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.

Planning bioinformatics workflows using an expert system

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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

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.  .

Model checking biological systems described using ambient calculus

DEFF Research Database (Denmark)

Mardare, Radu Iulian; Priami, Corrado; Qualia, Paola

2005-01-01

Model checking biological systems described using ambient calculus. In Proc. of the second International Workshop on Computational Methods in Systems Biology (CMSB04), Lecture Notes in Bioinformatics 3082:85-103, Springer, 2005.......Model checking biological systems described using ambient calculus. In Proc. of the second International Workshop on Computational Methods in Systems Biology (CMSB04), Lecture Notes in Bioinformatics 3082:85-103, Springer, 2005....

2K09 and thereafter : the coming era of integrative bioinformatics, systems biology and intelligent computing for functional genomics and personalized medicine research

Science.gov (United States)

2010-01-01

Significant interest exists in establishing synergistic research in bioinformatics, systems biology and intelligent computing. Supported by the United States National Science Foundation (NSF), International Society of Intelligent Biological Medicine (http://www.ISIBM.org), International Journal of Computational Biology and Drug Design (IJCBDD) and International Journal of Functional Informatics and Personalized Medicine, the ISIBM International Joint Conferences on Bioinformatics, Systems Biology and Intelligent Computing (ISIBM IJCBS 2009) attracted more than 300 papers and 400 researchers and medical doctors world-wide. It was the only inter/multidisciplinary conference aimed to promote synergistic research and education in bioinformatics, systems biology and intelligent computing. The conference committee was very grateful for the valuable advice and suggestions from honorary chairs, steering committee members and scientific leaders including Dr. Michael S. Waterman (USC, Member of United States National Academy of Sciences), Dr. Chih-Ming Ho (UCLA, Member of United States National Academy of Engineering and Academician of Academia Sinica), Dr. Wing H. Wong (Stanford, Member of United States National Academy of Sciences), Dr. Ruzena Bajcsy (UC Berkeley, Member of United States National Academy of Engineering and Member of United States Institute of Medicine of the National Academies), Dr. Mary Qu Yang (United States National Institutes of Health and Oak Ridge, DOE), Dr. Andrzej Niemierko (Harvard), Dr. A. Keith Dunker (Indiana), Dr. Brian D. Athey (Michigan), Dr. Weida Tong (FDA, United States Department of Health and Human Services), Dr. Cathy H. Wu (Georgetown), Dr. Dong Xu (Missouri), Drs. Arif Ghafoor and Okan K Ersoy (Purdue), Dr. Mark Borodovsky (Georgia Tech, President of ISIBM), Dr. Hamid R. Arabnia (UGA, Vice-President of ISIBM), and other scientific leaders. The committee presented the 2009 ISIBM Outstanding Achievement Awards to Dr. Joydeep Ghosh (UT

Emerging strengths in Asia Pacific bioinformatics.

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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.

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

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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.

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

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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…

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

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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

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.

7th International Conference on Practical Applications of Computational Biology & Bioinformatics

CERN Document Server

Nanni, Loris; Rocha, Miguel; Fdez-Riverola, Florentino

2013-01-01

The growth in the Bioinformatics and Computational Biology fields over the last few years has been remarkable and the trend is to increase its pace. In fact, the need for computational techniques that can efficiently handle the huge amounts of data produced by the new experimental techniques in Biology is still increasing driven by new advances in Next Generation Sequencing, several types of the so called omics data and image acquisition, just to name a few. The analysis of the datasets that produces and its integration call for new algorithms and approaches from fields such as Databases, Statistics, Data Mining, Machine Learning, Optimization, Computer Science and Artificial Intelligence. Within this scenario of increasing data availability, Systems Biology has also been emerging as an alternative to the reductionist view that dominated biological research in the last decades. Indeed, Biology is more and more a science of information requiring tools from the computational sciences. In the last few years, we ...

A bioinformatics potpourri.

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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.

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

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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…

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

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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...

Multiobjective optimization in bioinformatics and computational biology.

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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.

Bioinformatics for Exploration

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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.

Translational Bioinformatics and Clinical Research (Biomedical) Informatics.

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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.

Protecting innovation in bioinformatics and in-silico biology.

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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.

Bioinformatics approaches to single-cell analysis in developmental biology.

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Yalcin, Dicle; Hakguder, Zeynep M; Otu, Hasan H

2016-03-01

Individual cells within the same population show various degrees of heterogeneity, which may be better handled with single-cell analysis to address biological and clinical questions. Single-cell analysis is especially important in developmental biology as subtle spatial and temporal differences in cells have significant associations with cell fate decisions during differentiation and with the description of a particular state of a cell exhibiting an aberrant phenotype. Biotechnological advances, especially in the area of microfluidics, have led to a robust, massively parallel and multi-dimensional capturing, sorting, and lysis of single-cells and amplification of related macromolecules, which have enabled the use of imaging and omics techniques on single cells. There have been improvements in computational single-cell image analysis in developmental biology regarding feature extraction, segmentation, image enhancement and machine learning, handling limitations of optical resolution to gain new perspectives from the raw microscopy images. Omics approaches, such as transcriptomics, genomics and epigenomics, targeting gene and small RNA expression, single nucleotide and structural variations and methylation and histone modifications, rely heavily on high-throughput sequencing technologies. Although there are well-established bioinformatics methods for analysis of sequence data, there are limited bioinformatics approaches which address experimental design, sample size considerations, amplification bias, normalization, differential expression, coverage, clustering and classification issues, specifically applied at the single-cell level. In this review, we summarize biological and technological advancements, discuss challenges faced in the aforementioned data acquisition and analysis issues and present future prospects for application of single-cell analyses to developmental biology. © The Author 2015. Published by Oxford University Press on behalf of the European

Analyses of Brucella pathogenesis, host immunity, and vaccine targets using systems biology and bioinformatics

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Yongqun eHe

2012-02-01

Full Text Available Brucella is a Gram-negative, facultative intracellular bacterium that causes zoonotic brucellosis in humans and various animals. Out of ten classified Brucella species, B. melitensis, B. abortus, B. suis, and B. canis are pathogenic to humans. In the past decade, the mechanisms of Brucella pathogenesis and host immunity have been extensively investigated using the cutting edge systems biology and bioinformatics approaches. This article provides a comprehensive review of the applications of Omics (including genomics, transcriptomics, and proteomics and bioinformatics technologies for the analysis of Brucella pathogenesis, host immune responses, and vaccine targets. Based on more than 30 sequenced Brucella genomes, comparative genomics is able to identify gene variations among Brucella strains that help to explain host specificity and virulence differences among Brucella species. Diverse transcriptomics and proteomics gene expression studies have been conducted to analyze gene expression profiles of wild type Brucella strains and mutants under different laboratory conditions. High throughput Omics analyses of host responses to infections with virulent or attenuated Brucella strains have been focused on responses by mouse and cattle macrophages, bovine trophoblastic cells, mouse and boar splenocytes, and ram buffy coat. Differential serum responses in humans and rams to Brucella infections have been analyzed using high throughput serum antibody screening technology. The Vaxign reverse vaccinology has been used to predict many Brucella vaccine targets. More than 180 Brucella virulence factors and their gene interaction networks have been identified using advanced literature mining methods. The recent development of community-based Vaccine Ontology and Brucellosis Ontology provides an efficient way for Brucella data integration, exchange, and computer-assisted automated reasoning.

Analyses of Brucella Pathogenesis, Host Immunity, and Vaccine Targets using Systems Biology and Bioinformatics

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He, Yongqun

2011-01-01

Brucella is a Gram-negative, facultative intracellular bacterium that causes zoonotic brucellosis in humans and various animals. Out of 10 classified Brucella species, B. melitensis, B. abortus, B. suis, and B. canis are pathogenic to humans. In the past decade, the mechanisms of Brucella pathogenesis and host immunity have been extensively investigated using the cutting edge systems biology and bioinformatics approaches. This article provides a comprehensive review of the applications of Omics (including genomics, transcriptomics, and proteomics) and bioinformatics technologies for the analysis of Brucella pathogenesis, host immune responses, and vaccine targets. Based on more than 30 sequenced Brucella genomes, comparative genomics is able to identify gene variations among Brucella strains that help to explain host specificity and virulence differences among Brucella species. Diverse transcriptomics and proteomics gene expression studies have been conducted to analyze gene expression profiles of wild type Brucella strains and mutants under different laboratory conditions. High throughput Omics analyses of host responses to infections with virulent or attenuated Brucella strains have been focused on responses by mouse and cattle macrophages, bovine trophoblastic cells, mouse and boar splenocytes, and ram buffy coat. Differential serum responses in humans and rams to Brucella infections have been analyzed using high throughput serum antibody screening technology. The Vaxign reverse vaccinology has been used to predict many Brucella vaccine targets. More than 180 Brucella virulence factors and their gene interaction networks have been identified using advanced literature mining methods. The recent development of community-based Vaccine Ontology and Brucellosis Ontology provides an efficient way for Brucella data integration, exchange, and computer-assisted automated reasoning. PMID:22919594

MEDICAL DIAGNOSTICS BY MICROSTRUCTURAL ANALYSIS OF BIOLOGICAL LIQUID DRIED PATTERNS AS A PROBLEM OF BIOINFORMATICS

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Petr Vladimirovich Lebedev-Stepanov, Dr.

2018-02-01

Full Text Available Motivation: It is important to develop the high-precision computerized methods for medical rapid diagnostic which is generalizing the unique clinical experience obtained in the past decade as specialized solutions for diagnostic problems of control of specific diseases and, potentially, for a wide health monitoring of virtually healthy population, identify the reserves of human health and take the actions to prevent of these reserves depletion. In this work we present one of the new directions in bioinformatics, i.e. medical diagnostics by automated expert system on basis of morphology analysis of digital image of biological liquid dried pattern. Results: Proposed method is combination of bioinformatics and biochemistry approaches for obtaining diagnostic information from a morphological analysis of standardized dried patterns of biological liquid sessile drop. We have carried out own research in collaboration with medical diagnostic centers and formed the electronic database for recognition the following types of diseases: candidiasis; neoplasms; diabetes mellitus; diseases of the circulatory system; cerebrovascular disease; diseases of the digestive system; diseases of the genitourinary system; infectious diseases; factors relevant to the work; factors associated with environmental pollution; factors related to lifestyle. The laboratory setup for diagnostics of the human body in pathology states is developed. The diagnostic results are considered. Availability: Access to testing the software can be obtained on request to the contact email below.

Introduction to bioinformatics.

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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.

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

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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…

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

Biology in 'silico': The Bioinformatics Revolution.

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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…

Interdisciplinary Introductory Course in Bioinformatics

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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…

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.

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

Infusing Bioinformatics and Research-Like Experience into a Molecular Biology Laboratory Course

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Nogaj, Luiza A.

2014-01-01

A nine-week laboratory project designed for a sophomore level molecular biology course is described. Small groups of students (3-4 per group) choose a tumor suppressor gene (TSG) or an oncogene for this project. Each group researches the role of their TSG/oncogene from primary literature articles and uses bioinformatics engines to find the gene…

4273π: bioinformatics education on low cost ARM hardware.

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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.

The 2015 Bioinformatics Open Source Conference (BOSC 2015).

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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.

Systems biology: the reincarnation of systems theory applied in biology?

Science.gov (United States)

Wolkenhauer, O

2001-09-01

With the availability of quantitative data on the transcriptome and proteome level, there is an increasing interest in formal mathematical models of gene expression and regulation. International conferences, research institutes and research groups concerned with systems biology have appeared in recent years and systems theory, the study of organisation and behaviour per se, is indeed a natural conceptual framework for such a task. This is, however, not the first time that systems theory has been applied in modelling cellular processes. Notably in the 1960s systems theory and biology enjoyed considerable interest among eminent scientists, mathematicians and engineers. Why did these early attempts vanish from research agendas? Here we shall review the domain of systems theory, its application to biology and the lessons that can be learned from the work of Robert Rosen. Rosen emerged from the early developments in the 1960s as a main critic but also developed a new alternative perspective to living systems, a concept that deserves a fresh look in the post-genome era of bioinformatics.

11th International Conference on Practical Applications of Computational Biology & Bioinformatics

CERN Document Server

Mohamad, Mohd; Rocha, Miguel; Paz, Juan; Pinto, Tiago

2017-01-01

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 constantly evolving, distinct types of omics data technologies, have created an increasingly complex set of challenges for the growing fields of Bioinformatics and Computational Biology. The analysis of the datasets produced and their integration call for new algorithms and approaches from fields such as Databases, Statistics, Data Mining, Machine Learning, Optimization, Computer Science and Artificial Intelligence. Clearly, Biology is more and more a science of information and requires tools from the computational sciences. In the last few years, we have seen the rise of a new generation of interdisciplinary scientists with a strong background in the biological and computational sciences. In this context, the interaction of r...

8th International Conference on Practical Applications of Computational Biology & Bioinformatics

CERN Document Server

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

2014-01-01

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 of the datasets produced and their integration call for new algorithms and approaches from fields such as Databases, Statistics, Data Mining, Machine Learning, Optimization, Computer Science and Artificial Intelligence. Clearly, Biology is more and more a science of information requiring tools from the computational sciences. In the last few years, we have seen the surge of a new generation of interdisciplinary scientists that have a strong background in the biological and computational sciences. In this context, the interaction of researche...

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

CERN Document Server

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

2016-01-01

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 of the datasets produced and their integration call for new algorithms and approaches from fields such as Databases, Statistics, Data Mining, Machine Learning, Optimization, Computer Science and Artificial Intelligence. Clearly, Biology is more and more a science of information requiring tools from the computational sciences. In the last few years, we have seen the surge of a new generation of interdisciplinary scientists that have a strong background in the biological and computational sciences. In this context, the interaction of researche...

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.

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.

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.)

10 years for the Journal of Bioinformatics and Computational Biology (2003-2013) -- a retrospective.

Science.gov (United States)

Eisenhaber, Frank; Sherman, Westley Arthur

2014-06-01

The Journal of Bioinformatics and Computational Biology (JBCB) started publishing scientific articles in 2003. It has established itself as home for solid research articles in the field (~ 60 per year) that are surprisingly well cited. JBCB has an important function as alternative publishing channel in addition to other, bigger journals.

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...

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.

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

Ins and outs of systems biology vis-à-vis molecular biology: continuation or clear cut?

Science.gov (United States)

De Backer, Philippe; De Waele, Danny; Van Speybroeck, Linda

2010-03-01

The comprehension of living organisms in all their complexity poses a major challenge to the biological sciences. Recently, systems biology has been proposed as a new candidate in the development of such a comprehension. The main objective of this paper is to address what systems biology is and how it is practised. To this end, the basic tools of a systems biological approach are explored and illustrated. In addition, it is questioned whether systems biology 'revolutionizes' molecular biology and 'transcends' its assumed reductionism. The strength of this claim appears to depend on how molecular and systems biology are characterised and on how reductionism is interpreted. Doing credit to molecular biology and to methodological reductionism, it is argued that the distinction between molecular and systems biology is gradual rather than sharp. As such, the classical challenge in biology to manage, interpret and integrate biological data into functional wholes is further intensified by systems biology's use of modelling and bioinformatics, and by its scale enlargement.

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.

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.

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

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.

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.

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…

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.

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.

Plant Systems Biology at the Single-Cell Level.

Science.gov (United States)

Libault, Marc; Pingault, Lise; Zogli, Prince; Schiefelbein, John

2017-11-01

Our understanding of plant biology is increasingly being built upon studies using 'omics and system biology approaches performed at the level of the entire plant, organ, or tissue. Although these approaches open new avenues to better understand plant biology, they suffer from the cellular complexity of the analyzed sample. Recent methodological advances now allow plant scientists to overcome this limitation and enable biological analyses of single-cells or single-cell-types. Coupled with the development of bioinformatics and functional genomics resources, these studies provide opportunities for high-resolution systems analyses of plant phenomena. In this review, we describe the recent advances, current challenges, and future directions in exploring the biology of single-cells and single-cell-types to enhance our understanding of plant biology as a system. Copyright © 2017 Elsevier Ltd. All rights reserved.

Integrating phosphoproteomics in systems biology

Directory of Open Access Journals (Sweden)

Yu Liu

2014-07-01

Full Text Available Phosphorylation of serine, threonine and tyrosine plays significant roles in cellular signal transduction and in modifying multiple protein functions. Phosphoproteins are coordinated and regulated by a network of kinases, phosphatases and phospho-binding proteins, which modify the phosphorylation states, recognize unique phosphopeptides, or target proteins for degradation. Detailed and complete information on the structure and dynamics of these networks is required to better understand fundamental mechanisms of cellular processes and diseases. High-throughput technologies have been developed to investigate phosphoproteomes in model organisms and human diseases. Among them, mass spectrometry (MS-based technologies are the major platforms and have been widely applied, which has led to explosive growth of phosphoproteomic data in recent years. New bioinformatics tools are needed to analyze and make sense of these data. Moreover, most research has focused on individual phosphoproteins and kinases. To gain a more complete knowledge of cellular processes, systems biology approaches, including pathways and networks modeling, have to be applied to integrate all components of the phosphorylation machinery, including kinases, phosphatases, their substrates, and phospho-binding proteins. This review presents the latest developments of bioinformatics methods and attempts to apply systems biology to analyze phosphoproteomics data generated by MS-based technologies. Challenges and future directions in this field will be also discussed.

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....

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.

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.

SeqHound: biological sequence and structure database as a platform for bioinformatics research

Directory of Open Access Journals (Sweden)

Dumontier Michel

2002-10-01

Full Text Available Abstract Background SeqHound has been developed as an integrated biological sequence, taxonomy, annotation and 3-D structure database system. It provides a high-performance server platform for bioinformatics research in a locally-hosted environment. Results SeqHound is based on the National Center for Biotechnology Information data model and programming tools. It offers daily updated contents of all Entrez sequence databases in addition to 3-D structural data and information about sequence redundancies, sequence neighbours, taxonomy, complete genomes, functional annotation including Gene Ontology terms and literature links to PubMed. SeqHound is accessible via a web server through a Perl, C or C++ remote API or an optimized local API. It provides functionality necessary to retrieve specialized subsets of sequences, structures and structural domains. Sequences may be retrieved in FASTA, GenBank, ASN.1 and XML formats. Structures are available in ASN.1, XML and PDB formats. Emphasis has been placed on complete genomes, taxonomy, domain and functional annotation as well as 3-D structural functionality in the API, while fielded text indexing functionality remains under development. SeqHound also offers a streamlined WWW interface for simple web-user queries. Conclusions The system has proven useful in several published bioinformatics projects such as the BIND database and offers a cost-effective infrastructure for research. SeqHound will continue to develop and be provided as a service of the Blueprint Initiative at the Samuel Lunenfeld Research Institute. The source code and examples are available under the terms of the GNU public license at the Sourceforge site http://sourceforge.net/projects/slritools/ in the SLRI Toolkit.

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

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

Yeast systems biology to unravel the network of life

DEFF Research Database (Denmark)

Mustacchi, Roberta; Hohmann, S; Nielsen, Jens

2006-01-01

Systems biology focuses on obtaining a quantitative description of complete biological systems, even complete cellular function. In this way, it will be possible to perform computer-guided design of novel drugs, advanced therapies for treatment of complex diseases, and to perform in silico design....... Furthermore, it serves as an industrial workhorse for production of a wide range of chemicals and pharmaceuticals. Systems biology involves the combination of novel experimental techniques from different disciplines as well as functional genomics, bioinformatics and mathematical modelling, and hence no single...... laboratory has access to all the necessary competences. For this reason the Yeast Systems Biology Network (YSBN) has been established. YSBN will coordinate research efforts, in yeast systems biology and, through the recently obtained EU funding for a Coordination Action, it will be possible to set...

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.

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.

Metabolic, Replication and Genomic Category of Systems in Biology, Bioinformatics and Medicine

OpenAIRE

I. C. Baianu

2012-01-01

Metabolic-repair models, or (M,R)-systems were introduced in Relational Biology by Robert Rosen. Subsequently, Rosen represented such (M,R)-systems (or simply MRs)in terms of categories of sets, deliberately selected without any structure other than the discrete topology of sets. Theoreticians of life’s origins postulated that Life on Earth has begun with the simplest possible organism, called the primordial. Mathematicians interested in biology attempted to answer this important quest...

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.

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.

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.

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…

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

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

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.

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 ...

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.

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.

Combining chemoinformatics with bioinformatics: in silico prediction of bacterial flavor-forming pathways by a chemical systems biology approach "reverse pathway engineering".

Science.gov (United States)

Liu, Mengjin; Bienfait, Bruno; Sacher, Oliver; Gasteiger, Johann; Siezen, Roland J; Nauta, Arjen; Geurts, Jan M W

2014-01-01

The incompleteness of genome-scale metabolic models is a major bottleneck for systems biology approaches, which are based on large numbers of metabolites as identified and quantified by metabolomics. Many of the revealed secondary metabolites and/or their derivatives, such as flavor compounds, are non-essential in metabolism, and many of their synthesis pathways are unknown. In this study, we describe a novel approach, Reverse Pathway Engineering (RPE), which combines chemoinformatics and bioinformatics analyses, to predict the "missing links" between compounds of interest and their possible metabolic precursors by providing plausible chemical and/or enzymatic reactions. We demonstrate the added-value of the approach by using flavor-forming pathways in lactic acid bacteria (LAB) as an example. Established metabolic routes leading to the formation of flavor compounds from leucine were successfully replicated. Novel reactions involved in flavor formation, i.e. the conversion of alpha-hydroxy-isocaproate to 3-methylbutanoic acid and the synthesis of dimethyl sulfide, as well as the involved enzymes were successfully predicted. These new insights into the flavor-formation mechanisms in LAB can have a significant impact on improving the control of aroma formation in fermented food products. Since the input reaction databases and compounds are highly flexible, the RPE approach can be easily extended to a broad spectrum of applications, amongst others health/disease biomarker discovery as well as synthetic biology.

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:…

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…

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.

Application of Bioinformatics in Chronobiology Research

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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.

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).

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.

Network Reconstruction of Dynamic Biological Systems

OpenAIRE

Asadi, Behrang

2013-01-01

Inference of network topology from experimental data is a central endeavor in biology, since knowledge of the underlying signaling mechanisms a requirement for understanding biological phenomena. As one of the most important tools in bioinformatics area, development of methods to reconstruct biological networks has attracted remarkable attention in the current decade. Integration of different data types can lead to remarkable improvements in our ability to identify the connectivity of differe...

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…

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

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.

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.

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 ...

Exploiting graphics processing units for computational biology and bioinformatics.

Science.gov (United States)

Payne, Joshua L; Sinnott-Armstrong, Nicholas A; Moore, Jason H

2010-09-01

Advances in the video gaming industry have led to the production of low-cost, high-performance graphics processing units (GPUs) that possess more memory bandwidth and computational capability than central processing units (CPUs), the standard workhorses of scientific computing. With the recent release of generalpurpose GPUs and NVIDIA's GPU programming language, CUDA, graphics engines are being adopted widely in scientific computing applications, particularly in the fields of computational biology and bioinformatics. The goal of this article is to concisely present an introduction to GPU hardware and programming, aimed at the computational biologist or bioinformaticist. To this end, we discuss the primary differences between GPU and CPU architecture, introduce the basics of the CUDA programming language, and discuss important CUDA programming practices, such as the proper use of coalesced reads, data types, and memory hierarchies. We highlight each of these topics in the context of computing the all-pairs distance between instances in a dataset, a common procedure in numerous disciplines of scientific computing. We conclude with a runtime analysis of the GPU and CPU implementations of the all-pairs distance calculation. We show our final GPU implementation to outperform the CPU implementation by a factor of 1700.

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.

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

Bioinformatics resource manager v2.3: an integrated software environment for systems biology with microRNA and cross-species analysis tools

Directory of Open Access Journals (Sweden)

Tilton Susan C

2012-11-01

Full Text Available Abstract Background MicroRNAs (miRNAs are noncoding RNAs that direct post-transcriptional regulation of protein coding genes. Recent studies have shown miRNAs are important for controlling many biological processes, including nervous system development, and are highly conserved across species. Given their importance, computational tools are necessary for analysis, interpretation and integration of high-throughput (HTP miRNA data in an increasing number of model species. The Bioinformatics Resource Manager (BRM v2.3 is a software environment for data management, mining, integration and functional annotation of HTP biological data. In this study, we report recent updates to BRM for miRNA data analysis and cross-species comparisons across datasets. Results BRM v2.3 has the capability to query predicted miRNA targets from multiple databases, retrieve potential regulatory miRNAs for known genes, integrate experimentally derived miRNA and mRNA datasets, perform ortholog mapping across species, and retrieve annotation and cross-reference identifiers for an expanded number of species. Here we use BRM to show that developmental exposure of zebrafish to 30 uM nicotine from 6–48 hours post fertilization (hpf results in behavioral hyperactivity in larval zebrafish and alteration of putative miRNA gene targets in whole embryos at developmental stages that encompass early neurogenesis. We show typical workflows for using BRM to integrate experimental zebrafish miRNA and mRNA microarray datasets with example retrievals for zebrafish, including pathway annotation and mapping to human ortholog. Functional analysis of differentially regulated (p Conclusions BRM provides the ability to mine complex data for identification of candidate miRNAs or pathways that drive phenotypic outcome and, therefore, is a useful hypothesis generation tool for systems biology. The miRNA workflow in BRM allows for efficient processing of multiple miRNA and mRNA datasets in a single

Bioinformatics resource manager v2.3: an integrated software environment for systems biology with microRNA and cross-species analysis tools

Science.gov (United States)

2012-01-01

Background MicroRNAs (miRNAs) are noncoding RNAs that direct post-transcriptional regulation of protein coding genes. Recent studies have shown miRNAs are important for controlling many biological processes, including nervous system development, and are highly conserved across species. Given their importance, computational tools are necessary for analysis, interpretation and integration of high-throughput (HTP) miRNA data in an increasing number of model species. The Bioinformatics Resource Manager (BRM) v2.3 is a software environment for data management, mining, integration and functional annotation of HTP biological data. In this study, we report recent updates to BRM for miRNA data analysis and cross-species comparisons across datasets. Results BRM v2.3 has the capability to query predicted miRNA targets from multiple databases, retrieve potential regulatory miRNAs for known genes, integrate experimentally derived miRNA and mRNA datasets, perform ortholog mapping across species, and retrieve annotation and cross-reference identifiers for an expanded number of species. Here we use BRM to show that developmental exposure of zebrafish to 30 uM nicotine from 6–48 hours post fertilization (hpf) results in behavioral hyperactivity in larval zebrafish and alteration of putative miRNA gene targets in whole embryos at developmental stages that encompass early neurogenesis. We show typical workflows for using BRM to integrate experimental zebrafish miRNA and mRNA microarray datasets with example retrievals for zebrafish, including pathway annotation and mapping to human ortholog. Functional analysis of differentially regulated (p<0.05) gene targets in BRM indicates that nicotine exposure disrupts genes involved in neurogenesis, possibly through misregulation of nicotine-sensitive miRNAs. Conclusions BRM provides the ability to mine complex data for identification of candidate miRNAs or pathways that drive phenotypic outcome and, therefore, is a useful hypothesis

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…

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.

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

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…

Nonlinear dynamics in biological systems

CERN Document Server

Carballido-Landeira, Jorge

2016-01-01

This book presents recent research results relating to applications of nonlinear dynamics, focusing specifically on four topics of wide interest: heart dynamics, DNA/RNA, cell mobility, and proteins. The book derives from the First BCAM Workshop on Nonlinear Dynamics in Biological Systems, held in June 2014 at the Basque Center of Applied Mathematics (BCAM). At this international meeting, researchers from different but complementary backgrounds, including molecular dynamics, physical chemistry, bio-informatics and biophysics, presented their most recent results and discussed the future direction of their studies using theoretical, mathematical modeling and experimental approaches. Such was the level of interest stimulated that the decision was taken to produce this publication, with the organizers of the event acting as editors. All of the contributing authors are researchers working on diverse biological problems that can be approached using nonlinear dynamics. The book will appeal especially to applied math...

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...

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…

Supporting cognition in systems biology analysis: findings on users' processes and design implications.

Science.gov (United States)

Mirel, Barbara

2009-02-13

Current usability studies of bioinformatics tools suggest that tools for exploratory analysis support some tasks related to finding relationships of interest but not the deep causal insights necessary for formulating plausible and credible hypotheses. To better understand design requirements for gaining these causal insights in systems biology analyses a longitudinal field study of 15 biomedical researchers was conducted. Researchers interacted with the same protein-protein interaction tools to discover possible disease mechanisms for further experimentation. Findings reveal patterns in scientists' exploratory and explanatory analysis and reveal that tools positively supported a number of well-structured query and analysis tasks. But for several of scientists' more complex, higher order ways of knowing and reasoning the tools did not offer adequate support. Results show that for a better fit with scientists' cognition for exploratory analysis systems biology tools need to better match scientists' processes for validating, for making a transition from classification to model-based reasoning, and for engaging in causal mental modelling. As the next great frontier in bioinformatics usability, tool designs for exploratory systems biology analysis need to move beyond the successes already achieved in supporting formulaic query and analysis tasks and now reduce current mismatches with several of scientists' higher order analytical practices. The implications of results for tool designs are discussed.

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…

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.

Polynomial algebra of discrete models in systems biology.

Science.gov (United States)

Veliz-Cuba, Alan; Jarrah, Abdul Salam; Laubenbacher, Reinhard

2010-07-01

An increasing number of discrete mathematical models are being published in Systems Biology, ranging from Boolean network models to logical models and Petri nets. They are used to model a variety of biochemical networks, such as metabolic networks, gene regulatory networks and signal transduction networks. There is increasing evidence that such models can capture key dynamic features of biological networks and can be used successfully for hypothesis generation. This article provides a unified framework that can aid the mathematical analysis of Boolean network models, logical models and Petri nets. They can be represented as polynomial dynamical systems, which allows the use of a variety of mathematical tools from computer algebra for their analysis. Algorithms are presented for the translation into polynomial dynamical systems. Examples are given of how polynomial algebra can be used for the model analysis. alanavc@vt.edu Supplementary data are available at Bioinformatics online.

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 ...

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

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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

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

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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.

"Extreme Programming" in a Bioinformatics Class

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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).…

Bioinformatics in Undergraduate Education: Practical Examples

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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…

Modern bioinformatics meets traditional Chinese medicine.

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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.

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

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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.

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

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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.

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

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

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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

Combining medical informatics and bioinformatics toward tools for personalized medicine.

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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.

Data management and data enrichment for systems biology projects.

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Wittig, Ulrike; Rey, Maja; Weidemann, Andreas; Müller, Wolfgang

2017-11-10

Collecting, curating, interlinking, and sharing high quality data are central to de.NBI-SysBio, the systems biology data management service center within the de.NBI network (German Network for Bioinformatics Infrastructure). The work of the center is guided by the FAIR principles for scientific data management and stewardship. FAIR stands for the four foundational principles Findability, Accessibility, Interoperability, and Reusability which were established to enhance the ability of machines to automatically find, access, exchange and use data. Within this overview paper we describe three tools (SABIO-RK, Excemplify, SEEK) that exemplify the contribution of de.NBI-SysBio services to FAIR data, models, and experimental methods storage and exchange. The interconnectivity of the tools and the data workflow within systems biology projects will be explained. For many years we are the German partner in the FAIRDOM initiative (http://fair-dom.org) to establish a European data and model management service facility for systems biology. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

Specifications of Standards in Systems and Synthetic Biology: Status and Developments in 2016

Directory of Open Access Journals (Sweden)

Schreiber Falk

2016-09-01

Full Text Available Standards are essential to the advancement of science and technology. In systems and synthetic biology, numerous standards and associated tools have been developed over the last 16 years. This special issue of the Journal of Integrative Bioinformatics aims to support the exchange, distribution and archiving of these standards, as well as to provide centralised and easily citable access to them.

Biowep: a workflow enactment portal for bioinformatics applications.

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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

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

Component-Based Approach for Educating Students in Bioinformatics

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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…

Meta-learning framework applied in bioinformatics inference system design.

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Arredondo, Tomás; Ormazábal, Wladimir

2015-01-01

This paper describes a meta-learner inference system development framework which is applied and tested in the implementation of bioinformatic inference systems. These inference systems are used for the systematic classification of the best candidates for inclusion in bacterial metabolic pathway maps. This meta-learner-based approach utilises a workflow where the user provides feedback with final classification decisions which are stored in conjunction with analysed genetic sequences for periodic inference system training. The inference systems were trained and tested with three different data sets related to the bacterial degradation of aromatic compounds. The analysis of the meta-learner-based framework involved contrasting several different optimisation methods with various different parameters. The obtained inference systems were also contrasted with other standard classification methods with accurate prediction capabilities observed.

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

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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…

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

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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.

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

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.

A bioinformatics roadmap for the human vaccines project.

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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.

Bioboxes: standardised containers for interchangeable bioinformatics software.

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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.

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.

Genomics and bioinformatics resources for translational science in Rosaceae.

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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.

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

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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.

Genomewide effects of peroxisome proliferator-activated receptor gamma in macrophages and dendritic cells--revealing complexity through systems biology.

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Cuaranta-Monroy, Ixchelt; Kiss, Mate; Simandi, Zoltan; Nagy, Laszlo

2015-09-01

Systems biology approaches have become indispensable tools in biomedical and basic research. These data integrating bioinformatic methods gained prominence after high-throughput technologies became available to investigate complex cellular processes, such as transcriptional regulation and protein-protein interactions, on a scale that had not been studied before. Immunology is one of the medical fields that systems biology impacted profoundly due to the plasticity of cell types involved and the accessibility of a wide range of experimental models. In this review, we summarize the most important recent genomewide studies exploring the function of peroxisome proliferator-activated receptor γ in macrophages and dendritic cells. PPARγ ChIP-seq experiments were performed in adipocytes derived from embryonic stem cells to complement the existing data sets and to provide comparators to macrophage data. Finally, lists of regulated genes generated from such experiments were analysed with bioinformatics and system biology approaches. We show that genomewide studies utilizing high-throughput data acquisition methods made it possible to gain deeper insights into the role of PPARγ in these immune cell types. We also demonstrate that analysis and visualization of data using network-based approaches can be used to identify novel genes and functions regulated by the receptor. The example of PPARγ in macrophages and dendritic cells highlights the crucial importance of systems biology approaches in establishing novel cellular functions for long-known signaling pathways. © 2015 Stichting European Society for Clinical Investigation Journal Foundation.

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

Specifications of Standards in Systems and Synthetic Biology: Status and Developments in 2017

Directory of Open Access Journals (Sweden)

Schreiber Falk

2018-03-01

Full Text Available Standards are essential to the advancement of Systems and Synthetic Biology. COMBINE provides a formal body and a centralised platform to help develop and disseminate relevant standards and related resources. The regular special issue of the Journal of Integrative Bioinformatics aims to support the exchange, distribution and archiving of these standards by providing unified, easily citable access. This paper provides an overview of existing COMBINE standards and presents developments of the last year.

BpWrapper: BioPerl-based sequence and tree utilities for rapid prototyping of bioinformatics pipelines.

Science.gov (United States)

Hernández, Yözen; Bernstein, Rocky; Pagan, Pedro; Vargas, Levy; McCaig, William; Ramrattan, Girish; Akther, Saymon; Larracuente, Amanda; Di, Lia; Vieira, Filipe G; Qiu, Wei-Gang

2018-03-02

Automated bioinformatics workflows are more robust, easier to maintain, and results more reproducible when built with command-line utilities than with custom-coded scripts. Command-line utilities further benefit by relieving bioinformatics developers to learn the use of, or to interact directly with, biological software libraries. There is however a lack of command-line utilities that leverage popular Open Source biological software toolkits such as BioPerl ( http://bioperl.org ) to make many of the well-designed, robust, and routinely used biological classes available for a wider base of end users. Designed as standard utilities for UNIX-family operating systems, BpWrapper makes functionality of some of the most popular BioPerl modules readily accessible on the command line to novice as well as to experienced bioinformatics practitioners. The initial release of BpWrapper includes four utilities with concise command-line user interfaces, bioseq, bioaln, biotree, and biopop, specialized for manipulation of molecular sequences, sequence alignments, phylogenetic trees, and DNA polymorphisms, respectively. Over a hundred methods are currently available as command-line options and new methods are easily incorporated. Performance of BpWrapper utilities lags that of precompiled utilities while equivalent to that of other utilities based on BioPerl. BpWrapper has been tested on BioPerl Release 1.6, Perl versions 5.10.1 to 5.25.10, and operating systems including Apple macOS, Microsoft Windows, and GNU/Linux. Release code is available from the Comprehensive Perl Archive Network (CPAN) at https://metacpan.org/pod/Bio::BPWrapper . Source code is available on GitHub at https://github.com/bioperl/p5-bpwrapper . BpWrapper improves on existing sequence utilities by following the design principles of Unix text utilities such including a concise user interface, extensive command-line options, and standard input/output for serialized operations. Further, dozens of novel methods for

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

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.

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...

STOCHSIMGPU: parallel stochastic simulation for the Systems Biology Toolbox 2 for MATLAB.

Science.gov (United States)

Klingbeil, Guido; Erban, Radek; Giles, Mike; Maini, Philip K

2011-04-15

The importance of stochasticity in biological systems is becoming increasingly recognized and the computational cost of biologically realistic stochastic simulations urgently requires development of efficient software. We present a new software tool STOCHSIMGPU that exploits graphics processing units (GPUs) for parallel stochastic simulations of biological/chemical reaction systems and show that significant gains in efficiency can be made. It is integrated into MATLAB and works with the Systems Biology Toolbox 2 (SBTOOLBOX2) for MATLAB. The GPU-based parallel implementation of the Gillespie stochastic simulation algorithm (SSA), the logarithmic direct method (LDM) and the next reaction method (NRM) is approximately 85 times faster than the sequential implementation of the NRM on a central processing unit (CPU). Using our software does not require any changes to the user's models, since it acts as a direct replacement of the stochastic simulation software of the SBTOOLBOX2. The software is open source under the GPL v3 and available at http://www.maths.ox.ac.uk/cmb/STOCHSIMGPU. The web site also contains supplementary information. klingbeil@maths.ox.ac.uk Supplementary data are available at Bioinformatics online.

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.

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…

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

Secure Encapsulation and Publication of Biological Services in the Cloud Computing Environment

Science.gov (United States)

Zhang, Weizhe; Wang, Xuehui; Lu, Bo; Kim, Tai-hoon

2013-01-01

Secure encapsulation and publication for bioinformatics software products based on web service are presented, and the basic function of biological information is realized in the cloud computing environment. In the encapsulation phase, the workflow and function of bioinformatics software are conducted, the encapsulation interfaces are designed, and the runtime interaction between users and computers is simulated. In the publication phase, the execution and management mechanisms and principles of the GRAM components are analyzed. The functions such as remote user job submission and job status query are implemented by using the GRAM components. The services of bioinformatics software are published to remote users. Finally the basic prototype system of the biological cloud is achieved. PMID:24078906

Secure Encapsulation and Publication of Biological Services in the Cloud Computing Environment

Directory of Open Access Journals (Sweden)

Weizhe Zhang

2013-01-01

Full Text Available Secure encapsulation and publication for bioinformatics software products based on web service are presented, and the basic function of biological information is realized in the cloud computing environment. In the encapsulation phase, the workflow and function of bioinformatics software are conducted, the encapsulation interfaces are designed, and the runtime interaction between users and computers is simulated. In the publication phase, the execution and management mechanisms and principles of the GRAM components are analyzed. The functions such as remote user job submission and job status query are implemented by using the GRAM components. The services of bioinformatics software are published to remote users. Finally the basic prototype system of the biological cloud is achieved.

Secure encapsulation and publication of biological services in the cloud computing environment.

Science.gov (United States)

Zhang, Weizhe; Wang, Xuehui; Lu, Bo; Kim, Tai-hoon

2013-01-01

Secure encapsulation and publication for bioinformatics software products based on web service are presented, and the basic function of biological information is realized in the cloud computing environment. In the encapsulation phase, the workflow and function of bioinformatics software are conducted, the encapsulation interfaces are designed, and the runtime interaction between users and computers is simulated. In the publication phase, the execution and management mechanisms and principles of the GRAM components are analyzed. The functions such as remote user job submission and job status query are implemented by using the GRAM components. The services of bioinformatics software are published to remote users. Finally the basic prototype system of the biological cloud is achieved.

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.

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

International Conference on Intelligent Systems for Molecular Biology (ISMB)

Energy Technology Data Exchange (ETDEWEB)

Goldberg, Debra; Hibbs, Matthew; Kall, Lukas; Komandurglayavilli, Ravikumar; Mahony, Shaun; Marinescu, Voichita; Mayrose, Itay; Minin, Vladimir; Neeman, Yossef; Nimrod, Guy; Novotny, Marian; Opiyo, Stephen; Portugaly, Elon; Sadka, Tali; Sakabe, Noboru; Sarkar, Indra; Schaub, Marc; Shafer, Paul; Shmygelska, Olena; Singer, Gregory; Song, Yun; Soumyaroop, Bhattacharya; Stadler, Michael; Strope, Pooja; Su, Rong; Tabach, Yuval; Tae, Hongseok; Taylor, Todd; Terribilini, Michael; Thomas, Asha; Tran, Nam; Tseng, Tsai-Tien; Vashist, Akshay; Vijaya, Parthiban; Wang, Kai; Wang, Ting; Wei, Lai; Woo, Yong; Wu, Chunlei; Yamanishi, Yoshihiro; Yan, Changhui; Yang, Jack; Yang, Mary; Ye, Ping; Zhang, Miao

2009-12-29

The Intelligent Systems for Molecular Biology (ISMB) conference has provided a general forum for disseminating the latest developments in bioinformatics on an annual basis for the past 13 years. ISMB is a multidisciplinary conference that brings together scientists from computer science, molecular biology, mathematics and statistics. The goal of the ISMB meeting is to bring together biologists and computational scientists in a focus on actual biological problems, i.e., not simply theoretical calculations. The combined focus on "intelligent systems" and actual biological data makes ISMB a unique and highly important meeting, and 13 years of experience in holding the conference has resulted in a consistently well organized, well attended, and highly respected annual conference. The ISMB 2005 meeting was held June 25-29, 2005 at the Renaissance Center in Detroit, Michigan. The meeting attracted over 1,730 attendees. The science presented was exceptional, and in the course of the five-day meeting, 56 scientific papers, 710 posters, 47 Oral Abstracts, 76 Software demonstrations, and 14 tutorials were presented. The attendees represented a broad spectrum of backgrounds with 7% from commercial companies, over 28% qualifying for student registration, and 41 countries were represented at the conference, emphasizing its important international aspect. The ISMB conference is especially important because the cultures of computer science and biology are so disparate. ISMB, as a full-scale technical conference with refereed proceedings that have been indexed by both MEDLINE and Current Contents since 1996, bridges this cultural gap.

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.

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.

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…

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.

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…

On Designing Multicore-Aware Simulators for Systems Biology Endowed with OnLine Statistics

Directory of Open Access Journals (Sweden)

Marco Aldinucci

2014-01-01

Full Text Available The paper arguments are on enabling methodologies for the design of a fully parallel, online, interactive tool aiming to support the bioinformatics scientists .In particular, the features of these methodologies, supported by the FastFlow parallel programming framework, are shown on a simulation tool to perform the modeling, the tuning, and the sensitivity analysis of stochastic biological models. A stochastic simulation needs thousands of independent simulation trajectories turning into big data that should be analysed by statistic and data mining tools. In the considered approach the two stages are pipelined in such a way that the simulation stage streams out the partial results of all simulation trajectories to the analysis stage that immediately produces a partial result. The simulation-analysis workflow is validated for performance and effectiveness of the online analysis in capturing biological systems behavior on a multicore platform and representative proof-of-concept biological systems. The exploited methodologies include pattern-based parallel programming and data streaming that provide key features to the software designers such as performance portability and efficient in-memory (big data management and movement. Two paradigmatic classes of biological systems exhibiting multistable and oscillatory behavior are used as a testbed.

On designing multicore-aware simulators for systems biology endowed with OnLine statistics.

Science.gov (United States)

Aldinucci, Marco; Calcagno, Cristina; Coppo, Mario; Damiani, Ferruccio; Drocco, Maurizio; Sciacca, Eva; Spinella, Salvatore; Torquati, Massimo; Troina, Angelo

2014-01-01

The paper arguments are on enabling methodologies for the design of a fully parallel, online, interactive tool aiming to support the bioinformatics scientists .In particular, the features of these methodologies, supported by the FastFlow parallel programming framework, are shown on a simulation tool to perform the modeling, the tuning, and the sensitivity analysis of stochastic biological models. A stochastic simulation needs thousands of independent simulation trajectories turning into big data that should be analysed by statistic and data mining tools. In the considered approach the two stages are pipelined in such a way that the simulation stage streams out the partial results of all simulation trajectories to the analysis stage that immediately produces a partial result. The simulation-analysis workflow is validated for performance and effectiveness of the online analysis in capturing biological systems behavior on a multicore platform and representative proof-of-concept biological systems. The exploited methodologies include pattern-based parallel programming and data streaming that provide key features to the software designers such as performance portability and efficient in-memory (big) data management and movement. Two paradigmatic classes of biological systems exhibiting multistable and oscillatory behavior are used as a testbed.

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.

A Survey on Evolutionary Algorithm Based Hybrid Intelligence in Bioinformatics

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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.

Ruminant Metabolic Systems Biology: Reconstruction and Integration of Transcriptome Dynamics Underlying Functional Responses of Tissues to Nutrition and Physiological Statea

Science.gov (United States)

Bionaz, Massimo; Loor, Juan J.

2012-01-01

High-throughput ‘omics’ data analysis via bioinformatics is one key component of the systems biology approach. The systems approach is particularly well-suited for the study of the interactions between nutrition and physiological state with tissue metabolism and functions during key life stages of organisms such as the transition from pregnancy to lactation in mammals, ie, the peripartal period. In modern dairy cows with an unprecedented genetic potential for milk synthesis, the nature of the physiologic and metabolic adaptations during the peripartal period is multifaceted and involves key tissues such as liver, adipose, and mammary. In order to understand such adaptation, we have reviewed several works performed in our and other labs. In addition, we have used a novel bioinformatics approach, Dynamic Impact Approach (DIA), in combination with partly previously published data to help interpret longitudinal biological adaptations of bovine liver, adipose, and mammary tissue to lactation using transcriptomics datasets. Use of DIA with transcriptomic data from those tissues during normal physiological adaptations and in animals fed different levels of energy prepartum allowed visualization and integration of most-impacted metabolic pathways around the time of parturition. The DIA is a suitable tool for applying the integrative systems biology approach. The ultimate goal is to visualize the complexity of the systems at study and uncover key molecular players involved in the tissue’s adaptations to physiological state or nutrition. PMID:22807626

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…

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.

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.

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

JSBML 1.0: providing a smorgasbord of options to encode systems biology models

DEFF Research Database (Denmark)

Rodriguez, Nicolas; Thomas, Alex; Watanabe, Leandro

2015-01-01

JSBML, the official pure Java programming library for the Systems Biology Markup Language (SBML) format, has evolved with the advent of different modeling formalisms in systems biology and their ability to be exchanged and represented via extensions of SBML. JSBML has matured into a major, active...... open-source project with contributions from a growing, international team of developers who not only maintain compatibility with SBML, but also drive steady improvements to the Java interface and promote ease-of-use with end users. Source code, binaries and documentation for JSBML can be freely...... obtained under the terms of the LGPL 2.1 from the website http://sbml.org/Software/JSBML. More information about JSBML can be found in the user guide at http://sbml.org/Software/JSBML/docs/. jsbml-development@googlegroups.com or andraeger@eng.ucsd.edu Supplementary data are available at Bioinformatics...

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

Unified data model for biological data

International Nuclear Information System (INIS)

Idrees, M.

2014-01-01

A data model empowers us to store, retrieve and manipulate data in a unified way. We consider the biological data consists of DNA (De-Oxyribonucleic Acid), RNA (Ribonucleic Acid) and protein structures. In our Bioinformatics Lab (Bioinformatics Lab, Alkhawarizmi Institute of Computer Science, University of Engineering and Technology, Lahore, Pakistan), we have already proposed two data models for DNA and protein structures individually. In this paper, we propose a unified data model by using the data models of TOS (Temporal Object Oriented System) after making some necessary modifications to this data model and our already proposed the two data models. This proposed unified data model can be used for the modeling and maintaining the biological data (i.e. DNA, RNA and protein structures), in a single unified way. (author)

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.

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.

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

Biopython: freely available Python tools for computational molecular biology and bioinformatics

DEFF Research Database (Denmark)

Cock, Peter J A; Antao, Tiago; Chang, Jeffrey T

2009-01-01

SUMMARY: The Biopython project is a mature open source international collaboration of volunteer developers, providing Python libraries for a wide range of bioinformatics problems. Biopython includes modules for reading and writing different sequence file formats and multiple sequence alignments......, dealing with 3D macro molecular structures, interacting with common tools such as BLAST, ClustalW and EMBOSS, accessing key online databases, as well as providing numerical methods for statistical learning. AVAILABILITY: Biopython is freely available, with documentation and source code at (www...

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...

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.

Ramping up to the Biology Workbench: A Multi-Stage Approach to Bioinformatics Education

Science.gov (United States)

Greene, Kathleen; Donovan, Sam

2005-01-01

In the process of designing and field-testing bioinformatics curriculum materials, we have adopted a three-stage, progressive model that emphasizes collaborative scientific inquiry. The elements of the model include: (1) context setting, (2) introduction to concepts, processes, and tools, and (3) development of competent use of technologically…

How the strengths of Lisp-family languages facilitate building complex and flexible bioinformatics applications.

Science.gov (United States)

Khomtchouk, Bohdan B; Weitz, Edmund; Karp, Peter D; Wahlestedt, Claes

2016-12-31

We present a rationale for expanding the presence of the Lisp family of programming languages in bioinformatics and computational biology research. Put simply, Lisp-family languages enable programmers to more quickly write programs that run faster than in other languages. Languages such as Common Lisp, Scheme and Clojure facilitate the creation of powerful and flexible software that is required for complex and rapidly evolving domains like biology. We will point out several important key features that distinguish languages of the Lisp family from other programming languages, and we will explain how these features can aid researchers in becoming more productive and creating better code. We will also show how these features make these languages ideal tools for artificial intelligence and machine learning applications. We will specifically stress the advantages of domain-specific languages (DSLs): languages that are specialized to a particular area, and thus not only facilitate easier research problem formulation, but also aid in the establishment of standards and best programming practices as applied to the specific research field at hand. DSLs are particularly easy to build in Common Lisp, the most comprehensive Lisp dialect, which is commonly referred to as the 'programmable programming language'. We are convinced that Lisp grants programmers unprecedented power to build increasingly sophisticated artificial intelligence systems that may ultimately transform machine learning and artificial intelligence research in bioinformatics and computational biology. © The Author 2016. Published by Oxford University Press.

A Linked Series of Laboratory Exercises in Molecular Biology Utilizing Bioinformatics and GFP

Science.gov (United States)

Medin, Carey L.; Nolin, Katie L.

2011-01-01

Molecular biologists commonly use bioinformatics to map and analyze DNA and protein sequences and to align different DNA and protein sequences for comparison. Additionally, biologists can create and view 3D models of protein structures to further understand intramolecular interactions. The primary goal of this 10-week laboratory was to introduce…

BioGPS descriptors for rational engineering of enzyme promiscuity and structure based bioinformatic analysis.

Directory of Open Access Journals (Sweden)

Valerio Ferrario

Full Text Available A new bioinformatic methodology was developed founded on the Unsupervised Pattern Cognition Analysis of GRID-based BioGPS descriptors (Global Positioning System in Biological Space. The procedure relies entirely on three-dimensional structure analysis of enzymes and does not stem from sequence or structure alignment. The BioGPS descriptors account for chemical, geometrical and physical-chemical features of enzymes and are able to describe comprehensively the active site of enzymes in terms of "pre-organized environment" able to stabilize the transition state of a given reaction. The efficiency of this new bioinformatic strategy was demonstrated by the consistent clustering of four different Ser hydrolases classes, which are characterized by the same active site organization but able to catalyze different reactions. The method was validated by considering, as a case study, the engineering of amidase activity into the scaffold of a lipase. The BioGPS tool predicted correctly the properties of lipase variants, as demonstrated by the projection of mutants inside the BioGPS "roadmap".

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...

High-throughput bioinformatics with the Cyrille2 pipeline system

Directory of Open Access Journals (Sweden)

de Groot Joost CW

2008-02-01

Full Text Available Abstract Background Modern omics research involves the application of high-throughput technologies that generate vast volumes of data. These data need to be pre-processed, analyzed and integrated with existing knowledge through the use of diverse sets of software tools, models and databases. The analyses are often interdependent and chained together to form complex workflows or pipelines. Given the volume of the data used and the multitude of computational resources available, specialized pipeline software is required to make high-throughput analysis of large-scale omics datasets feasible. Results We have developed a generic pipeline system called Cyrille2. The system is modular in design and consists of three functionally distinct parts: 1 a web based, graphical user interface (GUI that enables a pipeline operator to manage the system; 2 the Scheduler, which forms the functional core of the system and which tracks what data enters the system and determines what jobs must be scheduled for execution, and; 3 the Executor, which searches for scheduled jobs and executes these on a compute cluster. Conclusion The Cyrille2 system is an extensible, modular system, implementing the stated requirements. Cyrille2 enables easy creation and execution of high throughput, flexible bioinformatics pipelines.

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.

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.

7th Annual Systems Biology Symposium: Systems Biology and Engineering

Energy Technology Data Exchange (ETDEWEB)

Galitski, Timothy P.

2008-04-01

Systems biology recognizes the complex multi-scale organization of biological systems, from molecules to ecosystems. The International Symposium on Systems Biology has been hosted by the Institute for Systems Biology in Seattle, Washington, since 2002. The annual two-day event gathers the most influential researchers transforming biology into an integrative discipline investingating complex systems. Engineering and application of new technology is a central element of systems biology. Genome-scale, or very small-scale, biological questions drive the enigneering of new technologies, which enable new modes of experimentation and computational analysis, leading to new biological insights and questions. Concepts and analytical methods in engineering are now finding direct applications in biology. Therefore, the 2008 Symposium, funded in partnership with the Department of Energy, featured global leaders in "Systems Biology and Engineering."

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…

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.

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

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.

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-...

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).

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.

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

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

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…

An "in silico" Bioinformatics Laboratory Manual for Bioscience Departments: "Prediction of Glycosylation Sites in Phosphoethanolamine Transferases"

Science.gov (United States)

Alyuruk, Hakan; Cavas, Levent

2014-01-01

Genomics and proteomics projects have produced a huge amount of raw biological data including DNA and protein sequences. Although these data have been stored in data banks, their evaluation is strictly dependent on bioinformatics tools. These tools have been developed by multidisciplinary experts for fast and robust analysis of biological data.…

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

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.

Documenting the emergence of bio-ontologies: or, why researching bioinformatics requires HPSSB.

Science.gov (United States)

Leonelli, Sabina

2010-01-01

This paper reflects on the analytic challenges emerging from the study of bioinformatic tools recently created to store and disseminate biological data, such as databases, repositories, and bio-ontologies. I focus my discussion on the Gene Ontology, a term that defines three entities at once: a classification system facilitating the distribution and use of genomic data as evidence towards new insights; an expert community specialised in the curation of those data; and a scientific institution promoting the use of this tool among experimental biologists. These three dimensions of the Gene Ontology can be clearly distinguished analytically, but are tightly intertwined in practice. I suggest that this is true of all bioinformatic tools: they need to be understood simultaneously as epistemic, social, and institutional entities, since they shape the knowledge extracted from data and at the same time regulate the organisation, development, and communication of research. This viewpoint has one important implication for the methodologies used to study these tools; that is, the need to integrate historical, philosophical, and sociological approaches. I illustrate this claim through examples of misunderstandings that may result from a narrowly disciplinary study of the Gene Ontology, as I experienced them in my own research.

Parallel metaheuristics in computational biology: an asynchronous cooperative enhanced scatter search method

OpenAIRE

Penas, David R.; González, Patricia; Egea, José A.; Banga, Julio R.; Doallo, Ramón

2015-01-01

Metaheuristics are gaining increased attention as efficient solvers for hard global optimization problems arising in bioinformatics and computational systems biology. Scatter Search (SS) is one of the recent outstanding algorithms in that class. However, its application to very hard problems, like those considering parameter estimation in dynamic models of systems biology, still results in excessive computation times. In order to reduce the computational cost of the SS and improve its success...

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.

Role of remote sensing, geographical information system (GIS) and bioinformatics in kala-azar epidemiology.

Science.gov (United States)

Bhunia, Gouri Sankar; Dikhit, Manas Ranjan; Kesari, Shreekant; Sahoo, Ganesh Chandra; Das, Pradeep

2011-11-01

Visceral leishmaniasis or kala-azar is a potent parasitic infection causing death of thousands of people each year. Medicinal compounds currently available for the treatment of kala-azar have serious side effects and decreased efficacy owing to the emergence of resistant strains. The type of immune reaction is also to be considered in patients infected with Leishmania donovani (L. donovani). For complete eradication of this disease, a high level modern research is currently being applied both at the molecular level as well as at the field level. The computational approaches like remote sensing, geographical information system (GIS) and bioinformatics are the key resources for the detection and distribution of vectors, patterns, ecological and environmental factors and genomic and proteomic analysis. Novel approaches like GIS and bioinformatics have been more appropriately utilized in determining the cause of visearal leishmaniasis and in designing strategies for preventing the disease from spreading from one region to another.

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...

Spatial Modeling Tools for Cell Biology

National Research Council Canada - National Science Library

Przekwas, Andrzej; Friend, Tom; Teixeira, Rodrigo; Chen, Z. J; Wilkerson, Patrick

2006-01-01

.... Scientific potentials and military relevance of computational biology and bioinformatics have inspired DARPA/IPTO's visionary BioSPICE project to develop computational framework and modeling tools for cell biology...

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.

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.

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

Circadian systems biology: When time matters

Directory of Open Access Journals (Sweden)

Luise Fuhr

2015-01-01

In this manuscript we review the combination of experimental methodologies, bioinformatics and theoretical models that have been essential to explore this remarkable timing-system. Such an integrative and interdisciplinary approach may provide new strategies with regard to chronotherapeutic treatment and new insights concerning the restoration of the circadian timing in clock-associated diseases.

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.

The Technical and Biological Reproducibility of Matrix-Assisted Laser Desorption Ionization-Time of Flight Mass Spectrometry (MALDI-TOF MS) Based Typing: Employment of Bioinformatics in a Multicenter Study.

Science.gov (United States)

Oberle, Michael; Wohlwend, Nadia; Jonas, Daniel; Maurer, Florian P; Jost, Geraldine; Tschudin-Sutter, Sarah; Vranckx, Katleen; Egli, Adrian

2016-01-01

The technical, biological, and inter-center reproducibility of matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI TOF MS) typing data has not yet been explored. The aim of this study is to compare typing data from multiple centers employing bioinformatics using bacterial strains from two past outbreaks and non-related strains. Participants received twelve extended spectrum betalactamase-producing E. coli isolates and followed the same standard operating procedure (SOP) including a full-protein extraction protocol. All laboratories provided visually read spectra via flexAnalysis (Bruker, Germany). Raw data from each laboratory allowed calculating the technical and biological reproducibility between centers using BioNumerics (Applied Maths NV, Belgium). Technical and biological reproducibility ranged between 96.8-99.4% and 47.6-94.4%, respectively. The inter-center reproducibility showed a comparable clustering among identical isolates. Principal component analysis indicated a higher tendency to cluster within the same center. Therefore, we used a discriminant analysis, which completely separated the clusters. Next, we defined a reference center and performed a statistical analysis to identify specific peaks to identify the outbreak clusters. Finally, we used a classifier algorithm and a linear support vector machine on the determined peaks as classifier. A validation showed that within the set of the reference center, the identification of the cluster was 100% correct with a large contrast between the score with the correct cluster and the next best scoring cluster. Based on the sufficient technical and biological reproducibility of MALDI-TOF MS based spectra, detection of specific clusters is possible from spectra obtained from different centers. However, we believe that a shared SOP and a bioinformatics approach are required to make the analysis robust and reliable.

The Technical and Biological Reproducibility of Matrix-Assisted Laser Desorption Ionization-Time of Flight Mass Spectrometry (MALDI-TOF MS Based Typing: Employment of Bioinformatics in a Multicenter Study.

Directory of Open Access Journals (Sweden)

Michael Oberle

Full Text Available The technical, biological, and inter-center reproducibility of matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI TOF MS typing data has not yet been explored. The aim of this study is to compare typing data from multiple centers employing bioinformatics using bacterial strains from two past outbreaks and non-related strains.Participants received twelve extended spectrum betalactamase-producing E. coli isolates and followed the same standard operating procedure (SOP including a full-protein extraction protocol. All laboratories provided visually read spectra via flexAnalysis (Bruker, Germany. Raw data from each laboratory allowed calculating the technical and biological reproducibility between centers using BioNumerics (Applied Maths NV, Belgium.Technical and biological reproducibility ranged between 96.8-99.4% and 47.6-94.4%, respectively. The inter-center reproducibility showed a comparable clustering among identical isolates. Principal component analysis indicated a higher tendency to cluster within the same center. Therefore, we used a discriminant analysis, which completely separated the clusters. Next, we defined a reference center and performed a statistical analysis to identify specific peaks to identify the outbreak clusters. Finally, we used a classifier algorithm and a linear support vector machine on the determined peaks as classifier. A validation showed that within the set of the reference center, the identification of the cluster was 100% correct with a large contrast between the score with the correct cluster and the next best scoring cluster.Based on the sufficient technical and biological reproducibility of MALDI-TOF MS based spectra, detection of specific clusters is possible from spectra obtained from different centers. However, we believe that a shared SOP and a bioinformatics approach are required to make the analysis robust and reliable.

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.

Naturally Speaking: A Systems Biology Tool With Natural Language Interfaces

National Research Council Canada - National Science Library

Antoniotti, Marco; Lau, Ian T; Mishra, Bud

2004-01-01

.... Thus, this bioinformatics system improves the quality of the interaction that a biologist can have with a system built on rigorous mathematical modeling, but without being aware of the underlying...

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

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

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

Education, collaboration, and innovation: intelligent biology and medicine in the era of big data.

Science.gov (United States)

Ruan, Jianhua; Jin, Victor; Huang, Yufei; Xu, Hua; Edwards, Jeremy S; Chen, Yidong; Zhao, Zhongming

2015-01-01

Here we present a summary of the 2014 International Conference on Intelligent Biology and Medicine (ICIBM 2014) and the editorial report of the supplement to BMC Genomics and BMC Systems Biology that includes 20 research articles selected from ICIBM 2014. The conference was held on December 4-6, 2014 at San Antonio, Texas, USA, and included six scientific sessions, four tutorials, four keynote presentations, nine highlight talks, and a poster session that covered cutting-edge research in bioinformatics, systems biology, and computational medicine.

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

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.

Integration of cardiac proteome biology and medicine by a specialized knowledgebase.

Science.gov (United States)

Zong, Nobel C; Li, Haomin; Li, Hua; Lam, Maggie P Y; Jimenez, Rafael C; Kim, Christina S; Deng, Ning; Kim, Allen K; Choi, Jeong Ho; Zelaya, Ivette; Liem, David; Meyer, David; Odeberg, Jacob; Fang, Caiyun; Lu, Hao-Jie; Xu, Tao; Weiss, James; Duan, Huilong; Uhlen, Mathias; Yates, John R; Apweiler, Rolf; Ge, Junbo; Hermjakob, Henning; Ping, Peipei

2013-10-12

Omics sciences enable a systems-level perspective in characterizing cardiovascular biology. Integration of diverse proteomics data via a computational strategy will catalyze the assembly of contextualized knowledge, foster discoveries through multidisciplinary investigations, and minimize unnecessary redundancy in research efforts. The goal of this project is to develop a consolidated cardiac proteome knowledgebase with novel bioinformatics pipeline and Web portals, thereby serving as a new resource to advance cardiovascular biology and medicine. We created Cardiac Organellar Protein Atlas Knowledgebase (COPaKB; www.HeartProteome.org), a centralized platform of high-quality cardiac proteomic data, bioinformatics tools, and relevant cardiovascular phenotypes. Currently, COPaKB features 8 organellar modules, comprising 4203 LC-MS/MS experiments from human, mouse, drosophila, and Caenorhabditis elegans, as well as expression images of 10,924 proteins in human myocardium. In addition, the Java-coded bioinformatics tools provided by COPaKB enable cardiovascular investigators in all disciplines to retrieve and analyze pertinent organellar protein properties of interest. COPaKB provides an innovative and interactive resource that connects research interests with the new biological discoveries in protein sciences. With an array of intuitive tools in this unified Web server, nonproteomics investigators can conveniently collaborate with proteomics specialists to dissect the molecular signatures of cardiovascular phenotypes.

An Integrated Bioinformatics and Computational Biology Approach Identifies New BH3-Only Protein Candidates.

Science.gov (United States)

Hawley, Robert G; Chen, Yuzhong; Riz, Irene; Zeng, Chen

2012-05-04

In this study, we utilized an integrated bioinformatics and computational biology approach in search of new BH3-only proteins belonging to the BCL2 family of apoptotic regulators. The BH3 (BCL2 homology 3) domain mediates specific binding interactions among various BCL2 family members. It is composed of an amphipathic α-helical region of approximately 13 residues that has only a few amino acids that are highly conserved across all members. Using a generalized motif, we performed a genome-wide search for novel BH3-containing proteins in the NCBI Consensus Coding Sequence (CCDS) database. In addition to known pro-apoptotic BH3-only proteins, 197 proteins were recovered that satisfied the search criteria. These were categorized according to α-helical content and predictive binding to BCL-xL (encoded by BCL2L1) and MCL-1, two representative anti-apoptotic BCL2 family members, using position-specific scoring matrix models. Notably, the list is enriched for proteins associated with autophagy as well as a broad spectrum of cellular stress responses such as endoplasmic reticulum stress, oxidative stress, antiviral defense, and the DNA damage response. Several potential novel BH3-containing proteins are highlighted. In particular, the analysis strongly suggests that the apoptosis inhibitor and DNA damage response regulator, AVEN, which was originally isolated as a BCL-xL-interacting protein, is a functional BH3-only protein representing a distinct subclass of BCL2 family members.

Bioinformatics Database Tools in Analysis of Genetics of Neurodevelopmental Disorders

Directory of Open Access Journals (Sweden)

Dibyashree Mallik

2017-10-01

Full Text Available Bioinformatics tools are recently used in various sectors of biology. Many questions regarding Neurodevelopmental disorder which arises as a major health issue recently can be solved by using various bioinformatics databases. Schizophrenia is such a mental disorder which is now arises as a major threat in young age people because it is mostly seen in case of people during their late adolescence or early adulthood period. Databases like DISGENET, GWAS, PHARMGKB, and DRUGBANK have huge repository of genes associated with schizophrenia. We found a lot of genes are being associated with schizophrenia, but approximately 200 genes are found to be present in any of these databases. After further screening out process 20 genes are found to be highly associated with each other and are also a common genes in many other diseases also. It is also found that they all are serves as a common targeting gene in many antipsychotic drugs. After analysis of various biological properties, molecular function it is found that these 20 genes are mostly involved in biological regulation process and are having receptor activity. They are belonging mainly to receptor protein class. Among these 20 genes CYP2C9, CYP3A4, DRD2, HTR1A, HTR2A are shown to be a main targeting genes of most of the antipsychotic drugs and are associated with  more than 40% diseases. The basic findings of the present study enumerated that a suitable combined drug can be design by targeting these genes which can be used for the better treatment of schizophrenia.

Design and bioinformatics analysis of novel biomimetic peptides as nanocarriers for gene transfer

Directory of Open Access Journals (Sweden)

Asia Majidi

2015-01-01

Full Text Available Objective(s: The introduction of nucleic acids into cells for therapeutic objectives is significantly hindered by the size and charge of these molecules and therefore requires efficient vectors that assist cellular uptake. For several years great efforts have been devoted to the study of development of recombinant vectors based on biological domains with potential applications in gene therapy. Such vectors have been synthesized in genetically engineered approach, resulting in biomacromolecules with new properties that are not present in nature. Materials and Methods: In this study, we have designed new peptides using homology modeling with the purpose of overcoming the cell barriers for successful gene delivery through Bioinformatics tools. Three different carriers were designed and one of those with better score through Bioinformatics tools was cloned, expressed and its affinity for pDNA was monitored. Results: The resultszz demonstrated that the vector can effectively condense pDNAinto nanoparticles with the average sizes about 100 nm. Conclusion: We hope these peptides can overcome the biological barriers associated with gene transfer, and mediate efficient gene delivery.

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.

The Virtual Institute for Integrative Biology (VIIB)

International Nuclear Information System (INIS)

Rivera, G.; Gonzalez-Nieto, F.; Perez-Acle, T.; Isea, R.; Holmes, D. S.

2007-01-01

The Virtual Institute for Integrative Biology (VII B) is a Latin American initiative for achieving global collaborative e-Science in the areas of bioinformatics, genome biology, systems biology, Metagenomic, medical applications and nanobiotechnolgy. The scientific agenda of VIIB includes: construction of databases for comparative genomic, the AlterORF database for alternate open reading frames discovery in genomes, bioinformatics services and protein simulations for biotechnological and medical applications. Human resource development has been promoted through co-sponsored students and shared teaching and seminars via video conferencing. E-Science challenges include: inter operability and connectivity concerns, high performance computing limitations, and the development of customized computational frameworks and flexible work flows to efficiently exploit shared resources without causing impediments to the user. Outreach programs include training workshops and classes for high school teachers and students and the new Adopt-a-Gene initiative. The VIIB has proved an effective way for small teams to transcend the critical mass problem, to overcome geographic limitations, to harness the power of large scale, collaborative science and improve the visibility of Latin American science It may provide a useful paradigm for developing further e-Science initiatives in Latin America and other emerging regions. (Author)

Bioinformatics strategies in life sciences: from data processing and data warehousing to biological knowledge extraction.

Science.gov (United States)

Thiele, Herbert; Glandorf, Jörg; Hufnagel, Peter

2010-05-27

With the large variety of Proteomics workflows, as well as the large variety of instruments and data-analysis software available, researchers today face major challenges validating and comparing their Proteomics data. Here we present a new generation of the ProteinScape bioinformatics platform, now enabling researchers to manage Proteomics data from the generation and data warehousing to a central data repository with a strong focus on the improved accuracy, reproducibility and comparability demanded by many researchers in the field. It addresses scientists; current needs in proteomics identification, quantification and validation. But producing large protein lists is not the end point in Proteomics, where one ultimately aims to answer specific questions about the biological condition or disease model of the analyzed sample. In this context, a new tool has been developed at the Spanish Centro Nacional de Biotecnologia Proteomics Facility termed PIKE (Protein information and Knowledge Extractor) that allows researchers to control, filter and access specific information from genomics and proteomic databases, to understand the role and relationships of the proteins identified in the experiments. Additionally, an EU funded project, ProDac, has coordinated systematic data collection in public standards-compliant repositories like PRIDE. This will cover all aspects from generating MS data in the laboratory, assembling the whole annotation information and storing it together with identifications in a standardised format.

Bioinformatics Strategies in Life Sciences: From Data Processing and Data Warehousing to Biological Knowledge Extraction

Directory of Open Access Journals (Sweden)

Thiele Herbert

2010-03-01

Full Text Available With the large variety of Proteomics workflows, as well as the large variety of instruments and data-analysis software available, researchers today face major challenges validating and comparing their Proteomics data. Here we present a new generation of the ProteinScapeTM bioinformatics platform, now enabling researchers to manage Proteomics data from the generation and data warehousing to a central data repository with a strong focus on the improved accuracy, reproducibility and comparability demanded by many researchers in the field. It addresses scientists` current needs in proteomics identification, quantification and validation. But producing large protein lists is not the end point in Proteomics, where one ultimately aims to answer specific questions about the biological condition or disease model of the analyzed sample. In this context, a new tool has been developed at the Spanish Centro Nacional de Biotecnologia Proteomics Facility termed PIKE (Protein information and Knowledge Extractor that allows researchers to control, filter and access specific information from genomics and proteomic databases, to understand the role and relationships of the proteins identified in the experiments. Additionally, an EU funded project, ProDac, has coordinated systematic data collection in public standards-compliant repositories like PRIDE. This will cover all aspects from generating MS data in the laboratory, assembling the whole annotation information and storing it together with identifications in a standardised format.

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.

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).

Applications of Structural Biology and Bioinformatics in the Investigation of Oxidative Stress-Related Processes

NARCIS (Netherlands)

Bersch, Beate; Groves, Matthew; Johann, Klare; Torda, Andrew; Ortiz, Dario; Laher, I.

2014-01-01

Reactive oxygen species (ROS)-mediated dysfunction of certain biological processes is implicated in different diseases in humans, including cardiovascular, cancer, or neurodegenerative disorders. Not only human cells and tissues are affected by ROS but also all other biological systems, including

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...

A semantic web approach applied to integrative bioinformatics experimentation: a biological use case with genomics data.

NARCIS (Netherlands)

Post, L.J.G.; Roos, M.; Marshall, M.S.; van Driel, R.; Breit, T.M.

2007-01-01

The numerous public data resources make integrative bioinformatics experimentation increasingly important in life sciences research. However, it is severely hampered by the way the data and information are made available. The semantic web approach enhances data exchange and integration by providing

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...

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.

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....

Feedback dynamics and cell function: Why systems biology is called Systems Biology.

Science.gov (United States)

Wolkenhauer, Olaf; Mesarovic, Mihajlo

2005-05-01

A new paradigm, like Systems Biology, should challenge the way research has been conducted previously. This Opinion article aims to present Systems Biology, not as the application of engineering principles to biology but as a merger of systems- and control theory with molecular- and cell biology. In our view, the central dogma of Systems Biology is that it is system dynamics that gives rise to the functioning and function of cells. The concepts of feedback regulation and control of pathways and the coordination of cell function are emphasized as an important area of Systems Biology research. The hurdles and risks for this area are discussed from the perspective of dynamic pathway modelling. Most of all, the aim of this article is to promote mathematical modelling and simulation as a part of molecular- and cell biology. Systems Biology is a success if it is widely accepted that there is nothing more practical than a good theory.

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...

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

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.

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.

ChlamyCyc: an integrative systems biology database and web-portal for Chlamydomonas reinhardtii.

Science.gov (United States)

May, Patrick; Christian, Jan-Ole; Kempa, Stefan; Walther, Dirk

2009-05-04

The unicellular green alga Chlamydomonas reinhardtii is an important eukaryotic model organism for the study of photosynthesis and plant growth. In the era of modern high-throughput technologies there is an imperative need to integrate large-scale data sets from high-throughput experimental techniques using computational methods and database resources to provide comprehensive information about the molecular and cellular organization of a single organism. In the framework of the German Systems Biology initiative GoFORSYS, a pathway database and web-portal for Chlamydomonas (ChlamyCyc) was established, which currently features about 250 metabolic pathways with associated genes, enzymes, and compound information. ChlamyCyc was assembled using an integrative approach combining the recently published genome sequence, bioinformatics methods, and experimental data from metabolomics and proteomics experiments. We analyzed and integrated a combination of primary and secondary database resources, such as existing genome annotations from JGI, EST collections, orthology information, and MapMan classification. ChlamyCyc provides a curated and integrated systems biology repository that will enable and assist in systematic studies of fundamental cellular processes in Chlamydomonas. The ChlamyCyc database and web-portal is freely available under http://chlamycyc.mpimp-golm.mpg.de.

Bioinformatics Mining and Modeling Methods for the Identification of Disease Mechanisms in Neurodegenerative Disorders

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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

Single-Cell Transcriptomics Bioinformatics and Computational Challenges

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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.

Mapping biological systems to network systems

CERN Document Server

Rathore, Heena

2016-01-01

The book presents the challenges inherent in the paradigm shift of network systems from static to highly dynamic distributed systems – it proposes solutions that the symbiotic nature of biological systems can provide into altering networking systems to adapt to these changes. The author discuss how biological systems – which have the inherent capabilities of evolving, self-organizing, self-repairing and flourishing with time – are inspiring researchers to take opportunities from the biology domain and map them with the problems faced in network domain. The book revolves around the central idea of bio-inspired systems -- it begins by exploring why biology and computer network research are such a natural match. This is followed by presenting a broad overview of biologically inspired research in network systems -- it is classified by the biological field that inspired each topic and by the area of networking in which that topic lies. Each case elucidates how biological concepts have been most successfully ...

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

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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.

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.

A P2P Framework for Developing Bioinformatics Applications in Dynamic Cloud Environments

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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.

Intelligent biology and medicine in 2015: advancing interdisciplinary education, collaboration, and data science.

Science.gov (United States)

Huang, Kun; Liu, Yunlong; Huang, Yufei; Li, Lang; Cooper, Lee; Ruan, Jianhua; Zhao, Zhongming

2016-08-22

We summarize the 2015 International Conference on Intelligent Biology and Medicine (ICIBM 2015) and the editorial report of the supplement to BMC Genomics. The supplement includes 20 research articles selected from the manuscripts submitted to ICIBM 2015. The conference was held on November 13-15, 2015 at Indianapolis, Indiana, USA. It included eight scientific sessions, three tutorials, four keynote presentations, three highlight talks, and a poster session that covered current research in bioinformatics, systems biology, computational biology, biotechnologies, and computational medicine.

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.

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.

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

Computational Systems Chemical Biology

OpenAIRE

Oprea, Tudor I.; May, Elebeoba E.; Leitão, Andrei; Tropsha, Alexander

2011-01-01

There is a critical need for improving the level of chemistry awareness in systems biology. The data and information related to modulation of genes and proteins by small molecules continue to accumulate at the same time as simulation tools in systems biology and whole body physiologically-based pharmacokinetics (PBPK) continue to evolve. We called this emerging area at the interface between chemical biology and systems biology systems chemical biology, SCB (Oprea et al., 2007).

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…

DATABASES DEVELOPED IN INDIA FOR BIOLOGICAL SCIENCES

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Gitanjali Yadav

2017-09-01

Full Text Available The complexity of biological systems requires use of a variety of experimental methods with ever increasing sophistication to probe various cellular processes at molecular and atomic resolution. The availability of technologies for determining nucleic acid sequences of genes and atomic resolution structures of biomolecules prompted development of major biological databases like GenBank and PDB almost four decades ago. India was one of the few countries to realize early, the utility of such databases for progress in modern biology/biotechnology. Department of Biotechnology (DBT, India established Biotechnology Information System (BTIS network in late eighties. Starting with the genome sequencing revolution at the turn of the century, application of high-throughput sequencing technologies in biology and medicine for analysis of genomes, transcriptomes, epigenomes and microbiomes have generated massive volumes of sequence data. BTIS network has not only provided state of the art computational infrastructure to research institutes and universities for utilizing various biological databases developed abroad in their research, it has also actively promoted research and development (R&D projects in Bioinformatics to develop a variety of biological databases in diverse areas. It is encouraging to note that, a large number of biological databases or data driven software tools developed in India, have been published in leading peer reviewed international journals like Nucleic Acids Research, Bioinformatics, Database, BMC, PLoS and NPG series publication. Some of these databases are not only unique, they are also highly accessed as reflected in number of citations. Apart from databases developed by individual research groups, BTIS has initiated consortium projects to develop major India centric databases on Mycobacterium tuberculosis, Rice and Mango, which can potentially have practical applications in health and agriculture. Many of these biological

Bioinformatics tools and database resources for systems genetics analysis in mice-a short review and an evaluation of future needs

NARCIS (Netherlands)

Durrant, Caroline; Swertz, Morris A.; Alberts, Rudi; Arends, Danny; Moeller, Steffen; Mott, Richard; Prins, Pjotr; van der Velde, K. Joeri; Jansen, Ritsert C.; Schughart, Klaus

During a meeting of the SYSGENET working group 'Bioinformatics', currently available software tools and databases for systems genetics in mice were reviewed and the needs for future developments discussed. The group evaluated interoperability and performed initial feasibility studies. To aid future

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.

Bioinformatic identification and characterization of human endothelial cell-restricted genes

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Keskin Derin B

2010-05-01

Full Text Available Abstract Background In this study, we used a systematic bioinformatics analysis approach to elucidate genes that exhibit an endothelial cell (EC restricted expression pattern, and began to define their regulation, tissue distribution, and potential biological role. Results Using a high throughput microarray platform, a primary set of 1,191 transcripts that are enriched in different primary ECs compared to non-ECs was identified (LCB >3, FDR Conclusion The study provides an initial catalogue of EC-restricted genes most of which are ubiquitously expressed in different endothelial cells.

From systems biology to systems biomedicine.

Science.gov (United States)

Antony, Paul M A; Balling, Rudi; Vlassis, Nikos

2012-08-01

Systems Biology is about combining theory, technology, and targeted experiments in a way that drives not only data accumulation but knowledge as well. The challenge in Systems Biomedicine is to furthermore translate mechanistic insights in biological systems to clinical application, with the central aim of improving patients' quality of life. The challenge is to find theoretically well-chosen models for the contextually correct and intelligible representation of multi-scale biological systems. In this review, we discuss the current state of Systems Biology, highlight the emergence of Systems Biomedicine, and highlight some of the topics and views that we think are important for the efficient application of Systems Theory in Biomedicine. Copyright © 2011 Elsevier Ltd. All rights reserved.

Systems Biology and Health Systems Complexity in;

NARCIS (Netherlands)

Donald Combs, C.; Barham, S.R.; Sloot, P.M.A.

2016-01-01

Systems biology addresses interactions in biological systems at different scales of biological organization, from the molecular to the cellular, organ, organism, societal, and ecosystem levels. This chapter expands on the concept of systems biology, explores its implications for individual patients

Systems Biology-an interdisciplinary approach.

Science.gov (United States)

Friboulet, Alain; Thomas, Daniel

2005-06-15

System-level approaches in biology are not new but foundations of "Systems Biology" are achieved only now at the beginning of the 21st century [Kitano, H., 2001. Foundations of Systems Biology. MIT Press, Cambridge, MA]. The renewed interest for a system-level approach is linked to the progress in collecting experimental data and to the limits of the "reductionist" approach. System-level understanding of native biological and pathological systems is needed to provide potential therapeutic targets. Examples of interdisciplinary approach in Systems Biology are described in U.S., Japan and Europe. Robustness in biology, metabolic engineering and idiotypic networks are discussed in the framework of Systems Biology.

ChlamyCyc: an integrative systems biology database and web-portal for Chlamydomonas reinhardtii

Directory of Open Access Journals (Sweden)

Kempa Stefan

2009-05-01

Full Text Available Abstract Background The unicellular green alga Chlamydomonas reinhardtii is an important eukaryotic model organism for the study of photosynthesis and plant growth. In the era of modern high-throughput technologies there is an imperative need to integrate large-scale data sets from high-throughput experimental techniques using computational methods and database resources to provide comprehensive information about the molecular and cellular organization of a single organism. Results In the framework of the German Systems Biology initiative GoFORSYS, a pathway database and web-portal for Chlamydomonas (ChlamyCyc was established, which currently features about 250 metabolic pathways with associated genes, enzymes, and compound information. ChlamyCyc was assembled using an integrative approach combining the recently published genome sequence, bioinformatics methods, and experimental data from metabolomics and proteomics experiments. We analyzed and integrated a combination of primary and secondary database resources, such as existing genome annotations from JGI, EST collections, orthology information, and MapMan classification. Conclusion ChlamyCyc provides a curated and integrated systems biology repository that will enable and assist in systematic studies of fundamental cellular processes in Chlamydomonas. The ChlamyCyc database and web-portal is freely available under http://chlamycyc.mpimp-golm.mpg.de.

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...

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.

Computational biology of genome expression and regulation--a review of microarray bioinformatics.

Science.gov (United States)

Wang, Junbai

2008-01-01

Microarray technology is being used widely in various biomedical research areas; the corresponding microarray data analysis is an essential step toward the best utilizing of array technologies. Here we review two components of the microarray data analysis: a low level of microarray data analysis that emphasizes the designing, the quality control, and the preprocessing of microarray experiments, then a high level of microarray data analysis that focuses on the domain-specific microarray applications such as tumor classification, biomarker prediction, analyzing array CGH experiments, and reverse engineering of gene expression networks. Additionally, we will review the recent development of building a predictive model in genome expression and regulation studies. This review may help biologists grasp a basic knowledge of microarray bioinformatics as well as its potential impact on the future evolvement of biomedical research fields.

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...

Deciphering psoriasis. A bioinformatic approach.

Science.gov (United States)

Melero, Juan L; Andrades, Sergi; Arola, Lluís; Romeu, Antoni

2018-02-01

Psoriasis is an immune-mediated, inflammatory and hyperproliferative disease of the skin and joints. The cause of psoriasis is still unknown. The fundamental feature of the disease is the hyperproliferation of keratinocytes and the recruitment of cells from the immune system in the region of the affected skin, which leads to deregulation of many well-known gene expressions. Based on data mining and bioinformatic scripting, here we show a new dimension of the effect of psoriasis at the genomic level. Using our own pipeline of scripts in Perl and MySql and based on the freely available NCBI Gene Expression Omnibus (GEO) database: DataSet Record GDS4602 (Series GSE13355), we explore the extent of the effect of psoriasis on gene expression in the affected tissue. We give greater insight into the effects of psoriasis on the up-regulation of some genes in the cell cycle (CCNB1, CCNA2, CCNE2, CDK1) or the dynamin system (GBPs, MXs, MFN1), as well as the down-regulation of typical antioxidant genes (catalase, CAT; superoxide dismutases, SOD1-3; and glutathione reductase, GSR). We also provide a complete list of the human genes and how they respond in a state of psoriasis. Our results show that psoriasis affects all chromosomes and many biological functions. If we further consider the stable and mitotically inheritable character of the psoriasis phenotype, and the influence of environmental factors, then it seems that psoriasis has an epigenetic origin. This fit well with the strong hereditary character of the disease as well as its complex genetic background. Copyright © 2017 Japanese Society for Investigative Dermatology. Published by Elsevier B.V. All rights reserved.

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.

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…

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.

The effect of network biology on drug toxicology

DEFF Research Database (Denmark)

Gautier, Laurent; Taboureau, Olivier; Audouze, Karine Marie Laure

2013-01-01

Introduction: The high failure rate of drug candidates due to toxicity, during clinical trials, is a critical issue in drug discovery. Network biology has become a promising approach, in this regard, using the increasingly large amount of biological and chemical data available and combining...... it with bioinformatics. With this approach, the assessment of chemical safety can be done across multiple scales of complexity from molecular to cellular and system levels in human health. Network biology can be used at several levels of complexity. Areas covered: This review describes the strengths and limitations...... of network biology. The authors specifically assess this approach across different biological scales when it is applied to toxicity. Expert opinion: There has been much progress made with the amount of data that is generated by various omics technologies. With this large amount of useful data, network...

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.

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

The role of genomics in the identification, prediction, and prevention of biological threats.

Directory of Open Access Journals (Sweden)

W Florian Fricke

2009-10-01

Full Text Available In all likelihood, it is only a matter of time before our public health system will face a major biological threat, whether intentionally dispersed or originating from a known or newly emerging infectious disease. It is necessary not only to increase our reactive "biodefense," but also to be proactive and increase our preparedness. To achieve this goal, it is essential that the scientific and public health communities fully embrace the genomic revolution, and that novel bioinformatic and computing tools necessary to make great strides in our understanding of these novel and emerging threats be developed. Genomics has graduated from a specialized field of science to a research tool that soon will be routine in research laboratories and clinical settings. Because the technology is becoming more affordable, genomics can and should be used proactively to build our preparedness and responsiveness to biological threats. All pieces, including major continued funding, advances in next-generation sequencing technologies, bioinformatics infrastructures, and open access to data and metadata, are being set in place for genomics to play a central role in our public health system.

Computer Simulation of Embryonic Systems: What can a virtual embryo teach us about developmental toxicity? (LA Conference on Computational Biology & Bioinformatics)

Science.gov (United States)

This presentation will cover work at EPA under the CSS program for: (1) Virtual Tissue Models built from the known biology of an embryological system and structured to recapitulate key cell signals and responses; (2) running the models with real (in vitro) or synthetic (in silico...

Lecture 10: The European Bioinformatics Institute - "Big data" for biomedical sciences

CERN Multimedia

CERN. Geneva; Dana, Jose

2013-01-01

Part 1: Big data for biomedical sciences (Tom Hancocks) Ten years ago witnessed the completion of the first international 'Big Biology' project that sequenced the human genome. In the years since biological sciences, have seen a vast growth in data. In the coming years advances will come from integration of experimental approaches and the translation into applied technologies is the hospital, clinic and even at home. This talk will examine the development of infrastructure, physical and virtual, that will allow millions of life scientists across Europe better access to biological data Tom studied Human Genetics at the University of Leeds and McMaster University, before completing an MSc in Analytical Genomics at the University of Birmingham. He has worked for the UK National Health Service in diagnostic genetics and in training healthcare scientists and clinicians in bioinformatics. Tom joined the EBI in 2012 and is responsible for the scientific development and delivery of training for the BioMedBridges pr...

Biological conversion system

Science.gov (United States)

Scott, C.D.

A system for bioconversion of organic material comprises a primary bioreactor column wherein a biological active agent (zymomonas mobilis) converts the organic material (sugar) to a product (alcohol), a rejuvenator column wherein the biological activity of said biological active agent is enhanced, and means for circulating said biological active agent between said primary bioreactor column and said rejuvenator column.

Systems Genetics and Transcriptomics of Feed Efficiency in Dairy Cattle

DEFF Research Database (Denmark)

Salleh, Suraya Binti Mohamad; Hoglund, J.; Løvendahl, P.

Feed is the largest variable cost in milk production industries, thus improving feed efficiency will give better use of resources. This project works closely on definitions of feed efficiency in dairy cattle and uses advanced integrated genomics, bioinformatics and systems biology methods linking......-hydroxybutyrates, Triacylglyceride and urea. Feed efficiency, namely Residual Feed Intake and Kleiber Ratio based on daily feed or dry matter intake, body weight and milk production records also will be calculated. The bovine RNAseq gene expression data will be analyzed using statistical-bioinformatics and systems biology...... partitioning and deliver predictive biomarkers for feed efficiency in cattle. This study will also contribute to systems genomic prediction or selection models including the information on potential causal genes / SNPs or their functional modules....

The DBCLS BioHackathon: standardization and interoperability for bioinformatics web services and workflows. The DBCLS BioHackathon Consortium*

Directory of Open Access Journals (Sweden)

Katayama Toshiaki

2010-08-01

Full Text Available Abstract Web services have become a key technology for bioinformatics, since life science databases are globally decentralized and the exponential increase in the amount of available data demands for efficient systems without the need to transfer entire databases for every step of an analysis. However, various incompatibilities among database resources and analysis services make it difficult to connect and integrate these into interoperable workflows. To resolve this situation, we invited domain specialists from web service providers, client software developers, Open Bio* projects, the BioMoby project and researchers of emerging areas where a standard exchange data format is not well established, for an intensive collaboration entitled the BioHackathon 2008. The meeting was hosted by the Database Center for Life Science (DBCLS and Computational Biology Research Center (CBRC and was held in Tokyo from February 11th to 15th, 2008. In this report we highlight the work accomplished and the common issues arisen from this event, including the standardization of data exchange formats and services in the emerging fields of glycoinformatics, biological interaction networks, text mining, and phyloinformatics. In addition, common shared object development based on BioSQL, as well as technical challenges in large data management, asynchronous services, and security are discussed. Consequently, we improved interoperability of web services in several fields, however, further cooperation among major database centers and continued collaborative efforts between service providers and software developers are still necessary for an effective advance in bioinformatics web service technologies.

DOE EPSCoR Initiative in Structural and computational Biology/Bioinformatics

Energy Technology Data Exchange (ETDEWEB)

Wallace, Susan S.

2008-02-21

The overall goal of the DOE EPSCoR Initiative in Structural and Computational Biology was to enhance the competiveness of Vermont research in these scientific areas. To develop self-sustaining infrastructure, we increased the critical mass of faculty, developed shared resources that made junior researchers more competitive for federal research grants, implemented programs to train graduate and undergraduate students who participated in these research areas and provided seed money for research projects. During the time period funded by this DOE initiative: (1) four new faculty were recruited to the University of Vermont using DOE resources, three in Computational Biology and one in Structural Biology; (2) technical support was provided for the Computational and Structural Biology facilities; (3) twenty-two graduate students were directly funded by fellowships; (4) fifteen undergraduate students were supported during the summer; and (5) twenty-eight pilot projects were supported. Taken together these dollars resulted in a plethora of published papers, many in high profile journals in the fields and directly impacted competitive extramural funding based on structural or computational biology resulting in 49 million dollars awarded in grants (Appendix I), a 600% return on investment by DOE, the State and University.

Development trend of radiation biology research-systems radiation biology

International Nuclear Information System (INIS)

Min Rui

2010-01-01

Radiation biology research has past 80 years. We have known much more about fundamentals, processes and results of biology effects induced by radiation and various factors that influence biology effects wide and deep, however many old and new scientific problems occurring in the field of radiation biology research remain to be illustrated. To explore and figure these scientific problems need systemic concept, methods and multi dimension view on the base of considerations of complexity of biology system, diversity of biology response, temporal and spatial process of biological effects during occurrence, and complex feed back network of biological regulations. (authors)

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.

Differential Expression of Proteins Associated with the Hair Follicle Cycle - Proteomics and Bioinformatics Analyses.

Directory of Open Access Journals (Sweden)

Lei Wang

Full Text Available Hair follicle cycling can be divided into the following three stages: anagen, catagen, and telogen. The molecular signals that orchestrate the follicular transition between phases are still unknown. To better understand the detailed protein networks controlling this process, proteomics and bioinformatics analyses were performed to construct comparative protein profiles of mouse skin at specific time points (0, 8, and 20 days. Ninety-five differentially expressed protein spots were identified by MALDI-TOF/TOF as 44 proteins, which were found to change during hair follicle cycle transition. Proteomics analysis revealed that these changes in protein expression are involved in Ca2+-regulated biological processes, migration, and regulation of signal transduction, among other processes. Subsequently, three proteins were selected to validate the reliability of expression patterns using western blotting. Cluster analysis revealed three expression patterns, and each pattern correlated with specific cell processes that occur during the hair cycle. Furthermore, bioinformatics analysis indicated that the differentially expressed proteins impacted multiple biological networks, after which detailed functional analyses were performed. Taken together, the above data may provide insight into the three stages of mouse hair follicle morphogenesis and provide a solid basis for potential therapeutic molecular targets for this hair disease.

International Journal of Biological and Chemical Sciences

African Journals Online (AJOL)

AFRICAN JOURNALS ONLINE (AJOL) · Journals · Advanced Search · USING AJOL ... toxicology, biotechnology, biostatistics, bioinformatics, environmental biology, ... IJBCS publishes original research papers, critical up-to-date and concise ...

System Genetics and Transcriptomic of Feed Efficiency in Nordic Dairy Cattle

DEFF Research Database (Denmark)

Salleh, Suraya Binti Mohamad; Höglund, Johanna; Løvendahl, Peter

Feed is the largest variable cost in milk production industries, thus improving feed efficiency will give better use of resources. This project works closely on definitions of feed efficiency in dairy cattle and uses advanced integrated genomics, bioinformatics and systems biology methods linking......-bioinformatics and systems biology approaches to identify a list of differentially expressed (DE) genes, co-expressed (CE) genes, differentially wired networks, co-expression, transcriptional regulatory networks and hub genes/biomarkers for feed efficiency. This study will provide molecular mechanisms of metabolic processes......, energy balance, nutrient partitioning and deliver predictive biomarkers for feed efficiency in cattle. This study will also contribute to systems genomic prediction or selection models including the information on potential causal genes / SNPs or their functional modules....

Integr8: enhanced inter-operability of European molecular biology databases.

Science.gov (United States)

Kersey, P J; Morris, L; Hermjakob, H; Apweiler, R

2003-01-01

The increasing production of molecular biology data in the post-genomic era, and the proliferation of databases that store it, require the development of an integrative layer in database services to facilitate the synthesis of related information. The solution of this problem is made more difficult by the absence of universal identifiers for biological entities, and the breadth and variety of available data. Integr8 was modelled using UML (Universal Modelling Language). Integr8 is being implemented as an n-tier system using a modern object-oriented programming language (Java). An object-relational mapping tool, OJB, is being used to specify the interface between the upper layers and an underlying relational database. The European Bioinformatics Institute is launching the Integr8 project. Integr8 will be an automatically populated database in which we will maintain stable identifiers for biological entities, describe their relationships with each other (in accordance with the central dogma of biology), and store equivalences between identified entities in the source databases. Only core data will be stored in Integr8, with web links to the source databases providing further information. Integr8 will provide the integrative layer of the next generation of bioinformatics services from the EBI. Web-based interfaces will be developed to offer gene-centric views of the integrated data, presenting (where known) the links between genome, proteome and phenotype.

Agent-based re-engineering of ErbB signaling: a modeling pipeline for integrative systems biology.

Science.gov (United States)

Das, Arya A; Ajayakumar Darsana, T; Jacob, Elizabeth

2017-03-01

Experiments in systems biology are generally supported by a computational model which quantitatively estimates the parameters of the system by finding the best fit to the experiment. Mathematical models have proved to be successful in reverse engineering the system. The data generated is interpreted to understand the dynamics of the underlying phenomena. The question we have sought to answer is that - is it possible to use an agent-based approach to re-engineer a biological process, making use of the available knowledge from experimental and modelling efforts? Can the bottom-up approach benefit from the top-down exercise so as to create an integrated modelling formalism for systems biology? We propose a modelling pipeline that learns from the data given by reverse engineering, and uses it for re-engineering the system, to carry out in-silico experiments. A mathematical model that quantitatively predicts co-expression of EGFR-HER2 receptors in activation and trafficking has been taken for this study. The pipeline architecture takes cues from the population model that gives the rates of biochemical reactions, to formulate knowledge-based rules for the particle model. Agent-based simulations using these rules, support the existing facts on EGFR-HER2 dynamics. We conclude that, re-engineering models, built using the results of reverse engineering, opens up the possibility of harnessing the power pack of data which now lies scattered in literature. Virtual experiments could then become more realistic when empowered with the findings of empirical cell biology and modelling studies. Implemented on the Agent Modelling Framework developed in-house. C ++ code templates available in Supplementary material . liz.csir@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

GeneLab: A Systems Biology Platform for Spaceflight Omics Data

Science.gov (United States)

Reinsch, Sigrid S.; Lai, San-Huei; Chen, Rick; Thompson, Terri; Berrios, Daniel; Fogle, Homer; Marcu, Oana; Timucin, Linda; Chakravarty, Kaushik; Coughlan, Joseph

2015-01-01

NASA's mission includes expanding our understanding of biological systems to improve life on Earth and to enable long-duration human exploration of space. Resources to support large numbers of spaceflight investigations are limited. NASA's GeneLab project is maximizing the science output from these experiments by: (1) developing a unique public bioinformatics database that includes space bioscience relevant "omics" data (genomics, transcriptomics, proteomics, and metabolomics) and experimental metadata; (2) partnering with NASA-funded flight experiments through bio-sample sharing or sample augmentation to expedite omics data input to the GeneLab database; and (3) developing community-driven reference flight experiments. The first database, GeneLab Data System Version 1.0, went online in April 2015. V1.0 contains numerous flight datasets and has search and download capabilities. Version 2.0 will be released in 2016 and will link to analytic tools. In 2015 Genelab partnered with two Biological Research in Canisters experiments (BBRIC-19 and BRIC-20) which examine responses of Arabidopsis thaliana to spaceflight. GeneLab also partnered with Rodent Research-1 (RR1), the maiden flight to test the newly developed rodent habitat. GeneLab developed protocols for maxiumum yield of RNA, DNA and protein from precious RR-1 tissues harvested and preserved during the SpaceX-4 mission, as well as from tissues from mice that were frozen intact during spaceflight and later dissected. GeneLab is establishing partnerships with at least three planned flights for 2016. Organism-specific nationwide Science Definition Teams (SDTs) will define future GeneLab dedicated missions and ensure the broader scientific impact of the GeneLab missions. GeneLab ensures prompt release and open access to all high-throughput omics data from spaceflight and ground-based simulations of microgravity and radiation. Overall, GeneLab will facilitate the generation and query of parallel multi-omics data, and

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.

Fostering synergy between cell biology and systems biology.

Science.gov (United States)

Eddy, James A; Funk, Cory C; Price, Nathan D

2015-08-01

In the shared pursuit of elucidating detailed mechanisms of cell function, systems biology presents a natural complement to ongoing efforts in cell biology. Systems biology aims to characterize biological systems through integrated and quantitative modeling of cellular information. The process of model building and analysis provides value through synthesizing and cataloging information about cells and molecules, predicting mechanisms and identifying generalizable themes, generating hypotheses and guiding experimental design, and highlighting knowledge gaps and refining understanding. In turn, incorporating domain expertise and experimental data is crucial for building towards whole cell models. An iterative cycle of interaction between cell and systems biologists advances the goals of both fields and establishes a framework for mechanistic understanding of the genome-to-phenome relationship. Crown Copyright © 2015. Published by Elsevier Ltd. All rights reserved.

Assimilating Text-Mining & Bio-Informatics Tools to Analyze Cellulase structures

Science.gov (United States)

Satyasree, K. P. N. V., Dr; Lalitha Kumari, B., Dr; Jyotsna Devi, K. S. N. V.; Choudri, S. M. Roy; Pratap Joshi, K.

2017-08-01

Text-mining is one of the best potential way of automatically extracting information from the huge biological literature. To exploit its prospective, the knowledge encrypted in the text should be converted to some semantic representation such as entities and relations, which could be analyzed by machines. But large-scale practical systems for this purpose are rare. But text mining could be helpful for generating or validating predictions. Cellulases have abundant applications in various industries. Cellulose degrading enzymes are cellulases and the same producing bacteria - Bacillus subtilis & fungus Pseudomonas putida were isolated from top soil of Guntur Dt. A.P. India. Absolute cultures were conserved on potato dextrose agar medium for molecular studies. In this paper, we presented how well the text mining concepts can be used to analyze cellulase producing bacteria and fungi, their comparative structures are also studied with the aid of well-establised, high quality standard bioinformatic tools such as Bioedit, Swissport, Protparam, EMBOSSwin with which a complete data on Cellulases like structure, constituents of the enzyme has been obtained.

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

first used with a bioinformatics system. Simplifying the validation of essential tabular data files, such as sample metadata, will reduce common errors and thereby improve the quality and reliability of research outcomes.

FY 1998 achievement report on the R and D for accelerating the basement arrangement of the biological resource information. Bioinformatics; 1998 nendo seibutsu shigen joho kiban seibi kasokuka kenkyu kaihatsu seika hokokusho. Bioinformatics

Energy Technology Data Exchange (ETDEWEB)

NONE

2000-04-01

The paper described the FY 1998 results of the development of bioinformatics. All structure/sequence known proteins from all public databases were hierarchically classified systematically and according to similarities among sequences. Individual proteins in each classified group were added with explanatory notes of structure and physiological function. The mutually related information in metabolic system/signal transfer system was also included. The state of each residue position was classified into three states in terms of the solvent accessibility and three states in terms of the secondary structure. Parameter sets of occurrence frequency for each state of 20 kinds of amino acid were made. By these, it can be evaluated how much the arbitrary amino acid sequence is suitable for each structure in database. The data on the structure of low molecular-weight compounds are also incorporated so that the search for the related biomolecular system information becomes possible. The metabolic system/signal transfer system information was made database, the link was formed between each protein and each low molecular-weight compound, and the information on biomolecular networks was made searchable. A system to predict/support protein structure and function was developed. (NEDO)

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.

Systems Biology and Bioinformatics in Medical Applications

Science.gov (United States)

2009-10-01

identified A. baumannii, along with Aspergillus spp., extended-spectrum -lactamase-produc- ing Enterobacteriaceae, vancomycin-resistant Enterococcus fae...C-terminal to arginine and lysine residues. Mol. Cell Proteomics 3:608–614. 34. Pajkos, A., K. Vickery, and Y. Cossart. 2004. Is biofilm accumulation

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...

International Conference on Medical and Biological Engineering 2017

CERN Document Server

2017-01-01

This volume presents the proceedings of the International Conference on Medical and Biological Engineering held from 16 to 18 March 2017 in Sarajevo, Bosnia and Herzegovina. Focusing on the theme of ‘Pursuing innovation. Shaping the future’, it highlights the latest advancements in Biomedical Engineering and also presents the latest findings, innovative solutions and emerging challenges in this field. Topics include: - Biomedical Signal Processing - Biomedical Imaging and Image Processing - Biosensors and Bioinstrumentation - Bio-Micro/Nano Technologies - Biomaterials - Biomechanics, Robotics and Minimally Invasive Surgery - Cardiovascular, Respiratory and Endocrine Systems Engineering - Neural and Rehabilitation Engineering - Molecular, Cellular and Tissue Engineering - Bioinformatics and Computational Biology - Clinical Engineering and Health Technology Assessment - Health Informatics, E-Health and Telemedicine - Biomedical Engineering Education - Pharmaceutical Engineering.

Can all heritable biology really be reduced to a single dimension?

Science.gov (United States)

Babbitt, Gregory A; Coppola, Erin E; Alawad, Mohammed A; Hudson, André O

2016-03-10

A long-held presupposition in the field of bioinformatics holds that genetic, and now even epigenetic 'information' can be abstracted from the physicochemical details of the macromolecular polymers in which it resides. It is perhaps rather ironic that this basic conjecture originated upon the first observations of DNA structure itself. This static model of DNA led very quickly to the conclusion that only the nucleobase sequence itself is rich enough in molecular complexity to replicate a complex biology. This idea has been pervasive throughout genomic science, higher education and popular culture ever since; to the point that most of us would accept it unquestioningly as fact. What is more alarming is that this conjecture is driving a significant portion of the technological development in modern genomics towards methods strongly rooted in DNA sequencing, thereby reducing a dynamic multi-dimensional biology into single-dimensional forms of data. Evidence countering this central tenet of bioinformatics has been quietly mounting over many decades, prompting some to propose that the genome must be studied from the perspective of its molecular reality, rather than as a body of information to be represented symbolically. Here, we explore the epistemological boundary between bioinformatics and molecular biology, and warn against an 'overtly' bioinformatic perspective. We review a selection of new bioinformatic methods that move beyond sequence-based approaches to include consideration of databased three dimensional structures. However, we also note that these hybrid methods still ignore the most important element of gene function when attempting to improve outcomes; the fourth dimension of molecular dynamics over time. Copyright © 2015 The Authors. Published by Elsevier B.V. All rights reserved.

Micro-separation toward systems biology.

Science.gov (United States)

Liu, Bi-Feng; Xu, Bo; Zhang, Guisen; Du, Wei; Luo, Qingming

2006-02-17

Current biology is experiencing transformation in logic or philosophy that forces us to reevaluate the concept of cell, tissue or entire organism as a collection of individual components. Systems biology that aims at understanding biological system at the systems level is an emerging research area, which involves interdisciplinary collaborations of life sciences, computational and mathematical sciences, systems engineering, and analytical technology, etc. For analytical chemistry, developing innovative methods to meet the requirement of systems biology represents new challenges as also opportunities and responsibility. In this review, systems biology-oriented micro-separation technologies are introduced for comprehensive profiling of genome, proteome and metabolome, characterization of biomolecules interaction and single cell analysis such as capillary electrophoresis, ultra-thin layer gel electrophoresis, micro-column liquid chromatography, and their multidimensional combinations, parallel integrations, microfabricated formats, and nano technology involvement. Future challenges and directions are also suggested.

Nutritional Systems Biology

DEFF Research Database (Denmark)

Jensen, Kasper

and network biology has the potential to increase our understanding of how small molecules affect metabolic pathways and homeostasis, how this perturbation changes at the disease state, and to what extent individual genotypes contribute to this. A fruitful strategy in approaching and exploring the field...... biology research. The paper also shows as a proof-of-concept that a systems biology approach to diet is meaningful and demonstrates some basic principles on how to work with diet systematic. The second chapter of this thesis we developed the resource NutriChem v1.0. A foodchemical database linking...... sites of diet on the disease pathway. We propose a framework for interrogating the critical targets in colon cancer process and identifying plant-based dietary interventions as important modifiers using a systems chemical biology approach. The fifth chapter of the thesis is on discovering of novel anti...

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.

Informing biological design by integration of systems and synthetic biology.

Science.gov (United States)

Smolke, Christina D; Silver, Pamela A

2011-03-18

Synthetic biology aims to make the engineering of biology faster and more predictable. In contrast, systems biology focuses on the interaction of myriad components and how these give rise to the dynamic and complex behavior of biological systems. Here, we examine the synergies between these two fields. Copyright © 2011 Elsevier Inc. All rights reserved.

Quantum Bio-Informatics II From Quantum Information to Bio-Informatics

Science.gov (United States)

Accardi, L.; Freudenberg, Wolfgang; Ohya, Masanori

2009-02-01

/ H. Kamimura -- Massive collection of full-length complementary DNA clones and microarray analyses: keys to rice transcriptome analysis / S. Kikuchi -- Changes of influenza A(H5) viruses by means of entropic chaos degree / K. Sato and M. Ohya -- Basics of genome sequence analysis in bioinformatics - its fundamental ideas and problems / T. Suzuki and S. Miyazaki -- A basic introduction to gene expression studies using microarray expression data analysis / D. Wanke and J. Kilian -- Integrating biological perspectives: a quantum leap for microarray expression analysis / D. Wanke ... [et al.].

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

BioJS: an open source JavaScript framework for biological data visualization.

Science.gov (United States)

Gómez, John; García, Leyla J; Salazar, Gustavo A; Villaveces, Jose; Gore, Swanand; García, Alexander; Martín, Maria J; Launay, Guillaume; Alcántara, Rafael; Del-Toro, Noemi; Dumousseau, Marine; Orchard, Sandra; Velankar, Sameer; Hermjakob, Henning; Zong, Chenggong; Ping, Peipei; Corpas, Manuel; Jiménez, Rafael C

2013-04-15

BioJS is an open-source project whose main objective is the visualization of biological data in JavaScript. BioJS provides an easy-to-use consistent framework for bioinformatics application programmers. It follows a community-driven standard specification that includes a collection of components purposely designed to require a very simple configuration and installation. In addition to the programming framework, BioJS provides a centralized repository of components available for reutilization by the bioinformatics community. http://code.google.com/p/biojs/. Supplementary data are available at Bioinformatics online.

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.…

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

Kmerind: A Flexible Parallel Library for K-mer Indexing of Biological Sequences on Distributed Memory Systems.

Science.gov (United States)

Pan, Tony; Flick, Patrick; Jain, Chirag; Liu, Yongchao; Aluru, Srinivas

2017-10-09

Counting and indexing fixed length substrings, or k-mers, in biological sequences is a key step in many bioinformatics tasks including genome alignment and mapping, genome assembly, and error correction. While advances in next generation sequencing technologies have dramatically reduced the cost and improved latency and throughput, few bioinformatics tools can efficiently process the datasets at the current generation rate of 1.8 terabases every 3 days. We present Kmerind, a high performance parallel k-mer indexing library for distributed memory environments. The Kmerind library provides a set of simple and consistent APIs with sequential semantics and parallel implementations that are designed to be flexible and extensible. Kmerind's k-mer counter performs similarly or better than the best existing k-mer counting tools even on shared memory systems. In a distributed memory environment, Kmerind counts k-mers in a 120 GB sequence read dataset in less than 13 seconds on 1024 Xeon CPU cores, and fully indexes their positions in approximately 17 seconds. Querying for 1% of the k-mers in these indices can be completed in 0.23 seconds and 28 seconds, respectively. Kmerind is the first k-mer indexing library for distributed memory environments, and the first extensible library for general k-mer indexing and counting. Kmerind is available at https://github.com/ParBLiSS/kmerind.

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.

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.

Excited states in biological systems

International Nuclear Information System (INIS)

Cilento, G.; Zinner, K.; Bechara, E.J.H.; Duran, N.; Baptista, R.C. de; Shimizu, Y.; Augusto, O.; Faljoni-Alario, A.; Vidigal, C.C.C.; Oliveira, O.M.M.F.; Haun, M.

1979-01-01

Some aspects of bioluminescence related to bioenergetics are discussed: 1. chemical generation of excited species, by means of two general processes: electron transference and cyclic - and linear peroxide cleavage; 2. biological systems capable of generating excited states and 3. biological functions of these states, specially the non-emissive ones (tripletes). The production and the role of non-emissive excited states in biological systems are analysed, the main purpose of the study being the search for non-emissive states. Experiences carried out in biological systems are described; results and conclusions are given. (M.A.) [pt

Parallel evolutionary computation in bioinformatics applications.

Science.gov (United States)

Pinho, Jorge; Sobral, João Luis; Rocha, Miguel

2013-05-01

A large number of optimization problems within the field of Bioinformatics require methods able to handle its inherent complexity (e.g. NP-hard problems) and also demand increased computational efforts. In this context, the use of parallel architectures is a necessity. In this work, we propose ParJECoLi, a Java based library that offers a large set of metaheuristic methods (such as Evolutionary Algorithms) and also addresses the issue of its efficient execution on a wide range of parallel architectures. The proposed approach focuses on the easiness of use, making the adaptation to distinct parallel environments (multicore, cluster, grid) transparent to the user. Indeed, this work shows how the development of the optimization library can proceed independently of its adaptation for several architectures, making use of Aspect-Oriented Programming. The pluggable nature of parallelism related modules allows the user to easily configure its environment, adding parallelism modules to the base source code when needed. The performance of the platform is validated with two case studies within biological model optimization. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

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…

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.

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.

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 ...

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 ...

The Importance of Biological Databases in Biological Discovery.

Science.gov (United States)

Baxevanis, Andreas D; Bateman, Alex

2015-06-19

Biological databases play a central role in bioinformatics. They offer scientists the opportunity to access a wide variety of biologically relevant data, including the genomic sequences of an increasingly broad range of organisms. This unit provides a brief overview of major sequence databases and portals, such as GenBank, the UCSC Genome Browser, and Ensembl. Model organism databases, including WormBase, The Arabidopsis Information Resource (TAIR), and those made available through the Mouse Genome Informatics (MGI) resource, are also covered. Non-sequence-centric databases, such as Online Mendelian Inheritance in Man (OMIM), the Protein Data Bank (PDB), MetaCyc, and the Kyoto Encyclopedia of Genes and Genomes (KEGG), are also discussed. Copyright © 2015 John Wiley & Sons, Inc.

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.

Telemetry System of Biological Parameters

Directory of Open Access Journals (Sweden)

Jan Spisak

2005-01-01

Full Text Available The mobile telemetry system of biological parameters serves for reading and wireless data transfer of measured values of selected biological parameters to an outlying computer. It concerns basically long time monitoring of vital function of car pilot.The goal of this projects is to propose mobile telemetry system for reading, wireless transfer and processing of biological parameters of car pilot during physical and psychical stress. It has to be made with respect to minimal consumption, weight and maximal device mobility. This system has to eliminate signal noise, which is created by biological artifacts and disturbances during the data transfer.

The International Conference on Intelligent Biology and Medicine (ICIBM) 2016: from big data to big analytical tools.

Science.gov (United States)

Liu, Zhandong; Zheng, W Jim; Allen, Genevera I; Liu, Yin; Ruan, Jianhua; Zhao, Zhongming

2017-10-03

The 2016 International Conference on Intelligent Biology and Medicine (ICIBM 2016) was held on December 8-10, 2016 in Houston, Texas, USA. ICIBM included eight scientific sessions, four tutorials, one poster session, four highlighted talks and four keynotes that covered topics on 3D genomics structural analysis, next generation sequencing (NGS) analysis, computational drug discovery, medical informatics, cancer genomics, and systems biology. Here, we present a summary of the nine research articles selected from ICIBM 2016 program for publishing in BMC Bioinformatics.

OPTSDNA: Performance evaluation of an efficient distributed bioinformatics system for DNA sequence analysis.

Science.gov (United States)

Khan, Mohammad Ibrahim; Sheel, Chotan

2013-01-01

Storage of sequence data is a big concern as the amount of data generated is exponential in nature at several locations. Therefore, there is a need to develop techniques to store data using compression algorithm. Here we describe optimal storage algorithm (OPTSDNA) for storing large amount of DNA sequences of varying length. This paper provides performance analysis of optimal storage algorithm (OPTSDNA) of a distributed bioinformatics computing system for analysis of DNA sequences. OPTSDNA algorithm is used for storing various sizes of DNA sequences into database. DNA sequences of different lengths were stored by using this algorithm. These input DNA sequences are varied in size from very small to very large. Storage size is calculated by this algorithm. Response time is also calculated in this work. The efficiency and performance of the algorithm is high (in size calculation with percentage) when compared with other known with sequential approach.

Logical analysis of biological systems

DEFF Research Database (Denmark)

Mardare, Radu Iulian

2005-01-01

R. Mardare, Logical analysis of biological systems. Fundamenta Informaticae, N 64:271-285, 2005.......R. Mardare, Logical analysis of biological systems. Fundamenta Informaticae, N 64:271-285, 2005....

Computational immunology meets bioinformatics: the use of prediction tools for molecular binding in the simulation of the immune system.

Directory of Open Access Journals (Sweden)

Nicolas Rapin

Full Text Available We present a new approach to the study of the immune system that combines techniques of systems biology with information provided by data-driven prediction methods. To this end, we have extended an agent-based simulator of the immune response, C-ImmSim, such that it represents pathogens, as well as lymphocytes receptors, by means of their amino acid sequences and makes use of bioinformatics methods for T and B cell epitope prediction. This is a key step for the simulation of the immune response, because it determines immunogenicity. The binding of the epitope, which is the immunogenic part of an invading pathogen, together with activation and cooperation from T helper cells, is required to trigger an immune response in the affected host. To determine a pathogen's epitopes, we use existing prediction methods. In addition, we propose a novel method, which uses Miyazawa and Jernigan protein-protein potential measurements, for assessing molecular binding in the context of immune complexes. We benchmark the resulting model by simulating a classical immunization experiment that reproduces the development of immune memory. We also investigate the role of major histocompatibility complex (MHC haplotype heterozygosity and homozygosity with respect to the influenza virus and show that there is an advantage to heterozygosity. Finally, we investigate the emergence of one or more dominating clones of lymphocytes in the situation of chronic exposure to the same immunogenic molecule and show that high affinity clones proliferate more than any other. These results show that the simulator produces dynamics that are stable and consistent with basic immunological knowledge. We believe that the combination of genomic information and simulation of the dynamics of the immune system, in one single tool, can offer new perspectives for a better understanding of the immune system.

Bioinformatics tools for the analysis of NMR metabolomics studies focused on the identification of clinically relevant biomarkers.

Science.gov (United States)

Puchades-Carrasco, Leonor; Palomino-Schätzlein, Martina; Pérez-Rambla, Clara; Pineda-Lucena, Antonio

2016-05-01

Metabolomics, a systems biology approach focused on the global study of the metabolome, offers a tremendous potential in the analysis of clinical samples. Among other applications, metabolomics enables mapping of biochemical alterations involved in the pathogenesis of diseases, and offers the opportunity to noninvasively identify diagnostic, prognostic and predictive biomarkers that could translate into early therapeutic interventions. Particularly, metabolomics by Nuclear Magnetic Resonance (NMR) has the ability to simultaneously detect and structurally characterize an abundance of metabolic components, even when their identities are unknown. Analysis of the data generated using this experimental approach requires the application of statistical and bioinformatics tools for the correct interpretation of the results. This review focuses on the different steps involved in the metabolomics characterization of biofluids for clinical applications, ranging from the design of the study to the biological interpretation of the results. Particular emphasis is devoted to the specific procedures required for the processing and interpretation of NMR data with a focus on the identification of clinically relevant biomarkers. © The Author 2015. Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

The making of the Women in Biology forum (WiB) at Bioclues.

Science.gov (United States)

Singhania, Reeta Rani; Madduru, Dhatri; Pappu, Pranathi; Panchangam, Sameera; Suravajhala, Renuka; Chandrasekharan, Mohanalatha

2014-01-01

The Women in Biology forum (WiB) of Bioclues (India) began in 2009 to promote and support women pursuing careers in bioinformatics and computational biology. WiB was formed in order to help women scientists deprived of basic research, boost the prominence of women scientists particularly from developing countries, and bridge the gender gap to innovation. WiB has also served as a platform to highlight the work of established female scientists in these fields. Several award-winning women researchers have shared their experiences and provided valuable suggestions to WiB. Headed by Mohanalatha Chandrasekharan and supported by Dr. Reeta Rani Singhania and Renuka Suravajhala, WiB has seen major progress in the last couple of years particularly in the two avenues Mentoring and Research, off the four avenues in Bioclues: Mentoring, Outreach, Research and Entrepreneurship (MORE). In line with the Bioclues vision for bioinformatics in India, the WiB Journal Club (JoC) recognizes women scientists working on functional genomics and bioinformatics, and provides scientific mentorship and support for project design and hypothesis formulation. As a part of Bioclues, WiB members practice the group's open-desk policy and its belief that all members are free to express their own thoughts and opinions. The WiB forum appreciates suggestions and welcomes scientists from around the world to be a part of their mission to encourage women to pursue computational biology and bioinformatics.

The making of the Women in Biology forum (WiB at Bioclues.

Directory of Open Access Journals (Sweden)

Reeta Rani Singhania

2014-01-01

Full Text Available The Women in Biology forum (WiB of Bioclues (India began in 2009 to promote and support women pursuing careers in bioinformatics and computational biology. WiB was formed in order to help women scientists deprived of basic research, boost the prominence of women scientists particularly from developing countries, and bridge the gender gap to innovation. WiB has also served as a platform to highlight the work of established female scientists in these fields. Several award-winning women researchers have shared their experiences and provided valuable suggestions to WiB. Headed by Mohanalatha Chandrasekharan and supported by Dr. Reeta Rani Singhania and Renuka Suravajhala, WiB has seen major progress in the last couple of years particularly in the two avenues Mentoring and Research, off the four avenues in Bioclues: Mentoring, Outreach, Research and Entrepreneurship (MORE. In line with the Bioclues vision for bioinformatics in India, the WiB Journal Club (JoC recognizes women scientists working on functional genomics and bioinformatics, and provides scientific mentorship and support for project design and hypothesis formulation. As a part of Bioclues, WiB members practice the group's open-desk policy and its belief that all members are free to express their own thoughts and opinions. The WiB forum appreciates suggestions and welcomes scientists from around the world to be a part of their mission to encourage women to pursue computational biology and bioinformatics.

Institute for Genomics and Systems Biology

Science.gov (United States)

Institute for Genomics and Systems Biology Discover. Predict. Improve. Advancing Human and , 2015 See all Research Papers Featured Video Introduction to Systems Biology Video: Introduction to Systems Biology News Jack Gilbert Heading UChicago Startup that Aims to Predict Behavior of Trillions of

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

Science.gov (United States)

Maréchal, Eric

2008-09-01

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

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...

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.

DNA mimic proteins: functions, structures, and bioinformatic analysis.

Science.gov (United States)

Wang, Hao-Ching; Ho, Chun-Han; Hsu, Kai-Cheng; Yang, Jinn-Moon; Wang, Andrew H-J

2014-05-13

DNA mimic proteins have DNA-like negative surface charge distributions, and they function by occupying the DNA binding sites of DNA binding proteins to prevent these sites from being accessed by DNA. DNA mimic proteins control the activities of a variety of DNA binding proteins and are involved in a wide range of cellular mechanisms such as chromatin assembly, DNA repair, transcription regulation, and gene recombination. However, the sequences and structures of DNA mimic proteins are diverse, making them difficult to predict by bioinformatic search. To date, only a few DNA mimic proteins have been reported. These DNA mimics were not found by searching for functional motifs in their sequences but were revealed only by structural analysis of their charge distribution. This review highlights the biological roles and structures of 16 reported DNA mimic proteins. We also discuss approaches that might be used to discover new DNA mimic proteins.

Biophysics and systems biology.

Science.gov (United States)

Noble, Denis

2010-03-13

Biophysics at the systems level, as distinct from molecular biophysics, acquired its most famous paradigm in the work of Hodgkin and Huxley, who integrated their equations for the nerve impulse in 1952. Their approach has since been extended to other organs of the body, notably including the heart. The modern field of computational biology has expanded rapidly during the first decade of the twenty-first century and, through its contribution to what is now called systems biology, it is set to revise many of the fundamental principles of biology, including the relations between genotypes and phenotypes. Evolutionary theory, in particular, will require re-assessment. To succeed in this, computational and systems biology will need to develop the theoretical framework required to deal with multilevel interactions. While computational power is necessary, and is forthcoming, it is not sufficient. We will also require mathematical insight, perhaps of a nature we have not yet identified. This article is therefore also a challenge to mathematicians to develop such insights.

Inverse problems in systems biology

International Nuclear Information System (INIS)

Engl, Heinz W; Lu, James; Müller, Stefan; Flamm, Christoph; Schuster, Peter; Kügler, Philipp

2009-01-01

Systems biology is a new discipline built upon the premise that an understanding of how cells and organisms carry out their functions cannot be gained by looking at cellular components in isolation. Instead, consideration of the interplay between the parts of systems is indispensable for analyzing, modeling, and predicting systems' behavior. Studying biological processes under this premise, systems biology combines experimental techniques and computational methods in order to construct predictive models. Both in building and utilizing models of biological systems, inverse problems arise at several occasions, for example, (i) when experimental time series and steady state data are used to construct biochemical reaction networks, (ii) when model parameters are identified that capture underlying mechanisms or (iii) when desired qualitative behavior such as bistability or limit cycle oscillations is engineered by proper choices of parameter combinations. In this paper we review principles of the modeling process in systems biology and illustrate the ill-posedness and regularization of parameter identification problems in that context. Furthermore, we discuss the methodology of qualitative inverse problems and demonstrate how sparsity enforcing regularization allows the determination of key reaction mechanisms underlying the qualitative behavior. (topical review)

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

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

Distributed intelligent systems: a coordination perspective

National Research Council Canada - National Science Library

Bedrouni, Abdellah

2009-01-01

... Computing, Electronic Business, Semantic Web, Bioinformatics, and Computational Biology will certainly influence the direction of future agent-oriented research and technologies. Over the next decade, it is thus expected that real-world problems will impose the emergence of truly-open, fully-scalable agent-oriented systems, spanning across di...

Systems biology in critical-care nursing.

Science.gov (United States)

Schallom, Lynn; Thimmesch, Amanda R; Pierce, Janet D

2011-01-01

Systems biology applies advances in technology and new fields of study including genomics, transcriptomics, proteomics, and metabolomics to the development of new treatments and approaches of care for the critically ill and injured patient. An understanding of systems biology enhances a nurse's ability to implement evidence-based practice and to educate patients and families on novel testing and therapies. Systems biology is an integrated and holistic view of humans in relationship with the environment. Biomarkers are used to measure the presence and severity of disease and are rapidly expanding in systems biology endeavors. A systems biology approach using predictive, preventive, and participatory involvement is being utilized in a plethora of conditions of critical illness and injury including sepsis, cancer, pulmonary disease, and traumatic injuries.

Compartmental study of biological systems

International Nuclear Information System (INIS)

Moretti, J.L.

1975-01-01

The compartmental analysis of biological system is dealt with on several chapters devoted successively to: terminology; a mathematical and symbolic account of a system at equilibrium; different compartment systems; analysis of the experimental results. For this it is pointed out that the application of compartmental systems to biological phenomena is not always without danger. Sometimes the compartmental system established in a reference subject fails to conform in the patient. The compartments can divide into two or join together, completely changing the aspect of the system so that parameters calculated with the old model become entirely false. The conclusion is that the setting up of a compartmental system to represent a biological phenomenon is a tricky undertaking and the results must be constantly criticized and questioned [fr

MpTheory Java library: a multi-platform Java library for systems biology based on the Metabolic P theory.

Science.gov (United States)

Marchetti, Luca; Manca, Vincenzo

2015-04-15

MpTheory Java library is an open-source project collecting a set of objects and algorithms for modeling observed dynamics by means of the Metabolic P (MP) theory, that is, a mathematical theory introduced in 2004 for modeling biological dynamics. By means of the library, it is possible to model biological systems both at continuous and at discrete time. Moreover, the library comprises a set of regression algorithms for inferring MP models starting from time series of observations. To enhance the modeling experience, beside a pure Java usage, the library can be directly used within the most popular computing environments, such as MATLAB, GNU Octave, Mathematica and R. The library is open-source and licensed under the GNU Lesser General Public License (LGPL) Version 3.0. Source code, binaries and complete documentation are available at http://mptheory.scienze.univr.it. luca.marchetti@univr.it, marchetti@cosbi.eu Supplementary data are available at Bioinformatics online. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Comparing biological networks via graph compression

Directory of Open Access Journals (Sweden)

Hayashida Morihiro

2010-09-01

Full Text Available Abstract Background Comparison of various kinds of biological data is one of the main problems in bioinformatics and systems biology. Data compression methods have been applied to comparison of large sequence data and protein structure data. Since it is still difficult to compare global structures of large biological networks, it is reasonable to try to apply data compression methods to comparison of biological networks. In existing compression methods, the uniqueness of compression results is not guaranteed because there is some ambiguity in selection of overlapping edges. Results This paper proposes novel efficient methods, CompressEdge and CompressVertices, for comparing large biological networks. In the proposed methods, an original network structure is compressed by iteratively contracting identical edges and sets of connected edges. Then, the similarity of two networks is measured by a compression ratio of the concatenated networks. The proposed methods are applied to comparison of metabolic networks of several organisms, H. sapiens, M. musculus, A. thaliana, D. melanogaster, C. elegans, E. coli, S. cerevisiae, and B. subtilis, and are compared with an existing method. These results suggest that our methods can efficiently measure the similarities between metabolic networks. Conclusions Our proposed algorithms, which compress node-labeled networks, are useful for measuring the similarity of large biological networks.

Philosophy of Systems and Synthetic Biology

DEFF Research Database (Denmark)

Green, Sara

2017-01-01

This entry aims to clarify how systems and synthetic biology contribute to and extend discussions within philosophy of science. Unlike fields such as developmental biology or molecular biology, systems and synthetic biology are not easily demarcated by a focus on a specific subject area or level...... of organization. Rather, they are characterized by the development and application of mathematical, computational, and synthetic modeling strategies in response to complex problems and challenges within the life sciences. Proponents of systems and synthetic biology often stress the necessity of a perspective...... that goes beyond the scope of molecular biology and genetic engineering, respectively. With the emphasis on systems and interaction networks, the approaches explicitly engage in one of the oldest philosophical discussions on the relationship between parts and wholes, or between reductionism and holism...

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.

LipSpin: A New Bioinformatics Tool for Quantitative 1H NMR Lipid Profiling.

Science.gov (United States)

Barrilero, Rubén; Gil, Miriam; Amigó, Núria; Dias, Cintia B; Wood, Lisa G; Garg, Manohar L; Ribalta, Josep; Heras, Mercedes; Vinaixa, Maria; Correig, Xavier

2018-02-06

The structural similarity among lipid species and the low sensitivity and spectral resolution of nuclear magnetic resonance (NMR) have traditionally hampered the routine use of 1 H NMR lipid profiling of complex biological samples in metabolomics, which remains mostly manual and lacks freely available bioinformatics tools. However, 1 H NMR lipid profiling provides fast quantitative screening of major lipid classes (fatty acids, glycerolipids, phospholipids, and sterols) and some individual species and has been used in several clinical and nutritional studies, leading to improved risk prediction models. In this Article, we present LipSpin, a free and open-source bioinformatics tool for quantitative 1 H NMR lipid profiling. LipSpin implements a constrained line shape fitting algorithm based on voigt profiles and spectral templates from spectra of lipid standards, which automates the analysis of severely overlapped spectral regions and lipid signals with complex coupling patterns. LipSpin provides the most detailed quantification of fatty acid families and choline phospholipids in serum lipid samples by 1 H NMR to date. Moreover, analytical and clinical results using LipSpin quantifications conform with other techniques commonly used for lipid analysis.

Systems Biology

Indian Academy of Sciences (India)

IAS Admin

study and understand the function of biological systems, particu- larly, the response of such .... understand the organisation and behaviour of prokaryotic sys- tems. ... relationship of the structure of a target molecule to its ability to bind a certain ...

Integrating systems biology models and biomedical ontologies.

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Hoehndorf, Robert; Dumontier, Michel; Gennari, John H; Wimalaratne, Sarala; de Bono, Bernard; Cook, Daniel L; Gkoutos, Georgios V

2011-08-11

Systems biology is an approach to biology that emphasizes the structure and dynamic behavior of biological systems and the interactions that occur within them. To succeed, systems biology crucially depends on the accessibility and integration of data across domains and levels of granularity. Biomedical ontologies were developed to facilitate such an integration of data and are often used to annotate biosimulation models in systems biology. We provide a framework to integrate representations of in silico systems biology with those of in vivo biology as described by biomedical ontologies and demonstrate this framework using the Systems Biology Markup Language. We developed the SBML Harvester software that automatically converts annotated SBML models into OWL and we apply our software to those biosimulation models that are contained in the BioModels Database. We utilize the resulting knowledge base for complex biological queries that can bridge levels of granularity, verify models based on the biological phenomenon they represent and provide a means to establish a basic qualitative layer on which to express the semantics of biosimulation models. We establish an information flow between biomedical ontologies and biosimulation models and we demonstrate that the integration of annotated biosimulation models and biomedical ontologies enables the verification of models as well as expressive queries. Establishing a bi-directional information flow between systems biology and biomedical ontologies has the potential to enable large-scale analyses of biological systems that span levels of granularity from molecules to organisms.

Calculating life? Duelling discourses in interdisciplinary systems biology.

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Calvert, Jane; Fujimura, Joan H

2011-06-01

A high profile context in which physics and biology meet today is in the new field of systems biology. Systems biology is a fascinating subject for sociological investigation because the demands of interdisciplinary collaboration have brought epistemological issues and debates front and centre in discussions amongst systems biologists in conference settings, in publications, and in laboratory coffee rooms. One could argue that systems biologists are conducting their own philosophy of science. This paper explores the epistemic aspirations of the field by drawing on interviews with scientists working in systems biology, attendance at systems biology conferences and workshops, and visits to systems biology laboratories. It examines the discourses of systems biologists, looking at how they position their work in relation to previous types of biological inquiry, particularly molecular biology. For example, they raise the issue of reductionism to distinguish systems biology from molecular biology. This comparison with molecular biology leads to discussions about the goals and aspirations of systems biology, including epistemic commitments to quantification, rigor and predictability. Some systems biologists aspire to make biology more similar to physics and engineering by making living systems calculable, modelable and ultimately predictable-a research programme that is perhaps taken to its most extreme form in systems biology's sister discipline: synthetic biology. Other systems biologists, however, do not think that the standards of the physical sciences are the standards by which we should measure the achievements of systems biology, and doubt whether such standards will ever be applicable to 'dirty, unruly living systems'. This paper explores these epistemic tensions and reflects on their sociological dimensions and their consequences for future work in the life sciences. Copyright © 2010 Elsevier Ltd. All rights reserved.

Heuristic Strategies in Systems Biology

Directory of Open Access Journals (Sweden)

Fridolin Gross

2016-06-01

Full Text Available Systems biology is sometimes presented as providing a superior approach to the problem of biological complexity. Its use of ‘unbiased’ methods and formal quantitative tools might lead to the impression that the human factor is effectively eliminated. However, a closer look reveals that this impression is misguided. Systems biologists cannot simply assemble molecular information and compute biological behavior. Instead, systems biology’s main contribution is to accelerate the discovery of mechanisms by applying models as heuristic tools. These models rely on a variety of idealizing and simplifying assumptions in order to be efficient for this purpose. The strategies of systems biologists are similar to those of experimentalists in that they attempt to reduce the complexity of the discovery process. Analyzing and comparing these strategies, or ‘heuristics’, reveals the importance of the human factor in computational approaches and helps to situate systems biology within the epistemic landscape of the life sciences.

Reproducible Bioinformatics Research for Biologists

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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...

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

The Annotation, Mapping, Expression and Network (AMEN suite of tools for molecular systems biology

Directory of Open Access Journals (Sweden)

Primig Michael

2008-02-01

Full Text Available Abstract Background High-throughput genome biological experiments yield large and multifaceted datasets that require flexible and user-friendly analysis tools to facilitate their interpretation by life scientists. Many solutions currently exist, but they are often limited to specific steps in the complex process of data management and analysis and some require extensive informatics skills to be installed and run efficiently. Results We developed the Annotation, Mapping, Expression and Network (AMEN software as a stand-alone, unified suite of tools that enables biological and medical researchers with basic bioinformatics training to manage and explore genome annotation, chromosomal mapping, protein-protein interaction, expression profiling and proteomics data. The current version provides modules for (i uploading and pre-processing data from microarray expression profiling experiments, (ii detecting groups of significantly co-expressed genes, and (iii searching for enrichment of functional annotations within those groups. Moreover, the user interface is designed to simultaneously visualize several types of data such as protein-protein interaction networks in conjunction with expression profiles and cellular co-localization patterns. We have successfully applied the program to interpret expression profiling data from budding yeast, rodents and human. Conclusion AMEN is an innovative solution for molecular systems biological data analysis freely available under the GNU license. The program is available via a website at the Sourceforge portal which includes a user guide with concrete examples, links to external databases and helpful comments to implement additional functionalities. We emphasize that AMEN will continue to be developed and maintained by our laboratory because it has proven to be extremely useful for our genome biological research program.

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

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Campbell, Chad E.; Nehm, Ross H.

2013-01-01

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

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

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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

The 2nd DBCLS BioHackathon: interoperable bioinformatics Web services for integrated applications

Directory of Open Access Journals (Sweden)

Katayama Toshiaki

2011-08-01

Full Text Available Abstract Background The interaction between biological researchers and the bioinformatics tools they use is still hampered by incomplete interoperability between such tools. To ensure interoperability initiatives are effectively deployed, end-user applications need to be aware of, and support, best practices and standards. Here, we report on an initiative in which software developers and genome biologists came together to explore and raise awareness of these issues: BioHackathon 2009. Results Developers in attendance came from diverse backgrounds, with experts in Web services, workflow tools, text mining and visualization. Genome biologists provided expertise and exemplar data from the domains of sequence and pathway analysis and glyco-informatics. One goal of the meeting was to evaluate the ability to address real world use cases in these domains using the tools that the developers represented. This resulted in i a workflow to annotate 100,000 sequences from an invertebrate species; ii an integrated system for analysis of the transcription factor binding sites (TFBSs enriched based on differential gene expression data obtained from a microarray experiment; iii a workflow to enumerate putative physical protein interactions among enzymes in a metabolic pathway using protein structure data; iv a workflow to analyze glyco-gene-related diseases by searching for human homologs of glyco-genes in other species, such as fruit flies, and retrieving their phenotype-annotated SNPs. Conclusions Beyond deriving prototype solutions for each use-case, a second major purpose of the BioHackathon was to highlight areas of insufficiency. We discuss the issues raised by our exploration of the problem/solution space, concluding that there are still problems with the way Web services are modeled and annotated, including: i the absence of several useful data or analysis functions in the Web service "space"; ii the lack of documentation of methods; iii lack of

The 2nd DBCLS BioHackathon: interoperable bioinformatics Web services for integrated applications

Science.gov (United States)

2011-01-01

Background The interaction between biological researchers and the bioinformatics tools they use is still hampered by incomplete interoperability between such tools. To ensure interoperability initiatives are effectively deployed, end-user applications need to be aware of, and support, best practices and standards. Here, we report on an initiative in which software developers and genome biologists came together to explore and raise awareness of these issues: BioHackathon 2009. Results Developers in attendance came from diverse backgrounds, with experts in Web services, workflow tools, text mining and visualization. Genome biologists provided expertise and exemplar data from the domains of sequence and pathway analysis and glyco-informatics. One goal of the meeting was to evaluate the ability to address real world use cases in these domains using the tools that the developers represented. This resulted in i) a workflow to annotate 100,000 sequences from an invertebrate species; ii) an integrated system for analysis of the transcription factor binding sites (TFBSs) enriched based on differential gene expression data obtained from a microarray experiment; iii) a workflow to enumerate putative physical protein interactions among enzymes in a metabolic pathway using protein structure data; iv) a workflow to analyze glyco-gene-related diseases by searching for human homologs of glyco-genes in other species, such as fruit flies, and retrieving their phenotype-annotated SNPs. Conclusions Beyond deriving prototype solutions for each use-case, a second major purpose of the BioHackathon was to highlight areas of insufficiency. We discuss the issues raised by our exploration of the problem/solution space, concluding that there are still problems with the way Web services are modeled and annotated, including: i) the absence of several useful data or analysis functions in the Web service "space"; ii) the lack of documentation of methods; iii) lack of compliance with the SOAP

Application of computational intelligence to biology

CERN Document Server

Sekhar, Akula

2016-01-01

This book is a contribution of translational and allied research to the proceedings of the International Conference on Computational Intelligence and Soft Computing. It explains how various computational intelligence techniques can be applied to investigate various biological problems. It is a good read for Research Scholars, Engineers, Medical Doctors and Bioinformatics researchers.

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…

InterMine: a flexible data warehouse system for the integration and analysis of heterogeneous biological data.

Science.gov (United States)

Smith, Richard N; Aleksic, Jelena; Butano, Daniela; Carr, Adrian; Contrino, Sergio; Hu, Fengyuan; Lyne, Mike; Lyne, Rachel; Kalderimis, Alex; Rutherford, Kim; Stepan, Radek; Sullivan, Julie; Wakeling, Matthew; Watkins, Xavier; Micklem, Gos

2012-12-01

InterMine is an open-source data warehouse system that facilitates the building of databases with complex data integration requirements and a need for a fast customizable query facility. Using InterMine, large biological databases can be created from a range of heterogeneous data sources, and the extensible data model allows for easy integration of new data types. The analysis tools include a flexible query builder, genomic region search and a library of 'widgets' performing various statistical analyses. The results can be exported in many commonly used formats. InterMine is a fully extensible framework where developers can add new tools and functionality. Additionally, there is a comprehensive set of web services, for which client libraries are provided in five commonly used programming languages. Freely available from http://www.intermine.org under the LGPL license. g.micklem@gen.cam.ac.uk Supplementary data are available at Bioinformatics online.

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.

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.

Strategic Integration of Multiple Bioinformatics Resources for System Level Analysis of Biological Networks.

Science.gov (United States)

D'Souza, Mark; Sulakhe, Dinanath; Wang, Sheng; Xie, Bing; Hashemifar, Somaye; Taylor, Andrew; Dubchak, Inna; Conrad Gilliam, T; Maltsev, Natalia

2017-01-01

Recent technological advances in genomics allow the production of biological data at unprecedented tera- and petabyte scales. Efficient mining of these vast and complex datasets for the needs of biomedical research critically depends on a seamless integration of the clinical, genomic, and experimental information with prior knowledge about genotype-phenotype relationships. Such experimental data accumulated in publicly available databases should be accessible to a variety of algorithms and analytical pipelines that drive computational analysis and data mining.We present an integrated computational platform Lynx (Sulakhe et al., Nucleic Acids Res 44:D882-D887, 2016) ( http://lynx.cri.uchicago.edu ), a web-based database and knowledge extraction engine. It provides advanced search capabilities and a variety of algorithms for enrichment analysis and network-based gene prioritization. It gives public access to the Lynx integrated knowledge base (LynxKB) and its analytical tools via user-friendly web services and interfaces. The Lynx service-oriented architecture supports annotation and analysis of high-throughput experimental data. Lynx tools assist the user in extracting meaningful knowledge from LynxKB and experimental data, and in the generation of weighted hypotheses regarding the genes and molecular mechanisms contributing to human phenotypes or conditions of interest. The goal of this integrated platform is to support the end-to-end analytical needs of various translational projects.

Mammalian Synthetic Biology: Engineering Biological Systems.

Science.gov (United States)

Black, Joshua B; Perez-Pinera, Pablo; Gersbach, Charles A

2017-06-21

The programming of new functions into mammalian cells has tremendous application in research and medicine. Continued improvements in the capacity to sequence and synthesize DNA have rapidly increased our understanding of mechanisms of gene function and regulation on a genome-wide scale and have expanded the set of genetic components available for programming cell biology. The invention of new research tools, including targetable DNA-binding systems such as CRISPR/Cas9 and sensor-actuator devices that can recognize and respond to diverse chemical, mechanical, and optical inputs, has enabled precise control of complex cellular behaviors at unprecedented spatial and temporal resolution. These tools have been critical for the expansion of synthetic biology techniques from prokaryotic and lower eukaryotic hosts to mammalian systems. Recent progress in the development of genome and epigenome editing tools and in the engineering of designer cells with programmable genetic circuits is expanding approaches to prevent, diagnose, and treat disease and to establish personalized theranostic strategies for next-generation medicines. This review summarizes the development of these enabling technologies and their application to transforming mammalian synthetic biology into a distinct field in research and medicine.

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...

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…

Applicability of Computational Systems Biology in Toxicology

DEFF Research Database (Denmark)

Kongsbak, Kristine Grønning; Hadrup, Niels; Audouze, Karine Marie Laure

2014-01-01

be used to establish hypotheses on links between the chemical and human diseases. Such information can also be applied for designing more intelligent animal/cell experiments that can test the established hypotheses. Here, we describe how and why to apply an integrative systems biology method......Systems biology as a research field has emerged within the last few decades. Systems biology, often defined as the antithesis of the reductionist approach, integrates information about individual components of a biological system. In integrative systems biology, large data sets from various sources...... and databases are used to model and predict effects of chemicals on, for instance, human health. In toxicology, computational systems biology enables identification of important pathways and molecules from large data sets; tasks that can be extremely laborious when performed by a classical literature search...

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

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.

6th European Conference of the International Federation for Medical and Biological Engineering

CERN Document Server

Vasic, Darko

2015-01-01

This volume presents the Proceedings of the 6th European Conference of the International Federation for Medical and Biological Engineering (MBEC2014), held in Dubrovnik September 7 – 11, 2014. The general theme of MBEC 2014 is "Towards new horizons in biomedical engineering" The scientific discussions in these conference proceedings include the following themes: - Biomedical Signal Processing - Biomedical Imaging and Image Processing - Biosensors and Bioinstrumentation - Bio-Micro/Nano Technologies - Biomaterials - Biomechanics, Robotics and Minimally Invasive Surgery - Cardiovascular, Respiratory and Endocrine Systems Engineering - Neural and Rehabilitation Engineering - Molecular, Cellular and Tissue Engineering - Bioinformatics and Computational Biology - Clinical Engineering and Health Technology Assessment - Health Informatics, E-Health and Telemedicine - Biomedical Engineering Education

Editorial overview : Systems biology for biotechnology

NARCIS (Netherlands)

Heinemann, Matthias; Pilpel, Yitzhak

About 15 years ago, systems biology was introduced as a novel approach to biological research. On the one side, its introduction was a result of the recognition that through solely the reductionist approach, we would ulti- mately not be able to understand how biological systems function as a whole.

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

Quantum Effects in Biological Systems

CERN Document Server

2016-01-01

Since the last decade the study of quantum mechanical phenomena in biological systems has become a vibrant field of research. Initially sparked by evidence of quantum effects in energy transport that is instrumental for photosynthesis, quantum biology asks the question of how methods and models from quantum theory can help us to understand fundamental mechanisms in living organisms. This approach entails a paradigm change challenging the related disciplines: The successful framework of quantum theory is taken out of its low-temperature, microscopic regimes and applied to hot and dense macroscopic environments, thereby extending the toolbox of biology and biochemistry at the same time. The Quantum Effects in Biological Systems conference is a platform for researchers from biology, chemistry and physics to present and discuss the latest developments in the field of quantum biology. After meetings in Lisbon (2009), Harvard (2010), Ulm (2011), Berkeley (2012), Vienna (2013), Singapore (2014) and Florence (2015),...

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.

Static Analysis for Systems Biology

DEFF Research Database (Denmark)

Nielson, Flemming; Nielson, Hanne Riis; Rosa, D. Schuch da

2004-01-01

This paper shows how static analysis techniques can help understanding biological systems. Based on a simple example we illustrate the outcome of performing three different analyses extracting information of increasing precision. We conclude by reporting on the potential impact and exploitation o...... of these techniques in systems biology....

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

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.

Importance of databases of nucleic acids for bioinformatic analysis focused to genomics

Science.gov (United States)

Jimenez-Gutierrez, L. R.; Barrios-Hernández, C. J.; Pedraza-Ferreira, G. R.; Vera-Cala, L.; Martinez-Perez, F.

2016-08-01

Recently, bioinformatics has become a new field of science, indispensable in the analysis of millions of nucleic acids sequences, which are currently deposited in international databases (public or private); these databases contain information of genes, RNA, ORF, proteins, intergenic regions, including entire genomes from some species. The analysis of this information requires computer programs; which were renewed in the use of new mathematical methods, and the introduction of the use of artificial intelligence. In addition to the constant creation of supercomputing units trained to withstand the heavy workload of sequence analysis. However, it is still necessary the innovation on platforms that allow genomic analyses, faster and more effectively, with a technological understanding of all biological processes.

The next generation of training for Arabidopsis researchers: bioinformatics and quantitative biology

Science.gov (United States)

It has been more than 50 years since Arabidopsis (Arabidopsis thaliana) was first introduced as a model organism to understand basic processes in plant biology. A well-organized scientific community has used this small reference plant species to make numerous fundamental plant biology discoveries (P...

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

Omics/systems biology and cancer cachexia.

Science.gov (United States)

Gallagher, Iain J; Jacobi, Carsten; Tardif, Nicolas; Rooyackers, Olav; Fearon, Kenneth

2016-06-01

Cancer cachexia is a complex syndrome generated by interaction between the host and tumour cells with a background of treatment effects and toxicity. The complexity of the physiological pathways likely involved in cancer cachexia necessitates a holistic view of the relevant biology. Emergent properties are characteristic of complex systems with the result that the end result is more than the sum of its parts. Recognition of the importance of emergent properties in biology led to the concept of systems biology wherein a holistic approach is taken to the biology at hand. Systems biology approaches will therefore play an important role in work to uncover key mechanisms with therapeutic potential in cancer cachexia. The 'omics' technologies provide a global view of biological systems. Genomics, transcriptomics, proteomics, lipidomics and metabolomics approaches all have application in the study of cancer cachexia to generate systems level models of the behaviour of this syndrome. The current work reviews recent applications of these technologies to muscle atrophy in general and cancer cachexia in particular with a view to progress towards integration of these approaches to better understand the pathology and potential treatment pathways in cancer cachexia. Copyright © 2016. Published by Elsevier Ltd.

The DBCLS BioHackathon: standardization and interoperability for bioinformatics web services and workflows

NARCIS (Netherlands)

Katayama, T.; Arakawa, K.; Nakao, M.; Prins, J.C.P.

2010-01-01

Web services have become a key technology for bioinformatics, since life science databases are globally decentralized and the exponential increase in the amount of available data demands for efficient systems without the need to transfer entire databases for every step of an analysis. However,

Bioinformatics, interaction network analysis, and neural networks to characterize gene expression of radicular cyst and periapical granuloma.

Science.gov (United States)

Poswar, Fabiano de Oliveira; Farias, Lucyana Conceição; Fraga, Carlos Alberto de Carvalho; Bambirra, Wilson; Brito-Júnior, Manoel; Sousa-Neto, Manoel Damião; Santos, Sérgio Henrique Souza; de Paula, Alfredo Maurício Batista; D'Angelo, Marcos Flávio Silveira Vasconcelos; Guimarães, André Luiz Sena

2015-06-01

Bioinformatics has emerged as an important tool to analyze the large amount of data generated by research in different diseases. In this study, gene expression for radicular cysts (RCs) and periapical granulomas (PGs) was characterized based on a leader gene approach. A validated bioinformatics algorithm was applied to identify leader genes for RCs and PGs. Genes related to RCs and PGs were first identified in PubMed, GenBank, GeneAtlas, and GeneCards databases. The Web-available STRING software (The European Molecular Biology Laboratory [EMBL], Heidelberg, Baden-Württemberg, Germany) was used in order to build the interaction map among the identified genes by a significance score named weighted number of links. Based on the weighted number of links, genes were clustered using k-means. The genes in the highest cluster were considered leader genes. Multilayer perceptron neural network analysis was used as a complementary supplement for gene classification. For RCs, the suggested leader genes were TP53 and EP300, whereas PGs were associated with IL2RG, CCL2, CCL4, CCL5, CCR1, CCR3, and CCR5 genes. Our data revealed different gene expression for RCs and PGs, suggesting that not only the inflammatory nature but also other biological processes might differentiate RCs and PGs. Copyright © 2015 American Association of Endodontists. Published by Elsevier Inc. All rights reserved.

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

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...

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...

Analyzing the Biology on the System Level

OpenAIRE

Tong, Wei

2016-01-01

Although various genome projects have provided us enormous static sequence information, understanding of the sophisticated biology continues to require integrating the computational modeling, system analysis, technology development for experiments, and quantitative experiments all together to analyze the biology architecture on various levels, which is just the origin of systems biology subject. This review discusses the object, its characteristics, and research attentions in systems biology,...

PIBAS FedSPARQL: a web-based platform for integration and exploration of bioinformatics datasets.

Science.gov (United States)

Djokic-Petrovic, Marija; Cvjetkovic, Vladimir; Yang, Jeremy; Zivanovic, Marko; Wild, David J

2017-09-20

There are a huge variety of data sources relevant to chemical, biological and pharmacological research, but these data sources are highly siloed and cannot be queried together in a straightforward way. Semantic technologies offer the ability to create links and mappings across datasets and manage them as a single, linked network so that searching can be carried out across datasets, independently of the source. We have developed an application called PIBAS FedSPARQL that uses semantic technologies to allow researchers to carry out such searching across a vast array of data sources. PIBAS FedSPARQL is a web-based query builder and result set visualizer of bioinformatics data. As an advanced feature, our system can detect similar data items identified by different Uniform Resource Identifiers (URIs), using a text-mining algorithm based on the processing of named entities to be used in Vector Space Model and Cosine Similarity Measures. According to our knowledge, PIBAS FedSPARQL was unique among the systems that we found in that it allows detecting of similar data items. As a query builder, our system allows researchers to intuitively construct and run Federated SPARQL queries across multiple data sources, including global initiatives, such as Bio2RDF, Chem2Bio2RDF, EMBL-EBI, and one local initiative called CPCTAS, as well as additional user-specified data source. From the input topic, subtopic, template and keyword, a corresponding initial Federated SPARQL query is created and executed. Based on the data obtained, end users have the ability to choose the most appropriate data sources in their area of interest and exploit their Resource Description Framework (RDF) structure, which allows users to select certain properties of data to enhance query results. The developed system is flexible and allows intuitive creation and execution of queries for an extensive range of bioinformatics topics. Also, the novel "similar data items detection" algorithm can be particularly

Enhancing the role of veterinary vaccines reducing zoonotic diseases of humans: Linking systems biology with vaccine development

Energy Technology Data Exchange (ETDEWEB)

Adams, Leslie G.; Khare, Sangeeta; Lawhon, Sara D.; Rossetti, Carlos A.; Lewin, Harris A.; Lipton, Mary S.; Turse, Joshua E.; Wylie, Dennis C.; Bai, Yu; Drake, Kenneth L.

2011-09-22

The aim of research on infectious diseases is their prevention, and brucellosis and salmonellosis as such are classic examples of worldwide zoonoses for application of a systems biology approach for enhanced rational vaccine development. When used optimally, vaccines prevent disease manifestations, reduce transmission of disease, decrease the need for pharmaceutical intervention, and improve the health and welfare of animals, as well as indirectly protecting against zoonotic diseases of people. Advances in the last decade or so using comprehensive systems biology approaches linking genomics, proteomics, bioinformatics, and biotechnology with immunology, pathogenesis and vaccine formulation and delivery are expected to enable enhanced approaches to vaccine development. The goal of this paper is to evaluate the role of computational systems biology analysis of host:pathogen interactions (the interactome) as a tool for enhanced rational design of vaccines. Systems biology is bringing a new, more robust approach to veterinary vaccine design based upon a deeper understanding of the host pathogen interactions and its impact on the host's molecular network of the immune system. A computational systems biology method was utilized to create interactome models of the host responses to Brucella melitensis (BMEL), Mycobacterium avium paratuberculosis (MAP), Salmonella enterica Typhimurium (STM), and a Salmonella mutant (isogenic *sipA, sopABDE2) and linked to the basis for rational development of vaccines for brucellosis and salmonellosis as reviewed by Adams et al. and Ficht et al. [1,2]. A bovine ligated ileal loop biological model was established to capture the host gene expression response at multiple time points post infection. New methods based on Dynamic Bayesian Network (DBN) machine learning were employed to conduct a comparative pathogenicity analysis of 219 signaling and metabolic pathways and 1620 gene ontology (GO) categories that defined the host

Adapting to Biology: Maintaining Container-Closure System Compatibility with the Therapeutic Biologic Revolution.

Science.gov (United States)

Degrazio, Dominick

Many pharmaceutical companies are transitioning their research and development drug product pipeline from traditional small-molecule injectables to the dimension of evolving therapeutic biologics. Important concerns associated with this changeover are becoming forefront, as challenges develop of varying complexity uncommon with the synthesis and production of traditional drugs. Therefore, alternative measures must be established that aim to preserve the efficacy and functionality of a biologic that might not be implemented for small molecules. Conserving protein stability is relative to perpetuating a net equilibrium of both intrinsic and extrinsic factors. Key to sustaining this balance is the ability of container-closure systems to maintain their compatibility with the ever-changing dynamics of therapeutic biologics. Failure to recognize and adjust the material properties of packaging components to support compatibility with therapeutic biologics can compromise patient safety, drug productivity, and biological stability. This review will examine the differences between small-molecule drugs and therapeutic biologics, lay a basic foundation for understanding the stability of therapeutic biologics, and demonstrate potential sources of container-closure systems' incompatibilities with therapeutic biologics at a mechanistic level. Many pharmaceutical companies are transitioning their research and development drug product pipeline from traditional small-molecule injectables to recombinantly derived therapeutic biologics. Concerns associated with this transformation are becoming prominent, as therapeutic biologics are uncharacteristic to small-molecule drugs. Maintaining the stability of a therapeutic biologic is a combination of balancing intrinsic factors and external elements within the biologic's microenvironment. An important aspect of this balance is relegated to the overall compatibility of primary, parenteral container-closure systems with therapeutic biologics

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.

Bioinformatics algorithm based on a parallel implementation of a machine learning approach using transducers

International Nuclear Information System (INIS)

Roche-Lima, Abiel; Thulasiram, Ruppa K

2012-01-01

Finite automata, in which each transition is augmented with an output label in addition to the familiar input label, are considered finite-state transducers. Transducers have been used to analyze some fundamental issues in bioinformatics. Weighted finite-state transducers have been proposed to pairwise alignments of DNA and protein sequences; as well as to develop kernels for computational biology. Machine learning algorithms for conditional transducers have been implemented and used for DNA sequence analysis. Transducer learning algorithms are based on conditional probability computation. It is calculated by using techniques, such as pair-database creation, normalization (with Maximum-Likelihood normalization) and parameters optimization (with Expectation-Maximization - EM). These techniques are intrinsically costly for computation, even worse when are applied to bioinformatics, because the databases sizes are large. In this work, we describe a parallel implementation of an algorithm to learn conditional transducers using these techniques. The algorithm is oriented to bioinformatics applications, such as alignments, phylogenetic trees, and other genome evolution studies. Indeed, several experiences were developed using the parallel and sequential algorithm on Westgrid (specifically, on the Breeze cluster). As results, we obtain that our parallel algorithm is scalable, because execution times are reduced considerably when the data size parameter is increased. Another experience is developed by changing precision parameter. In this case, we obtain smaller execution times using the parallel algorithm. Finally, number of threads used to execute the parallel algorithm on the Breezy cluster is changed. In this last experience, we obtain as result that speedup is considerably increased when more threads are used; however there is a convergence for number of threads equal to or greater than 16.

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…

Data mining and data integration in biology

DEFF Research Database (Denmark)

Ólason, Páll Ísólfur

2008-01-01

. They also necessitate new ways of data preparation as established methods for sequence sets are often useless when dealing with sets of sequence pairs. Therefore careful analysis on the sequence level as well as the integrated network level is needed to benchmark these data prior to use. The networks, which...... between molecules, the essence of systems biology. Internet technologies are very important in this respect as bioinformatics labs around the world generate staggering amounts of novel annotations, increasing the importance of on-line processing and distributed systems. One of the most important new data...... types in proteomics is protein-protein interactions. Interactions between the functional elements in the cell are a natural place to start when integrating protein annotations with the aim of gaining a systems view of the cell. Interaction data, however, are notoriously biased, erroneous and incomplete...

BATMAN-TCM: a Bioinformatics Analysis Tool for Molecular mechANism of Traditional Chinese Medicine

Science.gov (United States)

Liu, Zhongyang; Guo, Feifei; Wang, Yong; Li, Chun; Zhang, Xinlei; Li, Honglei; Diao, Lihong; Gu, Jiangyong; Wang, Wei; Li, Dong; He, Fuchu

2016-02-01

Traditional Chinese Medicine (TCM), with a history of thousands of years of clinical practice, is gaining more and more attention and application worldwide. And TCM-based new drug development, especially for the treatment of complex diseases is promising. However, owing to the TCM’s diverse ingredients and their complex interaction with human body, it is still quite difficult to uncover its molecular mechanism, which greatly hinders the TCM modernization and internationalization. Here we developed the first online Bioinformatics Analysis Tool for Molecular mechANism of TCM (BATMAN-TCM). Its main functions include 1) TCM ingredients’ target prediction; 2) functional analyses of targets including biological pathway, Gene Ontology functional term and disease enrichment analyses; 3) the visualization of ingredient-target-pathway/disease association network and KEGG biological pathway with highlighted targets; 4) comparison analysis of multiple TCMs. Finally, we applied BATMAN-TCM to Qishen Yiqi dripping Pill (QSYQ) and combined with subsequent experimental validation to reveal the functions of renin-angiotensin system responsible for QSYQ’s cardioprotective effects for the first time. BATMAN-TCM will contribute to the understanding of the “multi-component, multi-target and multi-pathway” combinational therapeutic mechanism of TCM, and provide valuable clues for subsequent experimental validation, accelerating the elucidation of TCM’s molecular mechanism. BATMAN-TCM is available at http://bionet.ncpsb.org/batman-tcm.

A Converter from the Systems Biology Markup Language to the Synthetic Biology Open Language.

Science.gov (United States)

Nguyen, Tramy; Roehner, Nicholas; Zundel, Zach; Myers, Chris J

2016-06-17

Standards are important to synthetic biology because they enable exchange and reproducibility of genetic designs. This paper describes a procedure for converting between two standards: the Systems Biology Markup Language (SBML) and the Synthetic Biology Open Language (SBOL). SBML is a standard for behavioral models of biological systems at the molecular level. SBOL describes structural and basic qualitative behavioral aspects of a biological design. Converting SBML to SBOL enables a consistent connection between behavioral and structural information for a biological design. The conversion process described in this paper leverages Systems Biology Ontology (SBO) annotations to enable inference of a designs qualitative function.

Application of proteomics to ecology and population biology.

Science.gov (United States)

Karr, T L

2008-02-01

Proteomics is a relatively new scientific discipline that merges protein biochemistry, genome biology and bioinformatics to determine the spatial and temporal expression of proteins in cells, tissues and whole organisms. There has been very little application of proteomics to the fields of behavioral genetics, evolution, ecology and population dynamics, and has only recently been effectively applied to the closely allied fields of molecular evolution and genetics. However, there exists considerable potential for proteomics to impact in areas related to functional ecology; this review will introduce the general concepts and methodologies that define the field of proteomics and compare and contrast the advantages and disadvantages with other methods. Examples of how proteomics can aid, complement and indeed extend the study of functional ecology will be discussed including the main tool of ecological studies, population genetics with an emphasis on metapopulation structure analysis. Because proteomic analyses provide a direct measure of gene expression, it obviates some of the limitations associated with other genomic approaches, such as microarray and EST analyses. Likewise, in conjunction with associated bioinformatics and molecular evolutionary tools, proteomics can provide the foundation of a systems-level integration approach that can enhance ecological studies. It can be envisioned that proteomics will provide important new information on issues specific to metapopulation biology and adaptive processes in nature. A specific example of the application of proteomics to sperm ageing is provided to illustrate the potential utility of the approach.

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.

Ten questions about systems biology

DEFF Research Database (Denmark)

Joyner, Michael J; Pedersen, Bente K

2011-01-01

to understand how whole animals adapt to the real world. We argue that a lack of fluency in these concepts is a major stumbling block for what has been narrowly defined as 'systems biology' by some of its leading advocates. We also point out that it is a failure of regulation at multiple levels that causes many......In this paper we raise 'ten questions' broadly related to 'omics', the term systems biology, and why the new biology has failed to deliver major therapeutic advances for many common diseases, especially diabetes and cardiovascular disease. We argue that a fundamentally narrow and reductionist...

Ten questions about systems biology

DEFF Research Database (Denmark)

Joyner, Michael J; Pedersen, Bente K

2011-01-01

In this paper we raise 'ten questions' broadly related to 'omics', the term systems biology, and why the new biology has failed to deliver major therapeutic advances for many common diseases, especially diabetes and cardiovascular disease. We argue that a fundamentally narrow and reductionist...... to understand how whole animals adapt to the real world. We argue that a lack of fluency in these concepts is a major stumbling block for what has been narrowly defined as 'systems biology' by some of its leading advocates. We also point out that it is a failure of regulation at multiple levels that causes many...

Genomes, Phylogeny, and Evolutionary Systems Biology

Energy Technology Data Exchange (ETDEWEB)

Medina, Monica

2005-03-25

With the completion of the human genome and the growing number of diverse genomes being sequenced, a new age of evolutionary research is currently taking shape. The myriad of technological breakthroughs in biology that are leading to the unification of broad scientific fields such as molecular biology, biochemistry, physics, mathematics and computer science are now known as systems biology. Here I present an overview, with an emphasis on eukaryotes, of how the postgenomics era is adopting comparative approaches that go beyond comparisons among model organisms to shape the nascent field of evolutionary systems biology.

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

DEFF Research Database (Denmark)

Kalas, M.; Puntervoll, P.; Joseph, A.

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...... 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....

Semantic Web meets Integrative Biology: a survey.

Science.gov (United States)

Chen, Huajun; Yu, Tong; Chen, Jake Y

2013-01-01

Integrative Biology (IB) uses experimental or computational quantitative technologies to characterize biological systems at the molecular, cellular, tissue and population levels. IB typically involves the integration of the data, knowledge and capabilities across disciplinary boundaries in order to solve complex problems. We identify a series of bioinformatics problems posed by interdisciplinary integration: (i) data integration that interconnects structured data across related biomedical domains; (ii) ontology integration that brings jargons, terminologies and taxonomies from various disciplines into a unified network of ontologies; (iii) knowledge integration that integrates disparate knowledge elements from multiple sources; (iv) service integration that build applications out of services provided by different vendors. We argue that IB can benefit significantly from the integration solutions enabled by Semantic Web (SW) technologies. The SW enables scientists to share content beyond the boundaries of applications and websites, resulting into a web of data that is meaningful and understandable to any computers. In this review, we provide insight into how SW technologies can be used to build open, standardized and interoperable solutions for interdisciplinary integration on a global basis. We present a rich set of case studies in system biology, integrative neuroscience, bio-pharmaceutics and translational medicine, to highlight the technical features and benefits of SW applications in IB.

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.

Aspergilli: Systems biology and industrial applications

DEFF Research Database (Denmark)

Knuf, Christoph; Nielsen, Jens

2012-01-01

possible to implement systems biology tools to advance metabolic engineering. These tools include genome-wide transcription analysis and genome-scale metabolic models. Herein, we review achievements in the field and highlight the impact of Aspergillus systems biology on industrial biotechnology....

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.

Systems Biology, Systems Medicine, Systems Pharmacology: The What and The Why.

Science.gov (United States)

Stéphanou, Angélique; Fanchon, Eric; Innominato, Pasquale F; Ballesta, Annabelle

2018-05-09

Systems biology is today such a widespread discipline that it becomes difficult to propose a clear definition of what it really is. For some, it remains restricted to the genomic field. For many, it designates the integrated approach or the corpus of computational methods employed to handle the vast amount of biological or medical data and investigate the complexity of the living. Although defining systems biology might be difficult, on the other hand its purpose is clear: systems biology, with its emerging subfields systems medicine and systems pharmacology, clearly aims at making sense of complex observations/experimental and clinical datasets to improve our understanding of diseases and their treatments without putting aside the context in which they appear and develop. In this short review, we aim to specifically focus on these new subfields with the new theoretical tools and approaches that were developed in the context of cancer. Systems pharmacology and medicine now give hope for major improvements in cancer therapy, making personalized medicine closer to reality. As we will see, the current challenge is to be able to improve the clinical practice according to the paradigm shift of systems sciences.

Complexity, Analysis and Control of Singular Biological Systems

CERN Document Server

Zhang, Qingling; Zhang, Xue

2012-01-01

Complexity, Analysis and Control of Singular Biological Systems follows the control of real-world biological systems at both ecological and phyisological levels concentrating on the application of now-extensively-investigated singular system theory. Much effort has recently been dedicated to the modelling and analysis of developing bioeconomic systems and the text establishes singular examples of these, showing how proper control can help to maintain sustainable economic development of biological resources. The book begins from the essentials of singular systems theory and bifurcations before tackling  the use of various forms of control in singular biological systems using examples including predator-prey relationships and viral vaccination and quarantine control. Researchers and graduate students studying the control of complex biological systems are shown how a variety of methods can be brought to bear and practitioners working with the economics of biological systems and their control will also find the ...

Biological Systems Thinking for Control Engineering Design

Directory of Open Access Journals (Sweden)

D. J. Murray-Smith

2004-01-01

Full Text Available Artificial neural networks and genetic algorithms are often quoted in discussions about the contribution of biological systems thinking to engineering design. This paper reviews work on the neuromuscular system, a field in which biological systems thinking could make specific contributions to the development and design of automatic control systems for mechatronics and robotics applications. The paper suggests some specific areas in which a better understanding of this biological control system could be expected to contribute to control engineering design methods in the future. Particular emphasis is given to the nonlinear nature of elements within the neuromuscular system and to processes of neural signal processing, sensing and system adaptivity. Aspects of the biological system that are of particular significance for engineering control systems include sensor fusion, sensor redundancy and parallelism, together with advanced forms of signal processing for adaptive and learning control. 

Network Analyses in Systems Biology: New Strategies for Dealing with Biological Complexity

DEFF Research Database (Denmark)

Green, Sara; Serban, Maria; Scholl, Raphael

2018-01-01

of biological networks using tools from graph theory to the application of dynamical systems theory to understand the behavior of complex biological systems. We show how network approaches support and extend traditional mechanistic strategies but also offer novel strategies for dealing with biological...... strategies? When and how can network and mechanistic approaches interact in productive ways? In this paper we address these questions by focusing on how biological networks are represented and analyzed in a diverse class of case studies. Our examples span from the investigation of organizational properties...

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.

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.

A system for success: BMC Systems Biology, a new open access journal.

Science.gov (United States)

Hodgkinson, Matt J; Webb, Penelope A

2007-09-04

BMC Systems Biology is the first open access journal spanning the growing field of systems biology from molecules up to ecosystems. The journal has launched as more and more institutes are founded that are similarly dedicated to this new approach. BMC Systems Biology builds on the ongoing success of the BMC series, providing a venue for all sound research in the systems-level analysis of biology.

Hierarchical structure of biological systems: a bioengineering approach.

Science.gov (United States)

Alcocer-Cuarón, Carlos; Rivera, Ana L; Castaño, Victor M

2014-01-01

A general theory of biological systems, based on few fundamental propositions, allows a generalization of both Wierner and Berthalanffy approaches to theoretical biology. Here, a biological system is defined as a set of self-organized, differentiated elements that interact pair-wise through various networks and media, isolated from other sets by boundaries. Their relation to other systems can be described as a closed loop in a steady-state, which leads to a hierarchical structure and functioning of the biological system. Our thermodynamical approach of hierarchical character can be applied to biological systems of varying sizes through some general principles, based on the exchange of energy information and/or mass from and within the systems.

An engineering design approach to systems biology.

Science.gov (United States)

Janes, Kevin A; Chandran, Preethi L; Ford, Roseanne M; Lazzara, Matthew J; Papin, Jason A; Peirce, Shayn M; Saucerman, Jeffrey J; Lauffenburger, Douglas A

2017-07-17

Measuring and modeling the integrated behavior of biomolecular-cellular networks is central to systems biology. Over several decades, systems biology has been shaped by quantitative biologists, physicists, mathematicians, and engineers in different ways. However, the basic and applied versions of systems biology are not typically distinguished, which blurs the separate aspirations of the field and its potential for real-world impact. Here, we articulate an engineering approach to systems biology, which applies educational philosophy, engineering design, and predictive models to solve contemporary problems in an age of biomedical Big Data. A concerted effort to train systems bioengineers will provide a versatile workforce capable of tackling the diverse challenges faced by the biotechnological and pharmaceutical sectors in a modern, information-dense economy.

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.

The Feasibility of Systems Thinking in Biology Education

Science.gov (United States)

Boersma, Kerst; Waarlo, Arend Jan; Klaassen, Kees

2011-01-01

Systems thinking in biology education is an up and coming research topic, as yet with contrasting feasibility claims. In biology education systems thinking can be understood as thinking backward and forward between concrete biological objects and processes and systems models representing systems theoretical characteristics. Some studies claim that…

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.

"Broadband" Bioinformatics Skills Transfer with the Knowledge Transfer Programme (KTP: Educational Model for Upliftment and Sustainable Development.

Directory of Open Access Journals (Sweden)

Emile R Chimusa

2015-11-01

Full Text Available A shortage of practical skills and relevant expertise is possibly the primary obstacle to social upliftment and sustainable development in Africa. The "omics" fields, especially genomics, are increasingly dependent on the effective interpretation of large and complex sets of data. Despite abundant natural resources and population sizes comparable with many first-world countries from which talent could be drawn, countries in Africa still lag far behind the rest of the world in terms of specialized skills development. Moreover, there are serious concerns about disparities between countries within the continent. The multidisciplinary nature of the bioinformatics field, coupled with rare and depleting expertise, is a critical problem for the advancement of bioinformatics in Africa. We propose a formalized matchmaking system, which is aimed at reversing this trend, by introducing the Knowledge Transfer Programme (KTP. Instead of individual researchers travelling to other labs to learn, researchers with desirable skills are invited to join African research groups for six weeks to six months. Visiting researchers or trainers will pass on their expertise to multiple people simultaneously in their local environments, thus increasing the efficiency of knowledge transference. In return, visiting researchers have the opportunity to develop professional contacts, gain industry work experience, work with novel datasets, and strengthen and support their ongoing research. The KTP develops a network with a centralized hub through which groups and individuals are put into contact with one another and exchanges are facilitated by connecting both parties with potential funding sources. This is part of the PLOS Computational Biology Education collection.

"Broadband" Bioinformatics Skills Transfer with the Knowledge Transfer Programme (KTP): Educational Model for Upliftment and Sustainable Development.

Science.gov (United States)

Chimusa, Emile R; Mbiyavanga, Mamana; Masilela, Velaphi; Kumuthini, Judit

2015-11-01

A shortage of practical skills and relevant expertise is possibly the primary obstacle to social upliftment and sustainable development in Africa. The "omics" fields, especially genomics, are increasingly dependent on the effective interpretation of large and complex sets of data. Despite abundant natural resources and population sizes comparable with many first-world countries from which talent could be drawn, countries in Africa still lag far behind the rest of the world in terms of specialized skills development. Moreover, there are serious concerns about disparities between countries within the continent. The multidisciplinary nature of the bioinformatics field, coupled with rare and depleting expertise, is a critical problem for the advancement of bioinformatics in Africa. We propose a formalized matchmaking system, which is aimed at reversing this trend, by introducing the Knowledge Transfer Programme (KTP). Instead of individual researchers travelling to other labs to learn, researchers with desirable skills are invited to join African research groups for six weeks to six months. Visiting researchers or trainers will pass on their expertise to multiple people simultaneously in their local environments, thus increasing the efficiency of knowledge transference. In return, visiting researchers have the opportunity to develop professional contacts, gain industry work experience, work with novel datasets, and strengthen and support their ongoing research. The KTP develops a network with a centralized hub through which groups and individuals are put into contact with one another and exchanges are facilitated by connecting both parties with potential funding sources. This is part of the PLOS Computational Biology Education collection.

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'…

BioQueue: a novel pipeline framework to accelerate bioinformatics analysis.

Science.gov (United States)

Yao, Li; Wang, Heming; Song, Yuanyuan; Sui, Guangchao

2017-10-15

With the rapid development of Next-Generation Sequencing, a large amount of data is now available for bioinformatics research. Meanwhile, the presence of many pipeline frameworks makes it possible to analyse these data. However, these tools concentrate mainly on their syntax and design paradigms, and dispatch jobs based on users' experience about the resources needed by the execution of a certain step in a protocol. As a result, it is difficult for these tools to maximize the potential of computing resources, and avoid errors caused by overload, such as memory overflow. Here, we have developed BioQueue, a web-based framework that contains a checkpoint before each step to automatically estimate the system resources (CPU, memory and disk) needed by the step and then dispatch jobs accordingly. BioQueue possesses a shell command-like syntax instead of implementing a new script language, which means most biologists without computer programming background can access the efficient queue system with ease. BioQueue is freely available at https://github.com/liyao001/BioQueue. The extensive documentation can be found at http://bioqueue.readthedocs.io. li_yao@outlook.com or gcsui@nefu.edu.cn. 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

Answering biological questions: Querying a systems biology database for nutrigenomics

NARCIS (Netherlands)

Evelo, C.T.; Bochove, K. van; Saito, J.T.

2011-01-01

The requirement of systems biology for connecting different levels of biological research leads directly to a need for integrating vast amounts of diverse information in general and of omics data in particular. The nutritional phenotype database addresses this challenge for nutrigenomics. A

Handling Gene and Protein Names in the Age of Bioinformatics: The Special Challenge of Secreted Multimodular Bacterial Enzymes such as the cbhA/cbh9A Gene of Clostridium thermocellum

Energy Technology Data Exchange (ETDEWEB)

Brunecky, Roman [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Schwarz, Wolfgang H. [Technical University of Munich; Broeker, Jannis [Technical University of Munich; Liebl, Wolfgang [Technical University of Munich; Zverlov, Vladimir V. [Technical University of Munich; Russian Academy of Science

2018-02-26

An increasing number of researchers working in biology, biochemistry, biotechnology, bioengineering, bioinformatics and other related fields of science are using biological molecules. As the scientific background of the members of different scientific communities is more diverse than ever before, the number of scientists not familiar with the rules for non-ambiguous designation of genetic elements is increasing. However, with biological molecules gaining importance through biotechnology, their functional and unambiguous designation is vital. Unfortunately, naming genes and proteins is not an easy task. In addition, the traditional concepts of bioinformatics are challenged with the appearance of proteins comprising different modules with a respective function in each module. This article highlights basic rules and novel solutions in designation recently used within the community of bacterial geneticists, and we discuss the present-day handling of gene and protein designations. As an example we will utilize a recent mischaracterization of gene nomenclature. We make suggestions for better handling of names in future literature as well as in databases and annotation projects. Our methodology emphasizes the hydrolytic function of multi-modular genes and extracellular proteins from bacteria.

Interactomes, manufacturomes and relational biology: analogies between systems biology and manufacturing systems

Science.gov (United States)

2011-01-01

Background We review and extend the work of Rosen and Casti who discuss category theory with regards to systems biology and manufacturing systems, respectively. Results We describe anticipatory systems, or long-range feed-forward chemical reaction chains, and compare them to open-loop manufacturing processes. We then close the loop by discussing metabolism-repair systems and describe the rationality of the self-referential equation f = f (f). This relationship is derived from some boundary conditions that, in molecular systems biology, can be stated as the cardinality of the following molecular sets must be about equal: metabolome, genome, proteome. We show that this conjecture is not likely correct so the problem of self-referential mappings for describing the boundary between living and nonliving systems remains an open question. We calculate a lower and upper bound for the number of edges in the molecular interaction network (the interactome) for two cellular organisms and for two manufacturomes for CMOS integrated circuit manufacturing. Conclusions We show that the relevant mapping relations may not be Abelian, and that these problems cannot yet be resolved because the interactomes and manufacturomes are incomplete. PMID:21689427

Network biology: Describing biological systems by complex networks. Comment on "Network science of biological systems at different scales: A review" by M. Gosak et al.

Science.gov (United States)

Jalili, Mahdi

2018-03-01

I enjoyed reading Gosak et al. review on analysing biological systems from network science perspective [1]. Network science, first started within Physics community, is now a mature multidisciplinary field of science with many applications ranging from Ecology to biology, medicine, social sciences, engineering and computer science. Gosak et al. discussed how biological systems can be modelled and described by complex network theory which is an important application of network science. Although there has been considerable progress in network biology over the past two decades, this is just the beginning and network science has a great deal to offer to biology and medical sciences.

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.

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.

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…

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…

Neuroproteomics and Systems Biology Approach to Identify Temporal Biomarker Changes Post Experimental Traumatic Brain Injury in Rats

Directory of Open Access Journals (Sweden)

Firas H Kobeissy

2016-11-01

Full Text Available Traumatic brain injury (TBI represents a critical health problem of which diagnosis, management and treatment remain challenging. TBI is a contributing factor in approximately 1/3 of all injury-related deaths in the United States. The Centers for Disease Control and Prevention (CDC estimate that 1.7 million TBI people suffer a TBI in the United States annually. Efforts continue to focus on elucidating the complex molecular mechanisms underlying TBI pathophysiology and defining sensitive and specific biomarkers that can aid in improving patient management and care. Recently, the area of neuroproteomics-systems biology is proving to be a prominent tool in biomarker discovery for central nervous system (CNS injury and other neurological diseases. In this work, we employed the controlled cortical impact (CCI model of experimental TBI in rat model to assess the temporal-global proteome changes after acute (1 day and for the first time, subacute (7 days, post-injury time frame using the established CAX-PAGE LC-MS/MS platform for protein separation combined with discrete systems biology analyses to identify temporal biomarker changes related to this rat TBI model. Rather than focusing on any one individual molecular entities, we used in silico systems biology approach to understand the global dynamics that govern proteins that are differentially altered post-injury. In addition, gene ontology analysis of the proteomic data was conducted in order to categorize the proteins by molecular function, biological process, and cellular localization. Results show alterations in several proteins related to inflammatory responses and oxidative stress in both acute (1 day and subacute (7 days periods post TBI. Moreover, results suggest a differential upregulation of neuroprotective proteins at 7-days post-CCI involved in cellular functions such as neurite growth, regeneration, and axonal guidance. Our study is amongst the first to assess temporal neuroproteome

Integrative radiation systems biology

International Nuclear Information System (INIS)

Unger, Kristian

2014-01-01