has been implemented in our software PyChemia, an open-source package for materials discovery. We acknowledge the support of DMREF-NSF 1434897 and the Donors of the American Chemical Society Petroleum Research Fund for partial support of this research under Contract 54075-ND10.

  5. Combining multiple decisions: applications to bioinformatics

    International Nuclear Information System (INIS)

    Yukinawa, N; Ishii, S; Takenouchi, T; Oba, S

    2008-01-01

    Multi-class classification is one of the fundamental tasks in bioinformatics and typically arises in cancer diagnosis studies by gene expression profiling. This article reviews two recent approaches to multi-class classification by combining multiple binary classifiers, which are formulated based on a unified framework of error-correcting output coding (ECOC). The first approach is to construct a multi-class classifier in which each binary classifier to be aggregated has a weight value to be optimally tuned based on the observed data. In the second approach, misclassification of each binary classifier is formulated as a bit inversion error with a probabilistic model by making an analogy to the context of information transmission theory. Experimental studies using various real-world datasets including cancer classification problems reveal that both of the new methods are superior or comparable to other multi-class classification methods

  6. Bioinformatics Analysis Reveals Genes Involved in the Pathogenesis of Ameloblastoma and Keratocystic Odontogenic Tumor.

    Science.gov (United States)

    Santos, Eliane Macedo Sobrinho; Santos, Hércules Otacílio; Dos Santos Dias, Ivoneth; Santos, Sérgio Henrique; Batista de Paula, Alfredo Maurício; Feltenberger, John David; Sena Guimarães, André Luiz; Farias, Lucyana Conceição

    2016-01-01

    Pathogenesis of odontogenic tumors is not well known. It is important to identify genetic deregulations and molecular alterations. This study aimed to investigate, through bioinformatic analysis, the possible genes involved in the pathogenesis of ameloblastoma (AM) and keratocystic odontogenic tumor (KCOT). Genes involved in the pathogenesis of AM and KCOT were identified in GeneCards. Gene list was expanded, and the gene interactions network was mapped using the STRING software. "Weighted number of links" (WNL) was calculated to identify "leader genes" (highest WNL). Genes were ranked by K-means method and Kruskal-Wallis test was used (Preview data was used to corroborate the bioinformatics data. CDK1 was identified as leader gene for AM. In KCOT group, results show PCNA and TP53 . Both tumors exhibit a power law behavior. Our topological analysis suggested leader genes possibly important in the pathogenesis of AM and KCOT, by clustering coefficient calculated for both odontogenic tumors (0.028 for AM, zero for KCOT). The results obtained in the scatter diagram suggest an important relationship of these genes with the molecular processes involved in AM and KCOT. Ontological analysis for both AM and KCOT demonstrated different mechanisms. Bioinformatics analyzes were confirmed through literature review. These results may suggest the involvement of promising genes for a better understanding of the pathogenesis of AM and KCOT.

  7. Secretome Analysis of Lipid-Induced Insulin Resistance in Skeletal Muscle Cells by a Combined Experimental and Bioinformatics Workflow

    DEFF Research Database (Denmark)

    Deshmukh, Atul S; Cox, Juergen; Jensen, Lars Juhl

    2015-01-01

    , in principle, allows an unbiased and comprehensive analysis of cellular secretomes; however, the distinction of bona fide secreted proteins from proteins released upon lysis of a small fraction of dying cells remains challenging. Here we applied highly sensitive MS and streamlined bioinformatics to analyze......-resistant conditions. Our study demonstrates an efficient combined experimental and bioinformatics workflow to identify putative secreted proteins from insulin-resistant skeletal muscle cells, which could easily be adapted to other cellular models....

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

    Science.gov (United States)

    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…

  9. Creating a specialist protein resource network: a meeting report for the protein bioinformatics and community resources retreat

    DEFF Research Database (Denmark)

    Babbitt, Patricia C.; Bagos, Pantelis G.; Bairoch, Amos

    2015-01-01

    During 11–12 August 2014, a Protein Bioinformatics and Community Resources Retreat was held at the Wellcome Trust Genome Campus in Hinxton, UK. This meeting brought together the principal investigators of several specialized protein resources (such as CAZy, TCDB and MEROPS) as well as those from...... protein databases from the large Bioinformatics centres (including UniProt and RefSeq). The retreat was divided into five sessions: (1) key challenges, (2) the databases represented, (3) best practices for maintenance and curation, (4) information flow to and from large data centers and (5) communication...

  10. 19 CFR 354.10 - Discovery.

    Science.gov (United States)

    2010-04-01

    ... 19 Customs Duties 3 2010-04-01 2010-04-01 false Discovery. 354.10 Section 354.10 Customs Duties... ANTIDUMPING OR COUNTERVAILING DUTY ADMINISTRATIVE PROTECTIVE ORDER § 354.10 Discovery. (a) Voluntary discovery. All parties are encouraged to engage in voluntary discovery procedures regarding any matter, not...

  11. 36 CFR 1150.63 - Discovery.

    Science.gov (United States)

    2010-07-01

    ... 36 Parks, Forests, and Public Property 3 2010-07-01 2010-07-01 false Discovery. 1150.63 Section... PRACTICE AND PROCEDURES FOR COMPLIANCE HEARINGS Prehearing Conferences and Discovery § 1150.63 Discovery. (a) Parties are encouraged to engage in voluntary discovery procedures. For good cause shown under...

  12. 37 CFR 11.52 - Discovery.

    Science.gov (United States)

    2010-07-01

    ... 37 Patents, Trademarks, and Copyrights 1 2010-07-01 2010-07-01 false Discovery. 11.52 Section 11... Disciplinary Proceedings; Jurisdiction, Sanctions, Investigations, and Proceedings § 11.52 Discovery. Discovery... establishes that discovery is reasonable and relevant, the hearing officer, under such conditions as he or she...

  13. Discovery of rare, diagnostic AluYb8/9 elements in diverse human populations.

    Science.gov (United States)

    Feusier, Julie; Witherspoon, David J; Scott Watkins, W; Goubert, Clément; Sasani, Thomas A; Jorde, Lynn B

    2017-01-01

    Polymorphic human Alu elements are excellent tools for assessing population structure, and new retrotransposition events can contribute to disease. Next-generation sequencing has greatly increased the potential to discover Alu elements in human populations, and various sequencing and bioinformatics methods have been designed to tackle the problem of detecting these highly repetitive elements. However, current techniques for Alu discovery may miss rare, polymorphic Alu elements. Combining multiple discovery approaches may provide a better profile of the polymorphic Alu mobilome. Alu Yb8/9 elements have been a focus of our recent studies as they are young subfamilies (~2.3 million years old) that contribute ~30% of recent polymorphic Alu retrotransposition events. Here, we update our ME-Scan methods for detecting Alu elements and apply these methods to discover new insertions in a large set of individuals with diverse ancestral backgrounds. We identified 5,288 putative Alu insertion events, including several hundred novel Alu Yb8/9 elements from 213 individuals from 18 diverse human populations. Hundreds of these loci were specific to continental populations, and 23 non-reference population-specific loci were validated by PCR. We provide high-quality sequence information for 68 rare Alu Yb8/9 elements, of which 11 have hallmarks of an active source element. Our subfamily distribution of rare Alu Yb8/9 elements is consistent with previous datasets, and may be representative of rare loci. We also find that while ME-Scan and low-coverage, whole-genome sequencing (WGS) detect different Alu elements in 41 1000 Genomes individuals, the two methods yield similar population structure results. Current in-silico methods for Alu discovery may miss rare, polymorphic Alu elements. Therefore, using multiple techniques can provide a more accurate profile of Alu elements in individuals and populations. We improved our false-negative rate as an indicator of sample quality for future

  14. Usability of Discovery Portals

    NARCIS (Netherlands)

    Bulens, J.D.; Vullings, L.A.E.; Houtkamp, J.M.; Vanmeulebrouk, B.

    2013-01-01

    As INSPIRE progresses to be implemented in the EU, many new discovery portals are built to facilitate finding spatial data. Currently the structure of the discovery portals is determined by the way spatial data experts like to work. However, we argue that the main target group for discovery portals

  15. Discovery of innovative therapeutics: today's realities and tomorrow's vision. 2. Pharma's challenges and their commitment to innovation.

    Science.gov (United States)

    Abou-Gharbia, Magid; Childers, Wayne E

    2014-07-10

    The pharmaceutical industry is facing enormous challenges, including reduced efficiency, stagnant success rate, patent expirations for key drugs, fierce price competition from generics, high regulatory hurdles, and the industry's perceived tarnished image. Pharma has responded by embarking on a range of initiatives. Other sectors, including NIH, have also responded. Academic drug discovery groups have appeared to support the transition of innovative academic discoveries and ideas into attractive drug discovery opportunities. Part 1 of this two-part series discussed the criticisms that have been leveled at the pharmaceutical industry over the past 3 decades and summarized the supporting data for and against these criticisms. This second installment will focus on the current challenges facing the pharmaceutical industry and Pharma's responses, focusing on the industry's changing perspective and new business models for coping with the loss of talent and declining clinical pipelines as well as presenting some examples of recent drug discovery successes.

  16. 14 CFR 16.213 - Discovery.

    Science.gov (United States)

    2010-01-01

    ... 14 Aeronautics and Space 1 2010-01-01 2010-01-01 false Discovery. 16.213 Section 16.213... PRACTICE FOR FEDERALLY-ASSISTED AIRPORT ENFORCEMENT PROCEEDINGS Hearings § 16.213 Discovery. (a) Discovery... discovery permitted by this section if a party shows that— (1) The information requested is cumulative or...

  17. 28 CFR 76.21 - Discovery.

    Science.gov (United States)

    2010-07-01

    ... 28 Judicial Administration 2 2010-07-01 2010-07-01 false Discovery. 76.21 Section 76.21 Judicial... POSSESSION OF CERTAIN CONTROLLED SUBSTANCES § 76.21 Discovery. (a) Scope. Discovery under this part covers... as a general guide for discovery practices in proceedings before the Judge. However, unless otherwise...

  18. A web services choreography scenario for interoperating bioinformatics applications

    Directory of Open Access Journals (Sweden)

    Cheung David W

    2004-03-01

    with these web services using a web services choreography language (BPEL4WS. Conclusion While it is relatively straightforward to implement and publish web services, the use of web services choreography engines is still in its infancy. However, industry-wide support and push for web services standards is quickly increasing the chance of success in using web services to unify heterogeneous bioinformatics applications. Due to the immaturity of currently available web services engines, it is still most practical to implement a simple, ad-hoc XML-based workflow by hard coding the workflow as a Java application. For advanced web service users the Collaxa BPEL engine facilitates a configuration and management environment that can fully handle XML-based workflow.

  19. Cluster Flow: A user-friendly bioinformatics workflow tool [version 1; referees: 3 approved

    Directory of Open Access Journals (Sweden)

    Philip Ewels

    2016-12-01

    Full Text Available Pipeline tools are becoming increasingly important within the field of bioinformatics. Using a pipeline manager to manage and run workflows comprised of multiple tools reduces workload and makes analysis results more reproducible. Existing tools require significant work to install and get running, typically needing pipeline scripts to be written from scratch before running any analysis. We present Cluster Flow, a simple and flexible bioinformatics pipeline tool designed to be quick and easy to install. Cluster Flow comes with 40 modules for common NGS processing steps, ready to work out of the box. Pipelines are assembled using these modules with a simple syntax that can be easily modified as required. Core helper functions automate many common NGS procedures, making running pipelines simple. Cluster Flow is available with an GNU GPLv3 license on GitHub. Documentation, examples and an online demo are available at http://clusterflow.io.

  20. The use of web ontology languages and other semantic web tools in drug discovery.

    Science.gov (United States)

    Chen, Huajun; Xie, Guotong

    2010-05-01

    To optimize drug development processes, pharmaceutical companies require principled approaches to integrate disparate data on a unified infrastructure, such as the web. The semantic web, developed on the web technology, provides a common, open framework capable of harmonizing diversified resources to enable networked and collaborative drug discovery. We survey the state of art of utilizing web ontologies and other semantic web technologies to interlink both data and people to support integrated drug discovery across domains and multiple disciplines. Particularly, the survey covers three major application categories including: i) semantic integration and open data linking; ii) semantic web service and scientific collaboration and iii) semantic data mining and integrative network analysis. The reader will gain: i) basic knowledge of the semantic web technologies; ii) an overview of the web ontology landscape for drug discovery and iii) a basic understanding of the values and benefits of utilizing the web ontologies in drug discovery. i) The semantic web enables a network effect for linking open data for integrated drug discovery; ii) The semantic web service technology can support instant ad hoc collaboration to improve pipeline productivity and iii) The semantic web encourages publishing data in a semantic way such as resource description framework attributes and thus helps move away from a reliance on pure textual content analysis toward more efficient semantic data mining.