Sample records for bioinformatics
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Bioinformatics: indispensable, yet hidden in plain sight?
Bartlett, Andrew; Penders, Bart; Lewis, Jamie
2017-06-21
Bioinformatics has multitudinous identities, organisational alignments and disciplinary links. This variety allows bioinformaticians and bioinformatic work to contribute to much (if not most) of life science research in profound ways. The multitude of bioinformatic work also translates into a multitude of credit-distribution arrangements, apparently dismissing that work. We report on the epistemic and social arrangements that characterise the relationship between bioinformatics and life science. We describe, in sociological terms, the character, power and future of bioinformatic work. The character of bioinformatic work is such that its cultural, institutional and technical structures allow for it to be black-boxed easily. The result is that bioinformatic expertise and contributions travel easily and quickly, yet remain largely uncredited. The power of bioinformatic work is shaped by its dependency on life science work, which combined with the black-boxed character of bioinformatic expertise further contributes to situating bioinformatics on the periphery of the life sciences. Finally, the imagined futures of bioinformatic work suggest that bioinformatics will become ever more indispensable without necessarily becoming more visible, forcing bioinformaticians into difficult professional and career choices. Bioinformatic expertise and labour is epistemically central but often institutionally peripheral. In part, this is a result of the ways in which the character, power distribution and potential futures of bioinformatics are constituted. However, alternative paths can be imagined.
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Navigating the changing learning landscape: perspective from bioinformatics.ca
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 Bioinformatics training programs that solely rely on traditional didactic methods are being superseded by these newer resources.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 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. PMID:23515468
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Towards a career in bioinformatics
2009-01-01
The 2009 annual conference of the Asia Pacific Bioinformatics Network (APBioNet), Asia's oldest bioinformatics organisation from 1998, was organized as the 8th International Conference on Bioinformatics (InCoB), Sept. 9-11, 2009 at Biopolis, Singapore. InCoB has actively engaged researchers from the area of life sciences, systems biology and clinicians, to facilitate greater synergy between these groups. To encourage bioinformatics students and new researchers, tutorials and student symposium, the Singapore Symposium on Computational Biology (SYMBIO) were organized, along with the Workshop on Education in Bioinformatics and Computational Biology (WEBCB) and the Clinical Bioinformatics (CBAS) Symposium. However, to many students and young researchers, pursuing a career in a multi-disciplinary area such as bioinformatics poses a Himalayan challenge. A collection to tips is presented here to provide signposts on the road to a career in bioinformatics. An overview of the application of bioinformatics to traditional and emerging areas, published in this supplement, is also presented to provide possible future avenues of bioinformatics investigation. A case study on the application of e-learning tools in undergraduate bioinformatics curriculum provides information on how to go impart targeted education, to sustain bioinformatics in the Asia-Pacific region. The next InCoB is scheduled to be held in Tokyo, Japan, Sept. 26-28, 2010. PMID:19958508
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Towards a career in bioinformatics.
Ranganathan, Shoba
2009-12-03
The 2009 annual conference of the Asia Pacific Bioinformatics Network (APBioNet), Asia's oldest bioinformatics organisation from 1998, was organized as the 8th International Conference on Bioinformatics (InCoB), Sept. 9-11, 2009 at Biopolis, Singapore. InCoB has actively engaged researchers from the area of life sciences, systems biology and clinicians, to facilitate greater synergy between these groups. To encourage bioinformatics students and new researchers, tutorials and student symposium, the Singapore Symposium on Computational Biology (SYMBIO) were organized, along with the Workshop on Education in Bioinformatics and Computational Biology (WEBCB) and the Clinical Bioinformatics (CBAS) Symposium. However, to many students and young researchers, pursuing a career in a multi-disciplinary area such as bioinformatics poses a Himalayan challenge. A collection to tips is presented here to provide signposts on the road to a career in bioinformatics. An overview of the application of bioinformatics to traditional and emerging areas, published in this supplement, is also presented to provide possible future avenues of bioinformatics investigation. A case study on the application of e-learning tools in undergraduate bioinformatics curriculum provides information on how to go impart targeted education, to sustain bioinformatics in the Asia-Pacific region. The next InCoB is scheduled to be held in Tokyo, Japan, Sept. 26-28, 2010.
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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 < 4.5 × 10(-29)). The 20-year trend in the average JIF between the two groups suggests the gap does not appear to be significantly narrowing. For a sampling of the journals producing top 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.
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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.
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Schönbach, Christian; Verma, Chandra; Bond, Peter J; Ranganathan, Shoba
2016-12-22
The International Conference on Bioinformatics (InCoB) has been publishing peer-reviewed conference papers in BMC Bioinformatics since 2006. Of the 44 articles accepted for publication in supplement issues of BMC Bioinformatics, BMC Genomics, BMC Medical Genomics and BMC Systems Biology, 24 articles with a bioinformatics or systems biology focus are reviewed in this editorial. InCoB2017 is scheduled to be held in Shenzen, China, September 20-22, 2017.
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Is there room for ethics within bioinformatics education?
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.
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Cancer Bioinformatics for Updating Anticancer Drug Developments and Personalized Therapeutics.
Lu, Da-Yong; Qu, Rong-Xin; Lu, Ting-Ren; Wu, Hong-Ying
2017-01-01
Last two to three decades, this world witnesses a rapid progress of biomarkers and bioinformatics technologies. Cancer bioinformatics is one of such important omics branches for experimental/clinical studies and applications. Same as other biological techniques or systems, bioinformatics techniques will be widely used. But they are presently not omni-potent. Despite great popularity and improvements, cancer bioinformatics has its own limitations and shortcomings at this stage of technical advancements. This article will offer a panorama of bioinformatics in cancer researches and clinical therapeutic applications-possible advantages and limitations relating to cancer therapeutics. A lot of beneficial capabilities and outcomes have been described. As a result, a successful new era for cancer bioinformatics is waiting for us if we can adhere on scientific studies of cancer bioinformatics in malignant- origin mining, medical verifications and clinical diagnostic applications. Cancer bioinformatics gave a great significance in disease diagnosis and therapeutic predictions. Many creative ideas and future perspectives are highlighted. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.
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Taleyarkhan, Manaz; Alvarado, Daniela Rivera; Kane, Michael; Springer, John; Clase, Kari
2014-01-01
Bioinformatics education can be broadly defined as the teaching and learning of the use of computer and information technology, along with mathematical and statistical analysis for gathering, storing, analyzing, interpreting, and integrating data to solve biological problems. The recent surge of genomics, proteomics, and structural biology in the potential advancement of research and development in complex biomedical systems has created a need for an educated workforce in bioinformatics. However, effectively integrating bioinformatics education through formal and informal educational settings has been a challenge due in part to its cross-disciplinary nature. In this article, we seek to provide an overview of the state of bioinformatics education. This article identifies: 1) current approaches of bioinformatics education at the undergraduate and graduate levels; 2) the most common concepts and skills being taught in bioinformatics education; 3) pedagogical approaches and methods of delivery for conveying bioinformatics concepts and skills; and 4) assessment results on the impact of these programs, approaches, and methods in students’ attitudes or learning. Based on these findings, it is our goal to describe the landscape of scholarly work in this area and, as a result, identify opportunities and challenges in bioinformatics education. PMID:25452484
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Rein, Diane C.
2006-01-01
Setting: 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. Program Components: 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. Evaluation Mechanisms: 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. Next Steps/Future Directions: 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. PMID:16888666
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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.
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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 study, we deliberately integrated bioinformatics instruction at multiple course levels into an existing biology curriculum. Students in an introductory biology course, intermediate lab courses, and advanced project-oriented courses all participated in new course components designed to sequentially introduce bioinformatics skills and knowledge, as well as computational approaches that are common to many bioinformatics applications. In each course, bioinformatics learning was embedded in an existing disciplinary instructional sequence, as opposed to having a single course where all bioinformatics learning occurs. We designed direct and indirect assessment tools to follow student progress through the course sequence. Our data show significant gains in both student confidence and ability in bioinformatics during individual courses and as course level increases. Despite evidence of substantial student learning in both bioinformatics and mathematics, students were skeptical about the link between learning bioinformatics and learning mathematics. While our approach resulted in substantial learning gains, student "buy-in" and engagement might be better in longer project-based activities that demand application of skills to research problems. Nevertheless, in situations where a concentrated focus on project-oriented bioinformatics is not possible or desirable, our approach of integrating multiple smaller components into an existing curriculum provides an alternative. Copyright © 2012 Wiley Periodicals, Inc.
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Continuing Education Workshops in Bioinformatics Positively Impact Research and Careers
Brazas, Michelle D.; Ouellette, B. F. Francis
2016-01-01
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. PMID:27281025
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Continuing Education Workshops in Bioinformatics Positively Impact Research and Careers.
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.
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Bioinformatics research in the Asia Pacific: a 2007 update.
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.
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Emerging strengths in Asia Pacific bioinformatics.
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.
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Emerging strengths in Asia Pacific bioinformatics
Ranganathan, Shoba; Hsu, Wen-Lian; Yang, Ueng-Cheng; Tan, Tin Wee
2008-01-01
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. PMID:19091008
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Extending Asia Pacific bioinformatics into new realms in the "-omics" era.
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.
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Lo, Chien-Chi
2015-08-03
Edge Bioinformatics is a developmental bioinformatics and data management platform which seeks to supply laboratories with bioinformatics pipelines for analyzing data associated with common samples case goals. Edge Bioinformatics enables sequencing as a solution and forward-deployed situations where human-resources, space, bandwidth, and time are limited. The Edge bioinformatics pipeline was designed based on following USE CASES and specific to illumina sequencing reads. 1. Assay performance adjudication (PCR): Analysis of an existing PCR assay in a genomic context, and automated design of a new assay to resolve conflicting results; 2. Clinical presentation with extreme symptoms: Characterization of a known pathogen ormore » co-infection with a. Novel emerging disease outbreak or b. Environmental surveillance« less
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Bioinformatics goes back to the future.
Miller, Crispin J; Attwood, Teresa K
2003-02-01
The need to turn raw data into knowledge has led the bioinformatics field to focus increasingly on the manipulation of information. By drawing parallels with both cryptography and artificial intelligence, we can develop an understanding of the changes that are occurring in bioinformatics, and how these changes are likely to influence the bioinformatics job market.
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ERIC Educational Resources Information Center
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'…
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ERIC Educational Resources Information Center
Miskowski, Jennifer A.; Howard, David R.; Abler, Michael L.; Grunwald, Sandra K.
2007-01-01
Over the past 10 years, there has been a technical revolution in the life sciences leading to the emergence of a new discipline called bioinformatics. In response, bioinformatics-related topics have been incorporated into various undergraduate courses along with the development of new courses solely focused on bioinformatics. This report describes…
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Component-Based Approach for Educating Students in Bioinformatics
ERIC Educational Resources Information Center
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…
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ERIC Educational Resources Information Center
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…
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ERIC Educational Resources Information Center
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.…
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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.
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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. PMID:25996054
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Computational biology and bioinformatics in Nigeria.
Fatumo, Segun A; Adoga, Moses P; Ojo, Opeolu O; Oluwagbemi, Olugbenga; Adeoye, Tolulope; Ewejobi, Itunuoluwa; Adebiyi, Marion; Adebiyi, Ezekiel; Bewaji, Clement; Nashiru, Oyekanmi
2014-04-01
Over the past few decades, major advances in the field of molecular biology, coupled with advances in genomic technologies, have led to an explosive growth in the biological data generated by the scientific community. The critical need to process and analyze such a deluge of data and turn it into useful knowledge has caused bioinformatics to gain prominence and importance. Bioinformatics is an interdisciplinary research area that applies techniques, methodologies, and tools in computer and information science to solve biological problems. In Nigeria, bioinformatics has recently played a vital role in the advancement of biological sciences. As a developing country, the importance of bioinformatics is rapidly gaining acceptance, and bioinformatics groups comprised of biologists, computer scientists, and computer engineers are being constituted at Nigerian universities and research institutes. In this article, we present an overview of bioinformatics education and research in Nigeria. We also discuss professional societies and academic and research institutions that play central roles in advancing the discipline in Nigeria. Finally, we propose strategies that can bolster bioinformatics education and support from policy makers in Nigeria, with potential positive implications for other developing countries.
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Computational Biology and Bioinformatics in Nigeria
Fatumo, Segun A.; Adoga, Moses P.; Ojo, Opeolu O.; Oluwagbemi, Olugbenga; Adeoye, Tolulope; Ewejobi, Itunuoluwa; Adebiyi, Marion; Adebiyi, Ezekiel; Bewaji, Clement; Nashiru, Oyekanmi
2014-01-01
Over the past few decades, major advances in the field of molecular biology, coupled with advances in genomic technologies, have led to an explosive growth in the biological data generated by the scientific community. The critical need to process and analyze such a deluge of data and turn it into useful knowledge has caused bioinformatics to gain prominence and importance. Bioinformatics is an interdisciplinary research area that applies techniques, methodologies, and tools in computer and information science to solve biological problems. In Nigeria, bioinformatics has recently played a vital role in the advancement of biological sciences. As a developing country, the importance of bioinformatics is rapidly gaining acceptance, and bioinformatics groups comprised of biologists, computer scientists, and computer engineers are being constituted at Nigerian universities and research institutes. In this article, we present an overview of bioinformatics education and research in Nigeria. We also discuss professional societies and academic and research institutions that play central roles in advancing the discipline in Nigeria. Finally, we propose strategies that can bolster bioinformatics education and support from policy makers in Nigeria, with potential positive implications for other developing countries. PMID:24763310
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NASA Astrophysics Data System (ADS)
Symeonidis, Iphigenia Sofia
This paper aims to elucidate guiding concepts for the design of powerful undergraduate bioinformatics degrees which will lead to a conceptual framework for the curriculum. "Powerful" here should be understood as having truly bioinformatics objectives rather than enrichment of existing computer science or life science degrees on which bioinformatics degrees are often based. As such, the conceptual framework will be one which aims to demonstrate intellectual honesty in regards to the field of bioinformatics. A synthesis/conceptual analysis approach was followed as elaborated by Hurd (1983). The approach takes into account the following: bioinfonnatics educational needs and goals as expressed by different authorities, five undergraduate bioinformatics degrees case-studies, educational implications of bioinformatics as a technoscience and approaches to curriculum design promoting interdisciplinarity and integration. Given these considerations, guiding concepts emerged and a conceptual framework was elaborated. The practice of bioinformatics was given a closer look, which led to defining tool-integration skills and tool-thinking capacity as crucial areas of the bioinformatics activities spectrum. It was argued, finally, that a process-based curriculum as a variation of a concept-based curriculum (where the concepts are processes) might be more conducive to the teaching of bioinformatics given a foundational first year of integrated science education as envisioned by Bialek and Botstein (2004). Furthermore, the curriculum design needs to define new avenues of communication and learning which bypass the traditional disciplinary barriers of academic settings as undertaken by Tador and Tidmor (2005) for graduate studies.
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Bioinformatics core competencies for undergraduate life sciences education.
Wilson Sayres, Melissa A; Hauser, Charles; Sierk, Michael; Robic, Srebrenka; Rosenwald, Anne G; Smith, Todd M; Triplett, Eric W; Williams, Jason J; Dinsdale, Elizabeth; Morgan, William R; Burnette, James M; Donovan, Samuel S; Drew, Jennifer C; Elgin, Sarah C R; Fowlks, Edison R; Galindo-Gonzalez, Sebastian; Goodman, Anya L; Grandgenett, Nealy F; Goller, Carlos C; Jungck, John R; Newman, Jeffrey D; Pearson, William; Ryder, Elizabeth F; Tosado-Acevedo, Rafael; Tapprich, William; Tobin, Tammy C; Toro-Martínez, Arlín; Welch, Lonnie R; Wright, Robin; Barone, Lindsay; Ebenbach, David; McWilliams, Mindy; Olney, Kimberly C; Pauley, Mark A
2018-01-01
Although bioinformatics is becoming increasingly central to research in the life sciences, bioinformatics skills and knowledge are not well integrated into undergraduate biology education. This curricular gap prevents biology students from harnessing the full potential of their education, limiting their career opportunities and slowing research innovation. To advance the integration of bioinformatics into life sciences education, a framework of core bioinformatics competencies is needed. To that end, we here report the results of a survey of biology faculty in the United States about teaching bioinformatics to undergraduate life scientists. Responses were received from 1,260 faculty representing institutions in all fifty states with a combined capacity to educate hundreds of thousands of students every year. Results indicate strong, widespread agreement that bioinformatics knowledge and skills are critical for undergraduate life scientists as well as considerable agreement about which skills are necessary. Perceptions of the importance of some skills varied with the respondent's degree of training, time since degree earned, and/or the Carnegie Classification of the respondent's institution. To assess which skills are currently being taught, we analyzed syllabi of courses with bioinformatics content submitted by survey respondents. Finally, we used the survey results, the analysis of the syllabi, and our collective research and teaching expertise to develop a set of bioinformatics core competencies for undergraduate biology students. These core competencies are intended to serve as a guide for institutions as they work to integrate bioinformatics into their life sciences curricula.
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Bioinformatics core competencies for undergraduate life sciences education
Wilson Sayres, Melissa A.; Hauser, Charles; Sierk, Michael; Robic, Srebrenka; Rosenwald, Anne G.; Smith, Todd M.; Triplett, Eric W.; Williams, Jason J.; Dinsdale, Elizabeth; Morgan, William R.; Burnette, James M.; Donovan, Samuel S.; Drew, Jennifer C.; Elgin, Sarah C. R.; Fowlks, Edison R.; Galindo-Gonzalez, Sebastian; Goodman, Anya L.; Grandgenett, Nealy F.; Goller, Carlos C.; Jungck, John R.; Newman, Jeffrey D.; Pearson, William; Ryder, Elizabeth F.; Tosado-Acevedo, Rafael; Tapprich, William; Tobin, Tammy C.; Toro-Martínez, Arlín; Welch, Lonnie R.; Wright, Robin; Ebenbach, David; McWilliams, Mindy; Olney, Kimberly C.
2018-01-01
Although bioinformatics is becoming increasingly central to research in the life sciences, bioinformatics skills and knowledge are not well integrated into undergraduate biology education. This curricular gap prevents biology students from harnessing the full potential of their education, limiting their career opportunities and slowing research innovation. To advance the integration of bioinformatics into life sciences education, a framework of core bioinformatics competencies is needed. To that end, we here report the results of a survey of biology faculty in the United States about teaching bioinformatics to undergraduate life scientists. Responses were received from 1,260 faculty representing institutions in all fifty states with a combined capacity to educate hundreds of thousands of students every year. Results indicate strong, widespread agreement that bioinformatics knowledge and skills are critical for undergraduate life scientists as well as considerable agreement about which skills are necessary. Perceptions of the importance of some skills varied with the respondent’s degree of training, time since degree earned, and/or the Carnegie Classification of the respondent’s institution. To assess which skills are currently being taught, we analyzed syllabi of courses with bioinformatics content submitted by survey respondents. Finally, we used the survey results, the analysis of the syllabi, and our collective research and teaching expertise to develop a set of bioinformatics core competencies for undergraduate biology students. These core competencies are intended to serve as a guide for institutions as they work to integrate bioinformatics into their life sciences curricula. PMID:29870542
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Report on the EMBER Project--A European Multimedia Bioinformatics Educational Resource
ERIC Educational Resources Information Center
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…
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The 2017 Bioinformatics Open Source Conference (BOSC)
Harris, Nomi L.; Cock, Peter J.A.; Chapman, Brad; Fields, Christopher J.; Hokamp, Karsten; Lapp, Hilmar; Munoz-Torres, Monica; Tzovaras, Bastian Greshake; Wiencko, Heather
2017-01-01
The Bioinformatics Open Source Conference (BOSC) is a 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. The 18th annual BOSC ( http://www.open-bio.org/wiki/BOSC_2017) took place in Prague, Czech Republic in July 2017. The conference brought together nearly 250 bioinformatics researchers, developers and users of open source software to interact and share ideas about standards, bioinformatics software development, open and reproducible science, and this year’s theme, open data. As in previous years, the conference was preceded by a two-day collaborative coding event open to the bioinformatics community, called the OBF Codefest. PMID:29118973
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The 2017 Bioinformatics Open Source Conference (BOSC).
Harris, Nomi L; Cock, Peter J A; Chapman, Brad; Fields, Christopher J; Hokamp, Karsten; Lapp, Hilmar; Munoz-Torres, Monica; Tzovaras, Bastian Greshake; Wiencko, Heather
2017-01-01
The Bioinformatics Open Source Conference (BOSC) is a 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. The 18th annual BOSC ( http://www.open-bio.org/wiki/BOSC_2017) took place in Prague, Czech Republic in July 2017. The conference brought together nearly 250 bioinformatics researchers, developers and users of open source software to interact and share ideas about standards, bioinformatics software development, open and reproducible science, and this year's theme, open data. As in previous years, the conference was preceded by a two-day collaborative coding event open to the bioinformatics community, called the OBF Codefest.
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Rising Strengths Hong Kong SAR in Bioinformatics.
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.
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Evolving from bioinformatics in-the-small to bioinformatics in-the-large.
Parker, D Stott; Gorlick, Michael M; Lee, Christopher J
2003-01-01
We argue the significance of a fundamental shift in bioinformatics, from in-the-small to in-the-large. Adopting a large-scale perspective is a way to manage the problems endemic to the world of the small-constellations of incompatible tools for which the effort required to assemble an integrated system exceeds the perceived benefit of the integration. Where bioinformatics in-the-small is about data and tools, bioinformatics in-the-large is about metadata and dependencies. Dependencies represent the complexities of large-scale integration, including the requirements and assumptions governing the composition of tools. The popular make utility is a very effective system for defining and maintaining simple dependencies, and it offers a number of insights about the essence of bioinformatics in-the-large. Keeping an in-the-large perspective has been very useful to us in large bioinformatics projects. We give two fairly different examples, and extract lessons from them showing how it has helped. These examples both suggest the benefit of explicitly defining and managing knowledge flows and knowledge maps (which represent metadata regarding types, flows, and dependencies), and also suggest approaches for developing bioinformatics database systems. Generally, we argue that large-scale engineering principles can be successfully adapted from disciplines such as software engineering and data management, and that having an in-the-large perspective will be a key advantage in the next phase of bioinformatics development.
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Bioinformatics education dissemination with an evolutionary problem solving perspective.
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.
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Bioinformatics education in India.
Kulkarni-Kale, Urmila; Sawant, Sangeeta; Chavan, Vishwas
2010-11-01
An account of bioinformatics education in India is presented along with future prospects. Establishment of BTIS network by Department of Biotechnology (DBT), Government of India in the 1980s had been a systematic effort in the development of bioinformatics infrastructure in India to provide services to scientific community. Advances in the field of bioinformatics underpinned the need for well-trained professionals with skills in information technology and biotechnology. As a result, programmes for capacity building in terms of human resource development were initiated. Educational programmes gradually evolved from the organisation of short-term workshops to the institution of formal diploma/degree programmes. A case study of the Master's degree course offered at the Bioinformatics Centre, University of Pune is discussed. Currently, many universities and institutes are offering bioinformatics courses at different levels with variations in the course contents and degree of detailing. BioInformatics National Certification (BINC) examination initiated in 2005 by DBT provides a common yardstick to assess the knowledge and skill sets of students passing out of various institutions. The potential for broadening the scope of bioinformatics to transform it into a data intensive discovery discipline is discussed. This necessitates introduction of amendments in the existing curricula to accommodate the upcoming developments.
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Kang, Jonghoon; Park, Seyeon; Venkat, Aarya; Gopinath, Adarsh
2015-12-01
New interdisciplinary biological sciences like bioinformatics, biophysics, and systems biology have become increasingly relevant in modern science. Many papers have suggested the importance of adding these subjects, particularly bioinformatics, to an undergraduate curriculum; however, most of their assertions have relied on qualitative arguments. In this paper, we will show our metadata analysis of a scientific literature database (PubMed) that quantitatively describes the importance of the subjects of bioinformatics, systems biology, and biophysics as compared with a well-established interdisciplinary subject, biochemistry. Specifically, we found that the development of each subject assessed by its publication volume was well described by a set of simple nonlinear equations, allowing us to characterize them quantitatively. Bioinformatics, which had the highest ratio of publications produced, was predicted to grow between 77% and 93% by 2025 according to the model. Due to the large number of publications produced in bioinformatics, which nearly matches the number published in biochemistry, it can be inferred that bioinformatics is almost equal in significance to biochemistry. Based on our analysis, we suggest that bioinformatics be added to the standard biology undergraduate curriculum. Adding this course to an undergraduate curriculum will better prepare students for future research in biology.
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A Web-based assessment of bioinformatics end-user support services at US universities.
Messersmith, Donna J; Benson, Dennis A; Geer, Renata C
2006-07-01
This study was conducted to gauge the availability of bioinformatics end-user support services at US universities and to identify the providers of those services. The study primarily focused on the availability of short-term workshops that introduce users to molecular biology databases and analysis software. Websites of selected US universities were reviewed to determine if bioinformatics educational workshops were offered, and, if so, what organizational units in the universities provided them. Of 239 reviewed universities, 72 (30%) offered bioinformatics educational workshops. These workshops were located at libraries (N = 15), bioinformatics centers (N = 38), or other facilities (N = 35). No such training was noted on the sites of 167 universities (70%). Of the 115 bioinformatics centers identified, two-thirds did not offer workshops. This analysis of university Websites indicates that a gap may exist in the availability of workshops and related training to assist researchers in the use of bioinformatics resources, representing a potential opportunity for libraries and other facilities to provide training and assistance for this growing user group.
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Bioinformatics Goes to School—New Avenues for Teaching Contemporary Biology
Wood, Louisa; Gebhardt, Philipp
2013-01-01
Since 2010, the European Molecular Biology Laboratory's (EMBL) Heidelberg laboratory and the European Bioinformatics Institute (EMBL-EBI) have jointly run bioinformatics training courses developed specifically for secondary school science teachers within Europe and EMBL member states. These courses focus on introducing bioinformatics, databases, and data-intensive biology, allowing participants to explore resources and providing classroom-ready materials to support them in sharing this new knowledge with their students. In this article, we chart our progress made in creating and running three bioinformatics training courses, including how the course resources are received by participants and how these, and bioinformatics in general, are subsequently used in the classroom. We assess the strengths and challenges of our approach, and share what we have learned through our interactions with European science teachers. PMID:23785266
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The 2016 Bioinformatics Open Source Conference (BOSC).
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.
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Bioinformatics clouds for big data manipulation.
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.
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NASA Astrophysics Data System (ADS)
Wefer, Stephen H.
The proliferation of bioinformatics in modern Biology marks a new revolution in science, which promises to influence science education at all levels. This thesis examined state standards for content that articulated bioinformatics, and explored secondary students' affective and cognitive perceptions of, and performance in, a bioinformatics mini-unit. The results are presented as three studies. The first study analyzed secondary science standards of 49 U.S States (Iowa has no science framework) and the District of Columbia for content related to bioinformatics at the introductory high school biology level. The bionformatics content of each state's Biology standards were categorized into nine areas and the prevalence of each area documented. The nine areas were: The Human Genome Project, Forensics, Evolution, Classification, Nucleotide Variations, Medicine, Computer Use, Agriculture/Food Technology, and Science Technology and Society/Socioscientific Issues (STS/SSI). Findings indicated a generally low representation of bioinformatics related content, which varied substantially across the different areas. Recommendations are made for reworking existing standards to incorporate bioinformatics and to facilitate the goal of promoting science literacy in this emerging new field among secondary school students. The second study examined thirty-two students' affective responses to, and content mastery of, a two-week bioinformatics mini-unit. The findings indicate that the students generally were positive relative to their interest level, the usefulness of the lessons, the difficulty level of the lessons, likeliness to engage in additional bioinformatics, and were overall successful on the assessments. A discussion of the results and significance is followed by suggestions for future research and implementation for transferability. The third study presents a case study of individual differences among ten secondary school students, whose cognitive and affective percepts were analyzed in relation to their experience in learning a bioinformatics mini-unit. There were distinct individual differences among the participants, especially in the way they processed information and integrated procedural and analytical thought during bioinformatics learning. These differences may provide insights into some of the specific needs of students that educators and curriculum designers should consider when designing bioinformatics learning experiences. Implications for teacher education and curriculum design are presented in addition to some suggestions for further research.
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Bioinformatics clouds for big data manipulation
2012-01-01
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. PMID:23190475
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The 2016 Bioinformatics Open Source Conference (BOSC)
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. PMID:27781083
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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.
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The 2015 Bioinformatics Open Source Conference (BOSC 2015).
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.
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Fang, Xiang; Li, Ning-qiu; Fu, Xiao-zhe; Li, Kai-bin; Lin, Qiang; Liu, Li-hui; Shi, Cun-bin; Wu, Shu-qin
2015-07-01
As a key component of life science, bioinformatics has been widely applied in genomics, transcriptomics, and proteomics. However, the requirement of high-performance computers rather than common personal computers for constructing a bioinformatics platform significantly limited the application of bioinformatics in aquatic science. In this study, we constructed a bioinformatic analysis platform for aquatic pathogen based on the MilkyWay-2 supercomputer. The platform consisted of three functional modules, including genomic and transcriptomic sequencing data analysis, protein structure prediction, and molecular dynamics simulations. To validate the practicability of the platform, we performed bioinformatic analysis on aquatic pathogenic organisms. For example, genes of Flavobacterium johnsoniae M168 were identified and annotated via Blast searches, GO and InterPro annotations. Protein structural models for five small segments of grass carp reovirus HZ-08 were constructed by homology modeling. Molecular dynamics simulations were performed on out membrane protein A of Aeromonas hydrophila, and the changes of system temperature, total energy, root mean square deviation and conformation of the loops during equilibration were also observed. These results showed that the bioinformatic analysis platform for aquatic pathogen has been successfully built on the MilkyWay-2 supercomputer. This study will provide insights into the construction of bioinformatic analysis platform for other subjects.
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Buying in to bioinformatics: an introduction to commercial sequence analysis software
2015-01-01
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. PMID:25183247
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Buying in to bioinformatics: an introduction to commercial sequence analysis software.
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.
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H3ABioNet, a sustainable pan-African bioinformatics network for human heredity and health in Africa
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
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InCoB2012 Conference: from biological data to knowledge to technological breakthroughs
2012-01-01
Ten years ago when Asia-Pacific Bioinformatics Network held the first International Conference on Bioinformatics (InCoB) in Bangkok its theme was North-South Networking. At that time InCoB aimed to provide biologists and bioinformatics researchers in the Asia-Pacific region a forum to meet, interact with, and disseminate knowledge about the burgeoning field of bioinformatics. Meanwhile InCoB has evolved into a major regional bioinformatics conference that attracts not only talented and established scientists from the region but increasingly also from East Asia, North America and Europe. Since 2006 InCoB yielded 114 articles in BMC Bioinformatics supplement issues that have been cited nearly 1,000 times to date. In part, these developments reflect the success of bioinformatics education and continuous efforts to integrate and utilize bioinformatics in biotechnology and biosciences in the Asia-Pacific region. A cross-section of research leading from biological data to knowledge and to technological applications, the InCoB2012 theme, is introduced in this editorial. Other highlights included sessions organized by the Pan-Asian Pacific Genome Initiative and a Machine Learning in Immunology competition. InCoB2013 is scheduled for September 18-21, 2013 at Suzhou, China. PMID:23281929
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OpenHelix: bioinformatics education outside of a different box.
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.
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OpenHelix: bioinformatics education outside of a different box
Mangan, Mary E.; Perreault-Micale, Cynthia; Lathe, Scott; Sirohi, Neeraj; Lathe, Warren C.
2010-01-01
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. PMID:20798181
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Translational bioinformatics: linking the molecular world to the clinical world.
Altman, R B
2012-06-01
Translational bioinformatics represents the union of translational medicine and bioinformatics. Translational medicine moves basic biological discoveries from the research bench into the patient-care setting and uses clinical observations to inform basic biology. It focuses on patient care, including the creation of new diagnostics, prognostics, prevention strategies, and therapies based on biological discoveries. Bioinformatics involves algorithms to represent, store, and analyze basic biological data, including DNA sequence, RNA expression, and protein and small-molecule abundance within cells. Translational bioinformatics spans these two fields; it involves the development of algorithms to analyze basic molecular and cellular data with an explicit goal of affecting clinical care.
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Deep learning in bioinformatics.
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.
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A Web-based assessment of bioinformatics end-user support services at US universities
Messersmith, Donna J.; Benson, Dennis A.; Geer, Renata C.
2006-01-01
Objectives: This study was conducted to gauge the availability of bioinformatics end-user support services at US universities and to identify the providers of those services. The study primarily focused on the availability of short-term workshops that introduce users to molecular biology databases and analysis software. Methods: Websites of selected US universities were reviewed to determine if bioinformatics educational workshops were offered, and, if so, what organizational units in the universities provided them. Results: Of 239 reviewed universities, 72 (30%) offered bioinformatics educational workshops. These workshops were located at libraries (N = 15), bioinformatics centers (N = 38), or other facilities (N = 35). No such training was noted on the sites of 167 universities (70%). Of the 115 bioinformatics centers identified, two-thirds did not offer workshops. Conclusions: This analysis of university Websites indicates that a gap may exist in the availability of workshops and related training to assist researchers in the use of bioinformatics resources, representing a potential opportunity for libraries and other facilities to provide training and assistance for this growing user group. PMID:16888663
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LXtoo: an integrated live Linux distribution for the bioinformatics community
2012-01-01
Background 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. Findings 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. Conclusions 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. PMID:22813356
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LXtoo: an integrated live Linux distribution for the bioinformatics community.
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.
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Expanding roles in a library-based bioinformatics service program: a case study
Li, Meng; Chen, Yi-Bu; Clintworth, William A
2013-01-01
Question: How can a library-based bioinformatics support program be implemented and expanded to continuously support the growing and changing needs of the research community? Setting: A program at a health sciences library serving a large academic medical center with a strong research focus is described. Methods: The bioinformatics service program was established at the Norris Medical Library in 2005. As part of program development, the library assessed users' bioinformatics needs, acquired additional funds, established and expanded service offerings, and explored additional roles in promoting on-campus collaboration. Results: Personnel and software have increased along with the number of registered software users and use of the provided services. Conclusion: With strategic efforts and persistent advocacy within the broader university environment, library-based bioinformatics service programs can become a key part of an institution's comprehensive solution to researchers' ever-increasing bioinformatics needs. PMID:24163602
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4273π: Bioinformatics education on low cost ARM hardware
2013-01-01
Background 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. Results 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. Conclusions 4273π is a means to teach bioinformatics, including systems administration tasks, to undergraduates at low cost. PMID:23937194
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4273π: bioinformatics education on low cost ARM hardware.
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.
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A decade of Web Server updates at the Bioinformatics Links Directory: 2003-2012.
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.
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Gelbart, Hadas; Ben-Dor, Shifra; Yarden, Anat
2017-01-01
Despite the central place held by bioinformatics in modern life sciences and related areas, it has only recently been integrated to a limited extent into high-school teaching and learning programs. Here we describe the assessment of a learning environment entitled ‘Bioinformatics in the Service of Biotechnology’. Students’ learning outcomes and attitudes toward the bioinformatics learning environment were measured by analyzing their answers to questions embedded within the activities, questionnaires, interviews and observations. Students’ difficulties and knowledge acquisition were characterized based on four categories: the required domain-specific knowledge (declarative, procedural, strategic or situational), the scientific field that each question stems from (biology, bioinformatics or their combination), the associated cognitive-process dimension (remember, understand, apply, analyze, evaluate, create) and the type of question (open-ended or multiple choice). Analysis of students’ cognitive outcomes revealed learning gains in bioinformatics and related scientific fields, as well as appropriation of the bioinformatics approach as part of the students’ scientific ‘toolbox’. For students, questions stemming from the ‘old world’ biology field and requiring declarative or strategic knowledge were harder to deal with. This stands in contrast to their teachers’ prediction. Analysis of students’ affective outcomes revealed positive attitudes toward bioinformatics and the learning environment, as well as their perception of the teacher’s role. Insights from this analysis yielded implications and recommendations for curriculum design, classroom enactment, teacher education and research. For example, we recommend teaching bioinformatics in an integrative and comprehensive manner, through an inquiry process, and linking it to the wider science curriculum. PMID:26801769
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The 2015 Bioinformatics Open Source Conference (BOSC 2015)
Harris, Nomi L.; Cock, Peter J. A.; Lapp, Hilmar
2016-01-01
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. PMID:26914653
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Ladics, Gregory S; Cressman, Robert F; Herouet-Guicheney, Corinne; Herman, Rod A; Privalle, Laura; Song, Ping; Ward, Jason M; McClain, Scott
2011-06-01
Bioinformatic tools are being increasingly utilized to evaluate the degree of similarity between a novel protein and known allergens within the context of a larger allergy safety assessment process. Importantly, bioinformatics is not a predictive analysis that can determine if a novel protein will ''become" an allergen, but rather a tool to assess whether the protein is a known allergen or is potentially cross-reactive with an existing allergen. Bioinformatic tools are key components of the 2009 CodexAlimentarius Commission's weight-of-evidence approach, which encompasses a variety of experimental approaches for an overall assessment of the allergenic potential of a novel protein. Bioinformatic search comparisons between novel protein sequences, as well as potential novel fusion sequences derived from the genome and transgene, and known allergens are required by all regulatory agencies that assess the safety of genetically modified (GM) products. The objective of this paper is to identify opportunities for consensus in the methods of applying bioinformatics and to outline differences that impact a consistent and reliable allergy safety assessment. The bioinformatic comparison process has some critical features, which are outlined in this paper. One of them is a curated, publicly available and well-managed database with known allergenic sequences. In this paper, the best practices, scientific value, and food safety implications of bioinformatic analyses, as they are applied to GM food crops are discussed. Recommendations for conducting bioinformatic analysis on novel food proteins for potential cross-reactivity to known allergens are also put forth. Copyright © 2011 Elsevier Inc. All rights reserved.
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Machluf, Yossy; Gelbart, Hadas; Ben-Dor, Shifra; Yarden, Anat
2017-01-01
Despite the central place held by bioinformatics in modern life sciences and related areas, it has only recently been integrated to a limited extent into high-school teaching and learning programs. Here we describe the assessment of a learning environment entitled 'Bioinformatics in the Service of Biotechnology'. Students' learning outcomes and attitudes toward the bioinformatics learning environment were measured by analyzing their answers to questions embedded within the activities, questionnaires, interviews and observations. Students' difficulties and knowledge acquisition were characterized based on four categories: the required domain-specific knowledge (declarative, procedural, strategic or situational), the scientific field that each question stems from (biology, bioinformatics or their combination), the associated cognitive-process dimension (remember, understand, apply, analyze, evaluate, create) and the type of question (open-ended or multiple choice). Analysis of students' cognitive outcomes revealed learning gains in bioinformatics and related scientific fields, as well as appropriation of the bioinformatics approach as part of the students' scientific 'toolbox'. For students, questions stemming from the 'old world' biology field and requiring declarative or strategic knowledge were harder to deal with. This stands in contrast to their teachers' prediction. Analysis of students' affective outcomes revealed positive attitudes toward bioinformatics and the learning environment, as well as their perception of the teacher's role. Insights from this analysis yielded implications and recommendations for curriculum design, classroom enactment, teacher education and research. For example, we recommend teaching bioinformatics in an integrative and comprehensive manner, through an inquiry process, and linking it to the wider science curriculum. © The Author 2016. Published by Oxford University Press.
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Oulas, Anastasis; Minadakis, George; Zachariou, Margarita; Sokratous, Kleitos; Bourdakou, Marilena M; Spyrou, George M
2017-11-27
Systems Bioinformatics is a relatively new approach, which lies in the intersection of systems biology and classical bioinformatics. It focuses on integrating information across different levels using a bottom-up approach as in systems biology with a data-driven top-down approach as in bioinformatics. The advent of omics technologies has provided the stepping-stone for the emergence of Systems Bioinformatics. These technologies provide a spectrum of information ranging from genomics, transcriptomics and proteomics to epigenomics, pharmacogenomics, metagenomics and metabolomics. Systems Bioinformatics is the framework in which systems approaches are applied to such data, setting the level of resolution as well as the boundary of the system of interest and studying the emerging properties of the system as a whole rather than the sum of the properties derived from the system's individual components. A key approach in Systems Bioinformatics is the construction of multiple networks representing each level of the omics spectrum and their integration in a layered network that exchanges information within and between layers. Here, we provide evidence on how Systems Bioinformatics enhances computational therapeutics and diagnostics, hence paving the way to precision medicine. The aim of this review is to familiarize the reader with the emerging field of Systems Bioinformatics and to provide a comprehensive overview of its current state-of-the-art methods and technologies. Moreover, we provide examples of success stories and case studies that utilize such methods and tools to significantly advance research in the fields of systems biology and systems medicine. © The Author 2017. Published by Oxford University Press.
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Interdisciplinary Introductory Course in Bioinformatics
ERIC Educational Resources Information Center
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…
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Survey of Natural Language Processing Techniques in Bioinformatics.
Zeng, Zhiqiang; Shi, Hua; Wu, Yun; Hong, Zhiling
2015-01-01
Informatics methods, such as text mining and natural language processing, are always involved in bioinformatics research. In this study, we discuss text mining and natural language processing methods in bioinformatics from two perspectives. First, we aim to search for knowledge on biology, retrieve references using text mining methods, and reconstruct databases. For example, protein-protein interactions and gene-disease relationship can be mined from PubMed. Then, we analyze the applications of text mining and natural language processing techniques in bioinformatics, including predicting protein structure and function, detecting noncoding RNA. Finally, numerous methods and applications, as well as their contributions to bioinformatics, are discussed for future use by text mining and natural language processing researchers.
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Scalability and Validation of Big Data Bioinformatics Software.
Yang, Andrian; Troup, Michael; Ho, Joshua W K
2017-01-01
This review examines two important aspects that are central to modern big data bioinformatics analysis - software scalability and validity. We argue that not only are the issues of scalability and validation common to all big data bioinformatics analyses, they can be tackled by conceptually related methodological approaches, namely divide-and-conquer (scalability) and multiple executions (validation). Scalability is defined as the ability for a program to scale based on workload. It has always been an important consideration when developing bioinformatics algorithms and programs. Nonetheless the surge of volume and variety of biological and biomedical data has posed new challenges. We discuss how modern cloud computing and big data programming frameworks such as MapReduce and Spark are being used to effectively implement divide-and-conquer in a distributed computing environment. Validation of software is another important issue in big data bioinformatics that is often ignored. Software validation is the process of determining whether the program under test fulfils the task for which it was designed. Determining the correctness of the computational output of big data bioinformatics software is especially difficult due to the large input space and complex algorithms involved. We discuss how state-of-the-art software testing techniques that are based on the idea of multiple executions, such as metamorphic testing, can be used to implement an effective bioinformatics quality assurance strategy. We hope this review will raise awareness of these critical issues in bioinformatics.
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ZBIT Bioinformatics Toolbox: A Web-Platform for Systems Biology and Expression Data Analysis
Römer, Michael; Eichner, Johannes; Dräger, Andreas; Wrzodek, Clemens; Wrzodek, Finja; Zell, Andreas
2016-01-01
Bioinformatics analysis has become an integral part of research in biology. However, installation and use of scientific software can be difficult and often requires technical expert knowledge. Reasons are dependencies on certain operating systems or required third-party libraries, missing graphical user interfaces and documentation, or nonstandard input and output formats. In order to make bioinformatics software easily accessible to researchers, we here present a web-based platform. The Center for Bioinformatics Tuebingen (ZBIT) Bioinformatics Toolbox provides web-based access to a collection of bioinformatics tools developed for systems biology, protein sequence annotation, and expression data analysis. Currently, the collection encompasses software for conversion and processing of community standards SBML and BioPAX, transcription factor analysis, and analysis of microarray data from transcriptomics and proteomics studies. All tools are hosted on a customized Galaxy instance and run on a dedicated computation cluster. Users only need a web browser and an active internet connection in order to benefit from this service. The web platform is designed to facilitate the usage of the bioinformatics tools for researchers without advanced technical background. Users can combine tools for complex analyses or use predefined, customizable workflows. All results are stored persistently and reproducible. For each tool, we provide documentation, tutorials, and example data to maximize usability. The ZBIT Bioinformatics Toolbox is freely available at https://webservices.cs.uni-tuebingen.de/. PMID:26882475
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[Application of bioinformatics in researches of industrial biocatalysis].
Yu, Hui-Min; Luo, Hui; Shi, Yue; Sun, Xu-Dong; Shen, Zhong-Yao
2004-05-01
Industrial biocatalysis is currently attracting much attention to rebuild or substitute traditional producing process of chemicals and drugs. One of key focuses in industrial biocatalysis is biocatalyst, which is usually one kind of microbial enzyme. In the recent, new technologies of bioinformatics have played and will continue to play more and more significant roles in researches of industrial biocatalysis in response to the waves of genomic revolution. One of the key applications of bioinformatics in biocatalysis is the discovery and identification of the new biocatalyst through advanced DNA and protein sequence search, comparison and analyses in Internet database using different algorithm and software. The unknown genes of microbial enzymes can also be simply harvested by primer design on the basis of bioinformatics analyses. The other key applications of bioinformatics in biocatalysis are the modification and improvement of existing industrial biocatalyst. In this aspect, bioinformatics is of great importance in both rational design and directed evolution of microbial enzymes. Based on the successful prediction of tertiary structures of enzymes using the tool of bioinformatics, the undermentioned experiments, i.e. site-directed mutagenesis, fusion protein construction, DNA family shuffling and saturation mutagenesis, etc, are usually of very high efficiency. On all accounts, bioinformatics will be an essential tool for either biologist or biological engineer in the future researches of industrial biocatalysis, due to its significant function in guiding and quickening the step of discovery and/or improvement of novel biocatalysts.
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Influenza research database: an integrated bioinformatics resource for influenza virus research
USDA-ARS?s Scientific Manuscript database
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...
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Rapid Development of Bioinformatics Education in China
ERIC Educational Resources Information Center
Zhong, Yang; Zhang, Xiaoyan; Ma, Jian; Zhang, Liang
2003-01-01
As the Human Genome Project experiences remarkable success and a flood of biological data is produced, bioinformatics becomes a very "hot" cross-disciplinary field, yet experienced bioinformaticians are urgently needed worldwide. This paper summarises the rapid development of bioinformatics education in China, especially related…
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Moore, Jason H
2007-11-01
Bioinformatics is an interdisciplinary field that blends computer science and biostatistics with biological and biomedical sciences such as biochemistry, cell biology, developmental biology, genetics, genomics, and physiology. An important goal of bioinformatics is to facilitate the management, analysis, and interpretation of data from biological experiments and observational studies. The goal of this review is to introduce some of the important concepts in bioinformatics that must be considered when planning and executing a modern biological research study. We review database resources as well as data mining software tools.
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2012-01-01
Background Bioinformatics services have been traditionally provided in the form of a web-server that is hosted at institutional infrastructure and serves multiple users. This model, however, is not flexible enough to cope with the increasing number of users, increasing data size, and new requirements in terms of speed and availability of service. The advent of cloud computing suggests a new service model that provides an efficient solution to these problems, based on the concepts of "resources-on-demand" and "pay-as-you-go". However, cloud computing has not yet been introduced within bioinformatics servers due to the lack of usage scenarios and software layers that address the requirements of the bioinformatics domain. Results In this paper, we provide different use case scenarios for providing cloud computing based services, considering both the technical and financial aspects of the cloud computing service model. These scenarios are for individual users seeking computational power as well as bioinformatics service providers aiming at provision of personalized bioinformatics services to their users. We also present elasticHPC, a software package and a library that facilitates the use of high performance cloud computing resources in general and the implementation of the suggested bioinformatics scenarios in particular. Concrete examples that demonstrate the suggested use case scenarios with whole bioinformatics servers and major sequence analysis tools like BLAST are presented. Experimental results with large datasets are also included to show the advantages of the cloud model. Conclusions Our use case scenarios and the elasticHPC package are steps towards the provision of cloud based bioinformatics services, which would help in overcoming the data challenge of recent biological research. All resources related to elasticHPC and its web-interface are available at http://www.elasticHPC.org. PMID:23281941
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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.
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Two interactive Bioinformatics courses at the Bielefeld University Bioinformatics Server.
Sczyrba, Alexander; Konermann, Susanne; Giegerich, Robert
2008-05-01
Conferences in computational biology continue to provide tutorials on classical and new methods in the field. This can be taken as an indicator that education is still a bottleneck in our field's process of becoming an established scientific discipline. Bielefeld University has been one of the early providers of bioinformatics education, both locally and via the internet. The Bielefeld Bioinformatics Server (BiBiServ) offers a variety of older and new materials. Here, we report on two online courses made available recently, one introductory and one on the advanced level: (i) SADR: Sequence Analysis with Distributed Resources (http://bibiserv.techfak.uni-bielefeld.de/sadr/) and (ii) ADP: Algebraic Dynamic Programming in Bioinformatics (http://bibiserv.techfak.uni-bielefeld.de/dpcourse/).
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Ramharack, Pritika; Soliman, Mahmoud E S
2018-06-01
Originally developed for the analysis of biological sequences, bioinformatics has advanced into one of the most widely recognized domains in the scientific community. Despite this technological evolution, there is still an urgent need for nontoxic and efficient drugs. The onus now falls on the 'omics domain to meet this need by implementing bioinformatics techniques that will allow for the introduction of pioneering approaches in the rational drug design process. Here, we categorize an updated list of informatics tools and explore the capabilities of integrative bioinformatics in disease control. We believe that our review will serve as a comprehensive guide toward bioinformatics-oriented disease and drug discovery research. Copyright © 2018 Elsevier Ltd. All rights reserved.
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Using "Arabidopsis" Genetic Sequences to Teach Bioinformatics
ERIC Educational Resources Information Center
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…
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BioStar: an online question & answer resource for the bioinformatics community
USDA-ARS?s Scientific Manuscript database
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...
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The 20th anniversary of EMBnet: 20 years of bioinformatics for the Life Sciences community
D'Elia, Domenica; Gisel, Andreas; Eriksson, Nils-Einar; Kossida, Sophia; Mattila, Kimmo; Klucar, Lubos; Bongcam-Rudloff, Erik
2009-01-01
The EMBnet Conference 2008, focusing on 'Leading Applications and Technologies in Bioinformatics', was organized by the European Molecular Biology network (EMBnet) to celebrate its 20th anniversary. Since its foundation in 1988, EMBnet has been working to promote collaborative development of bioinformatics services and tools to serve the European community of molecular biology laboratories. This conference was the first meeting organized by the network that was open to the international scientific community outside EMBnet. The conference covered a broad range of research topics in bioinformatics with a main focus on new achievements and trends in emerging technologies supporting genomics, transcriptomics and proteomics analyses such as high-throughput sequencing and data managing, text and data-mining, ontologies and Grid technologies. Papers selected for publication, in this supplement to BMC Bioinformatics, cover a broad range of the topics treated, providing also an overview of the main bioinformatics research fields that the EMBnet community is involved in. PMID:19534734
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Honts, Jerry E.
2003-01-01
Recent advances in genomics and structural biology have resulted in an unprecedented increase in biological data available from Internet-accessible databases. In order to help students effectively use this vast repository of information, undergraduate biology students at Drake University were introduced to bioinformatics software and databases in three courses, beginning with an introductory course in cell biology. The exercises and projects that were used to help students develop literacy in bioinformatics are described. In a recently offered course in bioinformatics, students developed their own simple sequence analysis tool using the Perl programming language. These experiences are described from the point of view of the instructor as well as the students. A preliminary assessment has been made of the degree to which students had developed a working knowledge of bioinformatics concepts and methods. Finally, some conclusions have been drawn from these courses that may be helpful to instructors wishing to introduce bioinformatics within the undergraduate biology curriculum. PMID:14673489
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Online Bioinformatics Tutorials | Office of Cancer Genomics
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.
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Evaluating an Inquiry-Based Bioinformatics Course Using Q Methodology
ERIC Educational Resources Information Center
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…
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Generative Topic Modeling in Image Data Mining and Bioinformatics Studies
ERIC Educational Resources Information Center
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…
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A Portable Bioinformatics Course for Upper-Division Undergraduate Curriculum in Sciences
ERIC Educational Resources Information Center
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…
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Incorporating a Collaborative Web-Based Virtual Laboratory in an Undergraduate Bioinformatics Course
ERIC Educational Resources Information Center
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…
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A Mathematical Optimization Problem in Bioinformatics
ERIC Educational Resources Information Center
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…
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Biology in 'silico': The Bioinformatics Revolution.
ERIC Educational Resources Information Center
Bloom, Mark
2001-01-01
Explains the Human Genome Project (HGP) and efforts to sequence the human genome. Describes the role of bioinformatics in the project and considers it the genetics Swiss Army Knife, which has many different uses, for use in forensic science, medicine, agriculture, and environmental sciences. Discusses the use of bioinformatics in the high school…
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ERIC Educational Resources Information Center
Rowe, Laura
2017-01-01
An introductory bioinformatics laboratory experiment focused on protein analysis has been developed that is suitable for undergraduate students in introductory biochemistry courses. The laboratory experiment is designed to be potentially used as a "stand-alone" activity in which students are introduced to basic bioinformatics tools and…
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Virtual Bioinformatics Distance Learning Suite
ERIC Educational Resources Information Center
Tolvanen, Martti; Vihinen, Mauno
2004-01-01
Distance learning as a computer-aided concept allows students to take courses from anywhere at any time. In bioinformatics, computers are needed to collect, store, process, and analyze massive amounts of biological and biomedical data. We have applied the concept of distance learning in virtual bioinformatics to provide university course material…
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A Summer Program Designed to Educate College Students for Careers in Bioinformatics
ERIC Educational Resources Information Center
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…
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Assessment of a Bioinformatics across Life Science Curricula Initiative
ERIC Educational Resources Information Center
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…
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Computer Programming and Biomolecular Structure Studies: A Step beyond Internet Bioinformatics
ERIC Educational Resources Information Center
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…
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Teaching Bioinformatics and Neuroinformatics by Using Free Web-Based Tools
ERIC Educational Resources Information Center
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…
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When cloud computing meets bioinformatics: a review.
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.
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Application of machine learning methods in bioinformatics
NASA Astrophysics Data System (ADS)
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.
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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.
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Park, Hyun-Seok
2012-12-01
Whereas a vast amount of new information on bioinformatics is made available to the public through patents, only a small set of patents are cited in academic papers. A detailed analysis of registered bioinformatics patents, using the existing patent search system, can provide valuable information links between science and technology. However, it is extremely difficult to select keywords to capture bioinformatics patents, reflecting the convergence of several underlying technologies. No single word or even several words are sufficient to identify such patents. The analysis of patent subclasses can provide valuable information. In this paper, I did a preliminary study of the current status of bioinformatics patents and their International Patent Classification (IPC) groups registered in the Korea Intellectual Property Rights Information Service (KIPRIS) database.
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GLAD: a system for developing and deploying large-scale bioinformatics grid.
Teo, Yong-Meng; Wang, Xianbing; Ng, Yew-Kwong
2005-03-01
Grid computing is used to solve large-scale bioinformatics problems with gigabytes database by distributing the computation across multiple platforms. Until now in developing bioinformatics grid applications, it is extremely tedious to design and implement the component algorithms and parallelization techniques for different classes of problems, and to access remotely located sequence database files of varying formats across the grid. In this study, we propose a grid programming toolkit, GLAD (Grid Life sciences Applications Developer), which facilitates the development and deployment of bioinformatics applications on a grid. GLAD has been developed using ALiCE (Adaptive scaLable Internet-based Computing Engine), a Java-based grid middleware, which exploits the task-based parallelism. Two bioinformatics benchmark applications, such as distributed sequence comparison and distributed progressive multiple sequence alignment, have been developed using GLAD.
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BIAS: Bioinformatics Integrated Application Software.
Finak, G; Godin, N; Hallett, M; Pepin, F; Rajabi, Z; Srivastava, V; Tang, Z
2005-04-15
We introduce a development platform especially tailored to Bioinformatics research and software development. BIAS (Bioinformatics Integrated Application Software) provides the tools necessary for carrying out integrative Bioinformatics research requiring multiple datasets and analysis tools. It follows an object-relational strategy for providing persistent objects, allows third-party tools to be easily incorporated within the system and supports standards and data-exchange protocols common to Bioinformatics. BIAS is an OpenSource project and is freely available to all interested users at http://www.mcb.mcgill.ca/~bias/. This website also contains a paper containing a more detailed description of BIAS and a sample implementation of a Bayesian network approach for the simultaneous prediction of gene regulation events and of mRNA expression from combinations of gene regulation events. hallett@mcb.mcgill.ca.
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Bioinformatics in High School Biology Curricula: A Study of State Science Standards
ERIC Educational Resources Information Center
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…
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ERIC Educational Resources Information Center
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…
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ERIC Educational Resources Information Center
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…
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ERIC Educational Resources Information Center
Magana, Alejandra J.; Taleyarkhan, Manaz; Alvarado, Daniela Rivera; Kane, Michael; Springer, John; Clase, Kari
2014-01-01
Bioinformatics education can be broadly defined as the teaching and learning of the use of computer and information technology, along with mathematical and statistical analysis for gathering, storing, analyzing, interpreting, and integrating data to solve biological problems. The recent surge of genomics, proteomics, and structural biology in the…
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XML schemas for common bioinformatic data types and their application in workflow systems
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
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Vignettes: diverse library staff offering diverse bioinformatics services*
Osterbur, David L.; Alpi, Kristine; Canevari, Catharine; Corley, Pamela M.; Devare, Medha; Gaedeke, Nicola; Jacobs, Donna K.; Kirlew, Peter; Ohles, Janet A.; Vaughan, K.T.L.; Wang, Lili; Wu, Yongchun; Geer, Renata C.
2006-01-01
Objectives: The paper gives examples of the bioinformatics services provided in a variety of different libraries by librarians with a broad range of educational background and training. Methods: Two investigators sent an email inquiry to attendees of the “National Center for Biotechnology Information's (NCBI) Introduction to Molecular Biology Information Resources” or “NCBI Advanced Workshop for Bioinformatics Information Specialists (NAWBIS)” courses. The thirty-five-item questionnaire addressed areas such as educational background, library setting, types and numbers of users served, and bioinformatics training and support services provided. Answers were compiled into program vignettes. Discussion: The bioinformatics support services addressed in the paper are based in libraries with academic and clinical settings. Services have been established through different means: in collaboration with biology faculty as part of formal courses, through teaching workshops in the library, through one-on-one consultations, and by other methods. Librarians with backgrounds from art history to doctoral degrees in genetics have worked to establish these programs. Conclusion: Successful bioinformatics support programs can be established in libraries in a variety of different settings and by staff with a variety of different backgrounds and approaches. PMID:16888664
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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. Furthermore, we believe that a true interdisciplinary science experience would be best served by introduction of bioinformatics modules within existing courses in biology and chemistry and other complementary departments. To that end, with support from the Howard Hughes Medical Institute, we have developed over a dozen independent bioinformatics modules for our students that are incorporated into courses ranging from general chemistry and biology, advanced specialty courses, and classes in complementary disciplines such as computer science, mathematics, and physics. These activities have largely promoted active learning in our classrooms and have enhanced student understanding of course materials. Herein, we describe our program, the activities we have developed, and assessment of our endeavors in this area. Copyright © 2009 International Union of Biochemistry and Molecular Biology, Inc.
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Generalized Centroid Estimators in Bioinformatics
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
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Chen, Yi-Bu; Chattopadhyay, Ansuman; Bergen, Phillip; Gadd, Cynthia; Tannery, Nancy
2007-01-01
To bridge the gap between the rising information needs of biological and medical researchers and the rapidly growing number of online bioinformatics resources, we have created the Online Bioinformatics Resources Collection (OBRC) at the Health Sciences Library System (HSLS) at the University of Pittsburgh. The OBRC, containing 1542 major online bioinformatics databases and software tools, was constructed using the HSLS content management system built on the Zope Web application server. To enhance the output of search results, we further implemented the Vivísimo Clustering Engine, which automatically organizes the search results into categories created dynamically based on the textual information of the retrieved records. As the largest online collection of its kind and the only one with advanced search results clustering, OBRC is aimed at becoming a one-stop guided information gateway to the major bioinformatics databases and software tools on the Web. OBRC is available at the University of Pittsburgh's HSLS Web site (http://www.hsls.pitt.edu/guides/genetics/obrc).
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Carving a niche: establishing bioinformatics collaborations
Lyon, Jennifer A.; Tennant, Michele R.; Messner, Kevin R.; Osterbur, David L.
2006-01-01
Objectives: The paper describes collaborations and partnerships developed between library bioinformatics programs and other bioinformatics-related units at four academic institutions. Methods: A call for information on bioinformatics partnerships was made via email to librarians who have participated in the National Center for Biotechnology Information's Advanced Workshop for Bioinformatics Information Specialists. Librarians from Harvard University, the University of Florida, the University of Minnesota, and Vanderbilt University responded and expressed willingness to contribute information on their institutions, programs, services, and collaborating partners. Similarities and differences in programs and collaborations were identified. Results: The four librarians have developed partnerships with other units on their campuses that can be categorized into the following areas: knowledge management, instruction, and electronic resource support. All primarily support freely accessible electronic resources, while other campus units deal with fee-based ones. These demarcations are apparent in resource provision as well as in subsequent support and instruction. Conclusions and Recommendations: Through environmental scanning and networking with colleagues, librarians who provide bioinformatics support can develop fruitful collaborations. Visibility is key to building collaborations, as is broad-based thinking in terms of potential partners. PMID:16888668
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Development of a cloud-based Bioinformatics Training Platform.
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.
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Development of a cloud-based Bioinformatics Training Platform
Revote, Jerico; Watson-Haigh, Nathan S.; Quenette, Steve; Bethwaite, Blair; McGrath, Annette
2017-01-01
Abstract 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. PMID:27084333
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BioShaDock: a community driven bioinformatics shared Docker-based tools registry
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. PMID:26913191
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BioShaDock: a community driven bioinformatics shared Docker-based tools registry.
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.
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Smith, Andy; Southgate, Joel; Poplawski, Radoslaw; Bull, Matthew J.; Richardson, Emily; Ismail, Matthew; Thompson, Simon Elwood-; Kitchen, Christine; Guest, Martyn; Bakke, Marius
2016-01-01
The increasing availability and decreasing cost of high-throughput sequencing has transformed academic medical microbiology, delivering an explosion in available genomes while also driving advances in bioinformatics. However, many microbiologists are unable to exploit the resulting large genomics datasets because they do not have access to relevant computational resources and to an appropriate bioinformatics infrastructure. Here, we present the Cloud Infrastructure for Microbial Bioinformatics (CLIMB) facility, a shared computing infrastructure that has been designed from the ground up to provide an environment where microbiologists can share and reuse methods and data. PMID:28785418
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Connor, Thomas R; Loman, Nicholas J; Thompson, Simon; Smith, Andy; Southgate, Joel; Poplawski, Radoslaw; Bull, Matthew J; Richardson, Emily; Ismail, Matthew; Thompson, Simon Elwood-; Kitchen, Christine; Guest, Martyn; Bakke, Marius; Sheppard, Samuel K; Pallen, Mark J
2016-09-01
The increasing availability and decreasing cost of high-throughput sequencing has transformed academic medical microbiology, delivering an explosion in available genomes while also driving advances in bioinformatics. However, many microbiologists are unable to exploit the resulting large genomics datasets because they do not have access to relevant computational resources and to an appropriate bioinformatics infrastructure. Here, we present the Cloud Infrastructure for Microbial Bioinformatics (CLIMB) facility, a shared computing infrastructure that has been designed from the ground up to provide an environment where microbiologists can share and reuse methods and data.
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Bioinformatics in the orphan crops.
Armstead, Ian; Huang, Lin; Ravagnani, Adriana; Robson, Paul; Ougham, Helen
2009-11-01
Orphan crops are those which are grown as food, animal feed or other crops of some importance in agriculture, but which have not yet received the investment of research effort or funding required to develop significant public bioinformatics resources. Where an orphan crop is related to a well-characterised model plant species, comparative genomics and bioinformatics can often, though not always, be exploited to assist research and crop improvement. This review addresses some challenges and opportunities presented by bioinformatics in the orphan crops, using three examples: forage grasses from the genera Lolium and Festuca, forage legumes and the second generation energy crop Miscanthus.
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An ontology-based framework for bioinformatics workflows.
Digiampietri, Luciano A; Perez-Alcazar, Jose de J; Medeiros, Claudia Bauzer
2007-01-01
The proliferation of bioinformatics activities brings new challenges - how to understand and organise these resources, how to exchange and reuse successful experimental procedures, and to provide interoperability among data and tools. This paper describes an effort toward these directions. It is based on combining research on ontology management, AI and scientific workflows to design, reuse and annotate bioinformatics experiments. The resulting framework supports automatic or interactive composition of tasks based on AI planning techniques and takes advantage of ontologies to support the specification and annotation of bioinformatics workflows. We validate our proposal with a prototype running on real data.
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Rebholz-Schuhman, Dietrich; Cameron, Graham; Clark, Dominic; van Mulligen, Erik; Coatrieux, Jean-Louis; Del Hoyo Barbolla, Eva; Martin-Sanchez, Fernando; Milanesi, Luciano; Porro, Ivan; Beltrame, Francesco; Tollis, Ioannis; Van der Lei, Johan
2007-03-08
The SYMBIOmatics Specific Support Action (SSA) is "an information gathering and dissemination activity" that seeks "to identify synergies between the bioinformatics and the medical informatics" domain to improve collaborative progress between both domains (ref. to http://www.symbiomatics.org). As part of the project experts in both research fields will be identified and approached through a survey. To provide input to the survey, the scientific literature was analysed to extract topics relevant to both medical informatics and bioinformatics. This paper presents results of a systematic analysis of the scientific literature from medical informatics research and bioinformatics research. In the analysis pairs of words (bigrams) from the leading bioinformatics and medical informatics journals have been used as indication of existing and emerging technologies and topics over the period 2000-2005 ("recent") and 1990-1990 ("past"). We identified emerging topics that were equally important to bioinformatics and medical informatics in recent years such as microarray experiments, ontologies, open source, text mining and support vector machines. Emerging topics that evolved only in bioinformatics were system biology, protein interaction networks and statistical methods for microarray analyses, whereas emerging topics in medical informatics were grid technology and tissue microarrays. We conclude that although both fields have their own specific domains of interest, they share common technological developments that tend to be initiated by new developments in biotechnology and computer science.
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Rebholz-Schuhman, Dietrich; Cameron, Graham; Clark, Dominic; van Mulligen, Erik; Coatrieux, Jean-Louis; Del Hoyo Barbolla, Eva; Martin-Sanchez, Fernando; Milanesi, Luciano; Porro, Ivan; Beltrame, Francesco; Tollis, Ioannis; Van der Lei, Johan
2007-01-01
Background The SYMBIOmatics Specific Support Action (SSA) is "an information gathering and dissemination activity" that seeks "to identify synergies between the bioinformatics and the medical informatics" domain to improve collaborative progress between both domains (ref. to ). As part of the project experts in both research fields will be identified and approached through a survey. To provide input to the survey, the scientific literature was analysed to extract topics relevant to both medical informatics and bioinformatics. Results This paper presents results of a systematic analysis of the scientific literature from medical informatics research and bioinformatics research. In the analysis pairs of words (bigrams) from the leading bioinformatics and medical informatics journals have been used as indication of existing and emerging technologies and topics over the period 2000–2005 ("recent") and 1990–1990 ("past"). We identified emerging topics that were equally important to bioinformatics and medical informatics in recent years such as microarray experiments, ontologies, open source, text mining and support vector machines. Emerging topics that evolved only in bioinformatics were system biology, protein interaction networks and statistical methods for microarray analyses, whereas emerging topics in medical informatics were grid technology and tissue microarrays. Conclusion We conclude that although both fields have their own specific domains of interest, they share common technological developments that tend to be initiated by new developments in biotechnology and computer science. PMID:17430562
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2009-01-01
Background The rapid advancement of computer and information technology in recent years has resulted in the rise of e-learning technologies to enhance and complement traditional classroom teaching in many fields, including bioinformatics. This paper records the experience of implementing e-learning technology to support problem-based learning (PBL) in the teaching of two undergraduate bioinformatics classes in the National University of Singapore. Results Survey results further established the efficiency and suitability of e-learning tools to supplement PBL in bioinformatics education. 63.16% of year three bioinformatics students showed a positive response regarding the usefulness of the Learning Activity Management System (LAMS) e-learning tool in guiding the learning and discussion process involved in PBL and in enhancing the learning experience by breaking down PBL activities into a sequential workflow. On the other hand, 89.81% of year two bioinformatics students indicated that their revision process was positively impacted with the use of LAMS for guiding the learning process, while 60.19% agreed that the breakdown of activities into a sequential step-by-step workflow by LAMS enhances the learning experience Conclusion We show that e-learning tools are useful for supplementing PBL in bioinformatics education. The results suggest that it is feasible to develop and adopt e-learning tools to supplement a variety of instructional strategies in the future. PMID:19958511
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ERIC Educational Resources Information Center
Wightman, Bruce; Hark, Amy T.
2012-01-01
The development of fields such as bioinformatics and genomics has created new challenges and opportunities for undergraduate biology curricula. Students preparing for careers in science, technology, and medicine need more intensive study of bioinformatics and more sophisticated training in the mathematics on which this field is based. In this…
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Bioinformatics in Middle East Program Curricula--A Focus on the Arabian Gulf
ERIC Educational Resources Information Center
Loucif, Samia
2014-01-01
The purpose of this paper is to investigate the inclusion of bioinformatics in program curricula in the Middle East, focusing on educational institutions in the Arabian Gulf. Bioinformatics is a multidisciplinary field which has emerged in response to the need for efficient data storage and retrieval, and accurate and fast computational and…
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ERIC Educational Resources Information Center
Sutcliffe, Iain C.; Cummings, Stephen P.
2007-01-01
Bioinformatics has emerged as an important discipline within the biological sciences that allows scientists to decipher and manage the vast quantities of data (such as genome sequences) that are now available. Consequently, there is an obvious need to provide graduates in biosciences with generic, transferable skills in bioinformatics. We present…
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ERIC Educational Resources Information Center
Brown, James A. L.
2016-01-01
A pedagogic intervention, in the form of an inquiry-based peer-assisted learning project (as a practical student-led bioinformatics module), was assessed for its ability to increase students' engagement, practical bioinformatic skills and process-specific knowledge. Elements assessed were process-specific knowledge following module completion,…
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The S-Star Trial Bioinformatics Course: An On-line Learning Success
ERIC Educational Resources Information Center
Lim, Yun Ping; Hoog, Jan-Olov; Gardner, Phyllis; Ranganathan, Shoba; Andersson, Siv; Subbiah, Subramanian; Tan, Tin Wee; Hide, Winston; Weiss, Anthony S.
2003-01-01
The S-Star Trial Bioinformatics on-line course (www.s-star.org) is a global experiment in bioinformatics distance education. Six universities from five continents have participated in this project. One hundred and fifty students participated in the first trial course of which 96 followed through the entire course and 70 fulfilled the overall…
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Microsoft Biology Initiative: .NET Bioinformatics Platform and Tools
Diaz Acosta, B.
2011-01-01
The Microsoft Biology Initiative (MBI) is an effort in Microsoft Research to bring new technology and tools to the area of bioinformatics and biology. This initiative is comprised of two primary components, the Microsoft Biology Foundation (MBF) and the Microsoft Biology Tools (MBT). MBF is a language-neutral bioinformatics toolkit built as an extension to the Microsoft .NET Framework—initially aimed at the area of Genomics research. Currently, it implements a range of parsers for common bioinformatics file formats; a range of algorithms for manipulating DNA, RNA, and protein sequences; and a set of connectors to biological web services such as NCBI BLAST. MBF is available under an open source license, and executables, source code, demo applications, documentation and training materials are freely downloadable from http://research.microsoft.com/bio. MBT is a collection of tools that enable biology and bioinformatics researchers to be more productive in making scientific discoveries.
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Bioinformatics in high school biology curricula: a study of state science standards.
Wefer, Stephen H; Sheppard, Keith
2008-01-01
The proliferation of bioinformatics in modern biology marks a modern revolution in science that promises to influence science education at all levels. This study analyzed secondary school science standards of 49 U.S. states (Iowa has no science framework) and the District of Columbia for content related to bioinformatics. The bioinformatics content of each state's biology standards was analyzed and categorized into nine areas: Human Genome Project/genomics, forensics, evolution, classification, nucleotide variations, medicine, computer use, agriculture/food technology, and science technology and society/socioscientific issues. Findings indicated a generally low representation of bioinformatics-related content, which varied substantially across the different areas, with Human Genome Project/genomics and computer use being the lowest (8%), and evolution being the highest (64%) among states' science frameworks. This essay concludes with recommendations for reworking/rewording existing standards to facilitate the goal of promoting science literacy among secondary school students.
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Cheng, Gong; Lu, Quan; Ma, Ling; Zhang, Guocai; Xu, Liang; Zhou, Zongshan
2017-01-01
Recently, Docker technology has received increasing attention throughout the bioinformatics community. However, its implementation has not yet been mastered by most biologists; accordingly, its application in biological research has been limited. In order to popularize this technology in the field of bioinformatics and to promote the use of publicly available bioinformatics tools, such as Dockerfiles and Images from communities, government sources, and private owners in the Docker Hub Registry and other Docker-based resources, we introduce here a complete and accurate bioinformatics workflow based on Docker. The present workflow enables analysis and visualization of pan-genomes and biosynthetic gene clusters of bacteria. This provides a new solution for bioinformatics mining of big data from various publicly available biological databases. The present step-by-step guide creates an integrative workflow through a Dockerfile to allow researchers to build their own Image and run Container easily.
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Cheng, Gong; Zhang, Guocai; Xu, Liang
2017-01-01
Recently, Docker technology has received increasing attention throughout the bioinformatics community. However, its implementation has not yet been mastered by most biologists; accordingly, its application in biological research has been limited. In order to popularize this technology in the field of bioinformatics and to promote the use of publicly available bioinformatics tools, such as Dockerfiles and Images from communities, government sources, and private owners in the Docker Hub Registry and other Docker-based resources, we introduce here a complete and accurate bioinformatics workflow based on Docker. The present workflow enables analysis and visualization of pan-genomes and biosynthetic gene clusters of bacteria. This provides a new solution for bioinformatics mining of big data from various publicly available biological databases. The present step-by-step guide creates an integrative workflow through a Dockerfile to allow researchers to build their own Image and run Container easily. PMID:29204317
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Agyei, Dominic; Tsopmo, Apollinaire; Udenigwe, Chibuike C
2018-06-01
There are emerging advancements in the strategies used for the discovery and development of food-derived bioactive peptides because of their multiple food and health applications. Bioinformatics and peptidomics are two computational and analytical techniques that have the potential to speed up the development of bioactive peptides from bench to market. Structure-activity relationships observed in peptides form the basis for bioinformatics and in silico prediction of bioactive sequences encrypted in food proteins. Peptidomics, on the other hand, relies on "hyphenated" (liquid chromatography-mass spectrometry-based) techniques for the detection, profiling, and quantitation of peptides. Together, bioinformatics and peptidomics approaches provide a low-cost and effective means of predicting, profiling, and screening bioactive protein hydrolysates and peptides from food. This article discuses the basis, strengths, and limitations of bioinformatics and peptidomics approaches currently used for the discovery and analysis of food-derived bioactive peptides.
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Metagenomics and Bioinformatics in Microbial Ecology: Current Status and Beyond.
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.
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[Integration of clinical and biological data in clinical practice using bioinformatics].
Coltell, Oscar; Arregui, María; Fabregat, Antonio; Portolés, Olga
2008-05-01
The aim of our work is to describe essential aspects of Medical Informatics, Bioinformatics and Biomedical Informatics, that are used in biomedical research and clinical practice. These disciplines have emerged from the need to find new scientific and technical approaches to manage, store, analyze and report data generated in clinical practice and molecular biology and other medical specialties. It can be also useful to integrate research information generated in different areas of health care. Moreover, these disciplines are interdisciplinary and integrative, two key features not shared by other areas of medical knowledge. Finally, when Bioinformatics and Biomedical Informatics approach to medical investigation and practice are applied, a new discipline, called Clinical Bioinformatics, emerges. The latter requires a specific training program to create a new professional profile. We have not been able to find a specific training program in Clinical Bioinformatics in Spain.
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Schneider, Maria Victoria; Griffin, Philippa C; Tyagi, Sonika; Flannery, Madison; Dayalan, Saravanan; Gladman, Simon; Watson-Haigh, Nathan; Bayer, Philipp E; Charleston, Michael; Cooke, Ira; Cook, Rob; Edwards, Richard J; Edwards, David; Gorse, Dominique; McConville, Malcolm; Powell, David; Wilkins, Marc R; Lonie, Andrew
2017-06-30
EMBL Australia Bioinformatics Resource (EMBL-ABR) is a developing national research infrastructure, providing bioinformatics resources and support to life science and biomedical researchers in Australia. EMBL-ABR comprises 10 geographically distributed national nodes with one coordinating hub, with current funding provided through Bioplatforms Australia and the University of Melbourne for its initial 2-year development phase. The EMBL-ABR mission is to: (1) increase Australia's capacity in bioinformatics and data sciences; (2) contribute to the development of training in bioinformatics skills; (3) showcase Australian data sets at an international level and (4) enable engagement in international programs. The activities of EMBL-ABR are focussed in six key areas, aligning with comparable international initiatives such as ELIXIR, CyVerse and NIH Commons. These key areas-Tools, Data, Standards, Platforms, Compute and Training-are described in this article. © The Author 2017. Published by Oxford University Press.
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Bioinformatics in High School Biology Curricula: A Study of State Science Standards
Sheppard, Keith
2008-01-01
The proliferation of bioinformatics in modern biology marks a modern revolution in science that promises to influence science education at all levels. This study analyzed secondary school science standards of 49 U.S. states (Iowa has no science framework) and the District of Columbia for content related to bioinformatics. The bioinformatics content of each state's biology standards was analyzed and categorized into nine areas: Human Genome Project/genomics, forensics, evolution, classification, nucleotide variations, medicine, computer use, agriculture/food technology, and science technology and society/socioscientific issues. Findings indicated a generally low representation of bioinformatics-related content, which varied substantially across the different areas, with Human Genome Project/genomics and computer use being the lowest (8%), and evolution being the highest (64%) among states' science frameworks. This essay concludes with recommendations for reworking/rewording existing standards to facilitate the goal of promoting science literacy among secondary school students. PMID:18316818
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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.
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No-boundary thinking in bioinformatics research
2013-01-01
Currently there are definitions from many agencies and research societies defining “bioinformatics” as deriving knowledge from computational analysis of large volumes of biological and biomedical data. Should this be the bioinformatics research focus? We will discuss this issue in this review article. We would like to promote the idea of supporting human-infrastructure (HI) with no-boundary thinking (NT) in bioinformatics (HINT). PMID:24192339
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ERIC Educational Resources Information Center
Barker, Daniel; Alderson, Rosanna G.; McDonagh, James L.; Plaisier, Heleen; Comrie, Muriel M.; Duncan, Leigh; Muirhead, Gavin T. P.; Sweeney, Stuart D.
2015-01-01
Background: Bioinformatics--the use of computers in biology--is of major and increasing importance to biological sciences and medicine. We conducted a preliminary investigation of the value of bringing practical, university-level bioinformatics education to the school level. We conducted voluntary activities for pupils at two schools in Scotland…
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The Air Force In Silico -- Computational Biology in 2025
2007-11-01
and chromosome) these new fields are commonly referred to as “~omics.” Proteomics , transcriptomics, metabolomics , epigenomics, physiomics... Bioinformatics , 2006, http://journal.imbio.de/ http://www-bm.ipk-gatersleben.de/stable/php/ journal /articles/pdf/jib-22.pdf (accessed 30 September...Chirino, G. Tansley and I. Dryden, “The implications for Bioinformatics of integration across physical scales,” Journal of Integrative Bioinformatics
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Online Tools for Bioinformatics Analyses in Nutrition Sciences12
Malkaram, Sridhar A.; Hassan, Yousef I.; Zempleni, Janos
2012-01-01
Recent advances in “omics” research have resulted in the creation of large datasets that were generated by consortiums and centers, small datasets that were generated by individual investigators, and bioinformatics tools for mining these datasets. It is important for nutrition laboratories to take full advantage of the analysis tools to interrogate datasets for information relevant to genomics, epigenomics, transcriptomics, proteomics, and metabolomics. This review provides guidance regarding bioinformatics resources that are currently available in the public domain, with the intent to provide a starting point for investigators who want to take advantage of the opportunities provided by the bioinformatics field. PMID:22983844
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Biotool2Web: creating simple Web interfaces for bioinformatics applications.
Shahid, Mohammad; Alam, Intikhab; Fuellen, Georg
2006-01-01
Currently there are many bioinformatics applications being developed, but there is no easy way to publish them on the World Wide Web. We have developed a Perl script, called Biotool2Web, which makes the task of creating web interfaces for simple ('home-made') bioinformatics applications quick and easy. Biotool2Web uses an XML document containing the parameters to run the tool on the Web, and generates the corresponding HTML and common gateway interface (CGI) files ready to be published on a web server. This tool is available for download at URL http://www.uni-muenster.de/Bioinformatics/services/biotool2web/ Georg Fuellen (fuellen@alum.mit.edu).
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Bioinformatics in translational drug discovery.
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).
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India's Computational Biology Growth and Challenges.
Chakraborty, Chiranjib; Bandyopadhyay, Sanghamitra; Agoramoorthy, Govindasamy
2016-09-01
India's computational science is growing swiftly due to the outburst of internet and information technology services. The bioinformatics sector of India has been transforming rapidly by creating a competitive position in global bioinformatics market. Bioinformatics is widely used across India to address a wide range of biological issues. Recently, computational researchers and biologists are collaborating in projects such as database development, sequence analysis, genomic prospects and algorithm generations. In this paper, we have presented the Indian computational biology scenario highlighting bioinformatics-related educational activities, manpower development, internet boom, service industry, research activities, conferences and trainings undertaken by the corporate and government sectors. Nonetheless, this new field of science faces lots of challenges.
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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 Gagne's Conditions of Learning instructional design theory. This theory, although first published in the early 1970s, is still fundamental in instructional design and instructional technology. First, top-level as well as prerequisite learning objectives for a microarray analysis workshop and a primer design workshop were defined. Then a hierarchy of objectives for each workshop was created. Hands-on tutorials were designed to meet these objectives. Finally, events of learning proposed by Gagne's theory were incorporated into the hands-on tutorials. The resultant manuals were tested on a small number of trainees, revised, and applied in 1-day bioinformatics workshops. Based on this experience and on observations made during the workshops, we conclude that Gagne's Conditions of Learning instructional design theory provides a useful framework for developing bioinformatics training, but may not be optimal as a method for teaching it. PMID:16220141
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XML schemas for common bioinformatic data types and their application in workflow systems.
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.
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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 face-to-face lecture course with a web-based virtual laboratory presents new opportunities for collaborative learning of the conceptual material, and for fostering peer support of technical bioinformatics questions. To explore this combination, an in-person lecture-only undergraduate bioinformatics course was augmented with a remote web-based laboratory, and tested with a large class. This study hypothesized that the collaborative virtual lab would foster active learning and peer support, and tested this hypothesis by conducting a student survey near the end of the semester. Respondents broadly reported strong benefits from the online laboratory, and strong benefits from peer-provided technical support. In comparison with traditional in-person teaching labs, students preferred the virtual lab by a factor of two. Key aspects of the course architecture and design are described to encourage further experimentation in teaching collaborative online bioinformatics laboratories. Copyright © 2010 International Union of Biochemistry and Molecular Biology, Inc.
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Taking Bioinformatics to Systems Medicine.
van Kampen, Antoine H C; Moerland, Perry D
2016-01-01
Systems medicine promotes a range of approaches and strategies to study human health and disease at a systems level with the aim of improving the overall well-being of (healthy) individuals, and preventing, diagnosing, or curing disease. In this chapter we discuss how bioinformatics critically contributes to systems medicine. First, we explain the role of bioinformatics in the management and analysis of data. In particular we show the importance of publicly available biological and clinical repositories to support systems medicine studies. Second, we discuss how the integration and analysis of multiple types of omics data through integrative bioinformatics may facilitate the determination of more predictive and robust disease signatures, lead to a better understanding of (patho)physiological molecular mechanisms, and facilitate personalized medicine. Third, we focus on network analysis and discuss how gene networks can be constructed from omics data and how these networks can be decomposed into smaller modules. We discuss how the resulting modules can be used to generate experimentally testable hypotheses, provide insight into disease mechanisms, and lead to predictive models. Throughout, we provide several examples demonstrating how bioinformatics contributes to systems medicine and discuss future challenges in bioinformatics that need to be addressed to enable the advancement of systems medicine.
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Revealing biological information using data structuring and automated learning.
Mohorianu, Irina; Moulton, Vincent
2010-11-01
The intermediary steps between a biological hypothesis, concretized in the input data, and meaningful results, validated using biological experiments, commonly employ bioinformatics tools. Starting with storage of the data and ending with a statistical analysis of the significance of the results, every step in a bioinformatics analysis has been intensively studied and the resulting methods and models patented. This review summarizes the bioinformatics patents that have been developed mainly for the study of genes, and points out the universal applicability of bioinformatics methods to other related studies such as RNA interference. More specifically, we overview the steps undertaken in the majority of bioinformatics analyses, highlighting, for each, various approaches that have been developed to reveal details from different perspectives. First we consider data warehousing, the first task that has to be performed efficiently, optimizing the structure of the database, in order to facilitate both the subsequent steps and the retrieval of information. Next, we review data mining, which occupies the central part of most bioinformatics analyses, presenting patents concerning differential expression, unsupervised and supervised learning. Last, we discuss how networks of interactions of genes or other players in the cell may be created, which help draw biological conclusions and have been described in several patents.
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The GMOD Drupal bioinformatic server framework.
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.
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The Topology Prediction of Membrane Proteins: A Web-Based Tutorial.
Kandemir-Cavas, Cagin; Cavas, Levent; Alyuruk, Hakan
2018-06-01
There is a great need for development of educational materials on the transfer of current bioinformatics knowledge to undergraduate students in bioscience departments. In this study, it is aimed to prepare an example in silico laboratory tutorial on the topology prediction of membrane proteins by bioinformatics tools. This laboratory tutorial is prepared for biochemistry lessons at bioscience departments (biology, chemistry, biochemistry, molecular biology and genetics, and faculty of medicine). The tutorial is intended for students who have not taken a bioinformatics course yet or already have taken a course as an introduction to bioinformatics. The tutorial is based on step-by-step explanations with illustrations. It can be applied under supervision of an instructor in the lessons, or it can be used as a self-study guide by students. In the tutorial, membrane-spanning regions and α-helices of membrane proteins were predicted by internet-based bioinformatics tools. According to the results achieved from internet-based bioinformatics tools, the algorithms and parameters used were effective on the accuracy of prediction. The importance of this laboratory tutorial lies on the facts that it provides an introduction to the bioinformatics and that it also demonstrates an in silico laboratory application to the students at natural sciences. The presented example education material is applicable easily at all departments that have internet connection. This study presents an alternative education material to the students in biochemistry laboratories in addition to classical laboratory experiments.
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ERIC Educational Resources Information Center
Nehm, Ross H.; Budd, Ann F.
2006-01-01
NMITA is a reef coral biodiversity database that we use to introduce students to the expansive realm of bioinformatics beyond genetics. We introduce a series of lessons that have students use this database, thereby accessing real data that can be used to test hypotheses about biodiversity and evolution while targeting the "National Science …
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Bioinformatics/biostatistics: microarray analysis.
Eichler, Gabriel S
2012-01-01
The quantity and complexity of the molecular-level data generated in both research and clinical settings require the use of sophisticated, powerful computational interpretation techniques. It is for this reason that bioinformatic analysis of complex molecular profiling data has become a fundamental technology in the development of personalized medicine. This chapter provides a high-level overview of the field of bioinformatics and outlines several, classic bioinformatic approaches. The highlighted approaches can be aptly applied to nearly any sort of high-dimensional genomic, proteomic, or metabolomic experiments. Reviewed technologies in this chapter include traditional clustering analysis, the Gene Expression Dynamics Inspector (GEDI), GoMiner (GoMiner), Gene Set Enrichment Analysis (GSEA), and the Learner of Functional Enrichment (LeFE).
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Integer Linear Programming in Computational Biology
NASA Astrophysics Data System (ADS)
Althaus, Ernst; Klau, Gunnar W.; Kohlbacher, Oliver; Lenhof, Hans-Peter; Reinert, Knut
Computational molecular biology (bioinformatics) is a young research field that is rich in NP-hard optimization problems. The problem instances encountered are often huge and comprise thousands of variables. Since their introduction into the field of bioinformatics in 1997, integer linear programming (ILP) techniques have been successfully applied to many optimization problems. These approaches have added much momentum to development and progress in related areas. In particular, ILP-based approaches have become a standard optimization technique in bioinformatics. In this review, we present applications of ILP-based techniques developed by members and former members of Kurt Mehlhorn’s group. These techniques were introduced to bioinformatics in a series of papers and popularized by demonstration of their effectiveness and potential.
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Bioinformatics projects supporting life-sciences learning in high schools.
Marques, Isabel; Almeida, Paulo; Alves, Renato; Dias, Maria João; Godinho, Ana; Pereira-Leal, José B
2014-01-01
The interdisciplinary nature of bioinformatics makes it an ideal framework to develop activities enabling enquiry-based learning. We describe here the development and implementation of a pilot project to use bioinformatics-based research activities in high schools, called "Bioinformatics@school." It includes web-based research projects that students can pursue alone or under teacher supervision and a teacher training program. The project is organized so as to enable discussion of key results between students and teachers. After successful trials in two high schools, as measured by questionnaires, interviews, and assessment of knowledge acquisition, the project is expanding by the action of the teachers involved, who are helping us develop more content and are recruiting more teachers and schools.
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The Interactions Between Clinical Informatics and Bioinformatics
Altman, Russ B.
2000-01-01
For the past decade, Stanford Medical Informatics has combined clinical informatics and bioinformatics research and training in an explicit way. The interest in applying informatics techniques to both clinical problems and problems in basic science can be traced to the Dendral project in the 1960s. Having bioinformatics and clinical informatics in the same academic unit is still somewhat unusual and can lead to clashes of clinical and basic science cultures. Nevertheless, the benefits of this organization have recently become clear, as the landscape of academic medicine in the next decades has begun to emerge. The author provides examples of technology transfer between clinical informatics and bioinformatics that illustrate how they complement each other. PMID:10984462
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Revote, Jerico; Suchecki, Radosław; Tyagi, Sonika; Corley, Susan M.; Shang, Catherine A.; McGrath, Annette
2017-01-01
Abstract There is a clear demand for hands-on bioinformatics training. The development of bioinformatics workshop content is both time-consuming and expensive. Therefore, enabling trainers to develop bioinformatics workshops in a way that facilitates reuse is becoming increasingly important. The most widespread practice for sharing workshop content is through making PDF, PowerPoint and Word documents available online. While this effort is to be commended, such content is usually not so easy to reuse or repurpose and does not capture all the information required for a third party to rerun a workshop. We present an open, collaborative framework for developing and maintaining, reusable and shareable hands-on training workshop content. PMID:26984618
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Extracting patterns of database and software usage from the bioinformatics literature
Duck, Geraint; Nenadic, Goran; Brass, Andy; Robertson, David L.; Stevens, Robert
2014-01-01
Motivation: As a natural consequence of being a computer-based discipline, bioinformatics has a strong focus on database and software development, but the volume and variety of resources are growing at unprecedented rates. An audit of database and software usage patterns could help provide an overview of developments in bioinformatics and community common practice, and comparing the links between resources through time could demonstrate both the persistence of existing software and the emergence of new tools. Results: We study the connections between bioinformatics resources and construct networks of database and software usage patterns, based on resource co-occurrence, that correspond to snapshots of common practice in the bioinformatics community. We apply our approach to pairings of phylogenetics software reported in the literature and argue that these could provide a stepping stone into the identification of scientific best practice. Availability and implementation: The extracted resource data, the scripts used for network generation and the resulting networks are available at http://bionerds.sourceforge.net/networks/ Contact: robert.stevens@manchester.ac.uk PMID:25161253
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Mello, Luciane V; Tregilgas, Luke; Cowley, Gwen; Gupta, Anshul; Makki, Fatima; Jhutty, Anjeet; Shanmugasundram, Achchuthan
2017-01-01
Teaching bioinformatics is a longstanding challenge for educators who need to demonstrate to students how skills developed in the classroom may be applied to real world research. This study employed an action research methodology which utilised student-staff partnership and peer-learning. It was centred on the experiences of peer-facilitators, students who had previously taken a postgraduate bioinformatics module, and had applied knowledge and skills gained from it to their own research. It aimed to demonstrate to peer-receivers, current students, how bioinformatics could be used in their own research while developing peer-facilitators' teaching and mentoring skills. This student-centred approach was well received by the peer-receivers, who claimed to have gained improved understanding of bioinformatics and its relevance to research. Equally, peer-facilitators also developed a better understanding of the subject and appreciated that the activity was a rare and invaluable opportunity to develop their teaching and mentoring skills, enhancing their employability.
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Relax with CouchDB - Into the non-relational DBMS era of Bioinformatics
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
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Agents in bioinformatics, computational and systems biology.
Merelli, Emanuela; Armano, Giuliano; Cannata, Nicola; Corradini, Flavio; d'Inverno, Mark; Doms, Andreas; Lord, Phillip; Martin, Andrew; Milanesi, Luciano; Möller, Steffen; Schroeder, Michael; Luck, Michael
2007-01-01
The adoption of agent technologies and multi-agent systems constitutes an emerging area in bioinformatics. In this article, we report on the activity of the Working Group on Agents in Bioinformatics (BIOAGENTS) founded during the first AgentLink III Technical Forum meeting on the 2nd of July, 2004, in Rome. The meeting provided an opportunity for seeding collaborations between the agent and bioinformatics communities to develop a different (agent-based) approach of computational frameworks both for data analysis and management in bioinformatics and for systems modelling and simulation in computational and systems biology. The collaborations gave rise to applications and integrated tools that we summarize and discuss in context of the state of the art in this area. We investigate on future challenges and argue that the field should still be explored from many perspectives ranging from bio-conceptual languages for agent-based simulation, to the definition of bio-ontology-based declarative languages to be used by information agents, and to the adoption of agents for computational grids.
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Mello, Luciane V.; Tregilgas, Luke; Cowley, Gwen; Gupta, Anshul; Makki, Fatima; Jhutty, Anjeet; Shanmugasundram, Achchuthan
2017-01-01
Abstract Teaching bioinformatics is a longstanding challenge for educators who need to demonstrate to students how skills developed in the classroom may be applied to real world research. This study employed an action research methodology which utilised student–staff partnership and peer-learning. It was centred on the experiences of peer-facilitators, students who had previously taken a postgraduate bioinformatics module, and had applied knowledge and skills gained from it to their own research. It aimed to demonstrate to peer-receivers, current students, how bioinformatics could be used in their own research while developing peer-facilitators’ teaching and mentoring skills. This student-centred approach was well received by the peer-receivers, who claimed to have gained improved understanding of bioinformatics and its relevance to research. Equally, peer-facilitators also developed a better understanding of the subject and appreciated that the activity was a rare and invaluable opportunity to develop their teaching and mentoring skills, enhancing their employability. PMID:29098185
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E-Learning as a new tool in bioinformatics teaching
Saravanan, Vijayakumar; Shanmughavel, Piramanayagam
2007-01-01
In recent years, virtual learning is growing rapidly. Universities, colleges, and secondary schools are now delivering training and education over the internet. Beside this, resources available over the WWW are huge and understanding the various techniques employed in the field of Bioinformatics is increasingly complex for students during implementation. Here, we discuss its importance in developing and delivering an educational system in Bioinformatics based on e-learning environment. PMID:18292800
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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.
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Teaching bioinformatics and neuroinformatics by using free web-based tools.
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 anatomy (Mouse Brain Library), quantitative trait locus analysis (WebQTL from GeneNetwork), bioinformatics and gene expression analyses (University of California, Santa Cruz Genome Browser, National Center for Biotechnology Information's Entrez Gene, and the Allen Brain Atlas), and information resources (PubMed). Instructors can use these various websites in concert to teach genetics from the phenotypic level to the molecular level, aspects of neuroanatomy and histology, statistics, quantitative trait locus analysis, and molecular biology (including in situ hybridization and microarray analysis), and to introduce bioinformatic resources. Students use these resources to discover 1) the region(s) of chromosome(s) influencing the phenotypic trait, 2) a list of candidate genes-narrowed by expression data, 3) the in situ pattern of a given gene in the region of interest, 4) the nucleotide sequence of the candidate gene, and 5) articles describing the gene. Teaching materials such as a detailed student/instructor's manual, PowerPoints, sample exams, and links to free Web resources can be found at http://mdcune.psych.ucla.edu/modules/bioinformatics.
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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. PMID:24006393
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NASA Astrophysics Data System (ADS)
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.
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Planning bioinformatics workflows using an expert system.
Chen, Xiaoling; Chang, Jeffrey T
2017-04-15
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. 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. https://github.com/jefftc/changlab. jeffrey.t.chang@uth.tmc.edu. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com
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The GMOD Drupal Bioinformatic Server Framework
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
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Planning bioinformatics workflows using an expert system
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
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Keemei: cloud-based validation of tabular bioinformatics file formats in Google Sheets.
Rideout, Jai Ram; Chase, John H; Bolyen, Evan; Ackermann, Gail; González, Antonio; Knight, Rob; Caporaso, J Gregory
2016-06-13
Bioinformatics software often requires human-generated tabular text files as input and has specific requirements for how those data are formatted. Users frequently manage these data in spreadsheet programs, which is convenient for researchers who are compiling the requisite information because the spreadsheet programs can easily be used on different platforms including laptops and tablets, and because they provide a familiar interface. It is increasingly common for many different researchers to be involved in compiling these data, including study coordinators, clinicians, lab technicians and bioinformaticians. As a result, many research groups are shifting toward using cloud-based spreadsheet programs, such as Google Sheets, which support the concurrent editing of a single spreadsheet by different users working on different platforms. Most of the researchers who enter data are not familiar with the formatting requirements of the bioinformatics programs that will be used, so validating and correcting file formats is often a bottleneck prior to beginning bioinformatics analysis. We present Keemei, a Google Sheets Add-on, for validating tabular files used in bioinformatics analyses. Keemei is available free of charge from Google's Chrome Web Store. Keemei can be installed and run on any web browser supported by Google Sheets. Keemei currently supports the validation of two widely used tabular bioinformatics formats, the Quantitative Insights into Microbial Ecology (QIIME) sample metadata mapping file format and the Spatially Referenced Genetic Data (SRGD) format, but is designed to easily support the addition of others. Keemei will save researchers time and frustration by providing a convenient interface for tabular bioinformatics file format validation. By allowing everyone involved with data entry for a project to easily validate their data, it will reduce the validation and formatting bottlenecks that are commonly encountered when human-generated data files are 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.
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Development of Bioinformatics Infrastructure for Genomics Research.
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 downstream interpretation of prioritized variants. To provide support for these and other bioinformatics queries, an online bioinformatics helpdesk backed by broad consortium expertise has been established. Further support is provided by means of various modes of bioinformatics training. For the past 4 years, the development of infrastructure support and human capacity through H3ABioNet, have significantly contributed to the establishment of African scientific networks, data analysis facilities, and training programs. Here, we describe the infrastructure and how it has affected genomics and bioinformatics research in Africa. Copyright © 2017 World Heart Federation (Geneva). Published by Elsevier B.V. All rights reserved.
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Decision tree and ensemble learning algorithms with their applications in bioinformatics.
Che, Dongsheng; Liu, Qi; Rasheed, Khaled; Tao, Xiuping
2011-01-01
Machine learning approaches have wide applications in bioinformatics, and decision tree is one of the successful approaches applied in this field. In this chapter, we briefly review decision tree and related ensemble algorithms and show the successful applications of such approaches on solving biological problems. We hope that by learning the algorithms of decision trees and ensemble classifiers, biologists can get the basic ideas of how machine learning algorithms work. On the other hand, by being exposed to the applications of decision trees and ensemble algorithms in bioinformatics, computer scientists can get better ideas of which bioinformatics topics they may work on in their future research directions. We aim to provide a platform to bridge the gap between biologists and computer scientists.
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Bioinformatics Projects Supporting Life-Sciences Learning in High Schools
Marques, Isabel; Almeida, Paulo; Alves, Renato; Dias, Maria João; Godinho, Ana; Pereira-Leal, José B.
2014-01-01
The interdisciplinary nature of bioinformatics makes it an ideal framework to develop activities enabling enquiry-based learning. We describe here the development and implementation of a pilot project to use bioinformatics-based research activities in high schools, called “Bioinformatics@school.” It includes web-based research projects that students can pursue alone or under teacher supervision and a teacher training program. The project is organized so as to enable discussion of key results between students and teachers. After successful trials in two high schools, as measured by questionnaires, interviews, and assessment of knowledge acquisition, the project is expanding by the action of the teachers involved, who are helping us develop more content and are recruiting more teachers and schools. PMID:24465192
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Survey of MapReduce frame operation in bioinformatics.
Zou, Quan; Li, Xu-Bin; Jiang, Wen-Rui; Lin, Zi-Yu; Li, Gui-Lin; Chen, Ke
2014-07-01
Bioinformatics is challenged by the fact that traditional analysis tools have difficulty in processing large-scale data from high-throughput sequencing. The open source Apache Hadoop project, which adopts the MapReduce framework and a distributed file system, has recently given bioinformatics researchers an opportunity to achieve scalable, efficient and reliable computing performance on Linux clusters and on cloud computing services. In this article, we present MapReduce frame-based applications that can be employed in the next-generation sequencing and other biological domains. In addition, we discuss the challenges faced by this field as well as the future works on parallel computing in bioinformatics. © The Author 2013. Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.
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BioSmalltalk: a pure object system and library for bioinformatics.
Morales, Hernán F; Giovambattista, Guillermo
2013-09-15
We have developed BioSmalltalk, a new environment system for pure object-oriented bioinformatics programming. Adaptive end-user programming systems tend to become more important for discovering biological knowledge, as is demonstrated by the emergence of open-source programming toolkits for bioinformatics in the past years. Our software is intended to bridge the gap between bioscientists and rapid software prototyping while preserving the possibility of scaling to whole-system biology applications. BioSmalltalk performs better in terms of execution time and memory usage than Biopython and BioPerl for some classical situations. BioSmalltalk is cross-platform and freely available (MIT license) through the Google Project Hosting at http://code.google.com/p/biosmalltalk hernan.morales@gmail.com Supplementary data are available at Bioinformatics online.
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2016 update on APBioNet's annual international conference on bioinformatics (InCoB).
Schönbach, Christian; Verma, Chandra; Wee, Lawrence Jin Kiat; Bond, Peter John; Ranganathan, Shoba
2016-12-22
InCoB became since its inception in 2002 one of the largest annual bioinformatics conferences in the Asia-Pacific region with attendance ranging between 150 and 250 delegates depending on the venue location. InCoB 2016 in Singapore was attended by almost 220 delegates. This year, sessions on structural bioinformatics, sequence and sequencing, and next-generation sequencing fielded the highest number of oral presentation. Forty-four out 96 oral presentations were associated with an accepted manuscript in supplemental issues of BMC Bioinformatics, BMC Genomics, BMC Medical Genomics or BMC Systems Biology. Articles with a genomics focus are reviewed in this editorial. Next year's InCoB will be held in Shenzen, China from September 20 to 22, 2017.
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Bioinformatic training needs at a health sciences campus.
Oliver, Jeffrey C
2017-01-01
Health sciences research is increasingly focusing on big data applications, such as genomic technologies and precision medicine, to address key issues in human health. These approaches rely on biological data repositories and bioinformatic analyses, both of which are growing rapidly in size and scope. Libraries play a key role in supporting researchers in navigating these and other information resources. With the goal of supporting bioinformatics research in the health sciences, the University of Arizona Health Sciences Library established a Bioinformation program. To shape the support provided by the library, I developed and administered a needs assessment survey to the University of Arizona Health Sciences campus in Tucson, Arizona. The survey was designed to identify the training topics of interest to health sciences researchers and the preferred modes of training. Survey respondents expressed an interest in a broad array of potential training topics, including "traditional" information seeking as well as interest in analytical training. Of particular interest were training in transcriptomic tools and the use of databases linking genotypes and phenotypes. Staff were most interested in bioinformatics training topics, while faculty were the least interested. Hands-on workshops were significantly preferred over any other mode of training. The University of Arizona Health Sciences Library is meeting those needs through internal programming and external partnerships. The results of the survey demonstrate a keen interest in a variety of bioinformatic resources; the challenge to the library is how to address those training needs. The mode of support depends largely on library staff expertise in the numerous subject-specific databases and tools. Librarian-led bioinformatic training sessions provide opportunities for engagement with researchers at multiple points of the research life cycle. When training needs exceed library capacity, partnering with intramural and extramural units will be crucial in library support of health sciences bioinformatic research.
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Mason, Amy; Foster, Dona; Bradley, Phelim; Golubchik, Tanya; Doumith, Michel; Gordon, N Claire; Pichon, Bruno; Iqbal, Zamin; Staves, Peter; Crook, Derrick; Walker, A Sarah; Kearns, Angela; Peto, Tim
2018-06-20
Background : In principle, whole genome sequencing (WGS) can predict phenotypic resistance directly from genotype, replacing laboratory-based tests. However, the contribution of different bioinformatics methods to genotype-phenotype discrepancies has not been systematically explored to date. Methods : We compared three WGS-based bioinformatics methods (Genefinder (read-based), Mykrobe (de Bruijn graph-based) and Typewriter (BLAST-based)) for predicting presence/absence of 83 different resistance determinants and virulence genes, and overall antimicrobial susceptibility, in 1379 Staphylococcus aureus isolates previously characterised by standard laboratory methods (disc diffusion, broth and/or agar dilution and PCR). Results : 99.5% (113830/114457) of individual resistance-determinant/virulence gene predictions were identical between all three methods, with only 627 (0.5%) discordant predictions, demonstrating high overall agreement (Fliess-Kappa=0.98, p<0.0001). Discrepancies when identified were in only one of the three methods for all genes except the cassette recombinase, ccrC(b ). Genotypic antimicrobial susceptibility prediction matched laboratory phenotype in 98.3% (14224/14464) cases (2720 (18.8%) resistant, 11504 (79.5%) susceptible). There was greater disagreement between the laboratory phenotypes and the combined genotypic predictions (97 (0.7%) phenotypically-susceptible but all bioinformatic methods reported resistance; 89 (0.6%) phenotypically-resistant, but all bioinformatics methods reported susceptible) than within the three bioinformatics methods (54 (0.4%) cases, 16 phenotypically-resistant, 38 phenotypically-susceptible). However, in 36/54 (67%), the consensus genotype matched the laboratory phenotype. Conclusions : In this study, the choice between these three specific bioinformatic methods to identify resistance-determinants or other genes in S. aureus did not prove critical, with all demonstrating high concordance with each other and phenotypic/molecular methods. However, each has some limitations and therefore consensus methods provide some assurance. Copyright © 2018 American Society for Microbiology.
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Brown, James A L
2016-05-06
A pedagogic intervention, in the form of an inquiry-based peer-assisted learning project (as a practical student-led bioinformatics module), was assessed for its ability to increase students' engagement, practical bioinformatic skills and process-specific knowledge. Elements assessed were process-specific knowledge following module completion, qualitative student-based module evaluation and the novelty, scientific validity and quality of written student reports. Bioinformatics is often the starting point for laboratory-based research projects, therefore high importance was placed on allowing students to individually develop and apply processes and methods of scientific research. Students led a bioinformatic inquiry-based project (within a framework of inquiry), discovering, justifying and exploring individually discovered research targets. Detailed assessable reports were produced, displaying data generated and the resources used. Mimicking research settings, undergraduates were divided into small collaborative groups, with distinctive central themes. The module was evaluated by assessing the quality and originality of the students' targets through reports, reflecting students' use and understanding of concepts and tools required to generate their data. Furthermore, evaluation of the bioinformatic module was assessed semi-quantitatively using pre- and post-module quizzes (a non-assessable activity, not contributing to their grade), which incorporated process- and content-specific questions (indicative of their use of the online tools). Qualitative assessment of the teaching intervention was performed using post-module surveys, exploring student satisfaction and other module specific elements. Overall, a positive experience was found, as was a post module increase in correct process-specific answers. In conclusion, an inquiry-based peer-assisted learning module increased students' engagement, practical bioinformatic skills and process-specific knowledge. © 2016 by The International Union of Biochemistry and Molecular Biology, 44:304-313 2016. © 2016 The International Union of Biochemistry and Molecular Biology.
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Skate Genome Project: Cyber-Enabled Bioinformatics Collaboration
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.
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Protein Bioinformatics Databases and Resources
Chen, Chuming; Huang, Hongzhan; Wu, Cathy H.
2017-01-01
Many publicly available data repositories and resources have been developed to support protein related information management, data-driven hypothesis generation and biological knowledge discovery. To help researchers quickly find the appropriate protein related informatics resources, we present a comprehensive review (with categorization and description) of major protein bioinformatics databases in this chapter. We also discuss the challenges and opportunities for developing next-generation protein bioinformatics databases and resources to support data integration and data analytics in the Big Data era. PMID:28150231
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Bioconductor: open software development for computational biology and bioinformatics
Gentleman, Robert C; Carey, Vincent J; Bates, Douglas M; Bolstad, Ben; Dettling, Marcel; Dudoit, Sandrine; Ellis, Byron; Gautier, Laurent; Ge, Yongchao; Gentry, Jeff; Hornik, Kurt; Hothorn, Torsten; Huber, Wolfgang; Iacus, Stefano; Irizarry, Rafael; Leisch, Friedrich; Li, Cheng; Maechler, Martin; Rossini, Anthony J; Sawitzki, Gunther; Smith, Colin; Smyth, Gordon; Tierney, Luke; Yang, Jean YH; Zhang, Jianhua
2004-01-01
The Bioconductor project is an initiative for the collaborative creation of extensible software for computational biology and bioinformatics. The goals of the project include: fostering collaborative development and widespread use of innovative software, reducing barriers to entry into interdisciplinary scientific research, and promoting the achievement of remote reproducibility of research results. We describe details of our aims and methods, identify current challenges, compare Bioconductor to other open bioinformatics projects, and provide working examples. PMID:15461798
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Prediction of Acute Mountain Sickness using a Blood-Based Test
2016-01-01
2015): In quarter 17 we focused on two major tasks: getting the RNA purified and ready for chip analysis and working on the bioinformatics ... bioinformatics organization of all the data we will examine for this study. To remind the reviewer, we have a primary dataset of ~120 subjects who were studied...companion study, AltitudeOmics, to the database of gene studies to be analyzed for AMS prediction • expansion of a bioinformatics team to include an
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Korcsmaros, Tamas; Dunai, Zsuzsanna A; Vellai, Tibor; Csermely, Peter
2013-09-01
The number of bioinformatics tools and resources that support molecular and cell biology approaches is continuously expanding. Moreover, systems and network biology analyses are accompanied more and more by integrated bioinformatics methods. Traditional information-centered university teaching methods often fail, as (1) it is impossible to cover all existing approaches in the frame of a single course, and (2) a large segment of the current bioinformation can become obsolete in a few years. Signaling network offers an excellent example for teaching bioinformatics resources and tools, as it is both focused and complex at the same time. Here, we present an outline of a university bioinformatics course with four sample practices to demonstrate how signaling network studies can integrate biochemistry, genetics, cell biology and network sciences. We show that several bioinformatics resources and tools, as well as important concepts and current trends, can also be integrated to signaling network studies. The research-type hands-on experiences we show enable the students to improve key competences such as teamworking, creative and critical thinking and problem solving. Our classroom course curriculum can be re-formulated as an e-learning material or applied as a part of a specific training course. The multi-disciplinary approach and the mosaic setup of the course have the additional benefit to support the advanced teaching of talented students.
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An overview of topic modeling and its current applications in bioinformatics.
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.
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Mayer, Gerhard; Quast, Christian; Felden, Janine; Lange, Matthias; Prinz, Manuel; Pühler, Alfred; Lawerenz, Chris; Scholz, Uwe; Glöckner, Frank Oliver; Müller, Wolfgang; Marcus, Katrin; Eisenacher, Martin
2017-10-30
Sustainable noncommercial bioinformatics infrastructures are a prerequisite to use and take advantage of the potential of big data analysis for research and economy. Consequently, funders, universities and institutes as well as users ask for a transparent value model for the tools and services offered. In this article, a generally applicable lightweight method is described by which bioinformatics infrastructure projects can estimate the value of tools and services offered without determining exactly the total costs of ownership. Five representative scenarios for value estimation from a rough estimation to a detailed breakdown of costs are presented. To account for the diversity in bioinformatics applications and services, the notion of service-specific 'service provision units' is introduced together with the factors influencing them and the main underlying assumptions for these 'value influencing factors'. Special attention is given on how to handle personnel costs and indirect costs such as electricity. Four examples are presented for the calculation of the value of tools and services provided by the German Network for Bioinformatics Infrastructure (de.NBI): one for tool usage, one for (Web-based) database analyses, one for consulting services and one for bioinformatics training events. Finally, from the discussed values, the costs of direct funding and the costs of payment of services by funded projects are calculated and compared. © The Author 2017. Published by Oxford University Press.
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Bioinformatic approaches to interrogating vitamin D receptor signaling.
Campbell, Moray J
2017-09-15
Bioinformatics applies unbiased approaches to develop statistically-robust insight into health and disease. At the global, or "20,000 foot" view bioinformatic analyses of vitamin D receptor (NR1I1/VDR) signaling can measure where the VDR gene or protein exerts a genome-wide significant impact on biology; VDR is significantly implicated in bone biology and immune systems, but not in cancer. With a more VDR-centric, or "2000 foot" view, bioinformatic approaches can interrogate events downstream of VDR activity. Integrative approaches can combine VDR ChIP-Seq in cell systems where significant volumes of publically available data are available. For example, VDR ChIP-Seq studies can be combined with genome-wide association studies to reveal significant associations to immune phenotypes. Similarly, VDR ChIP-Seq can be combined with data from Cancer Genome Atlas (TCGA) to infer the impact of VDR target genes in cancer progression. Therefore, bioinformatic approaches can reveal what aspects of VDR downstream networks are significantly related to disease or phenotype. Copyright © 2017 The Author. Published by Elsevier B.V. All rights reserved.
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Pitassi, Claudio; Gonçalves, Antonio Augusto; Moreno Júnior, Valter de Assis
2014-01-01
The scope of this article is to identify and analyze the factors that influence the adoption of ICT tools in experiments with bioinformatics at the Brazilian Cancer Institute (INCA). It involves a descriptive and exploratory qualitative field study. Evidence was collected mainly based on in-depth interviews with the management team at the Research Center and the IT Division. The answers were analyzed using the categorical content method. The categories were selected from the scientific literature and consolidated in the Technology-Organization-Environment (TOE) framework created for this study. The model proposed made it possible to demonstrate how the factors selected impacted INCA´s adoption of bioinformatics systems and tools, contributing to the investigation of two critical areas for the development of the health industry in Brazil, namely technological innovation and bioinformatics. Based on the evidence collected, a research question was posed: to what extent can the alignment of the factors related to the adoption of ICT tools in experiments with bioinformatics increase the innovation capacity of a Brazilian biopharmaceutical organization?
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Relax with CouchDB--into the non-relational DBMS era of bioinformatics.
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.
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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.
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Incorporating Genomics and Bioinformatics across the Life Sciences Curriculum
DOE Office of Scientific and Technical Information (OSTI.GOV)
Ditty, Jayna L.; Kvaal, Christopher A.; Goodner, Brad
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 methodologiesmore » in undergraduate education leads to increased undergraduate and post-graduate retention in the sciences. Toward this end, many undergraduate teaching organizations offer training and suggestions for faculty to update and improve their teaching approaches to help students learn as scientists, through design and discovery (e.g., Council of Undergraduate Research [www.cur.org] and Project Kaleidoscope [www.pkal.org]). With the advent of genome sequencing and bioinformatics, many scientists now formulate biological questions and interpret research results in the context of genomic information. Just as the use of bioinformatic tools and databases changed the way scientists investigate problems, it must change how scientists teach to create new opportunities for students to gain experiences reflecting the influence of genomics, proteomics, and bioinformatics on modern life sciences research. Educators have responded by incorporating bioinformatics into diverse life science curricula. While these published exercises in, and guidelines for, bioinformatics curricula are helpful and inspirational, faculty new to the area of bioinformatics inevitably need training in the theoretical underpinnings of the algorithms. Moreover, effectively integrating bioinformatics into courses or independent research projects requires infrastructure for organizing and assessing student work. Here, we present a new platform for faculty to keep current with the rapidly changing field of bioinformatics, the Integrated Microbial Genomes Annotation Collaboration Toolkit (IMG-ACT). It was developed by instructors from both research-intensive and predominately undergraduate institutions in collaboration with the Department of Energy-Joint Genome Institute (DOE-JGI) as a means to innovate and update undergraduate education and faculty development. The IMG-ACT program provides a cadre of tools, including access to a clearinghouse of genome sequences, bioinformatics databases, data storage, instructor course management, and student notebooks for organizing the results of their bioinformatic investigations. In the process, IMG-ACT makes it feasible to provide undergraduate research opportunities to a greater number and diversity of students, in contrast to the traditional mentor-to-student apprenticeship model for undergraduate research, which can be too expensive and time-consuming to provide for every undergraduate. The IMG-ACT serves as the hub for the network of faculty and students that use the system for microbial genome analysis. Open access of the IMG-ACT infrastructure to participating schools ensures that all types of higher education institutions can utilize it. With the infrastructure in place, faculty can focus their efforts on the pedagogy of bioinformatics, involvement of students in research, and use of this tool for their own research agenda. What the original faculty members of the IMG-ACT development team present here is an overview of how the IMG-ACT program has affected our development in terms of teaching and research with the hopes that it will inspire more faculty to get involved.« less
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Cake: a bioinformatics pipeline for the integrated analysis of somatic variants in cancer genomes
Rashid, Mamunur; Robles-Espinoza, Carla Daniela; Rust, Alistair G.; Adams, David J.
2013-01-01
Summary: We have developed Cake, a bioinformatics software pipeline that integrates four publicly available somatic variant-calling algorithms to identify single nucleotide variants with higher sensitivity and accuracy than any one algorithm alone. Cake can be run on a high-performance computer cluster or used as a stand-alone application. Availabilty: Cake is open-source and is available from http://cakesomatic.sourceforge.net/ Contact: da1@sanger.ac.uk Supplementary Information: Supplementary data are available at Bioinformatics online. PMID:23803469
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Glossary of bioinformatics terms.
2007-06-01
This collection of terms and definitions commonly encountered in the bioinformatics literature will be updated periodically as Current Protocols in Bioinformatics grows. In addition, an extensive glossary of genetic terms can be found on the Web site of the National Human Genome Research Institute (http://www.genome.gov/glossary.cfm). The entries in that online glossary provide a brief written definition of the term; the user can also listen to an informative explanation of the term using RealAudio or the Windows Media Player.
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Sundstrom, J.; Tash, B; Murakami, T
2009-01-01
The molecular function of occludin, an integral membrane component of tight junctions, remains unclear. VEGF-induced phosphorylation sites were mapped on occludin by combining MS data analysis with bioinformatics. In vivo phosphorylation of Ser490 was validated and protein interaction studies combined with crystal structure analysis suggest that Ser490 phosphorylation attenuates the interaction between occludin and ZO-1. This study demonstrates that combining MS data and bioinformatics can successfully identify novel phosphorylation sites from limiting samples.
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Bioinformatics in the Netherlands: the value of a nationwide community.
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.
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Generations of interdisciplinarity in bioinformatics
Bartlett, Andrew; Lewis, Jamie; Williams, Matthew L.
2016-01-01
Bioinformatics, a specialism propelled into relevance by the Human Genome Project and the subsequent -omic turn in the life science, is an interdisciplinary field of research. Qualitative work on the disciplinary identities of bioinformaticians has revealed the tensions involved in work in this “borderland.” As part of our ongoing work on the emergence of bioinformatics, between 2010 and 2011, we conducted a survey of United Kingdom-based academic bioinformaticians. Building on insights drawn from our fieldwork over the past decade, we present results from this survey relevant to a discussion of disciplinary generation and stabilization. Not only is there evidence of an attitudinal divide between the different disciplinary cultures that make up bioinformatics, but there are distinctions between the forerunners, founders and the followers; as inter/disciplines mature, they face challenges that are both inter-disciplinary and inter-generational in nature. PMID:27453689
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G2LC: Resources Autoscaling for Real Time Bioinformatics Applications in IaaS.
Hu, Rongdong; Liu, Guangming; Jiang, Jingfei; Wang, Lixin
2015-01-01
Cloud computing has started to change the way how bioinformatics research is being carried out. Researchers who have taken advantage of this technology can process larger amounts of data and speed up scientific discovery. The variability in data volume results in variable computing requirements. Therefore, bioinformatics researchers are pursuing more reliable and efficient methods for conducting sequencing analyses. This paper proposes an automated resource provisioning method, G2LC, for bioinformatics applications in IaaS. It enables application to output the results in a real time manner. Its main purpose is to guarantee applications performance, while improving resource utilization. Real sequence searching data of BLAST is used to evaluate the effectiveness of G2LC. Experimental results show that G2LC guarantees the application performance, while resource is saved up to 20.14%.
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BioContainers: an open-source and community-driven framework for software standardization.
da Veiga Leprevost, Felipe; Grüning, Björn A; Alves Aflitos, Saulo; Röst, Hannes L; Uszkoreit, Julian; Barsnes, Harald; Vaudel, Marc; Moreno, Pablo; Gatto, Laurent; Weber, Jonas; Bai, Mingze; Jimenez, Rafael C; Sachsenberg, Timo; Pfeuffer, Julianus; Vera Alvarez, Roberto; Griss, Johannes; Nesvizhskii, Alexey I; Perez-Riverol, Yasset
2017-08-15
BioContainers (biocontainers.pro) is an open-source and community-driven framework which provides platform independent executable environments for bioinformatics software. BioContainers allows labs of all sizes to easily install bioinformatics software, maintain multiple versions of the same software and combine tools into powerful analysis pipelines. BioContainers is based on popular open-source projects Docker and rkt frameworks, that allow software to be installed and executed under an isolated and controlled environment. Also, it provides infrastructure and basic guidelines to create, manage and distribute bioinformatics containers with a special focus on omics technologies. These containers can be integrated into more comprehensive bioinformatics pipelines and different architectures (local desktop, cloud environments or HPC clusters). The software is freely available at github.com/BioContainers/. yperez@ebi.ac.uk. © The Author(s) 2017. Published by Oxford University Press.
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BioContainers: an open-source and community-driven framework for software standardization
da Veiga Leprevost, Felipe; Grüning, Björn A.; Alves Aflitos, Saulo; Röst, Hannes L.; Uszkoreit, Julian; Barsnes, Harald; Vaudel, Marc; Moreno, Pablo; Gatto, Laurent; Weber, Jonas; Bai, Mingze; Jimenez, Rafael C.; Sachsenberg, Timo; Pfeuffer, Julianus; Vera Alvarez, Roberto; Griss, Johannes; Nesvizhskii, Alexey I.; Perez-Riverol, Yasset
2017-01-01
Abstract Motivation BioContainers (biocontainers.pro) is an open-source and community-driven framework which provides platform independent executable environments for bioinformatics software. BioContainers allows labs of all sizes to easily install bioinformatics software, maintain multiple versions of the same software and combine tools into powerful analysis pipelines. BioContainers is based on popular open-source projects Docker and rkt frameworks, that allow software to be installed and executed under an isolated and controlled environment. Also, it provides infrastructure and basic guidelines to create, manage and distribute bioinformatics containers with a special focus on omics technologies. These containers can be integrated into more comprehensive bioinformatics pipelines and different architectures (local desktop, cloud environments or HPC clusters). Availability and Implementation The software is freely available at github.com/BioContainers/. Contact yperez@ebi.ac.uk PMID:28379341
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G2LC: Resources Autoscaling for Real Time Bioinformatics Applications in IaaS
Hu, Rongdong; Liu, Guangming; Jiang, Jingfei; Wang, Lixin
2015-01-01
Cloud computing has started to change the way how bioinformatics research is being carried out. Researchers who have taken advantage of this technology can process larger amounts of data and speed up scientific discovery. The variability in data volume results in variable computing requirements. Therefore, bioinformatics researchers are pursuing more reliable and efficient methods for conducting sequencing analyses. This paper proposes an automated resource provisioning method, G2LC, for bioinformatics applications in IaaS. It enables application to output the results in a real time manner. Its main purpose is to guarantee applications performance, while improving resource utilization. Real sequence searching data of BLAST is used to evaluate the effectiveness of G2LC. Experimental results show that G2LC guarantees the application performance, while resource is saved up to 20.14%. PMID:26504488
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Chattopadhyay, Ansuman; Tannery, Nancy Hrinya; Silverman, Deborah A. L.; Bergen, Phillip; Epstein, Barbara A.
2006-01-01
Setting: In summer 2002, the Health Sciences Library System (HSLS) at the University of Pittsburgh initiated an information service in molecular biology and genetics to assist researchers with identifying and utilizing bioinformatics tools. Program Components: This novel information service comprises hands-on training workshops and consultation on the use of bioinformatics tools. The HSLS also provides an electronic portal and networked access to public and commercial molecular biology databases and software packages. Evaluation Mechanisms: Researcher feedback gathered during the first three years of workshops and individual consultation indicate that the information service is meeting user needs. Next Steps/Future Directions: The service's workshop offerings will expand to include emerging bioinformatics topics. A frequently asked questions database is also being developed to reuse advice on complex bioinformatics questions. PMID:16888665
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An overview of the Hadoop/MapReduce/HBase framework and its current applications in bioinformatics
DOE Office of Scientific and Technical Information (OSTI.GOV)
Taylor, Ronald C.
Bioinformatics researchers are increasingly confronted with analysis of ultra large-scale data sets, a problem that will only increase at an alarming rate in coming years. Recent developments in open source software, that is, the Hadoop project and associated software, provide a foundation for scaling to petabyte scale data warehouses on Linux clusters, providing fault-tolerant parallelized analysis on such data using a programming style named MapReduce. An overview is given of the current usage within the bioinformatics community of Hadoop, a top-level Apache Software Foundation project, and of associated open source software projects. The concepts behind Hadoop and the associated HBasemore » project are defined, and current bioinformatics software that employ Hadoop is described. The focus is on next-generation sequencing, as the leading application area to date.« less
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InCoB celebrates its tenth anniversary as first joint conference with ISCB-Asia
2011-01-01
In 2009 the International Society for Computational Biology (ISCB) started to roll out regional bioinformatics conferences in Africa, Latin America and Asia. The open and competitive bid for the first meeting in Asia (ISCB-Asia) was awarded to Asia-Pacific Bioinformatics Network (APBioNet) which has been running the International Conference on Bioinformatics (InCoB) in the Asia-Pacific region since 2002. InCoB/ISCB-Asia 2011 is held from November 30 to December 2, 2011 in Kuala Lumpur, Malaysia. Of 104 manuscripts submitted to BMC Genomics and BMC Bioinformatics conference supplements, 49 (47.1%) were accepted. The strong showing of Asia among submissions (82.7%) and acceptances (81.6%) signals the success of this tenth InCoB anniversary meeting, and bodes well for the future of ISCB-Asia. PMID:22369160
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Yan, Qing
2010-01-01
Bioinformatics is the rational study at an abstract level that can influence the way we understand biomedical facts and the way we apply the biomedical knowledge. Bioinformatics is facing challenges in helping with finding the relationships between genetic structures and functions, analyzing genotype-phenotype associations, and understanding gene-environment interactions at the systems level. One of the most important issues in bioinformatics is data integration. The data integration methods introduced here can be used to organize and integrate both public and in-house data. With the volume of data and the high complexity, computational decision support is essential for integrative transporter studies in pharmacogenomics, nutrigenomics, epigenetics, and systems biology. For the development of such a decision support system, object-oriented (OO) models can be constructed using the Unified Modeling Language (UML). A methodology is developed to build biomedical models at different system levels and construct corresponding UML diagrams, including use case diagrams, class diagrams, and sequence diagrams. By OO modeling using UML, the problems of transporter pharmacogenomics and systems biology can be approached from different angles with a more complete view, which may greatly enhance the efforts in effective drug discovery and development. Bioinformatics resources of membrane transporters and general bioinformatics databases and tools that are frequently used in transporter studies are also collected here. An informatics decision support system based on the models presented here is available at http://www.pharmtao.com/transporter . The methodology developed here can also be used for other biomedical fields.
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AnaBench: a Web/CORBA-based workbench for biomolecular sequence analysis
Badidi, Elarbi; De Sousa, Cristina; Lang, B Franz; Burger, Gertraud
2003-01-01
Background Sequence data analyses such as gene identification, structure modeling or phylogenetic tree inference involve a variety of bioinformatics software tools. Due to the heterogeneity of bioinformatics tools in usage and data requirements, scientists spend much effort on technical issues including data format, storage and management of input and output, and memorization of numerous parameters and multi-step analysis procedures. Results In this paper, we present the design and implementation of AnaBench, an interactive, Web-based bioinformatics Analysis workBench allowing streamlined data analysis. Our philosophy was to minimize the technical effort not only for the scientist who uses this environment to analyze data, but also for the administrator who manages and maintains the workbench. With new bioinformatics tools published daily, AnaBench permits easy incorporation of additional tools. This flexibility is achieved by employing a three-tier distributed architecture and recent technologies including CORBA middleware, Java, JDBC, and JSP. A CORBA server permits transparent access to a workbench management database, which stores information about the users, their data, as well as the description of all bioinformatics applications that can be launched from the workbench. Conclusion AnaBench is an efficient and intuitive interactive bioinformatics environment, which offers scientists application-driven, data-driven and protocol-driven analysis approaches. The prototype of AnaBench, managed by a team at the Université de Montréal, is accessible on-line at: . Please contact the authors for details about setting up a local-network AnaBench site elsewhere. PMID:14678565
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Wright, Victoria Ann; Vaughan, Brendan W; Laurent, Thomas; Lopez, Rodrigo; Brooksbank, Cath; Schneider, Maria Victoria
2010-11-01
Today's molecular life scientists are well educated in the emerging experimental tools of their trade, but when it comes to training on the myriad of resources and tools for dealing with biological data, a less ideal situation emerges. Often bioinformatics users receive no formal training on how to make the most of the bioinformatics resources and tools available in the public domain. The European Bioinformatics Institute, which is part of the European Molecular Biology Laboratory (EMBL-EBI), holds the world's most comprehensive collection of molecular data, and training the research community to exploit this information is embedded in the EBI's mission. We have evaluated eLearning, in parallel with face-to-face courses, as a means of training users of our data resources and tools. We anticipate that eLearning will become an increasingly important vehicle for delivering training to our growing user base, so we have undertaken an extensive review of Learning Content Management Systems (LCMSs). Here, we describe the process that we used, which considered the requirements of trainees, trainers and systems administrators, as well as taking into account our organizational values and needs. This review describes the literature survey, user discussions and scripted platform testing that we performed to narrow down our choice of platform from 36 to a single platform. We hope that it will serve as guidance for others who are seeking to incorporate eLearning into their bioinformatics training programmes.
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What is bioinformatics? A proposed definition and overview of the field.
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.
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Panji, Sumir; Fernandes, Pedro L.; Judge, David P.; Ghouila, Amel; Salifu, Samson P.; Ahmed, Rehab; Kayondo, Jonathan; Ssemwanga, Deogratius
2017-01-01
Africa is not unique in its need for basic bioinformatics training for individuals from a diverse range of academic backgrounds. However, particular logistical challenges in Africa, most notably access to bioinformatics expertise and internet stability, must be addressed in order to meet this need on the continent. H3ABioNet (www.h3abionet.org), the Pan African Bioinformatics Network for H3Africa, has therefore developed an innovative, free-of-charge “Introduction to Bioinformatics” course, taking these challenges into account as part of its educational efforts to provide on-site training and develop local expertise inside its network. A multiple-delivery–mode learning model was selected for this 3-month course in order to increase access to (mostly) African, expert bioinformatics trainers. The content of the course was developed to include a range of fundamental bioinformatics topics at the introductory level. For the first iteration of the course (2016), classrooms with a total of 364 enrolled participants were hosted at 20 institutions across 10 African countries. To ensure that classroom success did not depend on stable internet, trainers pre-recorded their lectures, and classrooms downloaded and watched these locally during biweekly contact sessions. The trainers were available via video conferencing to take questions during contact sessions, as well as via online “question and discussion” forums outside of contact session time. This learning model, developed for a resource-limited setting, could easily be adapted to other settings. PMID:28981516
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Datasets2Tools, repository and search engine for bioinformatics datasets, tools and canned analyses
Torre, Denis; Krawczuk, Patrycja; Jagodnik, Kathleen M.; Lachmann, Alexander; Wang, Zichen; Wang, Lily; Kuleshov, Maxim V.; Ma’ayan, Avi
2018-01-01
Biomedical data repositories such as the Gene Expression Omnibus (GEO) enable the search and discovery of relevant biomedical digital data objects. Similarly, resources such as OMICtools, index bioinformatics tools that can extract knowledge from these digital data objects. However, systematic access to pre-generated ‘canned’ analyses applied by bioinformatics tools to biomedical digital data objects is currently not available. Datasets2Tools is a repository indexing 31,473 canned bioinformatics analyses applied to 6,431 datasets. The Datasets2Tools repository also contains the indexing of 4,901 published bioinformatics software tools, and all the analyzed datasets. Datasets2Tools enables users to rapidly find datasets, tools, and canned analyses through an intuitive web interface, a Google Chrome extension, and an API. Furthermore, Datasets2Tools provides a platform for contributing canned analyses, datasets, and tools, as well as evaluating these digital objects according to their compliance with the findable, accessible, interoperable, and reusable (FAIR) principles. By incorporating community engagement, Datasets2Tools promotes sharing of digital resources to stimulate the extraction of knowledge from biomedical research data. Datasets2Tools is freely available from: http://amp.pharm.mssm.edu/datasets2tools. PMID:29485625
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Datasets2Tools, repository and search engine for bioinformatics datasets, tools and canned analyses.
Torre, Denis; Krawczuk, Patrycja; Jagodnik, Kathleen M; Lachmann, Alexander; Wang, Zichen; Wang, Lily; Kuleshov, Maxim V; Ma'ayan, Avi
2018-02-27
Biomedical data repositories such as the Gene Expression Omnibus (GEO) enable the search and discovery of relevant biomedical digital data objects. Similarly, resources such as OMICtools, index bioinformatics tools that can extract knowledge from these digital data objects. However, systematic access to pre-generated 'canned' analyses applied by bioinformatics tools to biomedical digital data objects is currently not available. Datasets2Tools is a repository indexing 31,473 canned bioinformatics analyses applied to 6,431 datasets. The Datasets2Tools repository also contains the indexing of 4,901 published bioinformatics software tools, and all the analyzed datasets. Datasets2Tools enables users to rapidly find datasets, tools, and canned analyses through an intuitive web interface, a Google Chrome extension, and an API. Furthermore, Datasets2Tools provides a platform for contributing canned analyses, datasets, and tools, as well as evaluating these digital objects according to their compliance with the findable, accessible, interoperable, and reusable (FAIR) principles. By incorporating community engagement, Datasets2Tools promotes sharing of digital resources to stimulate the extraction of knowledge from biomedical research data. Datasets2Tools is freely available from: http://amp.pharm.mssm.edu/datasets2tools.
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Opportunities at the Intersection of Bioinformatics and Health Informatics
Miller, Perry L.
2000-01-01
This paper provides a “viewpoint discussion” based on a presentation made to the 2000 Symposium of the American College of Medical Informatics. It discusses potential opportunities for researchers in health informatics to become involved in the rapidly growing field of bioinformatics, using the activities of the Yale Center for Medical Informatics as a case study. One set of opportunities occurs where bioinformatics research itself intersects with the clinical world. Examples include the correlations between individual genetic variation with clinical risk factors, disease presentation, and differential response to treatment; and the implications of including genetic test results in the patient record, which raises clinical decision support issues as well as legal and ethical issues. A second set of opportunities occurs where bioinformatics research can benefit from the technologic expertise and approaches that informaticians have used extensively in the clinical arena. Examples include database organization and knowledge representation, data mining, and modeling and simulation. Microarray technology is discussed as a specific potential area for collaboration. Related questions concern how best to establish collaborations with bioscientists so that the interests and needs of both sets of researchers can be met in a synergistic fashion, and the most appropriate home for bioinformatics in an academic medical center. PMID:10984461
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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.
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Assessing an effective undergraduate module teaching applied bioinformatics to biology students
2018-01-01
Applied bioinformatics skills are becoming ever more indispensable for biologists, yet incorporation of these skills into the undergraduate biology curriculum is lagging behind, in part due to a lack of instructors willing and able to teach basic bioinformatics in classes that don’t specifically focus on quantitative skill development, such as statistics or computer sciences. To help undergraduate course instructors who themselves did not learn bioinformatics as part of their own education and are hesitant to plunge into teaching big data analysis, a module was developed that is written in plain-enough language, using publicly available computing tools and data, to allow novice instructors to teach next-generation sequence analysis to upper-level undergraduate students. To determine if the module allowed students to develop a better understanding of and appreciation for applied bioinformatics, various tools were developed and employed to assess the impact of the module. This article describes both the module and its assessment. Students found the activity valuable for their education and, in focus group discussions, emphasized that they saw a need for more and earlier instruction of big data analysis as part of the undergraduate biology curriculum. PMID:29324777
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Mathematics and evolutionary biology make bioinformatics education comprehensible.
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.
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Mathematics and evolutionary biology make bioinformatics education comprehensible
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
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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
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González-Nilo, Fernando; Pérez-Acle, Tomás; Guínez-Molinos, Sergio; Geraldo, Daniela A; Sandoval, Claudia; Yévenes, Alejandro; Santos, Leonardo S; Laurie, V Felipe; Mendoza, Hegaly; Cachau, Raúl E
2011-01-01
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.
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Wenyi Wang, Statistical Bioinformatics Expert, Visits DCEG
In March 2018, Wenyi Wang, Ph.D., Associate Professor in the Department of Bioinformatics and Computational Biology at the University of Texas MD Anderson Cancer Center, visited DCEG to give a seminar and meet with staff.
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Identification of legionella effectors using bioinformatic approaches.
Segal, Gil
2013-01-01
Legionella pneumophila the causative agent of Legionnaires' disease, actively manipulates host cell processes to establish a replication niche inside host cells. The establishment of its replication niche requires a functional Icm/Dot type IV secretion system which translocates about 300 effector proteins into host cells during infection. Many of these effectors were first identified as effector candidates by several bioinformatic approaches, and these predicted effectors were later examined experimentally for translocation and a large number of which were validated as effector proteins. Here, I summarized the bioinformatic approaches that were used to identify these effectors.
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Murray-Rust, Peter; Mitchell, John BO; Rzepa, Henry S
2005-01-01
Chemical information is now seen as critical for most areas of life sciences. But unlike Bioinformatics, where data is openly available and freely re-usable, most chemical information is closed and cannot be re-distributed without permission. This has led to a failure to adopt modern informatics and software techniques and therefore paucity of chemistry in bioinformatics. New technology, however, offers the hope of making chemical data (compounds and properties) free during the authoring process. We argue that the technology is already available; we require a collective agreement to enhance publication protocols. PMID:15941476
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Intellectual property strategy in bioinformatics and biochips.
Fernandez, Dennis; Chow, Mary
2005-07-15
Intellectual property rights are essential in today's technology-driven age. A strong intellectual property protection strategy is crucial in the bioinformatics and biochips technology spaces as monetary and temporal resources are tremendous in finding a blockbuster drug or gene therapy, as well as in deploying advanced biosensor and other medical systems. Current problems and intellectual property practice in the genomic space are presented and analyzed. Various strategy and solutions are proposed to guide bioinformatic and biochip companies in forming an aggressive strategy to protect one's intellectual property and competitive positioning.
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Educational websites--Bioinformatics Tools II.
Lomberk, Gwen
2009-01-01
In this issue, the highlighted websites are a continuation of a series of educational websites; this one in particular from a couple of years ago, Bioinformatics Tools [Pancreatology 2005;5:314-315]. These include sites that are valuable resources for many research needs in genomics and proteomics. Bioinformatics has become a laboratory tool to map sequences to databases, develop models of molecular interactions, evaluate structural compatibilities, describe differences between normal and disease-associated DNA, identify conserved motifs within proteins, and chart extensive signaling networks, all in silico. Copyright 2008 S. Karger AG, Basel and IAP.
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A Survey of Bioinformatics Database and Software Usage through Mining the Literature.
Duck, Geraint; Nenadic, Goran; Filannino, Michele; Brass, Andy; Robertson, David L; Stevens, Robert
2016-01-01
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.
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A Scientific Software Product Line for the Bioinformatics domain.
Costa, Gabriella Castro B; Braga, Regina; David, José Maria N; Campos, Fernanda
2015-08-01
Most specialized users (scientists) that use bioinformatics applications do not have suitable training on software development. Software Product Line (SPL) employs the concept of reuse considering that it is defined as a set of systems that are developed from a common set of base artifacts. In some contexts, such as in bioinformatics applications, it is advantageous to develop a collection of related software products, using SPL approach. If software products are similar enough, there is the possibility of predicting their commonalities, differences and then reuse these common features to support the development of new applications in the bioinformatics area. This paper presents the PL-Science approach which considers the context of SPL and ontology in order to assist scientists to define a scientific experiment, and to specify a workflow that encompasses bioinformatics applications of a given experiment. This paper also focuses on the use of ontologies to enable the use of Software Product Line in biological domains. In the context of this paper, Scientific Software Product Line (SSPL) differs from the Software Product Line due to the fact that SSPL uses an abstract scientific workflow model. This workflow is defined according to a scientific domain and using this abstract workflow model the products (scientific applications/algorithms) are instantiated. Through the use of ontology as a knowledge representation model, we can provide domain restrictions as well as add semantic aspects in order to facilitate the selection and organization of bioinformatics workflows in a Scientific Software Product Line. The use of ontologies enables not only the expression of formal restrictions but also the inferences on these restrictions, considering that a scientific domain needs a formal specification. This paper presents the development of the PL-Science approach, encompassing a methodology and an infrastructure, and also presents an approach evaluation. This evaluation presents case studies in bioinformatics, which were conducted in two renowned research institutions in Brazil. Copyright © 2015 Elsevier Inc. All rights reserved.
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Partial protein domains: evolutionary insights and bioinformatics challenges.
Kelley, Lawrence A; Sternberg, Michael J E
2015-05-19
Protein domains are generally thought to correspond to units of evolution. New research raises questions about how such domains are defined with bioinformatics tools and sheds light on how evolution has enabled partial domains to be viable.
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Building a bioinformatics community of practice through library education programs.
Moore, Margaret E; Vaughan, K T L; Hayes, Barrie E
2004-01-01
This paper addresses the following questions:What makes the community of practice concept an intriguing framework for developing library services for bioinformatics? What is the campus context and setting? What has been the Health Sciences Library's role in bioinformatics at the University of North Carolina (UNC) Chapel Hill? What are the Health Sciences Library's goals? What services are currently offered? How will these services be evaluated and developed? How can libraries demonstrate their value? Providing library services for an emerging community such as bioinformatics and computational biology presents special challenges for libraries including understanding needs, defining and communicating the library's role, building relationships within the community, preparing staff, and securing funding. Like many academic health sciences libraries, the University of North Carolina (UNC) at Chapel Hill Health Sciences Library is addressing these challenges in the context of its overall mission and goals.
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Development of an undergraduate bioinformatics degree program at a liberal arts college.
Bagga, Paramjeet S
2012-09-01
The highly interdisciplinary field of bioinformatics has emerged as a powerful modern science. There has been a great demand for undergraduate- and graduate-level trained bioinformaticists in the industry as well in the academia. In order to address the needs for trained bioinformaticists, its curriculum must be offered at the undergraduate level, especially at four-year colleges, where a majority of the United States gets its education. There are many challenges in developing an undergraduate-level bioinformatics program that needs to be carefully designed as a well-integrated and cohesive interdisciplinary curriculum that prepares the students for a wide variety of career options. This article describes the challenges of establishing a highly interdisciplinary undergraduate major, the development of an undergraduate bioinformatics degree program at Ramapo College of New Jersey, and lessons learned in the last 10 years during its management.
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ENFIN--A European network for integrative systems biology.
Kahlem, Pascal; Clegg, Andrew; Reisinger, Florian; Xenarios, Ioannis; Hermjakob, Henning; Orengo, Christine; Birney, Ewan
2009-11-01
Integration of biological data of various types and the development of adapted bioinformatics tools represent critical objectives to enable research at the systems level. The European Network of Excellence ENFIN is engaged in developing an adapted infrastructure to connect databases, and platforms to enable both the generation of new bioinformatics tools and the experimental validation of computational predictions. With the aim of bridging the gap existing between standard wet laboratories and bioinformatics, the ENFIN Network runs integrative research projects to bring the latest computational techniques to bear directly on questions dedicated to systems biology in the wet laboratory environment. The Network maintains internally close collaboration between experimental and computational research, enabling a permanent cycling of experimental validation and improvement of computational prediction methods. The computational work includes the development of a database infrastructure (EnCORE), bioinformatics analysis methods and a novel platform for protein function analysis FuncNet.
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Bioinformatics: perspectives for the future.
Costa, Luciano da Fontoura
2004-12-30
I give here a very personal perspective of Bioinformatics and its future, starting by discussing the origin of the term (and area) of bioinformatics and proceeding by trying to foresee the development of related issues, including pattern recognition/data mining, the need to reintegrate biology, the potential of complex networks as a powerful and flexible framework for bioinformatics and the interplay between bio- and neuroinformatics. Human resource formation and market perspective are also addressed. Given the complexity and vastness of these issues and concepts, as well as the limited size of a scientific article and finite patience of the reader, these perspectives are surely incomplete and biased. However, it is expected that some of the questions and trends that are identified will motivate discussions during the IcoBiCoBi round table (with the same name as this article) and perhaps provide a more ample perspective among the participants of that conference and the readers of this text.
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The Development of Computational Biology in South Africa: Successes Achieved and Lessons Learnt
Mulder, Nicola J.; Christoffels, Alan; de Oliveira, Tulio; Gamieldien, Junaid; Hazelhurst, Scott; Joubert, Fourie; Kumuthini, Judit; Pillay, Ché S.; Snoep, Jacky L.; Tastan Bishop, Özlem; Tiffin, Nicki
2016-01-01
Bioinformatics is now a critical skill in many research and commercial environments as biological data are increasing in both size and complexity. South African researchers recognized this need in the mid-1990s and responded by working with the government as well as international bodies to develop initiatives to build bioinformatics capacity in the country. Significant injections of support from these bodies provided a springboard for the establishment of computational biology units at multiple universities throughout the country, which took on teaching, basic research and support roles. Several challenges were encountered, for example with unreliability of funding, lack of skills, and lack of infrastructure. However, the bioinformatics community worked together to overcome these, and South Africa is now arguably the leading country in bioinformatics on the African continent. Here we discuss how the discipline developed in the country, highlighting the challenges, successes, and lessons learnt. PMID:26845152
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2011-01-01
The 2011 International Conference on Bioinformatics (InCoB) conference, which is the annual scientific conference of the Asia-Pacific Bioinformatics Network (APBioNet), is hosted by Kuala Lumpur, Malaysia, is co-organized with the first ISCB-Asia conference of the International Society for Computational Biology (ISCB). InCoB and the sequencing of the human genome are both celebrating their tenth anniversaries and InCoB’s goalposts for the next decade, implementing standards in bioinformatics and globally distributed computational networks, will be discussed and adopted at this conference. Of the 49 manuscripts (selected from 104 submissions) accepted to BMC Genomics and BMC Bioinformatics conference supplements, 24 are featured in this issue, covering software tools, genome/proteome analysis, systems biology (networks, pathways, bioimaging) and drug discovery and design. PMID:22372736
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The Development of Computational Biology in South Africa: Successes Achieved and Lessons Learnt.
Mulder, Nicola J; Christoffels, Alan; de Oliveira, Tulio; Gamieldien, Junaid; Hazelhurst, Scott; Joubert, Fourie; Kumuthini, Judit; Pillay, Ché S; Snoep, Jacky L; Tastan Bishop, Özlem; Tiffin, Nicki
2016-02-01
Bioinformatics is now a critical skill in many research and commercial environments as biological data are increasing in both size and complexity. South African researchers recognized this need in the mid-1990s and responded by working with the government as well as international bodies to develop initiatives to build bioinformatics capacity in the country. Significant injections of support from these bodies provided a springboard for the establishment of computational biology units at multiple universities throughout the country, which took on teaching, basic research and support roles. Several challenges were encountered, for example with unreliability of funding, lack of skills, and lack of infrastructure. However, the bioinformatics community worked together to overcome these, and South Africa is now arguably the leading country in bioinformatics on the African continent. Here we discuss how the discipline developed in the country, highlighting the challenges, successes, and lessons learnt.
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The eBioKit, a stand-alone educational platform for bioinformatics.
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.
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Hidden in the Middle: Culture, Value and Reward in Bioinformatics.
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 'outputs' in academia are often defined and rewarded by discipline. Bioinformatics, as an interdisciplinary bricolage, incorporates experts from various disciplinary cultures with their own distinct ways of working. Perceived problems of interdisciplinarity include difficulties of making explicit knowledge that is practical, theoretical, or cognitive. But successful interdisciplinary research also depends on an understanding of disciplinary cultures and value systems, often only tacitly understood by members of the communities in question. In bioinformatics, the 'parent' disciplines have different value systems; for example, what is considered worthwhile research by computer scientists can be thought of as trivial by biologists, and vice versa . This paper concentrates on the problems of reward and recognition described by scientists working in academic bioinformatics in the United Kingdom. We highlight problems that are a consequence of its cross-cultural make-up, recognising that the mismatches in knowledge in this borderland take place not just at the level of the practical, theoretical, or epistemological, but also at the cultural level too. The trend in big, interdisciplinary science is towards multiple authors on a single paper; in bioinformatics this has created hybrid or fractional scientists who find they are being positioned not just in-between established disciplines but also in-between as middle authors or, worse still, left off papers altogether.
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The eBioKit, a stand-alone educational platform for bioinformatics
Conesa, Ana; Bongcam-Rudloff, Erik
2017-01-01
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. PMID:28910280
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Implementing bioinformatic workflows within the bioextract server
USDA-ARS?s Scientific Manuscript database
Computational workflows in bioinformatics are becoming increasingly important in the achievement of scientific advances. These workflows typically require the integrated use of multiple, distributed data sources and analytic tools. The BioExtract Server (http://bioextract.org) is a distributed servi...
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SPECIES DATABASES AND THE BIOINFORMATICS REVOLUTION.
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...
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A bioinformatics-based overview of protein Lys-Ne-acetylation
USDA-ARS?s Scientific Manuscript database
Among posttranslational modifications, there are some conceptual similarities between Lys-N'-acetylation and Ser/Thr/Tyr O-phosphorylation. Herein we present a bioinformatics-based overview of reversible protein Lys-acetylation, including some comparisons with reversible protein phosphorylation. T...
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Qaadri, Kashef [Biomatters Inc., San Francisco, CA (United States)
2018-05-21
Kashef Qaadri on "NGS for the Masses: Empowering biologists to improve bioinformatic productivity" at the 2012 Sequencing, Finishing, Analysis in the Future Meeting held June 5-7, 2012 in Santa Fe, New Mexico.
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Qaadri, Kashef
2012-06-01
Kashef Qaadri on "NGS for the Masses: Empowering biologists to improve bioinformatic productivity" at the 2012 Sequencing, Finishing, Analysis in the Future Meeting held June 5-7, 2012 in Santa Fe, New Mexico.
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Reproducible Bioinformatics Research for Biologists
USDA-ARS?s Scientific Manuscript database
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...
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A case study of tuning MapReduce for efficient Bioinformatics in the cloud
DOE Office of Scientific and Technical Information (OSTI.GOV)
Shi, Lizhen; Wang, Zhong; Yu, Weikuan
The combination of the Hadoop MapReduce programming model and cloud computing allows biological scientists to analyze next-generation sequencing (NGS) data in a timely and cost-effective manner. Cloud computing platforms remove the burden of IT facility procurement and management from end users and provide ease of access to Hadoop clusters. However, biological scientists are still expected to choose appropriate Hadoop parameters for running their jobs. More importantly, the available Hadoop tuning guidelines are either obsolete or too general to capture the particular characteristics of bioinformatics applications. In this paper, we aim to minimize the cloud computing cost spent on bioinformatics datamore » analysis by optimizing the extracted significant Hadoop parameters. When using MapReduce-based bioinformatics tools in the cloud, the default settings often lead to resource underutilization and wasteful expenses. We choose k-mer counting, a representative application used in a large number of NGS data analysis tools, as our study case. Experimental results show that, with the fine-tuned parameters, we achieve a total of 4× speedup compared with the original performance (using the default settings). Finally, this paper presents an exemplary case for tuning MapReduce-based bioinformatics applications in the cloud, and documents the key parameters that could lead to significant performance benefits.« less
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Introduction to bioinformatics.
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.
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An overview of the Hadoop/MapReduce/HBase framework and its current applications in bioinformatics
2010-01-01
Background Bioinformatics researchers are now confronted with analysis of ultra large-scale data sets, a problem that will only increase at an alarming rate in coming years. Recent developments in open source software, that is, the Hadoop project and associated software, provide a foundation for scaling to petabyte scale data warehouses on Linux clusters, providing fault-tolerant parallelized analysis on such data using a programming style named MapReduce. Description An overview is given of the current usage within the bioinformatics community of Hadoop, a top-level Apache Software Foundation project, and of associated open source software projects. The concepts behind Hadoop and the associated HBase project are defined, and current bioinformatics software that employ Hadoop is described. The focus is on next-generation sequencing, as the leading application area to date. Conclusions Hadoop and the MapReduce programming paradigm already have a substantial base in the bioinformatics community, especially in the field of next-generation sequencing analysis, and such use is increasing. This is due to the cost-effectiveness of Hadoop-based analysis on commodity Linux clusters, and in the cloud via data upload to cloud vendors who have implemented Hadoop/HBase; and due to the effectiveness and ease-of-use of the MapReduce method in parallelization of many data analysis algorithms. PMID:21210976
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An overview of the Hadoop/MapReduce/HBase framework and its current applications in bioinformatics.
Taylor, Ronald C
2010-12-21
Bioinformatics researchers are now confronted with analysis of ultra large-scale data sets, a problem that will only increase at an alarming rate in coming years. Recent developments in open source software, that is, the Hadoop project and associated software, provide a foundation for scaling to petabyte scale data warehouses on Linux clusters, providing fault-tolerant parallelized analysis on such data using a programming style named MapReduce. An overview is given of the current usage within the bioinformatics community of Hadoop, a top-level Apache Software Foundation project, and of associated open source software projects. The concepts behind Hadoop and the associated HBase project are defined, and current bioinformatics software that employ Hadoop is described. The focus is on next-generation sequencing, as the leading application area to date. Hadoop and the MapReduce programming paradigm already have a substantial base in the bioinformatics community, especially in the field of next-generation sequencing analysis, and such use is increasing. This is due to the cost-effectiveness of Hadoop-based analysis on commodity Linux clusters, and in the cloud via data upload to cloud vendors who have implemented Hadoop/HBase; and due to the effectiveness and ease-of-use of the MapReduce method in parallelization of many data analysis algorithms.
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Bioinformatic approaches to augment study of epithelial-to-mesenchymal transition in lung cancer
Beck, Tim N.; Chikwem, Adaeze J.; Solanki, Nehal R.
2014-01-01
Bioinformatic approaches are intended to provide systems level insight into the complex biological processes that underlie serious diseases such as cancer. In this review we describe current bioinformatic resources, and illustrate how they have been used to study a clinically important example: epithelial-to-mesenchymal transition (EMT) in lung cancer. Lung cancer is the leading cause of cancer-related deaths and is often diagnosed at advanced stages, leading to limited therapeutic success. While EMT is essential during development and wound healing, pathological reactivation of this program by cancer cells contributes to metastasis and drug resistance, both major causes of death from lung cancer. Challenges of studying EMT include its transient nature, its molecular and phenotypic heterogeneity, and the complicated networks of rewired signaling cascades. Given the biology of lung cancer and the role of EMT, it is critical to better align the two in order to advance the impact of precision oncology. This task relies heavily on the application of bioinformatic resources. Besides summarizing recent work in this area, we use four EMT-associated genes, TGF-β (TGFB1), NEDD9/HEF1, β-catenin (CTNNB1) and E-cadherin (CDH1), as exemplars to demonstrate the current capacities and limitations of probing bioinformatic resources to inform hypothesis-driven studies with therapeutic goals. PMID:25096367
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Malin, Bradley; Carley, Kathleen
2007-01-01
The goal of this research is to learn how the editorial staffs of bioinformatics and medical informatics journals provide support for cross-community exposure. Models such as co-citation and co-author analysis measure the relationships between researchers; but they do not capture how environments that support knowledge transfer across communities are organized. In this paper, we propose a social network analysis model to study how editorial boards integrate researchers from disparate communities. We evaluate our model by building relational networks based on the editorial boards of approximately 40 journals that serve as research outlets in medical informatics and bioinformatics. We track the evolution of editorial relationships through a longitudinal investigation over the years 2000 through 2005. Our findings suggest that there are research journals that support the collocation of editorial board members from the bioinformatics and medical informatics communities. Network centrality metrics indicate that editorial board members are located in the intersection of the communities and that the number of individuals in the intersection is growing with time. Social network analysis methods provide insight into the relationships between the medical informatics and bioinformatics communities. The number of editorial board members facilitating the publication intersection of the communities has grown, but the intersection remains dependent on a small group of individuals and fragile.
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Bellman’s GAP—a language and compiler for dynamic programming in sequence analysis
Sauthoff, Georg; Möhl, Mathias; Janssen, Stefan; Giegerich, Robert
2013-01-01
Motivation: Dynamic programming is ubiquitous in bioinformatics. Developing and implementing non-trivial dynamic programming algorithms is often error prone and tedious. Bellman’s GAP is a new programming system, designed to ease the development of bioinformatics tools based on the dynamic programming technique. Results: In Bellman’s GAP, dynamic programming algorithms are described in a declarative style by tree grammars, evaluation algebras and products formed thereof. This bypasses the design of explicit dynamic programming recurrences and yields programs that are free of subscript errors, modular and easy to modify. The declarative modules are compiled into C++ code that is competitive to carefully hand-crafted implementations. This article introduces the Bellman’s GAP system and its language, GAP-L. It then demonstrates the ease of development and the degree of re-use by creating variants of two common bioinformatics algorithms. Finally, it evaluates Bellman’s GAP as an implementation platform of ‘real-world’ bioinformatics tools. Availability: Bellman’s GAP is available under GPL license from http://bibiserv.cebitec.uni-bielefeld.de/bellmansgap. This Web site includes a repository of re-usable modules for RNA folding based on thermodynamics. Contact: robert@techfak.uni-bielefeld.de Supplementary information: Supplementary data are available at Bioinformatics online PMID:23355290
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Broad issues to consider for library involvement in bioinformatics*
Geer, Renata C.
2006-01-01
Background: The information landscape in biological and medical research has grown far beyond literature to include a wide variety of databases generated by research fields such as molecular biology and genomics. The traditional role of libraries to collect, organize, and provide access to information can expand naturally to encompass these new data domains. Methods: This paper discusses the current and potential role of libraries in bioinformatics using empirical evidence and experience from eleven years of work in user services at the National Center for Biotechnology Information. Findings: Medical and science libraries over the last decade have begun to establish educational and support programs to address the challenges users face in the effective and efficient use of a plethora of molecular biology databases and retrieval and analysis tools. As more libraries begin to establish a role in this area, the issues they face include assessment of user needs and skills, identification of existing services, development of plans for new services, recruitment and training of specialized staff, and establishment of collaborations with bioinformatics centers at their institutions. Conclusions: Increasing library involvement in bioinformatics can help address information needs of a broad range of students, researchers, and clinicians and ultimately help realize the power of bioinformatics resources in making new biological discoveries. PMID:16888662
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Karim, Md Rezaul; Michel, Audrey; Zappa, Achille; Baranov, Pavel; Sahay, Ratnesh; Rebholz-Schuhmann, Dietrich
2017-04-16
Data workflow systems (DWFSs) enable bioinformatics researchers to combine components for data access and data analytics, and to share the final data analytics approach with their collaborators. Increasingly, such systems have to cope with large-scale data, such as full genomes (about 200 GB each), public fact repositories (about 100 TB of data) and 3D imaging data at even larger scales. As moving the data becomes cumbersome, the DWFS needs to embed its processes into a cloud infrastructure, where the data are already hosted. As the standardized public data play an increasingly important role, the DWFS needs to comply with Semantic Web technologies. This advancement to DWFS would reduce overhead costs and accelerate the progress in bioinformatics research based on large-scale data and public resources, as researchers would require less specialized IT knowledge for the implementation. Furthermore, the high data growth rates in bioinformatics research drive the demand for parallel and distributed computing, which then imposes a need for scalability and high-throughput capabilities onto the DWFS. As a result, requirements for data sharing and access to public knowledge bases suggest that compliance of the DWFS with Semantic Web standards is necessary. In this article, we will analyze the existing DWFS with regard to their capabilities toward public open data use as well as large-scale computational and human interface requirements. We untangle the parameters for selecting a preferable solution for bioinformatics research with particular consideration to using cloud services and Semantic Web technologies. Our analysis leads to research guidelines and recommendations toward the development of future DWFS for the bioinformatics research community. © The Author 2017. Published by Oxford University Press.
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Bioclipse: an open source workbench for chemo- and bioinformatics.
Spjuth, Ola; Helmus, Tobias; Willighagen, Egon L; Kuhn, Stefan; Eklund, Martin; Wagener, Johannes; Murray-Rust, Peter; Steinbeck, Christoph; Wikberg, Jarl E S
2007-02-22
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 successful attempts have been made to integrate chemo- and bioinformatics into a single framework. 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. 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.
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A lightweight, flow-based toolkit for parallel and distributed bioinformatics pipelines
2011-01-01
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 includes extensive documentation and annotated usage examples. PMID:21352538
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Workflows in bioinformatics: meta-analysis and prototype implementation of a workflow generator.
Garcia Castro, Alexander; Thoraval, Samuel; Garcia, Leyla J; Ragan, Mark A
2005-04-07
Computational methods for problem solving need to interleave information access and algorithm execution in a problem-specific workflow. The structures of these workflows are defined by a scaffold of syntactic, semantic and algebraic objects capable of representing them. Despite the proliferation of GUIs (Graphic User Interfaces) in bioinformatics, only some of them provide workflow capabilities; surprisingly, no meta-analysis of workflow operators and components in bioinformatics has been reported. We present a set of syntactic components and algebraic operators capable of representing analytical workflows in bioinformatics. Iteration, recursion, the use of conditional statements, and management of suspend/resume tasks have traditionally been implemented on an ad hoc basis and hard-coded; by having these operators properly defined it is possible to use and parameterize them as generic re-usable components. To illustrate how these operations can be orchestrated, we present GPIPE, a prototype graphic pipeline generator for PISE that allows the definition of a pipeline, parameterization of its component methods, and storage of metadata in XML formats. This implementation goes beyond the macro capacities currently in PISE. As the entire analysis protocol is defined in XML, a complete bioinformatic experiment (linked sets of methods, parameters and results) can be reproduced or shared among users. http://if-web1.imb.uq.edu.au/Pise/5.a/gpipe.html (interactive), ftp://ftp.pasteur.fr/pub/GenSoft/unix/misc/Pise/ (download). From our meta-analysis we have identified syntactic structures and algebraic operators common to many workflows in bioinformatics. The workflow components and algebraic operators can be assimilated into re-usable software components. GPIPE, a prototype implementation of this framework, provides a GUI builder to facilitate the generation of workflows and integration of heterogeneous analytical tools.
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BioWarehouse: a bioinformatics database warehouse toolkit
Lee, Thomas J; Pouliot, Yannick; Wagner, Valerie; Gupta, Priyanka; Stringer-Calvert, David WJ; Tenenbaum, Jessica D; Karp, Peter D
2006-01-01
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 database integration problem for bioinformatics. PMID:16556315
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BioWarehouse: a bioinformatics database warehouse toolkit.
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.
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A lightweight, flow-based toolkit for parallel and distributed bioinformatics pipelines.
Cieślik, Marcin; Mura, Cameron
2011-02-25
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. 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). 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 includes extensive documentation and annotated usage examples.
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Agile parallel bioinformatics workflow management using Pwrake.
Mishima, Hiroyuki; Sasaki, Kensaku; Tanaka, Masahiro; Tatebe, Osamu; Yoshiura, Koh-Ichiro
2011-09-08
In bioinformatics projects, scientific workflow systems are widely used to manage computational procedures. Full-featured workflow systems have been proposed to fulfil the demand for workflow management. However, such systems tend to be over-weighted for actual bioinformatics practices. We realize that quick deployment of cutting-edge software implementing advanced algorithms and data formats, and continuous adaptation to changes in computational resources and the environment are often prioritized in scientific workflow management. These features have a greater affinity with the agile software development method through iterative development phases after trial and error.Here, we show the application of a scientific workflow system Pwrake to bioinformatics workflows. Pwrake is a parallel workflow extension of Ruby's standard build tool Rake, the flexibility of which has been demonstrated in the astronomy domain. Therefore, we hypothesize that Pwrake also has advantages in actual bioinformatics workflows. We implemented the Pwrake workflows to process next generation sequencing data using the Genomic Analysis Toolkit (GATK) and Dindel. GATK and Dindel workflows are typical examples of sequential and parallel workflows, respectively. We found that in practice, actual scientific workflow development iterates over two phases, the workflow definition phase and the parameter adjustment phase. We introduced separate workflow definitions to help focus on each of the two developmental phases, as well as helper methods to simplify the descriptions. This approach increased iterative development efficiency. Moreover, we implemented combined workflows to demonstrate modularity of the GATK and Dindel workflows. Pwrake enables agile management of scientific workflows in the bioinformatics domain. The internal domain specific language design built on Ruby gives the flexibility of rakefiles for writing scientific workflows. Furthermore, readability and maintainability of rakefiles may facilitate sharing workflows among the scientific community. Workflows for GATK and Dindel are available at http://github.com/misshie/Workflows.
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Agile parallel bioinformatics workflow management using Pwrake
2011-01-01
Background In bioinformatics projects, scientific workflow systems are widely used to manage computational procedures. Full-featured workflow systems have been proposed to fulfil the demand for workflow management. However, such systems tend to be over-weighted for actual bioinformatics practices. We realize that quick deployment of cutting-edge software implementing advanced algorithms and data formats, and continuous adaptation to changes in computational resources and the environment are often prioritized in scientific workflow management. These features have a greater affinity with the agile software development method through iterative development phases after trial and error. Here, we show the application of a scientific workflow system Pwrake to bioinformatics workflows. Pwrake is a parallel workflow extension of Ruby's standard build tool Rake, the flexibility of which has been demonstrated in the astronomy domain. Therefore, we hypothesize that Pwrake also has advantages in actual bioinformatics workflows. Findings We implemented the Pwrake workflows to process next generation sequencing data using the Genomic Analysis Toolkit (GATK) and Dindel. GATK and Dindel workflows are typical examples of sequential and parallel workflows, respectively. We found that in practice, actual scientific workflow development iterates over two phases, the workflow definition phase and the parameter adjustment phase. We introduced separate workflow definitions to help focus on each of the two developmental phases, as well as helper methods to simplify the descriptions. This approach increased iterative development efficiency. Moreover, we implemented combined workflows to demonstrate modularity of the GATK and Dindel workflows. Conclusions Pwrake enables agile management of scientific workflows in the bioinformatics domain. The internal domain specific language design built on Ruby gives the flexibility of rakefiles for writing scientific workflows. Furthermore, readability and maintainability of rakefiles may facilitate sharing workflows among the scientific community. Workflows for GATK and Dindel are available at http://github.com/misshie/Workflows. PMID:21899774
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Bioinformatics and School Biology
ERIC Educational Resources Information Center
Dalpech, Roger
2006-01-01
The rapidly changing field of bioinformatics is fuelling the need for suitably trained personnel with skills in relevant biological "sub-disciplines" such as proteomics, transcriptomics and metabolomics, etc. But because of the complexity--and sheer weight of data--associated with these new areas of biology, many school teachers feel…
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A BIOINFORMATIC STRATEGY TO RAPIDLY CHARACTERIZE CDNA LIBRARIES
A Bioinformatic Strategy to Rapidly Characterize cDNA Libraries
G. Charles Ostermeier1, David J. Dix2 and Stephen A. Krawetz1.
1Departments of Obstetrics and Gynecology, Center for Molecular Medicine and Genetics, & Institute for Scientific Computing, Wayne State Univer... -
An International Bioinformatics Infrastructure to Underpin the Arabidopsis Community
USDA-ARS?s Scientific Manuscript database
The future bioinformatics needs of the Arabidopsis community as well as those of other scientific communities that depend on Arabidopsis resources were discussed at a pair of recent meetings held by the Multinational Arabidopsis Steering Committee (MASC) and the North American Arabidopsis Steering C...
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Bioinformatics and the Undergraduate Curriculum
ERIC Educational Resources Information Center
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…
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Cellular automata and its applications in protein bioinformatics.
Xiao, Xuan; Wang, Pu; Chou, Kuo-Chen
2011-09-01
With the explosion of protein sequences generated in the postgenomic era, it is highly desirable to develop high-throughput tools for rapidly and reliably identifying various attributes of uncharacterized proteins based on their sequence information alone. The knowledge thus obtained can help us timely utilize these newly found protein sequences for both basic research and drug discovery. Many bioinformatics tools have been developed by means of machine learning methods. This review is focused on the applications of a new kind of science (cellular automata) in protein bioinformatics. A cellular automaton (CA) is an open, flexible and discrete dynamic model that holds enormous potentials in modeling complex systems, in spite of the simplicity of the model itself. Researchers, scientists and practitioners from different fields have utilized cellular automata for visualizing protein sequences, investigating their evolution processes, and predicting their various attributes. Owing to its impressive power, intuitiveness and relative simplicity, the CA approach has great potential for use as a tool for bioinformatics.
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Lipidomics informatics for life-science.
Schwudke, D; Shevchenko, A; Hoffmann, N; Ahrends, R
2017-11-10
Lipidomics encompasses analytical approaches that aim to identify and quantify the complete set of lipids, defined as lipidome in a given cell, tissue or organism as well as their interactions with other molecules. The majority of lipidomics workflows is based on mass spectrometry and has been proven as a powerful tool in system biology in concert with other Omics disciplines. Unfortunately, bioinformatics infrastructures for this relatively young discipline are limited only to some specialists. Search engines, quantification algorithms, visualization tools and databases developed by the 'Lipidomics Informatics for Life-Science' (LIFS) partners will be restructured and standardized to provide broad access to these specialized bioinformatics pipelines. There are many medical challenges related to lipid metabolic alterations that will be fostered by capacity building suggested by LIFS. LIFS as member of the 'German Network for Bioinformatics' (de.NBI) node for 'Bioinformatics for Proteomics' (BioInfra.Prot) and will provide access to the described software as well as to tutorials and consulting services via a unified web-portal. Copyright © 2017 Elsevier B.V. All rights reserved.
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GlycoRDF: an ontology to standardize glycomics data in RDF
Ranzinger, Rene; Aoki-Kinoshita, Kiyoko F.; Campbell, Matthew P.; Kawano, Shin; Lütteke, Thomas; Okuda, Shujiro; Shinmachi, Daisuke; Shikanai, Toshihide; Sawaki, Hiromichi; Toukach, Philip; Matsubara, Masaaki; Yamada, Issaku; Narimatsu, Hisashi
2015-01-01
Motivation: Over the last decades several glycomics-based bioinformatics resources and databases have been created and released to the public. Unfortunately, there is no common standard in the representation of the stored information or a common machine-readable interface allowing bioinformatics groups to easily extract and cross-reference the stored information. Results: An international group of bioinformatics experts in the field of glycomics have worked together to create a standard Resource Description Framework (RDF) representation for glycomics data, focused on glycan sequences and related biological source, publications and experimental data. This RDF standard is defined by the GlycoRDF ontology and will be used by database providers to generate common machine-readable exports of the data stored in their databases. Availability and implementation: The ontology, supporting documentation and source code used by database providers to generate standardized RDF are available online (http://www.glycoinfo.org/GlycoRDF/). Contact: rene@ccrc.uga.edu or kkiyoko@soka.ac.jp Supplementary information: Supplementary data are available at Bioinformatics online. PMID:25388145
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An integrated bioinformatics analysis to dissect kinase dependency in triple negative breast cancer.
Ryall, Karen A; Kim, Jihye; Klauck, Peter J; Shin, Jimin; Yoo, Minjae; Ionkina, Anastasia; Pitts, Todd M; Tentler, John J; Diamond, Jennifer R; Eckhardt, S Gail; Heasley, Lynn E; Kang, Jaewoo; Tan, Aik Choon
2015-01-01
Triple-Negative Breast Cancer (TNBC) is an aggressive disease with a poor prognosis. Clinically, TNBC patients have limited treatment options besides chemotherapy. The goal of this study was to determine the kinase dependency in TNBC cell lines and to predict compounds that could inhibit these kinases using integrative bioinformatics analysis. We integrated publicly available gene expression data, high-throughput pharmacological profiling data, and quantitative in vitro kinase binding data to determine the kinase dependency in 12 TNBC cell lines. We employed Kinase Addiction Ranker (KAR), a novel bioinformatics approach, which integrated these data sources to dissect kinase dependency in TNBC cell lines. We then used the kinase dependency predicted by KAR for each TNBC cell line to query K-Map for compounds targeting these kinases. We validated our predictions using published and new experimental data. In summary, we implemented an integrative bioinformatics analysis that determines kinase dependency in TNBC. Our analysis revealed candidate kinases as potential targets in TNBC for further pharmacological and biological studies.
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Combining medical informatics and bioinformatics toward tools for personalized medicine.
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.
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Adapting bioinformatics curricula for big data.
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.
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Adapting bioinformatics curricula for big data
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
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Application of bioinformatics in chronobiology research.
Lopes, Robson da Silva; Resende, Nathalia Maria; Honorio-França, Adenilda Cristina; França, Eduardo Luzía
2013-01-01
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.
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GOBLET: The Global Organisation for Bioinformatics Learning, Education and Training
Atwood, Teresa K.; Bongcam-Rudloff, Erik; Brazas, Michelle E.; Corpas, Manuel; Gaudet, Pascale; Lewitter, Fran; Mulder, Nicola; Palagi, Patricia M.; Schneider, Maria Victoria; van Gelder, Celia W. G.
2015-01-01
In recent years, high-throughput technologies have brought big data to the life sciences. The march of progress has been rapid, leaving in its wake a demand for courses in data analysis, data stewardship, computing fundamentals, etc., a need that universities have not yet been able to satisfy—paradoxically, many are actually closing “niche” bioinformatics courses at a time of critical need. The impact of this is being felt across continents, as many students and early-stage researchers are being left without appropriate skills to manage, analyse, and interpret their data with confidence. This situation has galvanised a group of scientists to address the problems on an international scale. For the first time, bioinformatics educators and trainers across the globe have come together to address common needs, rising above institutional and international boundaries to cooperate in sharing bioinformatics training expertise, experience, and resources, aiming to put ad hoc training practices on a more professional footing for the benefit of all. PMID:25856076
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An Online Bioinformatics Curriculum
Searls, David B.
2012-01-01
Online learning initiatives over the past decade have become increasingly comprehensive in their selection of courses and sophisticated in their presentation, culminating in the recent announcement of a number of consortium and startup activities that promise to make a university education on the internet, free of charge, a real possibility. At this pivotal moment it is appropriate to explore the potential for obtaining comprehensive bioinformatics training with currently existing free video resources. This article presents such a bioinformatics curriculum in the form of a virtual course catalog, together with editorial commentary, and an assessment of strengths, weaknesses, and likely future directions for open online learning in this field. PMID:23028269
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Nair, Pradeep S; John, Eugene B
2007-01-01
Aligning specific sequences against a very large number of other sequences is a central aspect of bioinformatics. With the widespread availability of personal computers in biology laboratories, sequence alignment is now often performed locally. This makes it necessary to analyse the performance of personal computers for sequence aligning bioinformatics benchmarks. In this paper, we analyse the performance of a personal computer for the popular BLAST and FASTA sequence alignment suites. Results indicate that these benchmarks have a large number of recurring operations and use memory operations extensively. It seems that the performance can be improved with a bigger L1-cache.
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Bioinformatics for Exploration
NASA Technical Reports Server (NTRS)
Johnson, Kathy A.
2006-01-01
For the purpose of this paper, bioinformatics is defined as the application of computer technology to the management of biological information. It can be thought of as the science of developing computer databases and algorithms to facilitate and expedite biological research. This is a crosscutting capability that supports nearly all human health areas ranging from computational modeling, to pharmacodynamics research projects, to decision support systems within autonomous medical care. Bioinformatics serves to increase the efficiency and effectiveness of the life sciences research program. It provides data, information, and knowledge capture which further supports management of the bioastronautics research roadmap - identifying gaps that still remain and enabling the determination of which risks have been addressed.
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Bioinformatic scaling of allosteric interactions in biomedical isozymes
NASA Astrophysics Data System (ADS)
Phillips, J. C.
2016-09-01
Allosteric (long-range) interactions can be surprisingly strong in proteins of biomedical interest. Here we use bioinformatic scaling to connect prior results on nonsteroidal anti-inflammatory drugs to promising new drugs that inhibit cancer cell metabolism. Many parallel features are apparent, which explain how even one amino acid mutation, remote from active sites, can alter medical results. The enzyme twins involved are cyclooxygenase (aspirin) and isocitrate dehydrogenase (IDH). The IDH results are accurate to 1% and are overdetermined by adjusting a single bioinformatic scaling parameter. It appears that the final stage in optimizing protein functionality may involve leveling of the hydrophobic limits of the arms of conformational hydrophilic hinges.
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Privacy Preserving PCA on Distributed Bioinformatics Datasets
ERIC Educational Resources Information Center
Li, Xin
2011-01-01
In recent years, new bioinformatics technologies, such as gene expression microarray, genome-wide association study, proteomics, and metabolomics, have been widely used to simultaneously identify a huge number of human genomic/genetic biomarkers, generate a tremendously large amount of data, and dramatically increase the knowledge on human…
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NASA Technical Reports Server (NTRS)
Karlin, Samuel
2004-01-01
We used bioinformatics methods to study phylogenetic relations and differentiation patterns of the archaeal chaperonin 60 kDa heat-shock protein (HSP60) genes in support of the study of differential expression patterns of the three chaperonin genes encoded in Sulfolobus shibatae.
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Bioinformatics in Undergraduate Education: Practical Examples
ERIC Educational Resources Information Center
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…
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"Extreme Programming" in a Bioinformatics Class
ERIC Educational Resources Information Center
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).…
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KDE Bioscience: platform for bioinformatics analysis workflows.
Lu, Qiang; Hao, Pei; Curcin, Vasa; He, Weizhong; Li, Yuan-Yuan; Luo, Qing-Ming; Guo, Yi-Ke; Li, Yi-Xue
2006-08-01
Bioinformatics is a dynamic research area in which a large number of algorithms and programs have been developed rapidly and independently without much consideration so far of the need for standardization. The lack of such common standards combined with unfriendly interfaces make it difficult for biologists to learn how to use these tools and to translate the data formats from one to another. Consequently, the construction of an integrative bioinformatics platform to facilitate biologists' research is an urgent and challenging task. KDE Bioscience is a java-based software platform that collects a variety of bioinformatics tools and provides a workflow mechanism to integrate them. Nucleotide and protein sequences from local flat files, web sites, and relational databases can be entered, annotated, and aligned. Several home-made or 3rd-party viewers are built-in to provide visualization of annotations or alignments. KDE Bioscience can also be deployed in client-server mode where simultaneous execution of the same workflow is supported for multiple users. Moreover, workflows can be published as web pages that can be executed from a web browser. The power of KDE Bioscience comes from the integrated algorithms and data sources. With its generic workflow mechanism other novel calculations and simulations can be integrated to augment the current sequence analysis functions. Because of this flexible and extensible architecture, KDE Bioscience makes an ideal integrated informatics environment for future bioinformatics or systems biology research.
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Bioinformatics Education—Perspectives and Challenges out of Africa
Adebiyi, Ezekiel F.; Alzohairy, Ahmed M.; Everett, Dean; Ghedira, Kais; Ghouila, Amel; Kumuthini, Judit; Mulder, Nicola J.; Panji, Sumir; Patterton, Hugh-G.
2015-01-01
The discipline of bioinformatics has developed rapidly since the complete sequencing of the first genomes in the 1990s. The development of many high-throughput techniques during the last decades has ensured that bioinformatics has grown into a discipline that overlaps with, and is required for, the modern practice of virtually every field in the life sciences. This has placed a scientific premium on the availability of skilled bioinformaticians, a qualification that is extremely scarce on the African continent. The reasons for this are numerous, although the absence of a skilled bioinformatician at academic institutions to initiate a training process and build sustained capacity seems to be a common African shortcoming. This dearth of bioinformatics expertise has had a knock-on effect on the establishment of many modern high-throughput projects at African institutes, including the comprehensive and systematic analysis of genomes from African populations, which are among the most genetically diverse anywhere on the planet. Recent funding initiatives from the National Institutes of Health and the Wellcome Trust are aimed at ameliorating this shortcoming. In this paper, we discuss the problems that have limited the establishment of the bioinformatics field in Africa, as well as propose specific actions that will help with the education and training of bioinformaticians on the continent. This is an absolute requirement in anticipation of a boom in high-throughput approaches to human health issues unique to data from African populations. PMID:24990350
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The structural bioinformatics library: modeling in biomolecular science and beyond.
Cazals, Frédéric; Dreyfus, Tom
2017-04-01
Software in structural bioinformatics has mainly been application driven. To favor practitioners seeking off-the-shelf applications, but also developers seeking advanced building blocks to develop novel applications, we undertook the design of the Structural Bioinformatics Library ( SBL , http://sbl.inria.fr ), a generic C ++/python cross-platform software library targeting complex problems in structural bioinformatics. Its tenet is based on a modular design offering a rich and versatile framework allowing the development of novel applications requiring well specified complex operations, without compromising robustness and performances. The SBL involves four software components (1-4 thereafter). For end-users, the SBL provides ready to use, state-of-the-art (1) applications to handle molecular models defined by unions of balls, to deal with molecular flexibility, to model macro-molecular assemblies. These applications can also be combined to tackle integrated analysis problems. For developers, the SBL provides a broad C ++ toolbox with modular design, involving core (2) algorithms , (3) biophysical models and (4) modules , the latter being especially suited to develop novel applications. The SBL comes with a thorough documentation consisting of user and reference manuals, and a bugzilla platform to handle community feedback. The SBL is available from http://sbl.inria.fr. Frederic.Cazals@inria.fr. Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com
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Clinical Bioinformatics: challenges and opportunities
2012-01-01
Background Network Tools and Applications in Biology (NETTAB) Workshops are a series of meetings focused on the most promising and innovative ICT tools and to their usefulness in Bioinformatics. The NETTAB 2011 workshop, held in Pavia, Italy, in October 2011 was aimed at presenting some of the most relevant methods, tools and infrastructures that are nowadays available for Clinical Bioinformatics (CBI), the research field that deals with clinical applications of bioinformatics. Methods In this editorial, the viewpoints and opinions of three world CBI leaders, who have been invited to participate in a panel discussion of the NETTAB workshop on the next challenges and future opportunities of this field, are reported. These include the development of data warehouses and ICT infrastructures for data sharing, the definition of standards for sharing phenotypic data and the implementation of novel tools to implement efficient search computing solutions. Results Some of the most important design features of a CBI-ICT infrastructure are presented, including data warehousing, modularity and flexibility, open-source development, semantic interoperability, integrated search and retrieval of -omics information. Conclusions Clinical Bioinformatics goals are ambitious. Many factors, including the availability of high-throughput "-omics" technologies and equipment, the widespread availability of clinical data warehouses and the noteworthy increase in data storage and computational power of the most recent ICT systems, justify research and efforts in this domain, which promises to be a crucial leveraging factor for biomedical research. PMID:23095472
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Hidden in the Middle: Culture, Value and Reward in Bioinformatics
ERIC Educational Resources Information Center
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…
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USDA-ARS?s Scientific Manuscript database
Remarkable advances in next-generation sequencing (NGS) technologies, bioinformatics algorithms, and computational technologies have significantly accelerated genomic research. However, complicated NGS data analysis still remains as a major bottleneck. RNA-seq, as one of the major area in the NGS fi...
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Bioinformatics for Undergraduates: Steps toward a Quantitative Bioscience Curriculum
ERIC Educational Resources Information Center
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…
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Bioinformatics: A History of Evolution "In Silico"
ERIC Educational Resources Information Center
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:…
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USDA-ARS?s Scientific Manuscript database
The Rhipicephalus microplus genome is large and complex in structure, making a genome sequence difficult to assemble and costly to resource the required bioinformatics. In light of this, a consortium of international collaborators was formed to pool resources to begin sequencing this genome. We have...
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Incorporation of Bioinformatics Exercises into the Undergraduate Biochemistry Curriculum
ERIC Educational Resources Information Center
Feig, Andrew L.; Jabri, Evelyn
2002-01-01
The field of bioinformatics is developing faster than most biochemistry textbooks can adapt. Supplementing the undergraduate biochemistry curriculum with data-mining exercises is an ideal way to expose the students to the common databases and tools that take advantage of this vast repository of biochemical information. An integrated collection of…
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Exploring DNA Structure with Cn3D
ERIC Educational Resources Information Center
Porter, Sandra G.; Day, Joseph; McCarty, Richard E.; Shearn, Allen; Shingles, Richard; Fletcher, Linnea; Murphy, Stephanie; Pearlman, Rebecca
2007-01-01
Researchers in the field of bioinformatics have developed a number of analytical programs and databases that are increasingly important for advancing biological research. Because bioinformatics programs are used to analyze, visualize, and/or compare biological data, it is likely that the use of these programs will have a positive impact on biology…
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Visualising "Junk" DNA through Bioinformatics
ERIC Educational Resources Information Center
Elwess, Nancy L.; Latourelle, Sandra M.; Cauthorn, Olivia
2005-01-01
One of the hottest areas of science today is the field in which biology, information technology,and computer science are merged into a single discipline called bioinformatics. This field enables the discovery and analysis of biological data, including nucleotide and amino acid sequences that are easily accessed through the use of computers. As…
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Bonnal, Raoul J P; Aerts, Jan; Githinji, George; Goto, Naohisa; MacLean, Dan; Miller, Chase A; Mishima, Hiroyuki; Pagani, Massimiliano; Ramirez-Gonzalez, Ricardo; Smant, Geert; Strozzi, Francesco; Syme, Rob; Vos, Rutger; Wennblom, Trevor J; Woodcroft, Ben J; Katayama, Toshiaki; Prins, Pjotr
2012-04-01
Biogem provides a software development environment for the Ruby programming language, which encourages community-based software development for bioinformatics while lowering the barrier to entry and encouraging best practices. Biogem, with its targeted modular and decentralized approach, software generator, tools and tight web integration, is an improved general model for scaling up collaborative open source software development in bioinformatics. Biogem and modules are free and are OSS. Biogem runs on all systems that support recent versions of Ruby, including Linux, Mac OS X and Windows. Further information at http://www.biogems.info. A tutorial is available at http://www.biogems.info/howto.html bonnal@ingm.org.
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Secure Encapsulation and Publication of Biological Services in the Cloud Computing Environment
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
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NASA Astrophysics Data System (ADS)
Jaenisch, Holger M.; Handley, James W.
2010-04-01
Malware are analogs of viruses. Viruses are comprised of large numbers of polypeptide proteins. The shape and function of the protein strands determines the functionality of the segment, similar to a subroutine in malware. The full combination of subroutines is the malware organism, in analogous fashion as a collection of polypeptides forms protein structures that are information bearing. We propose to apply the methods of Bioinformatics to analyze malware to provide a rich feature set for creating a unique and novel detection and classification scheme that is originally applied to Bioinformatics amino acid sequencing. Our proposed methods enable real time in situ (in contrast to in vivo) detection applications.
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A label distance maximum-based classifier for multi-label learning.
Liu, Xiaoli; Bao, Hang; Zhao, Dazhe; Cao, Peng
2015-01-01
Multi-label classification is useful in many bioinformatics tasks such as gene function prediction and protein site localization. This paper presents an improved neural network algorithm, Max Label Distance Back Propagation Algorithm for Multi-Label Classification. The method was formulated by modifying the total error function of the standard BP by adding a penalty term, which was realized by maximizing the distance between the positive and negative labels. Extensive experiments were conducted to compare this method against state-of-the-art multi-label methods on three popular bioinformatic benchmark datasets. The results illustrated that this proposed method is more effective for bioinformatic multi-label classification compared to commonly used techniques.
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Secure encapsulation and publication of biological services in the cloud computing environment.
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.
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Challenges of Identifying Clinically Actionable Genetic Variants for Precision Medicine
2016-01-01
Advances in genomic medicine have the potential to change the way we treat human disease, but translating these advances into reality for improving healthcare outcomes depends essentially on our ability to discover disease- and/or drug-associated clinically actionable genetic mutations. Integration and manipulation of diverse genomic data and comprehensive electronic health records (EHRs) on a big data infrastructure can provide an efficient and effective way to identify clinically actionable genetic variants for personalized treatments and reduce healthcare costs. We review bioinformatics processing of next-generation sequencing (NGS) data, bioinformatics infrastructures for implementing precision medicine, and bioinformatics approaches for identifying clinically actionable genetic variants using high-throughput NGS data and EHRs. PMID:27195526
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Naturally selecting solutions: the use of genetic algorithms in bioinformatics.
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.
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BIOINFORMATICS IN THE K-8 CLASSROOM: DESIGNING INNOVATIVE ACTIVITIES FOR TEACHER IMPLEMENTATION
Shuster, Michele; Claussen, Kira; Locke, Melly; Glazewski, Krista
2016-01-01
At the intersection of biology and computer science is the growing field of bioinformatics—the analysis of complex datasets of biological relevance. Despite the increasing importance of bioinformatics and associated practical applications, these are not standard topics in elementary and middle school classrooms. We report on a pilot project and its evolution to support implementation of bioinformatics-based activities in elementary and middle school classrooms. Specifically, we ultimately designed a multi-day summer teacher professional development workshop, in which teachers design innovative classroom activities. By focusing on teachers, our design leverages enhanced teacher knowledge and confidence to integrate innovative instructional materials into K-8 classrooms and contributes to capacity building in STEM instruction. PMID:27429860
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Using Next-Generation Sequencing to Explore Genetics and Race in the High School Classroom
ERIC Educational Resources Information Center
Yang, Xinmiao; Hartman, Mark R.; Harrington, Kristin T.; Etson, Candice M.; Fierman, Matthew B.; Slonim, Donna K.; Walt, David R.
2017-01-01
With the development of new sequencing and bioinformatics technologies, concepts relating to personal genomics play an increasingly important role in our society. To promote interest and understanding of sequencing and bioinformatics in the high school classroom, we developed and implemented a laboratory-based teaching module called "The…
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Implementation and Assessment of a Molecular Biology and Bioinformatics Undergraduate Degree Program
ERIC Educational Resources Information Center
Pham, Daphne Q. -D.; Higgs, David C.; Statham, Anne; Schleiter, Mary Kay
2008-01-01
The Department of Biological Sciences at the University of Wisconsin-Parkside has developed and implemented an innovative, multidisciplinary undergraduate curriculum in Molecular Biology and Bioinformatics (MBB). The objective of the MBB program is to give students a hands-on facility with molecular biology theories and laboratory techniques, an…
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ERIC Educational Resources Information Center
Honts, Jerry E.
2003-01-01
Recent advances in genomics and structural biology have resulted in an unprecedented increase in biological data available from Internet-accessible databases. In order to help students effectively use this vast repository of information, undergraduate biology students at Drake University were introduced to bioinformatics software and databases in…
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Abstract
Bioinformatics, or in silico biology, is a rapidly growing field that encompasses the theory and application of computational approaches to model, predict, and explain biological function at the molecular level. This information rich field requires new ...
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ERIC Educational Resources Information Center
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…
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USDA-ARS?s Scientific Manuscript database
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...
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Learning Genetics through an Authentic Research Simulation in Bioinformatics
ERIC Educational Resources Information Center
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…
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Ramping up to the Biology Workbench: A Multi-Stage Approach to Bioinformatics Education
ERIC Educational Resources Information Center
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…
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Why Choose This One? Factors in Scientists' Selection of Bioinformatics Tools
ERIC Educational Resources Information Center
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…
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A Critical Analysis of Assessment Quality in Genomics and Bioinformatics Education Research
ERIC Educational Resources Information Center
Campbell, Chad E.; Nehm, Ross H.
2013-01-01
The growing importance of genomics and bioinformatics methods and paradigms in biology has been accompanied by an explosion of new curricula and pedagogies. An important question to ask about these educational innovations is whether they are having a meaningful impact on students' knowledge, attitudes, or skills. Although assessments are…
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Strategies for Using Peer-Assisted Learning Effectively in an Undergraduate Bioinformatics Course
ERIC Educational Resources Information Center
Shapiro, Casey; Ayon, Carlos; Moberg-Parker, Jordan; Levis-Fitzgerald, Marc; Sanders, Erin R.
2013-01-01
This study used a mixed methods approach to evaluate hybrid peer-assisted learning approaches incorporated into a bioinformatics tutorial for a genome annotation research project. Quantitative and qualitative data were collected from undergraduates who enrolled in a research-based laboratory course during two different academic terms at UCLA.…
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ERIC Educational Resources Information Center
Elwess, Nancy L.; Duprey, Stephen L.; Harney, Lindesay A.; Langman, Jessie E.; Marino, Tara C.; Martinez, Carolina; McKeon, Lauren L.; Moss, Chantel I. E.; Myrie, Sasha S.; Taylor, Luke Ryan
2008-01-01
"Alu"-insertion polymorphisms were used by an undergraduate Bioinformatics class to study how these insertion sites could be the basis for an investigation in human population genetics. Based on the students' investigation, both allele and genotype "Alu" frequencies were determined for African-American and Japanese populations as well as a…
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In the loop: promoter–enhancer interactions and bioinformatics
Mora, Antonio; Sandve, Geir Kjetil; Gabrielsen, Odd Stokke
2016-01-01
Enhancer–promoter regulation is a fundamental mechanism underlying differential transcriptional regulation. Spatial chromatin organization brings remote enhancers in contact with target promoters in cis to regulate gene expression. There is considerable evidence for promoter–enhancer interactions (PEIs). In the recent years, genome-wide analyses have identified signatures and mapped novel enhancers; however, being able to precisely identify their target gene(s) requires massive biological and bioinformatics efforts. In this review, we give a short overview of the chromatin landscape and transcriptional regulation. We discuss some key concepts and problems related to chromatin interaction detection technologies, and emerging knowledge from genome-wide chromatin interaction data sets. Then, we critically review different types of bioinformatics analysis methods and tools related to representation and visualization of PEI data, raw data processing and PEI prediction. Lastly, we provide specific examples of how PEIs have been used to elucidate a functional role of non-coding single-nucleotide polymorphisms. The topic is at the forefront of epigenetic research, and by highlighting some future bioinformatics challenges in the field, this review provides a comprehensive background for future PEI studies. PMID:26586731
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mORCA: sailing bioinformatics world with mobile devices.
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.
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Bioinformatics on the cloud computing platform Azure.
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.
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A primer to frequent itemset mining for bioinformatics
Naulaerts, Stefan; Meysman, Pieter; Bittremieux, Wout; Vu, Trung Nghia; Vanden Berghe, Wim; Goethals, Bart
2015-01-01
Over the past two decades, pattern mining techniques have become an integral part of many bioinformatics solutions. Frequent itemset mining is a popular group of pattern mining techniques designed to identify elements that frequently co-occur. An archetypical example is the identification of products that often end up together in the same shopping basket in supermarket transactions. A number of algorithms have been developed to address variations of this computationally non-trivial problem. Frequent itemset mining techniques are able to efficiently capture the characteristics of (complex) data and succinctly summarize it. Owing to these and other interesting properties, these techniques have proven their value in biological data analysis. Nevertheless, information about the bioinformatics applications of these techniques remains scattered. In this primer, we introduce frequent itemset mining and their derived association rules for life scientists. We give an overview of various algorithms, and illustrate how they can be used in several real-life bioinformatics application domains. We end with a discussion of the future potential and open challenges for frequent itemset mining in the life sciences. PMID:24162173
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p3d--Python module for structural bioinformatics.
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.
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Bioinformatics on the Cloud Computing Platform Azure
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
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Bioinformatics for spermatogenesis: annotation of male reproduction based on proteomics
Zhou, Tao; Zhou, Zuo-Min; Guo, Xue-Jiang
2013-01-01
Proteomics strategies have been widely used in the field of male reproduction, both in basic and clinical research. Bioinformatics methods are indispensable in proteomics-based studies and are used for data presentation, database construction and functional annotation. In the present review, we focus on the functional annotation of gene lists obtained through qualitative or quantitative methods, summarizing the common and male reproduction specialized proteomics databases. We introduce several integrated tools used to find the hidden biological significance from the data obtained. We further describe in detail the information on male reproduction derived from Gene Ontology analyses, pathway analyses and biomedical analyses. We provide an overview of bioinformatics annotations in spermatogenesis, from gene function to biological function and from biological function to clinical application. On the basis of recently published proteomics studies and associated data, we show that bioinformatics methods help us to discover drug targets for sperm motility and to scan for cancer-testis genes. In addition, we summarize the online resources relevant to male reproduction research for the exploration of the regulation of spermatogenesis. PMID:23852026
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Best practices in bioinformatics training for life scientists.
Via, Allegra; Blicher, Thomas; Bongcam-Rudloff, Erik; Brazas, Michelle D; Brooksbank, Cath; Budd, Aidan; De Las Rivas, Javier; Dreyer, Jacqueline; Fernandes, Pedro L; van Gelder, Celia; Jacob, Joachim; Jimenez, Rafael C; Loveland, Jane; Moran, Federico; Mulder, Nicola; Nyrönen, Tommi; Rother, Kristian; Schneider, Maria Victoria; Attwood, Teresa K
2013-09-01
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.
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Phylogenetic trees in bioinformatics
DOE Office of Scientific and Technical Information (OSTI.GOV)
Burr, Tom L
2008-01-01
Genetic data is often used to infer evolutionary relationships among a collection of viruses, bacteria, animal or plant species, or other operational taxonomic units (OTU). A phylogenetic tree depicts such relationships and provides a visual representation of the estimated branching order of the OTUs. Tree estimation is unique for several reasons, including: the types of data used to represent each OTU; the use ofprobabilistic nucleotide substitution models; the inference goals involving both tree topology and branch length, and the huge number of possible trees for a given sample of a very modest number of OTUs, which implies that fmding themore » 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.« less
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Bellman's GAP--a language and compiler for dynamic programming in sequence analysis.
Sauthoff, Georg; Möhl, Mathias; Janssen, Stefan; Giegerich, Robert
2013-03-01
Dynamic programming is ubiquitous in bioinformatics. Developing and implementing non-trivial dynamic programming algorithms is often error prone and tedious. Bellman's GAP is a new programming system, designed to ease the development of bioinformatics tools based on the dynamic programming technique. In Bellman's GAP, dynamic programming algorithms are described in a declarative style by tree grammars, evaluation algebras and products formed thereof. This bypasses the design of explicit dynamic programming recurrences and yields programs that are free of subscript errors, modular and easy to modify. The declarative modules are compiled into C++ code that is competitive to carefully hand-crafted implementations. This article introduces the Bellman's GAP system and its language, GAP-L. It then demonstrates the ease of development and the degree of re-use by creating variants of two common bioinformatics algorithms. Finally, it evaluates Bellman's GAP as an implementation platform of 'real-world' bioinformatics tools. Bellman's GAP is available under GPL license from http://bibiserv.cebitec.uni-bielefeld.de/bellmansgap. This Web site includes a repository of re-usable modules for RNA folding based on thermodynamics.
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Best practices in bioinformatics training for life scientists
Blicher, Thomas; Bongcam-Rudloff, Erik; Brazas, Michelle D.; Brooksbank, Cath; Budd, Aidan; De Las Rivas, Javier; Dreyer, Jacqueline; Fernandes, Pedro L.; van Gelder, Celia; Jacob, Joachim; Jimenez, Rafael C.; Loveland, Jane; Moran, Federico; Mulder, Nicola; Nyrönen, Tommi; Rother, Kristian; Schneider, Maria Victoria; Attwood, Teresa K.
2013-01-01
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. PMID:23803301
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EDAM: an ontology of bioinformatics operations, types of data and identifiers, topics and formats
Ison, Jon; Kalaš, Matúš; Jonassen, Inge; Bolser, Dan; Uludag, Mahmut; McWilliam, Hamish; Malone, James; Lopez, Rodrigo; Pettifer, Steve; Rice, Peter
2013-01-01
Motivation: Advancing the search, publication and integration of bioinformatics tools and resources demands consistent machine-understandable descriptions. A comprehensive ontology allowing such descriptions is therefore required. Results: EDAM is an ontology of bioinformatics operations (tool or workflow functions), types of data and identifiers, application domains and data formats. EDAM supports semantic annotation of diverse entities such as Web services, databases, programmatic libraries, standalone tools, interactive applications, data schemas, datasets and publications within bioinformatics. EDAM applies to organizing and finding suitable tools and data and to automating their integration into complex applications or workflows. It includes over 2200 defined concepts and has successfully been used for annotations and implementations. Availability: The latest stable version of EDAM is available in OWL format from http://edamontology.org/EDAM.owl and in OBO format from http://edamontology.org/EDAM.obo. It can be viewed online at the NCBO BioPortal and the EBI Ontology Lookup Service. For documentation and license please refer to http://edamontology.org. This article describes version 1.2 available at http://edamontology.org/EDAM_1.2.owl. Contact: jison@ebi.ac.uk PMID:23479348
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Crowdsourcing for bioinformatics
Good, Benjamin M.; Su, Andrew I.
2013-01-01
Motivation: Bioinformatics is faced with a variety of problems that require human involvement. Tasks like genome annotation, image analysis, knowledge-base population and protein structure determination all benefit from human input. In some cases, people are needed in vast quantities, whereas in others, we need just a few with rare abilities. Crowdsourcing encompasses an emerging collection of approaches for harnessing such distributed human intelligence. Recently, the bioinformatics community has begun to apply crowdsourcing in a variety of contexts, yet few resources are available that describe how these human-powered systems work and how to use them effectively in scientific domains. Results: Here, we provide a framework for understanding and applying several different types of crowdsourcing. The framework considers two broad classes: systems for solving large-volume ‘microtasks’ and systems for solving high-difficulty ‘megatasks’. Within these classes, we discuss system types, including volunteer labor, games with a purpose, microtask markets and open innovation contests. We illustrate each system type with successful examples in bioinformatics and conclude with a guide for matching problems to crowdsourcing solutions that highlights the positives and negatives of different approaches. Contact: bgood@scripps.edu PMID:23782614
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de la Calle, Guillermo; García-Remesal, Miguel; Chiesa, Stefano; de la Iglesia, Diana; Maojo, Victor
2009-10-07
The rapid evolution of Internet technologies and the collaborative approaches that dominate the field have stimulated the development of numerous bioinformatics resources. To address this new framework, several initiatives have tried to organize these services and resources. In this paper, we present the BioInformatics Resource Inventory (BIRI), a new approach for automatically discovering and indexing available public bioinformatics resources using information extracted from the scientific literature. The index generated can be automatically updated by adding additional manuscripts describing new resources. We have developed web services and applications to test and validate our approach. It has not been designed to replace current indexes but to extend their capabilities with richer functionalities. We developed a web service to provide a set of high-level query primitives to access the index. The web service can be used by third-party web services or web-based applications. To test the web service, we created a pilot web application to access a preliminary knowledge base of resources. We tested our tool using an initial set of 400 abstracts. Almost 90% of the resources described in the abstracts were correctly classified. More than 500 descriptions of functionalities were extracted. These experiments suggest the feasibility of our approach for automatically discovering and indexing current and future bioinformatics resources. Given the domain-independent characteristics of this tool, it is currently being applied by the authors in other areas, such as medical nanoinformatics. BIRI is available at http://edelman.dia.fi.upm.es/biri/.
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A quick guide for building a successful bioinformatics community.
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
2015-02-01
"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).
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Computational intelligence techniques in bioinformatics.
Hassanien, Aboul Ella; Al-Shammari, Eiman Tamah; Ghali, Neveen I
2013-12-01
Computational intelligence (CI) is a well-established paradigm with current systems having many of the characteristics of biological computers and capable of performing a variety of tasks that are difficult to do using conventional techniques. It is a methodology involving adaptive mechanisms and/or an ability to learn that facilitate intelligent behavior in complex and changing environments, such that the system is perceived to possess one or more attributes of reason, such as generalization, discovery, association and abstraction. The objective of this article is to present to the CI and bioinformatics research communities some of the state-of-the-art in CI applications to bioinformatics and motivate research in new trend-setting directions. In this article, we present an overview of the CI techniques in bioinformatics. We will show how CI techniques including neural networks, restricted Boltzmann machine, deep belief network, fuzzy logic, rough sets, evolutionary algorithms (EA), genetic algorithms (GA), swarm intelligence, artificial immune systems and support vector machines, could be successfully employed to tackle various problems such as gene expression clustering and classification, protein sequence classification, gene selection, DNA fragment assembly, multiple sequence alignment, and protein function prediction and its structure. We discuss some representative methods to provide inspiring examples to illustrate how CI can be utilized to address these problems and how bioinformatics data can be characterized by CI. Challenges to be addressed and future directions of research are also presented and an extensive bibliography is included. Copyright © 2013 Elsevier Ltd. All rights reserved.
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Fortuno, Cristina; James, Paul A; Young, Erin L; Feng, Bing; Olivier, Magali; Pesaran, Tina; Tavtigian, Sean V; Spurdle, Amanda B
2018-05-18
Clinical interpretation of germline missense variants represents a major challenge, including those in the TP53 Li-Fraumeni syndrome gene. Bioinformatic prediction is a key part of variant classification strategies. We aimed to optimize the performance of the Align-GVGD tool used for p53 missense variant prediction, and compare its performance to other bioinformatic tools (SIFT, PolyPhen-2) and ensemble methods (REVEL, BayesDel). Reference sets of assumed pathogenic and assumed benign variants were defined using functional and/or clinical data. Area under the curve and Matthews correlation coefficient (MCC) values were used as objective functions to select an optimized protein multi-sequence alignment with best performance for Align-GVGD. MCC comparison of tools using binary categories showed optimized Align-GVGD (C15 cut-off) combined with BayesDel (0.16 cut-off), or with REVEL (0.5 cut-off), to have the best overall performance. Further, a semi-quantitative approach using multiple tiers of bioinformatic prediction, validated using an independent set of non-functional and functional variants, supported use of Align-GVGD and BayesDel prediction for different strength of evidence levels in ACMG/AMP rules. We provide rationale for bioinformatic tool selection for TP53 variant classification, and have also computed relevant bioinformatic predictions for every possible p53 missense variant to facilitate their use by the scientific and medical community. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.
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Robust enzyme design: bioinformatic tools for improved protein stability.
Suplatov, Dmitry; Voevodin, Vladimir; Švedas, Vytas
2015-03-01
The ability of proteins and enzymes to maintain a functionally active conformation under adverse environmental conditions is an important feature of biocatalysts, vaccines, and biopharmaceutical proteins. From an evolutionary perspective, robust stability of proteins improves their biological fitness and allows for further optimization. Viewed from an industrial perspective, enzyme stability is crucial for the practical application of enzymes under the required reaction conditions. In this review, we analyze bioinformatic-driven strategies that are used to predict structural changes that can be applied to wild type proteins in order to produce more stable variants. The most commonly employed techniques can be classified into stochastic approaches, empirical or systematic rational design strategies, and design of chimeric proteins. We conclude that bioinformatic analysis can be efficiently used to study large protein superfamilies systematically as well as to predict particular structural changes which increase enzyme stability. Evolution has created a diversity of protein properties that are encoded in genomic sequences and structural data. Bioinformatics has the power to uncover this evolutionary code and provide a reproducible selection of hotspots - key residues to be mutated in order to produce more stable and functionally diverse proteins and enzymes. Further development of systematic bioinformatic procedures is needed to organize and analyze sequences and structures of proteins within large superfamilies and to link them to function, as well as to provide knowledge-based predictions for experimental evaluation. Copyright © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
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Militello, Kevin T
2013-01-01
Epigenetic inheritance is the inheritance of genetic information that is not based on DNA sequence alone. One type of epigenetic information that has come to the forefront in the last few years is modified DNA bases. The most common modified DNA base in nature is 5-methylcytosine. Herein, we describe a laboratory experiment that combines bioinformatic and molecular approaches to study the presence and abundance of 5-methylcytosine in different organisms. Students were originally provided with the protein sequence of the Xenopus laevis DNMT1 cytosine-5 DNA methyltransferase and used BLASTP searches to detect the presence of protein orthologs in the genomes of several organisms including Homo sapiens, Mus musculus, Plasmodium falciparum, Drosophila melanogaster, Saccharomyces cerevisiae, Arabidopsis thaliana, and Caenorhabditis elegans. Students generated hypotheses regarding the presence and abundance of 5-methylcytosine in these organisms based on their bioinformatics data, and directly tested their predictions on a subset of DNAs using restriction enzyme isoschizomer assays. A southern blotting assay to answer the same question is also presented. In addition to exposure to the field of epigenetics, the strengths of the laboratory are students are able to make predictions using bioinformatic tools and quickly test them in the laboratory. In addition, students are exposed to two potential misinterpretations of bioinformatic search data. The laboratory is easily modified to incorporate outside research interests in epigenetics. © 2013 by The International Union of Biochemistry and Molecular Biology.
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Cloud BioLinux: pre-configured and on-demand bioinformatics computing for the genomics community.
Krampis, Konstantinos; Booth, Tim; Chapman, Brad; Tiwari, Bela; Bicak, Mesude; Field, Dawn; Nelson, Karen E
2012-03-19
A steep drop in the cost of next-generation sequencing during recent years has made the technology affordable to the majority of researchers, but downstream bioinformatic analysis still poses a resource bottleneck for smaller laboratories and institutes that do not have access to substantial computational resources. Sequencing instruments are typically bundled with only the minimal processing and storage capacity required for data capture during sequencing runs. Given the scale of sequence datasets, scientific value cannot be obtained from acquiring a sequencer unless it is accompanied by an equal investment in informatics infrastructure. Cloud BioLinux is a publicly accessible Virtual Machine (VM) that enables scientists to quickly provision on-demand infrastructures for high-performance bioinformatics computing using cloud platforms. Users have instant access to a range of pre-configured command line and graphical software applications, including a full-featured desktop interface, documentation and over 135 bioinformatics packages for applications including sequence alignment, clustering, assembly, display, editing, and phylogeny. Each tool's functionality is fully described in the documentation directly accessible from the graphical interface of the VM. Besides the Amazon EC2 cloud, we have started instances of Cloud BioLinux on a private Eucalyptus cloud installed at the J. Craig Venter Institute, and demonstrated access to the bioinformatic tools interface through a remote connection to EC2 instances from a local desktop computer. Documentation for using Cloud BioLinux on EC2 is available from our project website, while a Eucalyptus cloud image and VirtualBox Appliance is also publicly available for download and use by researchers with access to private clouds. Cloud BioLinux provides a platform for developing bioinformatics infrastructures on the cloud. An automated and configurable process builds Virtual Machines, allowing the development of highly customized versions from a shared code base. This shared community toolkit enables application specific analysis platforms on the cloud by minimizing the effort required to prepare and maintain them.
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Cloud BioLinux: pre-configured and on-demand bioinformatics computing for the genomics community
2012-01-01
Background A steep drop in the cost of next-generation sequencing during recent years has made the technology affordable to the majority of researchers, but downstream bioinformatic analysis still poses a resource bottleneck for smaller laboratories and institutes that do not have access to substantial computational resources. Sequencing instruments are typically bundled with only the minimal processing and storage capacity required for data capture during sequencing runs. Given the scale of sequence datasets, scientific value cannot be obtained from acquiring a sequencer unless it is accompanied by an equal investment in informatics infrastructure. Results Cloud BioLinux is a publicly accessible Virtual Machine (VM) that enables scientists to quickly provision on-demand infrastructures for high-performance bioinformatics computing using cloud platforms. Users have instant access to a range of pre-configured command line and graphical software applications, including a full-featured desktop interface, documentation and over 135 bioinformatics packages for applications including sequence alignment, clustering, assembly, display, editing, and phylogeny. Each tool's functionality is fully described in the documentation directly accessible from the graphical interface of the VM. Besides the Amazon EC2 cloud, we have started instances of Cloud BioLinux on a private Eucalyptus cloud installed at the J. Craig Venter Institute, and demonstrated access to the bioinformatic tools interface through a remote connection to EC2 instances from a local desktop computer. Documentation for using Cloud BioLinux on EC2 is available from our project website, while a Eucalyptus cloud image and VirtualBox Appliance is also publicly available for download and use by researchers with access to private clouds. Conclusions Cloud BioLinux provides a platform for developing bioinformatics infrastructures on the cloud. An automated and configurable process builds Virtual Machines, allowing the development of highly customized versions from a shared code base. This shared community toolkit enables application specific analysis platforms on the cloud by minimizing the effort required to prepare and maintain them. PMID:22429538
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Mining semantic networks of bioinformatics e-resources from the literature
2011-01-01
Background There have been a number of recent efforts (e.g. BioCatalogue, BioMoby) to systematically catalogue bioinformatics tools, services and datasets. These efforts rely on manual curation, making it difficult to cope with the huge influx of various electronic resources that have been provided by the bioinformatics community. We present a text mining approach that utilises the literature to automatically extract descriptions and semantically profile bioinformatics resources to make them available for resource discovery and exploration through semantic networks that contain related resources. Results The method identifies the mentions of resources in the literature and assigns a set of co-occurring terminological entities (descriptors) to represent them. We have processed 2,691 full-text bioinformatics articles and extracted profiles of 12,452 resources containing associated descriptors with binary and tf*idf weights. Since such representations are typically sparse (on average 13.77 features per resource), we used lexical kernel metrics to identify semantically related resources via descriptor smoothing. Resources are then clustered or linked into semantic networks, providing the users (bioinformaticians, curators and service/tool crawlers) with a possibility to explore algorithms, tools, services and datasets based on their relatedness. Manual exploration of links between a set of 18 well-known bioinformatics resources suggests that the method was able to identify and group semantically related entities. Conclusions The results have shown that the method can reconstruct interesting functional links between resources (e.g. linking data types and algorithms), in particular when tf*idf-like weights are used for profiling. This demonstrates the potential of combining literature mining and simple lexical kernel methods to model relatedness between resource descriptors in particular when there are few features, thus potentially improving the resource description, discovery and exploration process. The resource profiles are available at http://gnode1.mib.man.ac.uk/bioinf/semnets.html PMID:21388573
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Analyzing the field of bioinformatics with the multi-faceted topic modeling technique.
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 confirmed by integrated analysis of topic distribution as well as top ranked keyphrases, authors, and journals.
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A Linked Series of Laboratory Exercises in Molecular Biology Utilizing Bioinformatics and GFP
ERIC Educational Resources Information Center
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…
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ERIC Educational Resources Information Center
Holtzclaw, J. David; Eisen, Arri; Whitney, Erika M.; Penumetcha, Meera; Hoey, J. Joseph; Kimbro, K. Sean
2006-01-01
Many students at minority-serving institutions are underexposed to Internet resources such as the human genome project, PubMed, NCBI databases, and other Web-based technologies because of a lack of financial resources. To change this, we designed and implemented a new bioinformatics component to supplement the undergraduate Genetics course at…
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2010 Translational bioinformatics year in review
Miller, Katharine S
2011-01-01
A review of 2010 research in translational bioinformatics provides much to marvel at. We have seen notable advances in personal genomics, pharmacogenetics, and sequencing. At the same time, the infrastructure for the field has burgeoned. While acknowledging that, according to researchers, the members of this field tend to be overly optimistic, the authors predict a bright future. PMID:21672905
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Intrageneric Primer Design: Bringing Bioinformatics Tools to the Class
ERIC Educational Resources Information Center
Lima, Andre O. S.; Garces, Sergio P. S.
2006-01-01
Bioinformatics is one of the fastest growing scientific areas over the last decade. It focuses on the use of informatics tools for the organization and analysis of biological data. An example of their importance is the availability nowadays of dozens of software programs for genomic and proteomic studies. Thus, there is a growing field (private…
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ERIC Educational Resources Information Center
Wefer, Stephen H.
2003-01-01
"Name That Gene" is a simple classroom activity that incorporates bioinformatics (available biological information) into the classroom using "Basic Logical Alignment Search Tool (BLAST)." An excellent classroom activity involving bioinformatics and "BLAST" has been previously explored using sequences from bacteria, but it is tailored for college…
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Bioboxes: standardised containers for interchangeable bioinformatics software.
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.
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ERIC Educational Resources Information Center
Grunwald, Sandra K.; Krueger, Katherine J.
2008-01-01
Laboratory exercises, which utilize alkaline phosphatase as a model enzyme, have been developed and used extensively in undergraduate biochemistry courses to illustrate enzyme steady-state kinetics. A bioinformatics laboratory exercise for the biochemistry laboratory, which complements the traditional alkaline phosphatase kinetics exercise, was…
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Staff Scientist - RNA Bioinformatics | Center for Cancer Research
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
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10 years for the Journal of Bioinformatics and Computational Biology (2003-2013) -- a retrospective.
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.
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ERIC Educational Resources Information Center
Wefer, Stephen H.; Anderson, O. Roger
2008-01-01
Bioinformatics, merging biological data with computer science, is increasingly incorporated into school curricula at all levels. This case study of 10 secondary school students highlights student individual differences (especially the way they processed information and integrated procedural and analytical thought) and summarizes a variety of…
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Text mining meets workflow: linking U-Compare with Taverna
Kano, Yoshinobu; Dobson, Paul; Nakanishi, Mio; Tsujii, Jun'ichi; Ananiadou, Sophia
2010-01-01
Summary: Text mining from the biomedical literature is of increasing importance, yet it is not easy for the bioinformatics community to create and run text mining workflows due to the lack of accessibility and interoperability of the text mining resources. The U-Compare system provides a wide range of bio text mining resources in a highly interoperable workflow environment where workflows can very easily be created, executed, evaluated and visualized without coding. We have linked U-Compare to Taverna, a generic workflow system, to expose text mining functionality to the bioinformatics community. Availability: http://u-compare.org/taverna.html, http://u-compare.org Contact: kano@is.s.u-tokyo.ac.jp Supplementary information: Supplementary data are available at Bioinformatics online. PMID:20709690
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Controlling for confounding variables in MS-omics protocol: why modularity matters.
Smith, Rob; Ventura, Dan; Prince, John T
2014-09-01
As the field of bioinformatics research continues to grow, more and more novel techniques are proposed to meet new challenges and improvements upon solutions to long-standing problems. These include data processing techniques and wet lab protocol techniques. Although the literature is consistently thorough in experimental detail and variable-controlling rigor for wet lab protocol techniques, bioinformatics techniques tend to be less described and less controlled. As the validation or rejection of hypotheses rests on the experiment's ability to isolate and measure a variable of interest, we urge the importance of reducing confounding variables in bioinformatics techniques during mass spectrometry experimentation. © The Author 2013. Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.
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Bioinformatics data distribution and integration via Web Services and XML.
Li, Xiao; Zhang, Yizheng
2003-11-01
It is widely recognized that exchange, distribution, and integration of biological data are the keys to improve bioinformatics and genome biology in post-genomic era. However, the problem of exchanging and integrating biology data is not solved satisfactorily. The eXtensible Markup Language (XML) is rapidly spreading as an emerging standard for structuring documents to exchange and integrate data on the World Wide Web (WWW). Web service is the next generation of WWW and is founded upon the open standards of W3C (World Wide Web Consortium) and IETF (Internet Engineering Task Force). This paper presents XML and Web Services technologies and their use for an appropriate solution to the problem of bioinformatics data exchange and integration.
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PyPedia: using the wiki paradigm as crowd sourcing environment for bioinformatics protocols.
Kanterakis, Alexandros; Kuiper, Joël; Potamias, George; Swertz, Morris A
2015-01-01
Today researchers can choose from many bioinformatics protocols for all types of life sciences research, computational environments and coding languages. Although the majority of these are open source, few of them possess all virtues to maximize reuse and promote reproducible science. Wikipedia has proven a great tool to disseminate information and enhance collaboration between users with varying expertise and background to author qualitative content via crowdsourcing. However, it remains an open question whether the wiki paradigm can be applied to bioinformatics protocols. We piloted PyPedia, a wiki where each article is both implementation and documentation of a bioinformatics computational protocol in the python language. Hyperlinks within the wiki can be used to compose complex workflows and induce reuse. A RESTful API enables code execution outside the wiki. Initial content of PyPedia contains articles for population statistics, bioinformatics format conversions and genotype imputation. Use of the easy to learn wiki syntax effectively lowers the barriers to bring expert programmers and less computer savvy researchers on the same page. PyPedia demonstrates how wiki can provide a collaborative development, sharing and even execution environment for biologists and bioinformaticians that complement existing resources, useful for local and multi-center research teams. PyPedia is available online at: http://www.pypedia.com. The source code and installation instructions are available at: https://github.com/kantale/PyPedia_server. The PyPedia python library is available at: https://github.com/kantale/pypedia. PyPedia is open-source, available under the BSD 2-Clause License.
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BIRCH: a user-oriented, locally-customizable, bioinformatics system.
Fristensky, Brian
2007-02-09
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. 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. 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.
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Watson-Haigh, Nathan S; Shang, Catherine A; Haimel, Matthias; Kostadima, Myrto; Loos, Remco; Deshpande, Nandan; Duesing, Konsta; Li, Xi; McGrath, Annette; McWilliam, Sean; Michnowicz, Simon; Moolhuijzen, Paula; Quenette, Steve; Revote, Jerico Nico De Leon; Tyagi, Sonika; Schneider, Maria V
2013-09-01
The widespread adoption of high-throughput next-generation sequencing (NGS) technology among the Australian life science research community is highlighting an urgent need to up-skill biologists in tools required for handling and analysing their NGS data. There is currently a shortage of cutting-edge bioinformatics training courses in Australia as a consequence of a scarcity of skilled trainers with time and funding to develop and deliver training courses. To address this, a consortium of Australian research organizations, including Bioplatforms Australia, the Commonwealth Scientific and Industrial Research Organisation and the Australian Bioinformatics Network, have been collaborating with EMBL-EBI training team. A group of Australian bioinformaticians attended the train-the-trainer workshop to improve training skills in developing and delivering bioinformatics workshop curriculum. A 2-day NGS workshop was jointly developed to provide hands-on knowledge and understanding of typical NGS data analysis workflows. The road show-style workshop was successfully delivered at five geographically distant venues in Australia using the newly established Australian NeCTAR Research Cloud. We highlight the challenges we had to overcome at different stages from design to delivery, including the establishment of an Australian bioinformatics training network and the computing infrastructure and resource development. A virtual machine image, workshop materials and scripts for configuring a machine with workshop contents have all been made available under a Creative Commons Attribution 3.0 Unported License. This means participants continue to have convenient access to an environment they had become familiar and bioinformatics trainers are able to access and reuse these resources.
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BIRCH: A user-oriented, locally-customizable, bioinformatics system
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
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Bioinformatics meets user-centred design: a perspective.
Pavelin, Katrina; Cham, Jennifer A; de Matos, Paula; Brooksbank, Cath; Cameron, Graham; Steinbeck, Christoph
2012-01-01
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.
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Watson-Haigh, Nathan S.; Shang, Catherine A.; Haimel, Matthias; Kostadima, Myrto; Loos, Remco; Deshpande, Nandan; Duesing, Konsta; Li, Xi; McGrath, Annette; McWilliam, Sean; Michnowicz, Simon; Moolhuijzen, Paula; Quenette, Steve; Revote, Jerico Nico De Leon; Tyagi, Sonika; Schneider, Maria V.
2013-01-01
The widespread adoption of high-throughput next-generation sequencing (NGS) technology among the Australian life science research community is highlighting an urgent need to up-skill biologists in tools required for handling and analysing their NGS data. There is currently a shortage of cutting-edge bioinformatics training courses in Australia as a consequence of a scarcity of skilled trainers with time and funding to develop and deliver training courses. To address this, a consortium of Australian research organizations, including Bioplatforms Australia, the Commonwealth Scientific and Industrial Research Organisation and the Australian Bioinformatics Network, have been collaborating with EMBL-EBI training team. A group of Australian bioinformaticians attended the train-the-trainer workshop to improve training skills in developing and delivering bioinformatics workshop curriculum. A 2-day NGS workshop was jointly developed to provide hands-on knowledge and understanding of typical NGS data analysis workflows. The road show–style workshop was successfully delivered at five geographically distant venues in Australia using the newly established Australian NeCTAR Research Cloud. We highlight the challenges we had to overcome at different stages from design to delivery, including the establishment of an Australian bioinformatics training network and the computing infrastructure and resource development. A virtual machine image, workshop materials and scripts for configuring a machine with workshop contents have all been made available under a Creative Commons Attribution 3.0 Unported License. This means participants continue to have convenient access to an environment they had become familiar and bioinformatics trainers are able to access and reuse these resources. PMID:23543352
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A Quick Guide for Building a Successful Bioinformatics Community
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
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SeWeR: a customizable and integrated dynamic HTML interface to bioinformatics services.
Basu, M K
2001-06-01
Sequence analysis using Web Resources (SeWeR) is an integrated, Dynamic HTML (DHTML) interface to commonly used bioinformatics services available on the World Wide Web. It is highly customizable, extendable, platform neutral, completely server-independent and can be hosted as a web page as well as being used as stand-alone software running within a web browser.
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ERIC Educational Resources Information Center
Almeida, Craig A.; Tardiff, Daniel F.; De Luca, Jane P.
2004-01-01
We have developed an introductory bioinformatics exercise for sophomore biology and biochemistry students that reinforces the understanding of the structure of a gene and the principles and events involved in its expression. In addition, the activity illustrates the severe effect mutations in a gene sequence can have on the protein product.…
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ERIC Educational Resources Information Center
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.…
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Infusing Bioinformatics and Research-Like Experience into a Molecular Biology Laboratory Course
ERIC Educational Resources Information Center
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…
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Development of a Web-Enabled Informatics Platform for Manipulation of Gene Expression Data
2004-12-01
genomic platforms such as metabolomics and proteomics , and to federated databases for knowledge management. A successful SBIR Phase I completed...measurements that require sophisticated bioinformatic platforms for data archival, management, integration, and analysis if researchers are to derive...web-enabled bioinformatic platform consisting of a Laboratory Information Management System (LIMS), an Analysis Information Management System (AIMS
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Wilson, Justin; Dai, Manhong; Jakupovic, Elvis; Watson, Stanley; Meng, Fan
2007-01-01
Modern video cards and game consoles typically have much better performance to price ratios than that of general purpose CPUs. The parallel processing capabilities of game hardware are well-suited for high throughput biomedical data analysis. Our initial results suggest that game hardware is a cost-effective platform for some computationally demanding bioinformatics problems.
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ERIC Educational Resources Information Center
Mello, Luciane V.; Tregilgas, Luke; Cowley, Gwen; Gupta, Anshul; Makki, Fatima; Jhutty, Anjeet; Shanmugasundram, Achchuthan
2017-01-01
Teaching bioinformatics is a longstanding challenge for educators who need to demonstrate to students how skills developed in the classroom may be applied to real world research. This study employed an action research methodology which utilised student-staff partnership and peer-learning. It was centred on the experiences of peer-facilitators,…
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VLSI Microsystem for Rapid Bioinformatic Pattern Recognition
NASA Technical Reports Server (NTRS)
Fang, Wai-Chi; Lue, Jaw-Chyng
2009-01-01
A system comprising very-large-scale integrated (VLSI) circuits is being developed as a means of bioinformatics-oriented analysis and recognition of patterns of fluorescence generated in a microarray in an advanced, highly miniaturized, portable genetic-expression-assay instrument. Such an instrument implements an on-chip combination of polymerase chain reactions and electrochemical transduction for amplification and detection of deoxyribonucleic acid (DNA).
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Expanding the horizons of microRNA bioinformatics.
Huntley, Rachael P; Kramarz, Barbara; Sawford, Tony; Umrao, Zara; Kalea, Anastasia Z; Acquaah, Vanessa; Martin, Maria-Jesus; Mayr, Manuel; Lovering, Ruth C
2018-06-05
MicroRNA regulation of key biological and developmental pathways is a rapidly expanding area of research, accompanied by vast amounts of experimental data. This data, however, is not widely available in bioinformatic resources, making it difficult for researchers to find and analyse microRNA-related experimental data and define further research projects. We are addressing this problem by providing two new bioinformatics datasets that contain experimentally verified functional information for mammalian microRNAs involved in cardiovascular-relevant, and other, processes. To date, our resource provides over 3,900 Gene Ontology annotations associated with almost 500 miRNAs from human, mouse and rat and over 2,200 experimentally validated miRNA:target interactions. We illustrate how this resource can be used to create miRNA-focused interaction networks with a biological context using the known biological role of miRNAs and the mRNAs they regulate, enabling discovery of associations between gene products, biological pathways and, ultimately, diseases. This data will be crucial in advancing the field of microRNA bioinformatics and will establish consistent datasets for reproducible functional analysis of microRNAs across all biological research areas. Published by Cold Spring Harbor Laboratory Press for the RNA Society.
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KBWS: an EMBOSS associated package for accessing bioinformatics web services.
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).
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Bioinformatic pipelines in Python with Leaf
2013-01-01
Background An incremental, loosely planned development approach is often used in bioinformatic studies when dealing with custom data analysis in a rapidly changing environment. Unfortunately, the lack of a rigorous software structuring can undermine the maintainability, communicability and replicability of the process. To ameliorate this problem we propose the Leaf system, the aim of which is to seamlessly introduce the pipeline formality on top of a dynamical development process with minimum overhead for the programmer, thus providing a simple layer of software structuring. Results Leaf includes a formal language for the definition of pipelines with code that can be transparently inserted into the user’s Python code. Its syntax is designed to visually highlight dependencies in the pipeline structure it defines. While encouraging the developer to think in terms of bioinformatic pipelines, Leaf supports a number of automated features including data and session persistence, consistency checks between steps of the analysis, processing optimization and publication of the analytic protocol in the form of a hypertext. Conclusions Leaf offers a powerful balance between plan-driven and change-driven development environments in the design, management and communication of bioinformatic pipelines. Its unique features make it a valuable alternative to other related tools. PMID:23786315
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A comparison of common programming languages used in bioinformatics.
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.
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ISMB 2016 offers outstanding science, networking, and celebration
Fogg, Christiana
2016-01-01
The annual international conference on Intelligent Systems for Molecular Biology (ISMB) is the major meeting of the International Society for Computational Biology (ISCB). Over the past 23 years the ISMB conference has grown to become the world's largest bioinformatics/computational biology conference. ISMB 2016 will be the year's most important computational biology event globally. The conferences provide a multidisciplinary forum for disseminating the latest developments in bioinformatics/computational biology. ISMB brings together scientists from computer science, molecular biology, mathematics, statistics and related fields. Its principal focus is on the development and application of advanced computational methods for biological problems. ISMB 2016 offers the strongest scientific program and the broadest scope of any international bioinformatics/computational biology conference. Building on past successes, the conference is designed to cater to variety of disciplines within the bioinformatics/computational biology community. ISMB 2016 takes place July 8 - 12 at the Swan and Dolphin Hotel in Orlando, Florida, United States. For two days preceding the conference, additional opportunities including Satellite Meetings, Student Council Symposium, and a selection of Special Interest Group Meetings and Applied Knowledge Exchange Sessions (AKES) are all offered to enable registered participants to learn more on the latest methods and tools within specialty research areas. PMID:27347392
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ISMB 2016 offers outstanding science, networking, and celebration.
Fogg, Christiana
2016-01-01
The annual international conference on Intelligent Systems for Molecular Biology (ISMB) is the major meeting of the International Society for Computational Biology (ISCB). Over the past 23 years the ISMB conference has grown to become the world's largest bioinformatics/computational biology conference. ISMB 2016 will be the year's most important computational biology event globally. The conferences provide a multidisciplinary forum for disseminating the latest developments in bioinformatics/computational biology. ISMB brings together scientists from computer science, molecular biology, mathematics, statistics and related fields. Its principal focus is on the development and application of advanced computational methods for biological problems. ISMB 2016 offers the strongest scientific program and the broadest scope of any international bioinformatics/computational biology conference. Building on past successes, the conference is designed to cater to variety of disciplines within the bioinformatics/computational biology community. ISMB 2016 takes place July 8 - 12 at the Swan and Dolphin Hotel in Orlando, Florida, United States. For two days preceding the conference, additional opportunities including Satellite Meetings, Student Council Symposium, and a selection of Special Interest Group Meetings and Applied Knowledge Exchange Sessions (AKES) are all offered to enable registered participants to learn more on the latest methods and tools within specialty research areas.
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Better bioinformatics through usability analysis.
Bolchini, Davide; Finkelstein, Anthony; Perrone, Vito; Nagl, Sylvia
2009-02-01
Improving the usability of bioinformatics resources enables researchers to find, interact with, share, compare and manipulate important information more effectively and efficiently. It thus enables researchers to gain improved insights into biological processes with the potential, ultimately, of yielding new scientific results. Usability 'barriers' can pose significant obstacles to a satisfactory user experience and force researchers to spend unnecessary time and effort to complete their tasks. The number of online biological databases available is growing and there is an expanding community of diverse users. In this context there is an increasing need to ensure the highest standards of usability. Using 'state-of-the-art' usability evaluation methods, we have identified and characterized a sample of usability issues potentially relevant to web bioinformatics resources, in general. These specifically concern the design of the navigation and search mechanisms available to the user. The usability issues we have discovered in our substantial case studies are undermining the ability of users to find the information they need in their daily research activities. In addition to characterizing these issues, specific recommendations for improvements are proposed leveraging proven practices from web and usability engineering. The methods and approach we exemplify can be readily adopted by the developers of bioinformatics resources.
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Interoperability of GADU in using heterogeneous Grid resources for bioinformatics applications.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Sulakhe, D.; Rodriguez, A.; Wilde, M.
2008-03-01
Bioinformatics tools used for efficient and computationally intensive analysis of genetic sequences require large-scale computational resources to accommodate the growing data. Grid computational resources such as the Open Science Grid and TeraGrid have proved useful for scientific discovery. The genome analysis and database update system (GADU) is a high-throughput computational system developed to automate the steps involved in accessing the Grid resources for running bioinformatics applications. This paper describes the requirements for building an automated scalable system such as GADU that can run jobs on different Grids. The paper describes the resource-independent configuration of GADU using the Pegasus-based virtual datamore » system that makes high-throughput computational tools interoperable on heterogeneous Grid resources. The paper also highlights the features implemented to make GADU a gateway to computationally intensive bioinformatics applications on the Grid. The paper will not go into the details of problems involved or the lessons learned in using individual Grid resources as it has already been published in our paper on genome analysis research environment (GNARE) and will focus primarily on the architecture that makes GADU resource independent and interoperable across heterogeneous Grid resources.« less
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Anslan, Sten; Bahram, Mohammad; Hiiesalu, Indrek; Tedersoo, Leho
2017-11-01
High-throughput sequencing methods have become a routine analysis tool in environmental sciences as well as in public and private sector. These methods provide vast amount of data, which need to be analysed in several steps. Although the bioinformatics may be applied using several public tools, many analytical pipelines allow too few options for the optimal analysis for more complicated or customized designs. Here, we introduce PipeCraft, a flexible and handy bioinformatics pipeline with a user-friendly graphical interface that links several public tools for analysing amplicon sequencing data. Users are able to customize the pipeline by selecting the most suitable tools and options to process raw sequences from Illumina, Pacific Biosciences, Ion Torrent and Roche 454 sequencing platforms. We described the design and options of PipeCraft and evaluated its performance by analysing the data sets from three different sequencing platforms. We demonstrated that PipeCraft is able to process large data sets within 24 hr. The graphical user interface and the automated links between various bioinformatics tools enable easy customization of the workflow. All analytical steps and options are recorded in log files and are easily traceable. © 2017 John Wiley & Sons Ltd.
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Quantifying the Relationships among Drug Classes
Hert, Jérôme; Keiser, Michael J.; Irwin, John J.; Oprea, Tudor I.; Shoichet, Brian K.
2009-01-01
The similarity of drug targets is typically measured using sequence or structural information. Here, we consider chemo-centric approaches that measure target similarity on the basis of their ligands, asking how chemoinformatics similarities differ from those derived bioinformatically, how stable the ligand networks are to changes in chemoinformatics metrics, and which network is the most reliable for prediction of pharmacology. We calculated the similarities between hundreds of drug targets and their ligands and mapped the relationship between them in a formal network. Bioinformatics networks were based on the BLAST similarity between sequences, while chemoinformatics networks were based on the ligand-set similarities calculated with either the Similarity Ensemble Approach (SEA) or a method derived from Bayesian statistics. By multiple criteria, bioinformatics and chemoinformatics networks differed substantially, and only occasionally did a high sequence similarity correspond to a high ligand-set similarity. In contrast, the chemoinformatics networks were stable to the method used to calculate the ligand-set similarities and to the chemical representation of the ligands. Also, the chemoinformatics networks were more natural and more organized, by network theory, than their bioinformatics counterparts: ligand-based networks were found to be small-world and broad-scale. PMID:18335977
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Models@Home: distributed computing in bioinformatics using a screensaver based approach.
Krieger, Elmar; Vriend, Gert
2002-02-01
Due to the steadily growing computational demands in bioinformatics and related scientific disciplines, one is forced to make optimal use of the available resources. A straightforward solution is to build a network of idle computers and let each of them work on a small piece of a scientific challenge, as done by Seti@Home (http://setiathome.berkeley.edu), the world's largest distributed computing project. We developed a generally applicable distributed computing solution that uses a screensaver system similar to Seti@Home. The software exploits the coarse-grained nature of typical bioinformatics projects. Three major considerations for the design were: (1) often, many different programs are needed, while the time is lacking to parallelize them. Models@Home can run any program in parallel without modifications to the source code; (2) in contrast to the Seti project, bioinformatics applications are normally more sensitive to lost jobs. Models@Home therefore includes stringent control over job scheduling; (3) to allow use in heterogeneous environments, Linux and Windows based workstations can be combined with dedicated PCs to build a homogeneous cluster. We present three practical applications of Models@Home, running the modeling programs WHAT IF and YASARA on 30 PCs: force field parameterization, molecular dynamics docking, and database maintenance.
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Jones, Bethan M; Edwards, Richard J; Skipp, Paul J; O'Connor, C David; Iglesias-Rodriguez, M Debora
2011-06-01
Emiliania huxleyi is a unicellular marine phytoplankton species known to play a significant role in global biogeochemistry. Through the dual roles of photosynthesis and production of calcium carbonate (calcification), carbon is transferred from the atmosphere to ocean sediments. Almost nothing is known about the molecular mechanisms that control calcification, a process that is tightly regulated within the cell. To initiate proteomic studies on this important and phylogenetically remote organism, we have devised efficient protein extraction protocols and developed a bioinformatics pipeline that allows the statistically robust assignment of proteins from MS/MS data using preexisting EST sequences. The bioinformatics tool, termed BUDAPEST (Bioinformatics Utility for Data Analysis of Proteomics using ESTs), is fully automated and was used to search against data generated from three strains. BUDAPEST increased the number of identifications over standard protein database searches from 37 to 99 proteins when data were amalgamated. Proteins involved in diverse cellular processes were uncovered. For example, experimental evidence was obtained for a novel type I polyketide synthase and for various photosystem components. The proteomic and bioinformatic approaches developed in this study are of wider applicability, particularly to the oceanographic community where genomic sequence data for species of interest are currently scarce.
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Tao, Yuan; Liu, Juan
2005-01-01
The Internet has already deflated our world of working and living into a very small scope, thus bringing out the concept of Earth Village, in which people could communicate and co-work though thousands' miles far away from each other. This paper describes a prototype, which is just like an Earth Lab for bioinformatics, based on Web services framework to build up a network architecture for bioinformatics research and for world wide biologists to easily implement enormous, complex processes, and effectively share and access computing resources and data, regardless of how heterogeneous the format of the data is and how decentralized and distributed these resources are around the world. A diminutive and simplified example scenario is given out to realize the prototype after that.
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Manning, Timmy; Sleator, Roy D; Walsh, Paul
2014-01-01
Artificial neural networks (ANNs) are a class of powerful machine learning models for classification and function approximation which have analogs in nature. An ANN learns to map stimuli to responses through repeated evaluation of exemplars of the mapping. This learning approach results in networks which are recognized for their noise tolerance and ability to generalize meaningful responses for novel stimuli. It is these properties of ANNs which make them appealing for applications to bioinformatics problems where interpretation of data may not always be obvious, and where the domain knowledge required for deductive techniques is incomplete or can cause a combinatorial explosion of rules. In this paper, we provide an introduction to artificial neural network theory and review some interesting recent applications to bioinformatics problems.
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Open discovery: An integrated live Linux platform of Bioinformatics tools.
Vetrivel, Umashankar; Pilla, Kalabharath
2008-01-01
Historically, live linux distributions for Bioinformatics have paved way for portability of Bioinformatics workbench in a platform independent manner. Moreover, most of the existing live Linux distributions limit their usage to sequence analysis and basic molecular visualization programs and are devoid of data persistence. Hence, open discovery - a live linux distribution has been developed with the capability to perform complex tasks like molecular modeling, docking and molecular dynamics in a swift manner. Furthermore, it is also equipped with complete sequence analysis environment and is capable of running windows executable programs in Linux environment. Open discovery portrays the advanced customizable configuration of fedora, with data persistency accessible via USB drive or DVD. The Open Discovery is distributed free under Academic Free License (AFL) and can be downloaded from http://www.OpenDiscovery.org.in.
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Meeting review: 2002 O'Reilly Bioinformatics Technology Conference.
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.
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The MIGenAS integrated bioinformatics toolkit for web-based sequence analysis
Rampp, Markus; Soddemann, Thomas; Lederer, Hermann
2006-01-01
We describe a versatile and extensible integrated bioinformatics toolkit for the analysis of biological sequences over the Internet. The web portal offers convenient interactive access to a growing pool of chainable bioinformatics software tools and databases that are centrally installed and maintained by the RZG. Currently, supported tasks comprise sequence similarity searches in public or user-supplied databases, computation and validation of multiple sequence alignments, phylogenetic analysis and protein–structure prediction. Individual tools can be seamlessly chained into pipelines allowing the user to conveniently process complex workflows without the necessity to take care of any format conversions or tedious parsing of intermediate results. The toolkit is part of the Max-Planck Integrated Gene Analysis System (MIGenAS) of the Max Planck Society available at (click ‘Start Toolkit’). PMID:16844980
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Trace Elements and Healthcare: A Bioinformatics Perspective.
Zhang, Yan
2017-01-01
Biological trace elements are essential for human health. Imbalance in trace element metabolism and homeostasis may play an important role in a variety of diseases and disorders. While the majority of previous researches focused on experimental verification of genes involved in trace element metabolism and those encoding trace element-dependent proteins, bioinformatics study on trace elements is relatively rare and still at the starting stage. This chapter offers an overview of recent progress in bioinformatics analyses of trace element utilization, metabolism, and function, especially comparative genomics of several important metals. The relationship between individual elements and several diseases based on recent large-scale systematic studies such as genome-wide association studies and case-control studies is discussed. Lastly, developments of ionomics and its recent application in human health are also introduced.
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Advances in Omics and Bioinformatics Tools for Systems Analyses of Plant Functions
Mochida, Keiichi; Shinozaki, Kazuo
2011-01-01
Omics and bioinformatics are essential to understanding the molecular systems that underlie various plant functions. Recent game-changing sequencing technologies have revitalized sequencing approaches in genomics and have produced opportunities for various emerging analytical applications. Driven by technological advances, several new omics layers such as the interactome, epigenome and hormonome have emerged. Furthermore, in several plant species, the development of omics resources has progressed to address particular biological properties of individual species. Integration of knowledge from omics-based research is an emerging issue as researchers seek to identify significance, gain biological insights and promote translational research. From these perspectives, we provide this review of the emerging aspects of plant systems research based on omics and bioinformatics analyses together with their associated resources and technological advances. PMID:22156726
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WIWS: a protein structure bioinformatics Web service collection.
Hekkelman, M L; Te Beek, T A H; Pettifer, S R; Thorne, D; Attwood, T K; Vriend, G
2010-07-01
The WHAT IF molecular-modelling and drug design program is widely distributed in the world of protein structure bioinformatics. Although originally designed as an interactive application, its highly modular design and inbuilt control language have recently enabled its deployment as a collection of programmatically accessible web services. We report here a collection of WHAT IF-based protein structure bioinformatics web services: these relate to structure quality, the use of symmetry in crystal structures, structure correction and optimization, adding hydrogens and optimizing hydrogen bonds and a series of geometric calculations. The freely accessible web services are based on the industry standard WS-I profile and the EMBRACE technical guidelines, and are available via both REST and SOAP paradigms. The web services run on a dedicated computational cluster; their function and availability is monitored daily.
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Meeting Review: 2002 O'Reilly Bioinformatics Technology Conference
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 [14]. 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. PMID:18628852
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Personalized medicine: challenges and opportunities for translational bioinformatics
Overby, Casey Lynnette; Tarczy-Hornoch, Peter
2013-01-01
Personalized medicine can be defined broadly as a model of healthcare that is predictive, personalized, preventive and participatory. Two US President’s Council of Advisors on Science and Technology reports illustrate challenges in personalized medicine (in a 2008 report) and in use of health information technology (in a 2010 report). Translational bioinformatics is a field that can help address these challenges and is defined by the American Medical Informatics Association as “the development of storage, analytic and interpretive methods to optimize the transformation of increasing voluminous biomedical data into proactive, predictive, preventative and participatory health.” This article discusses barriers to implementing genomics applications and current progress toward overcoming barriers, describes lessons learned from early experiences of institutions engaged in personalized medicine and provides example areas for translational bioinformatics research inquiry. PMID:24039624
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Eisenhaber, Frank
2014-06-01
Remarkably, Singapore as one of today's hotspots for bioinformatics and computational biology research appeared de novo out of pioneering efforts of engaged local individuals in the early 90-s that, supported with increasing public funds from 1996 on, morphed into the present vibrant research community. This article brings to mind the pioneers, their first successes and early institutional developments.
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Chain, Patrick
Genomics — the genetic mapping and DNA sequencing of sets of genes or the complete genomes of organisms, along with related genome analysis and database work — is emerging as one of the transformative sciences of the 21st century. But current bioinformatics tools are not accessible to most biological researchers. Now, a new computational and web-based tool called EDGE Bioinformatics is working to fulfill the promise of democratizing genomics.
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2013-12-30
MIT Lincoln Laboratory in cooperation with Edgewood Chemical Biological Center (ECBC). These events explored the utility of a short-term “ hack day...conceived as an experiment applying a short “ hack day” format to bioinformatics problems of interest to DTRA. Participants of diverse technical...organizers took note of different types of previous hack day formats that had been very open-ended (i.e., gave participants a collection of hardware or
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Scalable computing for evolutionary genomics.
Prins, Pjotr; Belhachemi, Dominique; Möller, Steffen; Smant, Geert
2012-01-01
Genomic data analysis in evolutionary biology is becoming so computationally intensive that analysis of multiple hypotheses and scenarios takes too long on a single desktop computer. In this chapter, we discuss techniques for scaling computations through parallelization of calculations, after giving a quick overview of advanced programming techniques. Unfortunately, parallel programming is difficult and requires special software design. The alternative, especially attractive for legacy software, is to introduce poor man's parallelization by running whole programs in parallel as separate processes, using job schedulers. Such pipelines are often deployed on bioinformatics computer clusters. Recent advances in PC virtualization have made it possible to run a full computer operating system, with all of its installed software, on top of another operating system, inside a "box," or virtual machine (VM). Such a VM can flexibly be deployed on multiple computers, in a local network, e.g., on existing desktop PCs, and even in the Cloud, to create a "virtual" computer cluster. Many bioinformatics applications in evolutionary biology can be run in parallel, running processes in one or more VMs. Here, we show how a ready-made bioinformatics VM image, named BioNode, effectively creates a computing cluster, and pipeline, in a few steps. This allows researchers to scale-up computations from their desktop, using available hardware, anytime it is required. BioNode is based on Debian Linux and can run on networked PCs and in the Cloud. Over 200 bioinformatics and statistical software packages, of interest to evolutionary biology, are included, such as PAML, Muscle, MAFFT, MrBayes, and BLAST. Most of these software packages are maintained through the Debian Med project. In addition, BioNode contains convenient configuration scripts for parallelizing bioinformatics software. Where Debian Med encourages packaging free and open source bioinformatics software through one central project, BioNode encourages creating free and open source VM images, for multiple targets, through one central project. BioNode can be deployed on Windows, OSX, Linux, and in the Cloud. Next to the downloadable BioNode images, we provide tutorials online, which empower bioinformaticians to install and run BioNode in different environments, as well as information for future initiatives, on creating and building such images.
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bioNerDS: exploring bioinformatics’ database and software use through literature mining
2013-01-01
Background Biology-focused databases and software define bioinformatics and their use is central to computational biology. In such a complex and dynamic field, it is of interest to understand what resources are available, which are used, how much they are used, and for what they are used. While scholarly literature surveys can provide some insights, large-scale computer-based approaches to identify mentions of bioinformatics databases and software from primary literature would automate systematic cataloguing, facilitate the monitoring of usage, and provide the foundations for the recovery of computational methods for analysing biological data, with the long-term aim of identifying best/common practice in different areas of biology. Results We have developed bioNerDS, a named entity recogniser for the recovery of bioinformatics databases and software from primary literature. We identify such entities with an F-measure ranging from 63% to 91% at the mention level and 63-78% at the document level, depending on corpus. Not attaining a higher F-measure is mostly due to high ambiguity in resource naming, which is compounded by the on-going introduction of new resources. To demonstrate the software, we applied bioNerDS to full-text articles from BMC Bioinformatics and Genome Biology. General mention patterns reflect the remit of these journals, highlighting BMC Bioinformatics’s emphasis on new tools and Genome Biology’s greater emphasis on data analysis. The data also illustrates some shifts in resource usage: for example, the past decade has seen R and the Gene Ontology join BLAST and GenBank as the main components in bioinformatics processing. Abstract Conclusions We demonstrate the feasibility of automatically identifying resource names on a large-scale from the scientific literature and show that the generated data can be used for exploration of bioinformatics database and software usage. For example, our results help to investigate the rate of change in resource usage and corroborate the suspicion that a vast majority of resources are created, but rarely (if ever) used thereafter. bioNerDS is available at http://bionerds.sourceforge.net/. PMID:23768135
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Bioinformatics of cardiovascular miRNA biology.
Kunz, Meik; Xiao, Ke; Liang, Chunguang; Viereck, Janika; Pachel, Christina; Frantz, Stefan; Thum, Thomas; Dandekar, Thomas
2015-12-01
MicroRNAs (miRNAs) are small ~22 nucleotide non-coding RNAs and are highly conserved among species. Moreover, miRNAs regulate gene expression of a large number of genes associated with important biological functions and signaling pathways. Recently, several miRNAs have been found to be associated with cardiovascular diseases. Thus, investigating the complex regulatory effect of miRNAs may lead to a better understanding of their functional role in the heart. To achieve this, bioinformatics approaches have to be coupled with validation and screening experiments to understand the complex interactions of miRNAs with the genome. This will boost the subsequent development of diagnostic markers and our understanding of the physiological and therapeutic role of miRNAs in cardiac remodeling. In this review, we focus on and explain different bioinformatics strategies and algorithms for the identification and analysis of miRNAs and their regulatory elements to better understand cardiac miRNA biology. Starting with the biogenesis of miRNAs, we present approaches such as LocARNA and miRBase for combining sequence and structure analysis including phylogenetic comparisons as well as detailed analysis of RNA folding patterns, functional target prediction, signaling pathway as well as functional analysis. We also show how far bioinformatics helps to tackle the unprecedented level of complexity and systemic effects by miRNA, underlining the strong therapeutic potential of miRNA and miRNA target structures in cardiovascular disease. In addition, we discuss drawbacks and limitations of bioinformatics algorithms and the necessity of experimental approaches for miRNA target identification. This article is part of a Special Issue entitled 'Non-coding RNAs'. Copyright © 2014 Elsevier Ltd. All rights reserved.
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Can all heritable biology really be reduced to a single dimension?
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.
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Reproducible Bioconductor workflows using browser-based interactive notebooks and containers.
Almugbel, Reem; Hung, Ling-Hong; Hu, Jiaming; Almutairy, Abeer; Ortogero, Nicole; Tamta, Yashaswi; Yeung, Ka Yee
2018-01-01
Bioinformatics publications typically include complex software workflows that are difficult to describe in a manuscript. We describe and demonstrate the use of interactive software notebooks to document and distribute bioinformatics research. We provide a user-friendly tool, BiocImageBuilder, that allows users to easily distribute their bioinformatics protocols through interactive notebooks uploaded to either a GitHub repository or a private server. We present four different interactive Jupyter notebooks using R and Bioconductor workflows to infer differential gene expression, analyze cross-platform datasets, process RNA-seq data and KinomeScan data. These interactive notebooks are available on GitHub. The analytical results can be viewed in a browser. Most importantly, the software contents can be executed and modified. This is accomplished using Binder, which runs the notebook inside software containers, thus avoiding the need to install any software and ensuring reproducibility. All the notebooks were produced using custom files generated by BiocImageBuilder. BiocImageBuilder facilitates the publication of workflows with a point-and-click user interface. We demonstrate that interactive notebooks can be used to disseminate a wide range of bioinformatics analyses. The use of software containers to mirror the original software environment ensures reproducibility of results. Parameters and code can be dynamically modified, allowing for robust verification of published results and encouraging rapid adoption of new methods. Given the increasing complexity of bioinformatics workflows, we anticipate that these interactive software notebooks will become as necessary for documenting software methods as traditional laboratory notebooks have been for documenting bench protocols, and as ubiquitous. © The Author 2017. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For Permissions, please email: journals.permissions@oup.com
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ballaxy: web services for structural bioinformatics.
Hildebrandt, Anna Katharina; Stöckel, Daniel; Fischer, Nina M; de la Garza, Luis; Krüger, Jens; Nickels, Stefan; Röttig, Marc; Schärfe, Charlotta; Schumann, Marcel; Thiel, Philipp; Lenhof, Hans-Peter; Kohlbacher, Oliver; Hildebrandt, Andreas
2015-01-01
Web-based workflow systems have gained considerable momentum in sequence-oriented bioinformatics. In structural bioinformatics, however, such systems are still relatively rare; while commercial stand-alone workflow applications are common in the pharmaceutical industry, academic researchers often still rely on command-line scripting to glue individual tools together. In this work, we address the problem of building a web-based system for workflows in structural bioinformatics. For the underlying molecular modelling engine, we opted for the BALL framework because of its extensive and well-tested functionality in the field of structural bioinformatics. The large number of molecular data structures and algorithms implemented in BALL allows for elegant and sophisticated development of new approaches in the field. We hence connected the versatile BALL library and its visualization and editing front end BALLView with the Galaxy workflow framework. The result, which we call ballaxy, enables the user to simply and intuitively create sophisticated pipelines for applications in structure-based computational biology, integrated into a standard tool for molecular modelling. ballaxy consists of three parts: some minor modifications to the Galaxy system, a collection of tools and an integration into the BALL framework and the BALLView application for molecular modelling. Modifications to Galaxy will be submitted to the Galaxy project, and the BALL and BALLView integrations will be integrated in the next major BALL release. After acceptance of the modifications into the Galaxy project, we will publish all ballaxy tools via the Galaxy toolshed. In the meantime, all three components are available from http://www.ball-project.org/ballaxy. Also, docker images for ballaxy are available at https://registry.hub.docker.com/u/anhi/ballaxy/dockerfile/. ballaxy is licensed under the terms of the GPL. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.
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Comprehensive decision tree models in bioinformatics.
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 redundant attributes that are very common in bioinformatics.
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Comprehensive Decision Tree Models in Bioinformatics
Stiglic, Gregor; Kocbek, Simon; Pernek, Igor; Kokol, Peter
2012-01-01
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 with binary class attributes and a high number of possibly redundant attributes that are very common in bioinformatics. PMID:22479449
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The growing need for microservices in bioinformatics.
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 implementation of reliable and innovative software, made possible in a highly collaborative setting.
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The growing need for microservices in bioinformatics
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 methodology for the fabrication and implementation of reliable and innovative software, made possible in a highly collaborative setting. PMID:27994937
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Using Kepler for Tool Integration in Microarray Analysis Workflows.
Gan, Zhuohui; Stowe, Jennifer C; Altintas, Ilkay; McCulloch, Andrew D; Zambon, Alexander C
Increasing numbers of genomic technologies are leading to massive amounts of genomic data, all of which requires complex analysis. More and more bioinformatics analysis tools are being developed by scientist to simplify these analyses. However, different pipelines have been developed using different software environments. This makes integrations of these diverse bioinformatics tools difficult. Kepler provides an open source environment to integrate these disparate packages. Using Kepler, we integrated several external tools including Bioconductor packages, AltAnalyze, a python-based open source tool, and R-based comparison tool to build an automated workflow to meta-analyze both online and local microarray data. The automated workflow connects the integrated tools seamlessly, delivers data flow between the tools smoothly, and hence improves efficiency and accuracy of complex data analyses. Our workflow exemplifies the usage of Kepler as a scientific workflow platform for bioinformatics pipelines.
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Open discovery: An integrated live Linux platform of Bioinformatics tools
Vetrivel, Umashankar; Pilla, Kalabharath
2008-01-01
Historically, live linux distributions for Bioinformatics have paved way for portability of Bioinformatics workbench in a platform independent manner. Moreover, most of the existing live Linux distributions limit their usage to sequence analysis and basic molecular visualization programs and are devoid of data persistence. Hence, open discovery ‐ a live linux distribution has been developed with the capability to perform complex tasks like molecular modeling, docking and molecular dynamics in a swift manner. Furthermore, it is also equipped with complete sequence analysis environment and is capable of running windows executable programs in Linux environment. Open discovery portrays the advanced customizable configuration of fedora, with data persistency accessible via USB drive or DVD. Availability The Open Discovery is distributed free under Academic Free License (AFL) and can be downloaded from http://www.OpenDiscovery.org.in PMID:19238235
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A review of estimation of distribution algorithms in bioinformatics
Armañanzas, Rubén; Inza, Iñaki; Santana, Roberto; Saeys, Yvan; Flores, Jose Luis; Lozano, Jose Antonio; Peer, Yves Van de; Blanco, Rosa; Robles, Víctor; Bielza, Concha; Larrañaga, Pedro
2008-01-01
Evolutionary search algorithms have become an essential asset in the algorithmic toolbox for solving high-dimensional optimization problems in across a broad range of bioinformatics problems. Genetic algorithms, the most well-known and representative evolutionary search technique, have been the subject of the major part of such applications. Estimation of distribution algorithms (EDAs) offer a novel evolutionary paradigm that constitutes a natural and attractive alternative to genetic algorithms. They make use of a probabilistic model, learnt from the promising solutions, to guide the search process. In this paper, we set out a basic taxonomy of EDA techniques, underlining the nature and complexity of the probabilistic model of each EDA variant. We review a set of innovative works that make use of EDA techniques to solve challenging bioinformatics problems, emphasizing the EDA paradigm's potential for further research in this domain. PMID:18822112
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Hodor, Paul; Chawla, Amandeep; Clark, Andrew; Neal, Lauren
2016-01-15
: One of the solutions proposed for addressing the challenge of the overwhelming abundance of genomic sequence and other biological data is the use of the Hadoop computing framework. Appropriate tools are needed to set up computational environments that facilitate research of novel bioinformatics methodology using Hadoop. Here, we present cl-dash, a complete starter kit for setting up such an environment. Configuring and deploying new Hadoop clusters can be done in minutes. Use of Amazon Web Services ensures no initial investment and minimal operation costs. Two sample bioinformatics applications help the researcher understand and learn the principles of implementing an algorithm using the MapReduce programming pattern. Source code is available at https://bitbucket.org/booz-allen-sci-comp-team/cl-dash.git. hodor_paul@bah.com. © The Author 2015. Published by Oxford University Press.
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Silicon Era of Carbon-Based Life: Application of Genomics and Bioinformatics in Crop Stress Research
Li, Man-Wah; Qi, Xinpeng; Ni, Meng; Lam, Hon-Ming
2013-01-01
Abiotic and biotic stresses lead to massive reprogramming of different life processes and are the major limiting factors hampering crop productivity. Omics-based research platforms allow for a holistic and comprehensive survey on crop stress responses and hence may bring forth better crop improvement strategies. Since high-throughput approaches generate considerable amounts of data, bioinformatics tools will play an essential role in storing, retrieving, sharing, processing, and analyzing them. Genomic and functional genomic studies in crops still lag far behind similar studies in humans and other animals. In this review, we summarize some useful genomics and bioinformatics resources available to crop scientists. In addition, we also discuss the major challenges and advancements in the “-omics” studies, with an emphasis on their possible impacts on crop stress research and crop improvement. PMID:23759993
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Tong, Weida; Harris, Stephen C; Fang, Hong; Shi, Leming; Perkins, Roger; Goodsaid, Federico; Frueh, Felix W
2007-01-01
Pharmacogenomics (PGx) is identified in the FDA Critical Path document as a major opportunity for advancing medical product development and personalized medicine. An integrated bioinformatics infrastructure for use in FDA data review is crucial to realize the benefits of PGx for public health. We have developed an integrated bioinformatics tool, called ArrayTrack, for managing, analyzing and interpreting genomic and other biomarker data (e.g. proteomic and metabolomic data). ArrayTrack is a highly flexible and robust software platform, which allows evolving with technological advances and changing user needs. ArrayTrack is used in the routine review of genomic data submitted to the FDA; here, three hypothetical examples of its use in the Voluntary eXploratory Data Submission (VXDS) program are illustrated.: © Published by Elsevier Ltd.
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Thomas, Karluss; Bannon, Gary; Hefle, Susan; Herouet, Corinne; Holsapple, Michael; Ladics, Gregory; MacIntosh, Sue; Privalle, Laura
2005-12-01
The ILSI Health and Environmental Sciences Institute (HESI) hosted an expert workshop 22-24 February 2005 in Mallorca, Spain, to review the state-of-the-science for conducting a sequence homology/bioinformatics evaluation in the context of a comprehensive allergenicity assessment for novel proteins, to obtain consensus on the value and role of bioinformatics in evaluating novel proteins, and to discuss the utility and methods of allergen-specific IgE testing in the diagnosis of food allergy. The workshop participants included over forty international experts from academia, industry, and government. The workshop was hosted by the HESI Protein Allergenicity Technical committee, which has established a long-term program whose mission is to advance the scientific understanding of the relevant parameters for characterizing the allergenic potential of novel proteins.
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Hodor, Paul; Chawla, Amandeep; Clark, Andrew; Neal, Lauren
2016-01-01
Summary: One of the solutions proposed for addressing the challenge of the overwhelming abundance of genomic sequence and other biological data is the use of the Hadoop computing framework. Appropriate tools are needed to set up computational environments that facilitate research of novel bioinformatics methodology using Hadoop. Here, we present cl-dash, a complete starter kit for setting up such an environment. Configuring and deploying new Hadoop clusters can be done in minutes. Use of Amazon Web Services ensures no initial investment and minimal operation costs. Two sample bioinformatics applications help the researcher understand and learn the principles of implementing an algorithm using the MapReduce programming pattern. Availability and implementation: Source code is available at https://bitbucket.org/booz-allen-sci-comp-team/cl-dash.git. Contact: hodor_paul@bah.com PMID:26428290
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A Bioinformatics Facility for NASA
NASA Technical Reports Server (NTRS)
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.
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Chain, Patrick
2018-05-31
Genomics â the genetic mapping and DNA sequencing of sets of genes or the complete genomes of organisms, along with related genome analysis and database work â is emerging as one of the transformative sciences of the 21st century. But current bioinformatics tools are not accessible to most biological researchers. Now, a new computational and web-based tool called EDGE Bioinformatics is working to fulfill the promise of democratizing genomics.
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BOWS (bioinformatics open web services) to centralize bioinformatics tools in web services.
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.
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Chapter 16: text mining for translational bioinformatics.
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.
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The Web as an educational tool for/in learning/teaching bioinformatics statistics.
Oliver, J; Pisano, M E; Alonso, T; Roca, P
2005-12-01
Statistics provides essential tool in Bioinformatics to interpret the results of a database search or for the management of enormous amounts of information provided from genomics, proteomics and metabolomics. The goal of this project was the development of a software tool that would be as simple as possible to demonstrate the use of the Bioinformatics statistics. Computer Simulation Methods (CSMs) developed using Microsoft Excel were chosen for their broad range of applications, immediate and easy formula calculation, immediate testing and easy graphics representation, and of general use and acceptance by the scientific community. The result of these endeavours is a set of utilities which can be accessed from the following URL: http://gmein.uib.es/bioinformatica/statistics. When tested on students with previous coursework with traditional statistical teaching methods, the general opinion/overall consensus was that Web-based instruction had numerous advantages, but traditional methods with manual calculations were also needed for their theory and practice. Once having mastered the basic statistical formulas, Excel spreadsheets and graphics were shown to be very useful for trying many parameters in a rapid fashion without having to perform tedious calculations. CSMs will be of great importance for the formation of the students and professionals in the field of bioinformatics, and for upcoming applications of self-learning and continuous formation.
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TeachEnG: a Teaching Engine for Genomics.
Kim, Minji; Kim, Yeonsung; Qian, Lei; Song, Jun S
2017-10-15
Bioinformatics is a rapidly growing field that has emerged from the synergy of computer science, statistics and biology. Given the interdisciplinary nature of bioinformatics, many students from diverse fields struggle with grasping bioinformatic concepts only from classroom lectures. Interactive tools for helping students reinforce their learning would be thus desirable. Here, we present an interactive online educational tool called TeachEnG (acronym for Teaching Engine for Genomics) for reinforcing key concepts in sequence alignment and phylogenetic tree reconstruction. Our instructional games allow students to align sequences by hand, fill out the dynamic programming matrix in the Needleman-Wunsch global sequence alignment algorithm, and reconstruct phylogenetic trees via the maximum parsimony, Unweighted Pair Group Method with Arithmetic mean (UPGMA) and Neighbor-Joining algorithms. With an easily accessible interface and instant visual feedback, TeachEnG will help promote active learning in bioinformatics. TeachEnG is freely available at http://teacheng.illinois.edu. The source code is available from https://github.com/KnowEnG/TeachEnG under the Artistic License 2.0. It is written in JavaScript and compatible with Firefox, Safari, Chrome and Microsoft Edge. songj@illinois.edu. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com
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Robust High-dimensional Bioinformatics Data Streams Mining by ODR-ioVFDT
Wang, Dantong; Fong, Simon; Wong, Raymond K.; Mohammed, Sabah; Fiaidhi, Jinan; Wong, Kelvin K. L.
2017-01-01
Outlier detection in bioinformatics data streaming mining has received significant attention by research communities in recent years. The problems of how to distinguish noise from an exception and deciding whether to discard it or to devise an extra decision path for accommodating it are causing dilemma. In this paper, we propose a novel algorithm called ODR with incrementally Optimized Very Fast Decision Tree (ODR-ioVFDT) for taking care of outliers in the progress of continuous data learning. By using an adaptive interquartile-range based identification method, a tolerance threshold is set. It is then used to judge if a data of exceptional value should be included for training or otherwise. This is different from the traditional outlier detection/removal approaches which are two separate steps in processing through the data. The proposed algorithm is tested using datasets of five bioinformatics scenarios and comparing the performance of our model and other ones without ODR. The results show that ODR-ioVFDT has better performance in classification accuracy, kappa statistics, and time consumption. The ODR-ioVFDT applied onto bioinformatics streaming data processing for detecting and quantifying the information of life phenomena, states, characters, variables and components of the organism can help to diagnose and treat disease more effectively. PMID:28230161
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Kravatsky, Yuri; Chechetkin, Vladimir; Fedoseeva, Daria; Gorbacheva, Maria; Kravatskaya, Galina; Kretova, Olga; Tchurikov, Nickolai
2017-11-23
The efficient development of antiviral drugs, including efficient antiviral small interfering RNAs (siRNAs), requires continuous monitoring of the strict correspondence between a drug and the related highly variable viral DNA/RNA target(s). Deep sequencing is able to provide an assessment of both the general target conservation and the frequency of particular mutations in the different target sites. The aim of this study was to develop a reliable bioinformatic pipeline for the analysis of millions of short, deep sequencing reads corresponding to selected highly variable viral sequences that are drug target(s). The suggested bioinformatic pipeline combines the available programs and the ad hoc scripts based on an original algorithm of the search for the conserved targets in the deep sequencing data. We also present the statistical criteria for the threshold of reliable mutation detection and for the assessment of variations between corresponding data sets. These criteria are robust against the possible sequencing errors in the reads. As an example, the bioinformatic pipeline is applied to the study of the conservation of RNA interference (RNAi) targets in human immunodeficiency virus 1 (HIV-1) subtype A. The developed pipeline is freely available to download at the website http://virmut.eimb.ru/. Brief comments and comparisons between VirMut and other pipelines are also presented.
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Suh, K. Stephen; Sarojini, Sreeja; Youssif, Maher; Nalley, Kip; Milinovikj, Natasha; Elloumi, Fathi; Russell, Steven; Pecora, Andrew; Schecter, Elyssa; Goy, Andre
2013-01-01
Personalized medicine promises patient-tailored treatments that enhance patient care and decrease overall treatment costs by focusing on genetics and “-omics” data obtained from patient biospecimens and records to guide therapy choices that generate good clinical outcomes. The approach relies on diagnostic and prognostic use of novel biomarkers discovered through combinations of tissue banking, bioinformatics, and electronic medical records (EMRs). The analytical power of bioinformatic platforms combined with patient clinical data from EMRs can reveal potential biomarkers and clinical phenotypes that allow researchers to develop experimental strategies using selected patient biospecimens stored in tissue banks. For cancer, high-quality biospecimens collected at diagnosis, first relapse, and various treatment stages provide crucial resources for study designs. To enlarge biospecimen collections, patient education regarding the value of specimen donation is vital. One approach for increasing consent is to offer publically available illustrations and game-like engagements demonstrating how wider sample availability facilitates development of novel therapies. The critical value of tissue bank samples, bioinformatics, and EMR in the early stages of the biomarker discovery process for personalized medicine is often overlooked. The data obtained also require cross-disciplinary collaborations to translate experimental results into clinical practice and diagnostic and prognostic use in personalized medicine. PMID:23818899
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Gruenstaeudl, Michael; Gerschler, Nico; Borsch, Thomas
2018-06-21
The sequencing and comparison of plastid genomes are becoming a standard method in plant genomics, and many researchers are using this approach to infer plant phylogenetic relationships. Due to the widespread availability of next-generation sequencing, plastid genome sequences are being generated at breakneck pace. This trend towards massive sequencing of plastid genomes highlights the need for standardized bioinformatic workflows. In particular, documentation and dissemination of the details of genome assembly, annotation, alignment and phylogenetic tree inference are needed, as these processes are highly sensitive to the choice of software and the precise settings used. Here, we present the procedure and results of sequencing, assembling, annotating and quality-checking of three complete plastid genomes of the aquatic plant genus Cabomba as well as subsequent gene alignment and phylogenetic tree inference. We accompany our findings by a detailed description of the bioinformatic workflow employed. Importantly, we share a total of eleven software scripts for each of these bioinformatic processes, enabling other researchers to evaluate and replicate our analyses step by step. The results of our analyses illustrate that the plastid genomes of Cabomba are highly conserved in both structure and gene content.
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Hernandez-Valladares, Maria; Vaudel, Marc; Selheim, Frode; Berven, Frode; Bruserud, Øystein
2017-08-01
Mass spectrometry (MS)-based proteomics has become an indispensable tool for the characterization of the proteome and its post-translational modifications (PTM). In addition to standard protein sequence databases, proteogenomics strategies search the spectral data against the theoretical spectra obtained from customized protein sequence databases. Up to date, there are no published proteogenomics studies on acute myeloid leukemia (AML) samples. Areas covered: Proteogenomics involves the understanding of genomic and proteomic data. The intersection of both datatypes requires advanced bioinformatics skills. A standard proteogenomics workflow that could be used for the study of AML samples is described. The generation of customized protein sequence databases as well as bioinformatics tools and pipelines commonly used in proteogenomics are discussed in detail. Expert commentary: Drawing on evidence from recent cancer proteogenomics studies and taking into account the public availability of AML genomic data, the interpretation of present and future MS-based AML proteomic data using AML-specific protein sequence databases could discover new biological mechanisms and targets in AML. However, proteogenomics workflows including bioinformatics guidelines can be challenging for the wide AML research community. It is expected that further automation and simplification of the bioinformatics procedures might attract AML investigators to adopt the proteogenomics strategy.
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Novel approaches for bioinformatic analysis of salivary RNA sequencing data for development.
Kaczor-Urbanowicz, Karolina Elzbieta; Kim, Yong; Li, Feng; Galeev, Timur; Kitchen, Rob R; Gerstein, Mark; Koyano, Kikuye; Jeong, Sung-Hee; Wang, Xiaoyan; Elashoff, David; Kang, So Young; Kim, Su Mi; Kim, Kyoung; Kim, Sung; Chia, David; Xiao, Xinshu; Rozowsky, Joel; Wong, David T W
2018-01-01
Analysis of RNA sequencing (RNA-Seq) data in human saliva is challenging. Lack of standardization and unification of the bioinformatic procedures undermines saliva's diagnostic potential. Thus, it motivated us to perform this study. We applied principal pipelines for bioinformatic analysis of small RNA-Seq data of saliva of 98 healthy Korean volunteers including either direct or indirect mapping of the reads to the human genome using Bowtie1. Analysis of alignments to exogenous genomes by another pipeline revealed that almost all of the reads map to bacterial genomes. Thus, salivary exRNA has fundamental properties that warrant the design of unique additional steps while performing the bioinformatic analysis. Our pipelines can serve as potential guidelines for processing of RNA-Seq data of human saliva. Processing and analysis results of the experimental data generated by the exceRpt (v4.6.3) small RNA-seq pipeline (github.gersteinlab.org/exceRpt) are available from exRNA atlas (exrna-atlas.org). Alignment to exogenous genomes and their quantification results were used in this paper for the analyses of small RNAs of exogenous origin. dtww@ucla.edu. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com
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Precision medicine needs pioneering clinical bioinformaticians.
Gómez-López, Gonzalo; Dopazo, Joaquín; Cigudosa, Juan C; Valencia, Alfonso; Al-Shahrour, Fátima
2017-10-25
Success in precision medicine depends on accessing high-quality genetic and molecular data from large, well-annotated patient cohorts that couple biological samples to comprehensive clinical data, which in conjunction can lead to effective therapies. From such a scenario emerges the need for a new professional profile, an expert bioinformatician with training in clinical areas who can make sense of multi-omics data to improve therapeutic interventions in patients, and the design of optimized basket trials. In this review, we first describe the main policies and international initiatives that focus on precision medicine. Secondly, we review the currently ongoing clinical trials in precision medicine, introducing the concept of 'precision bioinformatics', and we describe current pioneering bioinformatics efforts aimed at implementing tools and computational infrastructures for precision medicine in health institutions around the world. Thirdly, we discuss the challenges related to the clinical training of bioinformaticians, and the urgent need for computational specialists capable of assimilating medical terminologies and protocols to address real clinical questions. We also propose some skills required to carry out common tasks in clinical bioinformatics and some tips for emergent groups. Finally, we explore the future perspectives and the challenges faced by precision medicine bioinformatics. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.
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Neonatal Informatics: Transforming Neonatal Care Through Translational Bioinformatics
Palma, Jonathan P.; Benitz, William E.; Tarczy-Hornoch, Peter; Butte, Atul J.; Longhurst, Christopher A.
2012-01-01
The future of neonatal informatics will be driven by the availability of increasingly vast amounts of clinical and genetic data. The field of translational bioinformatics is concerned with linking and learning from these data and applying new findings to clinical care to transform the data into proactive, predictive, preventive, and participatory health. As a result of advances in translational informatics, the care of neonates will become more data driven, evidence based, and personalized. PMID:22924023
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A toolbox for developing bioinformatics software
Potrzebowski, Wojciech; Puton, Tomasz; Rother, Magdalena; Wywial, Ewa; Bujnicki, Janusz M.
2012-01-01
Creating useful software is a major activity of many scientists, including bioinformaticians. Nevertheless, software development in an academic setting is often unsystematic, which can lead to problems associated with maintenance and long-term availibility. Unfortunately, well-documented software development methodology is difficult to adopt, and technical measures that directly improve bioinformatic programming have not been described comprehensively. We have examined 22 software projects and have identified a set of practices for software development in an academic environment. We found them useful to plan a project, support the involvement of experts (e.g. experimentalists), and to promote higher quality and maintainability of the resulting programs. This article describes 12 techniques that facilitate a quick start into software engineering. We describe 3 of the 22 projects in detail and give many examples to illustrate the usage of particular techniques. We expect this toolbox to be useful for many bioinformatics programming projects and to the training of scientific programmers. PMID:21803787
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Menegidio, Fabiano B; Jabes, Daniela L; Costa de Oliveira, Regina; Nunes, Luiz R
2018-02-01
This manuscript introduces and describes Dugong, a Docker image based on Ubuntu 16.04, which automates installation of more than 3500 bioinformatics tools (along with their respective libraries and dependencies), in alternative computational environments. The software operates through a user-friendly XFCE4 graphic interface that allows software management and installation by users not fully familiarized with the Linux command line and provides the Jupyter Notebook to assist in the delivery and exchange of consistent and reproducible protocols and results across laboratories, assisting in the development of open science projects. Source code and instructions for local installation are available at https://github.com/DugongBioinformatics, under the MIT open source license. Luiz.nunes@ufabc.edu.br. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com
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Learning nucleic acids solving by bioinformatics problems.
Nunes, Rhewter; Barbosa de Almeida Júnior, Edivaldo; Pessoa Pinto de Menezes, Ivandilson; Malafaia, Guilherme
2015-01-01
The article describes the development of a new approach to teach molecular biology to undergraduate biology students. The 34 students who participated in this research belonged to the first period of the Biological Sciences teaching course of the Instituto Federal Goiano at Urutaí Campus, Brazil. They were registered in Cell Biology in the first semester of 2013. They received four 55 min-long expository/dialogued lectures that covered the content of "structure and functions of nucleic acids". Later the students were invited to attend four meetings (in a computer laboratory) in which some concepts of Bioinformatics were presented and some problems of the Rosalind platform were solved. The observations we report here are very useful as a broad groundwork to development new research. An interesting possibility is research into the effects of bioinformatics interventions that improve molecular biology learning. © 2015 The International Union of Biochemistry and Molecular Biology.
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NASA Astrophysics Data System (ADS)
Seto, Donald
The convergence and wealth of informatics, bioinformatics and genomics methods and associated resources allow a comprehensive and rapid approach for the surveillance and detection of bacterial and viral organisms. Coupled with the continuing race for the fastest, most cost-efficient and highest-quality DNA sequencing technology, that is, "next generation sequencing", the detection of biological threat agents by `cheaper and faster' means is possible. With the application of improved bioinformatic tools for the understanding of these genomes and for parsing unique pathogen genome signatures, along with `state-of-the-art' informatics which include faster computational methods, equipment and databases, it is feasible to apply new algorithms to biothreat agent detection. Two such methods are high-throughput DNA sequencing-based and resequencing microarray-based identification. These are illustrated and validated by two examples involving human adenoviruses, both from real-world test beds.
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SOBA: sequence ontology bioinformatics analysis.
Moore, Barry; Fan, Guozhen; Eilbeck, Karen
2010-07-01
The advent of cheaper, faster sequencing technologies has pushed the task of sequence annotation from the exclusive domain of large-scale multi-national sequencing projects to that of research laboratories and small consortia. The bioinformatics burden placed on these laboratories, some with very little programming experience can be daunting. Fortunately, there exist software libraries and pipelines designed with these groups in mind, to ease the transition from an assembled genome to an annotated and accessible genome resource. We have developed the Sequence Ontology Bioinformatics Analysis (SOBA) tool to provide a simple statistical and graphical summary of an annotated genome. We envisage its use during annotation jamborees, genome comparison and for use by developers for rapid feedback during annotation software development and testing. SOBA also provides annotation consistency feedback to ensure correct use of terminology within annotations, and guides users to add new terms to the Sequence Ontology when required. SOBA is available at http://www.sequenceontology.org/cgi-bin/soba.cgi.
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Bruder, Katherine; Malki, Kema; Cooper, Alexandria; Sible, Emily; Shapiro, Jason W.; Watkins, Siobhan C.; Putonti, Catherine
2016-01-01
Advances in bioinformatics and sequencing technologies have allowed for the analysis of complex microbial communities at an unprecedented rate. While much focus is often placed on the cellular members of these communities, viruses play a pivotal role, particularly bacteria-infecting viruses (bacteriophages); phages mediate global biogeochemical processes and drive microbial evolution through bacterial grazing and horizontal gene transfer. Despite their importance and ubiquity in nature, very little is known about the diversity and structure of viral communities. Though the need for culture-based methods for viral identification has been somewhat circumvented through metagenomic techniques, the analysis of metaviromic data is marred with many unique issues. In this review, we examine the current bioinformatic approaches for metavirome analyses and the inherent challenges facing the field as illustrated by the ongoing efforts in the exploration of freshwater phage populations. PMID:27375355
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Bioinformatics and Microarray Data Analysis on the Cloud.
Calabrese, Barbara; Cannataro, Mario
2016-01-01
High-throughput platforms such as microarray, mass spectrometry, and next-generation sequencing are producing an increasing volume of omics data that needs large data storage and computing power. Cloud computing offers massive scalable computing and storage, data sharing, on-demand anytime and anywhere access to resources and applications, and thus, it may represent the key technology for facing those issues. In fact, in the recent years it has been adopted for the deployment of different bioinformatics solutions and services both in academia and in the industry. Although this, cloud computing presents several issues regarding the security and privacy of data, that are particularly important when analyzing patients data, such as in personalized medicine. This chapter reviews main academic and industrial cloud-based bioinformatics solutions; with a special focus on microarray data analysis solutions and underlines main issues and problems related to the use of such platforms for the storage and analysis of patients data.
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R-Based Software for the Integration of Pathway Data into Bioinformatic Algorithms
Kramer, Frank; Bayerlová, Michaela; Beißbarth, Tim
2014-01-01
Putting new findings into the context of available literature knowledge is one approach to deal with the surge of high-throughput data results. Furthermore, prior knowledge can increase the performance and stability of bioinformatic algorithms, for example, methods for network reconstruction. In this review, we examine software packages for the statistical computing framework R, which enable the integration of pathway data for further bioinformatic analyses. Different approaches to integrate and visualize pathway data are identified and packages are stratified concerning their features according to a number of different aspects: data import strategies, the extent of available data, dependencies on external tools, integration with further analysis steps and visualization options are considered. A total of 12 packages integrating pathway data are reviewed in this manuscript. These are supplemented by five R-specific packages for visualization and six connector packages, which provide access to external tools. PMID:24833336
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A survey on evolutionary algorithm based hybrid intelligence in bioinformatics.
Li, Shan; Kang, Liying; Zhao, Xing-Ming
2014-01-01
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.
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Bioinformatics Meets Virology: The European Virus Bioinformatics Center's Second Annual Meeting.
Ibrahim, Bashar; Arkhipova, Ksenia; Andeweg, Arno C; Posada-Céspedes, Susana; Enault, François; Gruber, Arthur; Koonin, Eugene V; Kupczok, Anne; Lemey, Philippe; McHardy, Alice C; McMahon, Dino P; Pickett, Brett E; Robertson, David L; Scheuermann, Richard H; Zhernakova, Alexandra; Zwart, Mark P; Schönhuth, Alexander; Dutilh, Bas E; Marz, Manja
2018-05-14
The Second Annual Meeting of the European Virus Bioinformatics Center (EVBC), held in Utrecht, Netherlands, focused on computational approaches in virology, with topics including (but not limited to) virus discovery, diagnostics, (meta-)genomics, modeling, epidemiology, molecular structure, evolution, and viral ecology. The goals of the Second Annual Meeting were threefold: (i) to bring together virologists and bioinformaticians from across the academic, industrial, professional, and training sectors to share best practice; (ii) to provide a meaningful and interactive scientific environment to promote discussion and collaboration between students, postdoctoral fellows, and both new and established investigators; (iii) to inspire and suggest new research directions and questions. Approximately 120 researchers from around the world attended the Second Annual Meeting of the EVBC this year, including 15 renowned international speakers. This report presents an overview of new developments and novel research findings that emerged during the meeting.
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Web-based services for drug design and discovery.
Frey, Jeremy G; Bird, Colin L
2011-09-01
Reviews of the development of drug discovery through the 20(th) century recognised the importance of chemistry and increasingly bioinformatics, but had relatively little to say about the importance of computing and networked computing in particular. However, the design and discovery of new drugs is arguably the most significant single application of bioinformatics and cheminformatics to have benefitted from the increases in the range and power of the computational techniques since the emergence of the World Wide Web, commonly now referred to as simply 'the Web'. Web services have enabled researchers to access shared resources and to deploy standardized calculations in their search for new drugs. This article first considers the fundamental principles of Web services and workflows, and then explores the facilities and resources that have evolved to meet the specific needs of chem- and bio-informatics. This strategy leads to a more detailed examination of the basic components that characterise molecules and the essential predictive techniques, followed by a discussion of the emerging networked services that transcend the basic provisions, and the growing trend towards embracing modern techniques, in particular the Semantic Web. In the opinion of the authors, the issues that require community action are: increasing the amount of chemical data available for open access; validating the data as provided; and developing more efficient links between the worlds of cheminformatics and bioinformatics. The goal is to create ever better drug design services.
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Kang, Yuan; Dong, Xinran; Zhou, Qiongjie; Zhang, Ying; Cheng, Yan; Hu, Rong; Su, Cuihong; Jin, Hong; Liu, Xiaohui; Ma, Duan; Tian, Weidong; Li, Xiaotian
2012-03-01
This study aimed to identify candidate protein biomarkers from maternal serum for Down syndrome (DS) by integrated proteomic and bioinformatics analysis. A pregnancy DS group of 18 women and a control group with the same number were prepared, and the maternal serum proteins were analyzed by isobaric tags for relative and absolute quantitation and mass spectrometry, to identify DS differentially expressed maternal serum proteins (DS-DEMSPs). Comprehensive bioinformatics analysis was then employed to analyze DS-DEMSPs both in this paper and seven related publications. Down syndrome differentially expressed maternal serum proteins from different studies are significantly enriched with common Gene Ontology functions, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways, transcription factor binding sites, and Pfam protein domains, However, the DS-DEMSPs are less functionally related to known DS-related genes. These evidences suggest that common molecular mechanisms induced by secondary effects may be present upon DS carrying. A simple scoring scheme revealed Alpha-2-macroglobulin, Apolipoprotein A1, Apolipoprotein E, Complement C1s subcomponent, Complement component 5, Complement component 8, alpha polypeptide, Complement component 8, beta polypeptide and Fibronectin as potential DS biomarkers. The integration of proteomics and bioinformatics studies provides a novel approach to develop new prenatal screening methods for noninvasive yet accurate diagnosis of DS. Copyright © 2012 John Wiley & Sons, Ltd.
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Food Safety in the Age of Next Generation Sequencing, Bioinformatics, and Open Data Access.
Taboada, Eduardo N; Graham, Morag R; Carriço, João A; Van Domselaar, Gary
2017-01-01
Public health labs and food regulatory agencies globally are embracing whole genome sequencing (WGS) as a revolutionary new method that is positioned to replace numerous existing diagnostic and microbial typing technologies with a single new target: the microbial draft genome. The ability to cheaply generate large amounts of microbial genome sequence data, combined with emerging policies of food regulatory and public health institutions making their microbial sequences increasingly available and public, has served to open up the field to the general scientific community. This open data access policy shift has resulted in a proliferation of data being deposited into sequence repositories and of novel bioinformatics software designed to analyze these vast datasets. There also has been a more recent drive for improved data sharing to achieve more effective global surveillance, public health and food safety. Such developments have heightened the need for enhanced analytical systems in order to process and interpret this new type of data in a timely fashion. In this review we outline the emergence of genomics, bioinformatics and open data in the context of food safety. We also survey major efforts to translate genomics and bioinformatics technologies out of the research lab and into routine use in modern food safety labs. We conclude by discussing the challenges and opportunities that remain, including those expected to play a major role in the future of food safety science.
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Zoukhri, Driss; Rawe, Ian; Singh, Mabi; Brown, Ashley; Kublin, Claire L; Dawson, Kevin; Haddon, William F; White, Earl L; Hanley, Kathleen M; Tusé, Daniel; Malyj, Wasyl; Papas, Athena
2012-03-01
The purpose of the current study was to determine if saliva contains biomarkers that can be used as diagnostic tools for Sjögren's syndrome (SjS). Twenty seven SjS patients and 27 age-matched healthy controls were recruited for these studies. Unstimulated glandular saliva was collected from the Wharton's duct using a suction device. Two µl of salvia were processed for mass spectrometry analyses on a prOTOF 2000 matrix-assisted laser desorption/ionization orthogonal time of flight (MALDI O-TOF) mass spectrometer. Raw data were analyzed using bioinformatic tools to identify biomarkers. MALDI O-TOF MS analyses of saliva samples were highly reproducible and the mass spectra generated were very rich in peptides and peptide fragments in the 750-7,500 Da range. Data analysis using bioinformatic tools resulted in several classification models being built and several biomarkers identified. One model based on 7 putative biomarkers yielded a sensitivity of 97.5%, specificity of 97.8% and an accuracy of 97.6%. One biomarker was present only in SjS samples and was identified as a proteolytic peptide originating from human basic salivary proline-rich protein 3 precursor. We conclude that salivary biomarkers detected by high-resolution mass spectrometry coupled with powerful bioinformatic tools offer the potential to serve as diagnostic/prognostic tools for SjS.
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Bringing Web 2.0 to bioinformatics.
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.
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The making of the Women in Biology forum (WiB) at Bioclues.
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.
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Rahpeyma, Mehdi; Fotouhi, Fatemeh; Makvandi, Manouchehr; Ghadiri, Ata; Samarbaf-Zadeh, Alireza
2015-11-01
Crimean-Congo hemorrhagic fever virus (CCHFV) is a member of the nairovirus, a genus in the Bunyaviridae family, which causes a life threatening disease in human. Currently, there is no vaccine against CCHFV and detailed structural analysis of CCHFV proteins remains undefined. The CCHFV M RNA segment encodes two viral surface glycoproteins known as Gn and Gc. Viral glycoproteins can be considered as key targets for vaccine development. The current study aimed to investigate structural bioinformatics of CCHFV Gn protein and design a construct to make a recombinant bacmid to express by baculovirus system. To express the Gn protein in insect cells that can be used as antigen in animal model vaccine studies. Bioinformatic analysis of CCHFV Gn protein was performed and designed a construct and cloned into pFastBacHTb vector and a recombinant Gn-bacmid was generated by Bac to Bac system. Primary, secondary, and 3D structure of CCHFV Gn were obtained and PCR reaction with M13 forward and reverse primers confirmed the generation of recombinant bacmid DNA harboring Gn coding region under polyhedron promoter. Characterization of the detailed structure of CCHFV Gn by bioinformatics software provides the basis for development of new experiments and construction of a recombinant bacmid harboring CCHFV Gn, which is valuable for designing a recombinant vaccine against deadly pathogens like CCHFV.
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Field of genes: using Apache Kafka as a bioinformatic data repository.
Lawlor, Brendan; Lynch, Richard; Mac Aogáin, Micheál; Walsh, Paul
2018-04-01
Bioinformatic research is increasingly dependent on large-scale datasets, accessed either from private or public repositories. An example of a public repository is National Center for Biotechnology Information's (NCBI's) Reference Sequence (RefSeq). These repositories must decide in what form to make their data available. Unstructured data can be put to almost any use but are limited in how access to them can be scaled. Highly structured data offer improved performance for specific algorithms but limit the wider usefulness of the data. We present an alternative: lightly structured data stored in Apache Kafka in a way that is amenable to parallel access and streamed processing, including subsequent transformations into more highly structured representations. We contend that this approach could provide a flexible and powerful nexus of bioinformatic data, bridging the gap between low structure on one hand, and high performance and scale on the other. To demonstrate this, we present a proof-of-concept version of NCBI's RefSeq database using this technology. We measure the performance and scalability characteristics of this alternative with respect to flat files. The proof of concept scales almost linearly as more compute nodes are added, outperforming the standard approach using files. Apache Kafka merits consideration as a fast and more scalable but general-purpose way to store and retrieve bioinformatic data, for public, centralized reference datasets such as RefSeq and for private clinical and experimental data.
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2007-03-08
with CD3D 50848 PAR1/UBE3A Prader–Willi syndrome chromosome region 1, GMCSFRalpha precursor, IL3Ralpha precursor (CD123) Brain development...intervention programs justifiable? Emerg. Infect. Dis. 3, 83–94. iebel, U., Kindler , B., Pepperkok, R., 2004. ‘Harvester’: a fast meta search engine of human...protein resources. Bioinformatics 20, 1962–1963. iebel, U., Kindler , B., Pepperkok, R., 2005. Bioinformatic “Harvester”: a search engine for genome
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ENFIN a network to enhance integrative systems biology.
Kahlem, Pascal; Birney, Ewan
2007-12-01
Integration of biological data of various types and development of adapted bioinformatics tools represent critical objectives to enable research at the systems level. The European Network of Excellence ENFIN is engaged in developing both an adapted infrastructure to connect databases and platforms to enable the generation of new bioinformatics tools as well as the experimental validation of computational predictions. We will give an overview of the projects tackled within ENFIN and discuss the challenges associated with integration for systems biology.
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NASA Astrophysics Data System (ADS)
Feodorova, Valentina A.; Saltykov, Yury V.; Zaytsev, Sergey S.; Ulyanov, Sergey S.; Ulianova, Onega V.
2018-04-01
Method of phase-shifting speckle-interferometry has been used as a new tool with high potency for modern bioinformatics. Virtual phase-shifting speckle-interferometry has been applied for detection of polymorphism in the of Chlamydia trachomatis omp1 gene. It has been shown, that suggested method is very sensitive to natural genetic mutations as single nucleotide polymorphism (SNP). Effectiveness of proposed method has been compared with effectiveness of the newest bioinformatic tools, based on nucleotide sequence alignment.
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Nawrocki, Eric P.; Burge, Sarah W.
2013-01-01
The development of RNA bioinformatic tools began more than 30 y ago with the description of the Nussinov and Zuker dynamic programming algorithms for single sequence RNA secondary structure prediction. Since then, many tools have been developed for various RNA sequence analysis problems such as homology search, multiple sequence alignment, de novo RNA discovery, read-mapping, and many more. In this issue, we have collected a sampling of reviews and original research that demonstrate some of the many ways bioinformatics is integrated with current RNA biology research. PMID:23948768
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Feature selection methods for big data bioinformatics: A survey from the search perspective.
Wang, Lipo; Wang, Yaoli; Chang, Qing
2016-12-01
This paper surveys main principles of feature selection and their recent applications in big data bioinformatics. Instead of the commonly used categorization into filter, wrapper, and embedded approaches to feature selection, we formulate feature selection as a combinatorial optimization or search problem and categorize feature selection methods into exhaustive search, heuristic search, and hybrid methods, where heuristic search methods may further be categorized into those with or without data-distilled feature ranking measures. Copyright © 2016 Elsevier Inc. All rights reserved.
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Advantages and disadvantages in usage of bioinformatic programs in promoter region analysis
NASA Astrophysics Data System (ADS)
Pawełkowicz, Magdalena E.; Skarzyńska, Agnieszka; Posyniak, Kacper; ZiÄ bska, Karolina; PlÄ der, Wojciech; Przybecki, Zbigniew
2015-09-01
An important computational challenge is finding the regulatory elements across the promotor region. In this work we present the advantages and disadvantages from the application of different bioinformatics programs for localization of transcription factor binding sites in the upstream region of genes connected with sex determination in cucumber. We use PlantCARE, PlantPAN and SignalScan to find motifs in the promotor regions. The results have been compared and possible function of chosen motifs has been described.
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ExPASy: SIB bioinformatics resource portal.
Artimo, Panu; Jonnalagedda, Manohar; Arnold, Konstantin; Baratin, Delphine; Csardi, Gabor; de Castro, Edouard; Duvaud, Séverine; Flegel, Volker; Fortier, Arnaud; Gasteiger, Elisabeth; Grosdidier, Aurélien; Hernandez, Céline; Ioannidis, Vassilios; Kuznetsov, Dmitry; Liechti, Robin; Moretti, Sébastien; Mostaguir, Khaled; Redaschi, Nicole; Rossier, Grégoire; Xenarios, Ioannis; Stockinger, Heinz
2012-07-01
ExPASy (http://www.expasy.org) has worldwide reputation as one of the main bioinformatics resources for proteomics. It has now evolved, becoming an extensible and integrative portal accessing many scientific resources, databases and software tools in different areas of life sciences. Scientists can henceforth access seamlessly a wide range of resources in many different domains, such as proteomics, genomics, phylogeny/evolution, systems biology, population genetics, transcriptomics, etc. The individual resources (databases, web-based and downloadable software tools) are hosted in a 'decentralized' way by different groups of the SIB Swiss Institute of Bioinformatics and partner institutions. Specifically, a single web portal provides a common entry point to a wide range of resources developed and operated by different SIB groups and external institutions. The portal features a search function across 'selected' resources. Additionally, the availability and usage of resources are monitored. The portal is aimed for both expert users and people who are not familiar with a specific domain in life sciences. The new web interface provides, in particular, visual guidance for newcomers to ExPASy.
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CBESW: sequence alignment on the Playstation 3.
Wirawan, Adrianto; Kwoh, Chee Keong; Hieu, Nim Tri; Schmidt, Bertil
2008-09-17
The exponential growth of available biological data has caused bioinformatics to be rapidly moving towards a data-intensive, computational science. As a result, the computational power needed by bioinformatics applications is growing exponentially as well. The recent emergence of accelerator technologies has made it possible to achieve an excellent improvement in execution time for many bioinformatics applications, compared to current general-purpose platforms. In this paper, we demonstrate how the PlayStation 3, powered by the Cell Broadband Engine, can be used as a computational platform to accelerate the Smith-Waterman algorithm. For large datasets, our implementation on the PlayStation 3 provides a significant improvement in running time compared to other implementations such as SSEARCH, Striped Smith-Waterman and CUDA. Our implementation achieves a peak performance of up to 3,646 MCUPS. The results from our experiments demonstrate that the PlayStation 3 console can be used as an efficient low cost computational platform for high performance sequence alignment applications.
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CBESW: Sequence Alignment on the Playstation 3
Wirawan, Adrianto; Kwoh, Chee Keong; Hieu, Nim Tri; Schmidt, Bertil
2008-01-01
Background The exponential growth of available biological data has caused bioinformatics to be rapidly moving towards a data-intensive, computational science. As a result, the computational power needed by bioinformatics applications is growing exponentially as well. The recent emergence of accelerator technologies has made it possible to achieve an excellent improvement in execution time for many bioinformatics applications, compared to current general-purpose platforms. In this paper, we demonstrate how the PlayStation® 3, powered by the Cell Broadband Engine, can be used as a computational platform to accelerate the Smith-Waterman algorithm. Results For large datasets, our implementation on the PlayStation® 3 provides a significant improvement in running time compared to other implementations such as SSEARCH, Striped Smith-Waterman and CUDA. Our implementation achieves a peak performance of up to 3,646 MCUPS. Conclusion The results from our experiments demonstrate that the PlayStation® 3 console can be used as an efficient low cost computational platform for high performance sequence alignment applications. PMID:18798993
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RImmPort: an R/Bioconductor package that enables ready-for-analysis immunology research data.
Shankar, Ravi D; Bhattacharya, Sanchita; Jujjavarapu, Chethan; Andorf, Sandra; Wiser, Jeffery A; Butte, Atul J
2017-04-01
: Open access to raw clinical and molecular data related to immunological studies has created a tremendous opportunity for data-driven science. We have developed RImmPort that prepares NIAID-funded research study datasets in ImmPort (immport.org) for analysis in R. RImmPort comprises of three main components: (i) a specification of R classes that encapsulate study data, (ii) foundational methods to load data of a specific study and (iii) generic methods to slice and dice data across different dimensions in one or more studies. Furthermore, RImmPort supports open formalisms, such as CDISC standards on the open source bioinformatics platform Bioconductor, to ensure that ImmPort curated study datasets are seamlessly accessible and ready for analysis, thus enabling innovative bioinformatics research in immunology. RImmPort is available as part of Bioconductor (bioconductor.org/packages/RImmPort). rshankar@stanford.edu. 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
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Reanalysis of RNA-Sequencing Data Reveals Several Additional Fusion Genes with Multiple Isoforms
Kangaspeska, Sara; Hultsch, Susanne; Edgren, Henrik; Nicorici, Daniel; Murumägi, Astrid; Kallioniemi, Olli
2012-01-01
RNA-sequencing and tailored bioinformatic methodologies have paved the way for identification of expressed fusion genes from the chaotic genomes of solid tumors. We have recently successfully exploited RNA-sequencing for the discovery of 24 novel fusion genes in breast cancer. Here, we demonstrate the importance of continuous optimization of the bioinformatic methodology for this purpose, and report the discovery and experimental validation of 13 additional fusion genes from the same samples. Integration of copy number profiling with the RNA-sequencing results revealed that the majority of the gene fusions were promoter-donating events that occurred at copy number transition points or involved high-level DNA-amplifications. Sequencing of genomic fusion break points confirmed that DNA-level rearrangements underlie selected fusion transcripts. Furthermore, a significant portion (>60%) of the fusion genes were alternatively spliced. This illustrates the importance of reanalyzing sequencing data as gene definitions change and bioinformatic methods improve, and highlights the previously unforeseen isoform diversity among fusion transcripts. PMID:23119097
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Reanalysis of RNA-sequencing data reveals several additional fusion genes with multiple isoforms.
Kangaspeska, Sara; Hultsch, Susanne; Edgren, Henrik; Nicorici, Daniel; Murumägi, Astrid; Kallioniemi, Olli
2012-01-01
RNA-sequencing and tailored bioinformatic methodologies have paved the way for identification of expressed fusion genes from the chaotic genomes of solid tumors. We have recently successfully exploited RNA-sequencing for the discovery of 24 novel fusion genes in breast cancer. Here, we demonstrate the importance of continuous optimization of the bioinformatic methodology for this purpose, and report the discovery and experimental validation of 13 additional fusion genes from the same samples. Integration of copy number profiling with the RNA-sequencing results revealed that the majority of the gene fusions were promoter-donating events that occurred at copy number transition points or involved high-level DNA-amplifications. Sequencing of genomic fusion break points confirmed that DNA-level rearrangements underlie selected fusion transcripts. Furthermore, a significant portion (>60%) of the fusion genes were alternatively spliced. This illustrates the importance of reanalyzing sequencing data as gene definitions change and bioinformatic methods improve, and highlights the previously unforeseen isoform diversity among fusion transcripts.
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Building international genomics collaboration for global health security
DOE Office of Scientific and Technical Information (OSTI.GOV)
Cui, Helen H.; Erkkila, Tracy; Chain, Patrick S. G.
Genome science and technologies are transforming life sciences globally in many ways and becoming a highly desirable area for international collaboration to strengthen global health. The Genome Science Program at the Los Alamos National Laboratory is leveraging a long history of expertise in genomics research to assist multiple partner nations in advancing their genomics and bioinformatics capabilities. The capability development objectives focus on providing a molecular genomics-based scientific approach for pathogen detection, characterization, and biosurveillance applications. The general approaches include introduction of basic principles in genomics technologies, training on laboratory methodologies and bioinformatic analysis of resulting data, procurement, and installationmore » of next-generation sequencing instruments, establishing bioinformatics software capabilities, and exploring collaborative applications of the genomics capabilities in public health. Genome centers have been established with public health and research institutions in the Republic of Georgia, Kingdom of Jordan, Uganda, and Gabon; broader collaborations in genomics applications have also been developed with research institutions in many other countries.« less
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Contribution of bioinformatics prediction in microRNA-based cancer therapeutics.
Banwait, Jasjit K; Bastola, Dhundy R
2015-01-01
Despite enormous efforts, cancer remains one of the most lethal diseases in the world. With the advancement of high throughput technologies massive amounts of cancer data can be accessed and analyzed. Bioinformatics provides a platform to assist biologists in developing minimally invasive biomarkers to detect cancer, and in designing effective personalized therapies to treat cancer patients. Still, the early diagnosis, prognosis, and treatment of cancer are an open challenge for the research community. MicroRNAs (miRNAs) are small non-coding RNAs that serve to regulate gene expression. The discovery of deregulated miRNAs in cancer cells and tissues has led many to investigate the use of miRNAs as potential biomarkers for early detection, and as a therapeutic agent to treat cancer. Here we describe advancements in computational approaches to predict miRNAs and their targets, and discuss the role of bioinformatics in studying miRNAs in the context of human cancer. Published by Elsevier B.V.
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Building international genomics collaboration for global health security
Cui, Helen H.; Erkkila, Tracy; Chain, Patrick S. G.; ...
2015-12-07
Genome science and technologies are transforming life sciences globally in many ways and becoming a highly desirable area for international collaboration to strengthen global health. The Genome Science Program at the Los Alamos National Laboratory is leveraging a long history of expertise in genomics research to assist multiple partner nations in advancing their genomics and bioinformatics capabilities. The capability development objectives focus on providing a molecular genomics-based scientific approach for pathogen detection, characterization, and biosurveillance applications. The general approaches include introduction of basic principles in genomics technologies, training on laboratory methodologies and bioinformatic analysis of resulting data, procurement, and installationmore » of next-generation sequencing instruments, establishing bioinformatics software capabilities, and exploring collaborative applications of the genomics capabilities in public health. Genome centers have been established with public health and research institutions in the Republic of Georgia, Kingdom of Jordan, Uganda, and Gabon; broader collaborations in genomics applications have also been developed with research institutions in many other countries.« less
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Wang, Pengfei; Wang, Yingfang; Duan, Guangcai; Xue, Zerun; Wang, Linlin; Guo, Xiangjiao; Yang, Haiyan; Xi, Yuanlin
2015-04-01
This study was aimed to explore the features of clustered regularly interspaced short palindromic repeats (CRISPR) structures in Shigella by using bioinformatics. We used bioinformatics methods, including BLAST, alignment and RNA structure prediction, to analyze the CRISPR structures of Shigella genomes. The results showed that the CRISPRs existed in the four groups of Shigella, and the flanking sequences of upstream CRISPRs could be classified into the same group with those of the downstream. We also found some relatively conserved palindromic motifs in the leader sequences. Repeat sequences had the same group with corresponding flanking sequences, and could be classified into two different types by their RNA secondary structures, which contain "stem" and "ring". Some spacers were found to homologize with part sequences of plasmids or phages. The study indicated that there were correlations between repeat sequences and flanking sequences, and the repeats might act as a kind of recognition mechanism to mediate the interaction between foreign genetic elements and Cas proteins.
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PCDDB: new developments at the Protein Circular Dichroism Data Bank.
Whitmore, Lee; Miles, Andrew John; Mavridis, Lazaros; Janes, Robert W; Wallace, B A
2017-01-04
The Protein Circular Dichroism Data Bank (PCDDB) has been in operation for more than 5 years as a public repository for archiving circular dichroism spectroscopic data and associated bioinformatics and experimental metadata. Since its inception, many improvements and new developments have been made in data display, searching algorithms, data formats, data content, auxillary information, and validation techniques, as well as, of course, an increase in the number of holdings. It provides a site (http://pcddb.cryst.bbk.ac.uk) for authors to deposit experimental data as well as detailed information on methods and calculations associated with published work. It also includes links for each entry to bioinformatics databases. The data are freely available to accessors either as single files or as complete data bank downloads. The PCDDB has found broad usage by the structural biology, bioinformatics, analytical and pharmaceutical communities, and has formed the basis for new software and methods developments. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.
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Treetrimmer: a method for phylogenetic dataset size reduction.
Maruyama, Shinichiro; Eveleigh, Robert J M; Archibald, John M
2013-04-12
With rapid advances in genome sequencing and bioinformatics, it is now possible to generate phylogenetic trees containing thousands of operational taxonomic units (OTUs) from a wide range of organisms. However, use of rigorous tree-building methods on such large datasets is prohibitive and manual 'pruning' of sequence alignments is time consuming and raises concerns over reproducibility. There is a need for bioinformatic tools with which to objectively carry out such pruning procedures. Here we present 'TreeTrimmer', a bioinformatics procedure that removes unnecessary redundancy in large phylogenetic datasets, alleviating the size effect on more rigorous downstream analyses. The method identifies and removes user-defined 'redundant' sequences, e.g., orthologous sequences from closely related organisms and 'recently' evolved lineage-specific paralogs. Representative OTUs are retained for more rigorous re-analysis. TreeTrimmer reduces the OTU density of phylogenetic trees without sacrificing taxonomic diversity while retaining the original tree topology, thereby speeding up downstream computer-intensive analyses, e.g., Bayesian and maximum likelihood tree reconstructions, in a reproducible fashion.
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GlycoRDF: an ontology to standardize glycomics data in RDF.
Ranzinger, Rene; Aoki-Kinoshita, Kiyoko F; Campbell, Matthew P; Kawano, Shin; Lütteke, Thomas; Okuda, Shujiro; Shinmachi, Daisuke; Shikanai, Toshihide; Sawaki, Hiromichi; Toukach, Philip; Matsubara, Masaaki; Yamada, Issaku; Narimatsu, Hisashi
2015-03-15
Over the last decades several glycomics-based bioinformatics resources and databases have been created and released to the public. Unfortunately, there is no common standard in the representation of the stored information or a common machine-readable interface allowing bioinformatics groups to easily extract and cross-reference the stored information. An international group of bioinformatics experts in the field of glycomics have worked together to create a standard Resource Description Framework (RDF) representation for glycomics data, focused on glycan sequences and related biological source, publications and experimental data. This RDF standard is defined by the GlycoRDF ontology and will be used by database providers to generate common machine-readable exports of the data stored in their databases. The ontology, supporting documentation and source code used by database providers to generate standardized RDF are available online (http://www.glycoinfo.org/GlycoRDF/). © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.
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Bioinformatics in protein kinases regulatory network and drug discovery.
Chen, Qingfeng; Luo, Haiqiong; Zhang, Chengqi; Chen, Yi-Ping Phoebe
2015-04-01
Protein kinases have been implicated in a number of diseases, where kinases participate many aspects that control cell growth, movement and death. The deregulated kinase activities and the knowledge of these disorders are of great clinical interest of drug discovery. The most critical issue is the development of safe and efficient disease diagnosis and treatment for less cost and in less time. It is critical to develop innovative approaches that aim at the root cause of a disease, not just its symptoms. Bioinformatics including genetic, genomic, mathematics and computational technologies, has become the most promising option for effective drug discovery, and has showed its potential in early stage of drug-target identification and target validation. It is essential that these aspects are understood and integrated into new methods used in drug discovery for diseases arisen from deregulated kinase activity. This article reviews bioinformatics techniques for protein kinase data management and analysis, kinase pathways and drug targets and describes their potential application in pharma ceutical industry. Copyright © 2015 Elsevier Inc. All rights reserved.
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2015-01-01
Contextual data collected concurrently with molecular samples are critical to the use of metagenomics in the fields of marine biodiversity, bioinformatics and biotechnology. We present here Marine Microbial Biodiversity, Bioinformatics and Biotechnology (M2B3) standards for “Reporting” and “Serving” data. The M2B3 Reporting Standard (1) describes minimal mandatory and recommended contextual information for a marine microbial sample obtained in the epipelagic zone, (2) includes meaningful information for researchers in the oceanographic, biodiversity and molecular disciplines, and (3) can easily be adopted by any marine laboratory with minimum sampling resources. The M2B3 Service Standard defines a software interface through which these data can be discovered and explored in data repositories. The M2B3 Standards were developed by the European project Micro B3, funded under 7th Framework Programme “Ocean of Tomorrow”, and were first used with the Ocean Sampling Day initiative. We believe that these standards have value in broader marine science. PMID:26203332
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Soulet, Fabienne; Kilarski, Witold W.; Roux-Dalvai, Florence; Herbert, John M. J.; Sacewicz, Izabela; Mouton-Barbosa, Emmanuelle; Bicknell, Roy; Lalor, Patricia; Monsarrat, Bernard; Bikfalvi, Andreas
2013-01-01
In order to map the extracellular or membrane proteome associated with the vasculature and the stroma in an embryonic organism in vivo, we developed a biotinylation technique for chicken embryo and combined it with mass spectrometry and bioinformatic analysis. We also applied this procedure to implanted tumors growing on the chorioallantoic membrane or after the induction of granulation tissue. Membrane and extracellular matrix proteins were the most abundant components identified. Relative quantitative analysis revealed differential protein expression patterns in several tissues. Through a bioinformatic approach, we determined endothelial cell protein expression signatures, which allowed us to identify several proteins not yet reported to be associated with endothelial cells or the vasculature. This is the first study reported so far that applies in vivo biotinylation, in combination with robust label-free quantitative proteomics approaches and bioinformatic analysis, to an embryonic organism. It also provides the first description of the vascular and matrix proteome of the embryo that might constitute the starting point for further developments. PMID:23674615
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EVALLER: a web server for in silico assessment of potential protein allergenicity
Barrio, Alvaro Martinez; Soeria-Atmadja, Daniel; Nistér, Anders; Gustafsson, Mats G.; Hammerling, Ulf; Bongcam-Rudloff, Erik
2007-01-01
Bioinformatics testing approaches for protein allergenicity, involving amino acid sequence comparisons, have evolved appreciably over the last several years to increased sophistication and performance. EVALLER, the web server presented in this article is based on our recently published ‘Detection based on Filtered Length-adjusted Allergen Peptides’ (DFLAP) algorithm, which affords in silico determination of potential protein allergenicity of high sensitivity and excellent specificity. To strengthen bioinformatics risk assessment in allergology EVALLER provides a comprehensive outline of its judgment on a query protein's potential allergenicity. Each such textual output incorporates a scoring figure, a confidence numeral of the assignment and information on high- or low-scoring matches to identified allergen-related motifs, including their respective location in accordingly derived allergens. The interface, built on a modified Perl Open Source package, enables dynamic and color-coded graphic representation of key parts of the output. Moreover, pertinent details can be examined in great detail through zoomed views. The server can be accessed at http://bioinformatics.bmc.uu.se/evaller.html. PMID:17537818
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Bhunia, Gouri Sankar; Dikhit, Manas Ranjan; Kesari, Shreekant; Sahoo, Ganesh Chandra; Das, Pradeep
2011-01-01
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. PMID:23554714
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Brooks, Mark A; Gewartowski, Kamil; Mitsiki, Eirini; Létoquart, Juliette; Pache, Roland A; Billier, Ysaline; Bertero, Michela; Corréa, Margot; Czarnocki-Cieciura, Mariusz; Dadlez, Michal; Henriot, Véronique; Lazar, Noureddine; Delbos, Lila; Lebert, Dorothée; Piwowarski, Jan; Rochaix, Pascal; Böttcher, Bettina; Serrano, Luis; Séraphin, Bertrand; van Tilbeurgh, Herman; Aloy, Patrick; Perrakis, Anastassis; Dziembowski, Andrzej
2010-09-08
For high-throughput structural studies of protein complexes of composition inferred from proteomics data, it is crucial that candidate complexes are selected accurately. Herein, we exemplify a procedure that combines a bioinformatics tool for complex selection with in vivo validation, to deliver structural results in a medium-throughout manner. We have selected a set of 20 yeast complexes, which were predicted to be feasible by either an automated bioinformatics algorithm, by manual inspection of primary data, or by literature searches. These complexes were validated with two straightforward and efficient biochemical assays, and heterologous expression technologies of complex components were then used to produce the complexes to assess their feasibility experimentally. Approximately one-half of the selected complexes were useful for structural studies, and we detail one particular success story. Our results underscore the importance of accurate target selection and validation in avoiding transient, unstable, or simply nonexistent complexes from the outset. Copyright © 2010 Elsevier Ltd. All rights reserved.
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Augustin, Regina; Lichtenthaler, Stefan F.; Greeff, Michael; Hansen, Jens; Wurst, Wolfgang; Trümbach, Dietrich
2011-01-01
The molecular mechanisms and genetic risk factors underlying Alzheimer's disease (AD) pathogenesis are only partly understood. To identify new factors, which may contribute to AD, different approaches are taken including proteomics, genetics, and functional genomics. Here, we used a bioinformatics approach and found that distinct AD-related genes share modules of transcription factor binding sites, suggesting a transcriptional coregulation. To detect additional coregulated genes, which may potentially contribute to AD, we established a new bioinformatics workflow with known multivariate methods like support vector machines, biclustering, and predicted transcription factor binding site modules by using in silico analysis and over 400 expression arrays from human and mouse. Two significant modules are composed of three transcription factor families: CTCF, SP1F, and EGRF/ZBPF, which are conserved between human and mouse APP promoter sequences. The specific combination of in silico promoter and multivariate analysis can identify regulation mechanisms of genes involved in multifactorial diseases. PMID:21559189
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BioPig: a Hadoop-based analytic toolkit for large-scale sequence data.
Nordberg, Henrik; Bhatia, Karan; Wang, Kai; Wang, Zhong
2013-12-01
The recent revolution in sequencing technologies has led to an exponential growth of sequence data. As a result, most of the current bioinformatics tools become obsolete as they fail to scale with data. To tackle this 'data deluge', here we introduce the BioPig sequence analysis toolkit as one of the solutions that scale to data and computation. We built BioPig on the Apache's Hadoop MapReduce system and the Pig data flow language. Compared with traditional serial and MPI-based algorithms, BioPig has three major advantages: first, BioPig's programmability greatly reduces development time for parallel bioinformatics applications; second, testing BioPig with up to 500 Gb sequences demonstrates that it scales automatically with size of data; and finally, BioPig can be ported without modification on many Hadoop infrastructures, as tested with Magellan system at National Energy Research Scientific Computing Center and the Amazon Elastic Compute Cloud. In summary, BioPig represents a novel program framework with the potential to greatly accelerate data-intensive bioinformatics analysis.
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Prospects and limitations of full-text index structures in genome analysis
Vyverman, Michaël; De Baets, Bernard; Fack, Veerle; Dawyndt, Peter
2012-01-01
The combination of incessant advances in sequencing technology producing large amounts of data and innovative bioinformatics approaches, designed to cope with this data flood, has led to new interesting results in the life sciences. Given the magnitude of sequence data to be processed, many bioinformatics tools rely on efficient solutions to a variety of complex string problems. These solutions include fast heuristic algorithms and advanced data structures, generally referred to as index structures. Although the importance of index structures is generally known to the bioinformatics community, the design and potency of these data structures, as well as their properties and limitations, are less understood. Moreover, the last decade has seen a boom in the number of variant index structures featuring complex and diverse memory-time trade-offs. This article brings a comprehensive state-of-the-art overview of the most popular index structures and their recently developed variants. Their features, interrelationships, the trade-offs they impose, but also their practical limitations, are explained and compared. PMID:22584621
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Zhou, Zhiwei; Xiong, Xin; Zhu, Zheng-Jiang
2017-07-15
In metabolomics, rigorous structural identification of metabolites presents a challenge for bioinformatics. The use of collision cross-section (CCS) values of metabolites derived from ion mobility-mass spectrometry effectively increases the confidence of metabolite identification, but this technique suffers from the limit number of available CCS values. Currently, there is no software available for rapidly generating the metabolites' CCS values. Here, we developed the first web server, namely, MetCCS Predictor, for predicting CCS values. It can predict the CCS values of metabolites using molecular descriptors within a few seconds. Common users with limited background on bioinformatics can benefit from this software and effectively improve the metabolite identification in metabolomics. The web server is freely available at: http://www.metabolomics-shanghai.org/MetCCS/ . jiangzhu@sioc.ac.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
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Integrative workflows for metagenomic analysis
Ladoukakis, Efthymios; Kolisis, Fragiskos N.; Chatziioannou, Aristotelis A.
2014-01-01
The rapid evolution of all sequencing technologies, described by the term Next Generation Sequencing (NGS), have revolutionized metagenomic analysis. They constitute a combination of high-throughput analytical protocols, coupled to delicate measuring techniques, in order to potentially discover, properly assemble and map allelic sequences to the correct genomes, achieving particularly high yields for only a fraction of the cost of traditional processes (i.e., Sanger). From a bioinformatic perspective, this boils down to many GB of data being generated from each single sequencing experiment, rendering the management or even the storage, critical bottlenecks with respect to the overall analytical endeavor. The enormous complexity is even more aggravated by the versatility of the processing steps available, represented by the numerous bioinformatic tools that are essential, for each analytical task, in order to fully unveil the genetic content of a metagenomic dataset. These disparate tasks range from simple, nonetheless non-trivial, quality control of raw data to exceptionally complex protein annotation procedures, requesting a high level of expertise for their proper application or the neat implementation of the whole workflow. Furthermore, a bioinformatic analysis of such scale, requires grand computational resources, imposing as the sole realistic solution, the utilization of cloud computing infrastructures. In this review article we discuss different, integrative, bioinformatic solutions available, which address the aforementioned issues, by performing a critical assessment of the available automated pipelines for data management, quality control, and annotation of metagenomic data, embracing various, major sequencing technologies and applications. PMID:25478562
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Bio-Docklets: virtualization containers for single-step execution of NGS pipelines.
Kim, Baekdoo; Ali, Thahmina; Lijeron, Carlos; Afgan, Enis; Krampis, Konstantinos
2017-08-01
Processing of next-generation sequencing (NGS) data requires significant technical skills, involving installation, configuration, and execution of bioinformatics data pipelines, in addition to specialized postanalysis visualization and data mining software. In order to address some of these challenges, developers have leveraged virtualization containers toward seamless deployment of preconfigured bioinformatics software and pipelines on any computational platform. We present an approach for abstracting the complex data operations of multistep, bioinformatics pipelines for NGS data analysis. As examples, we have deployed 2 pipelines for RNA sequencing and chromatin immunoprecipitation sequencing, preconfigured within Docker virtualization containers we call Bio-Docklets. Each Bio-Docklet exposes a single data input and output endpoint and from a user perspective, running the pipelines as simply as running a single bioinformatics tool. This is achieved using a "meta-script" that automatically starts the Bio-Docklets and controls the pipeline execution through the BioBlend software library and the Galaxy Application Programming Interface. The pipeline output is postprocessed by integration with the Visual Omics Explorer framework, providing interactive data visualizations that users can access through a web browser. Our goal is to enable easy access to NGS data analysis pipelines for nonbioinformatics experts on any computing environment, whether a laboratory workstation, university computer cluster, or a cloud service provider. Beyond end users, the Bio-Docklets also enables developers to programmatically deploy and run a large number of pipeline instances for concurrent analysis of multiple datasets. © The Authors 2017. Published by Oxford University Press.
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Bioinformatics analysis and detection of gelatinase encoded gene in Lysinibacillussphaericus
NASA Astrophysics Data System (ADS)
Repin, Rul Aisyah Mat; Mutalib, Sahilah Abdul; Shahimi, Safiyyah; Khalid, Rozida Mohd.; Ayob, Mohd. Khan; Bakar, Mohd. Faizal Abu; Isa, Mohd Noor Mat
2016-11-01
In this study, we performed bioinformatics analysis toward genome sequence of Lysinibacillussphaericus (L. sphaericus) to determine gene encoded for gelatinase. L. sphaericus was isolated from soil and gelatinase species-specific bacterium to porcine and bovine gelatin. This bacterium offers the possibility of enzymes production which is specific to both species of meat, respectively. The main focus of this research is to identify the gelatinase encoded gene within the bacteria of L. Sphaericus using bioinformatics analysis of partially sequence genome. From the research study, three candidate gene were identified which was, gelatinase candidate gene 1 (P1), NODE_71_length_93919_cov_158.931839_21 which containing 1563 base pair (bp) in size with 520 amino acids sequence; Secondly, gelatinase candidate gene 2 (P2), NODE_23_length_52851_cov_190.061386_17 which containing 1776 bp in size with 591 amino acids sequence; and Thirdly, gelatinase candidate gene 3 (P3), NODE_106_length_32943_cov_169.147919_8 containing 1701 bp in size with 566 amino acids sequence. Three pairs of oligonucleotide primers were designed and namely as, F1, R1, F2, R2, F3 and R3 were targeted short sequences of cDNA by PCR. The amplicons were reliably results in 1563 bp in size for candidate gene P1 and 1701 bp in size for candidate gene P3. Therefore, the results of bioinformatics analysis of L. Sphaericus resulting in gene encoded gelatinase were identified.
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High-throughput protein analysis integrating bioinformatics and experimental assays
del Val, Coral; Mehrle, Alexander; Falkenhahn, Mechthild; Seiler, Markus; Glatting, Karl-Heinz; Poustka, Annemarie; Suhai, Sandor; Wiemann, Stefan
2004-01-01
The wealth of transcript information that has been made publicly available in recent years requires the development of high-throughput functional genomics and proteomics approaches for its analysis. Such approaches need suitable data integration procedures and a high level of automation in order to gain maximum benefit from the results generated. We have designed an automatic pipeline to analyse annotated open reading frames (ORFs) stemming from full-length cDNAs produced mainly by the German cDNA Consortium. The ORFs are cloned into expression vectors for use in large-scale assays such as the determination of subcellular protein localization or kinase reaction specificity. Additionally, all identified ORFs undergo exhaustive bioinformatic analysis such as similarity searches, protein domain architecture determination and prediction of physicochemical characteristics and secondary structure, using a wide variety of bioinformatic methods in combination with the most up-to-date public databases (e.g. PRINTS, BLOCKS, INTERPRO, PROSITE SWISSPROT). Data from experimental results and from the bioinformatic analysis are integrated and stored in a relational database (MS SQL-Server), which makes it possible for researchers to find answers to biological questions easily, thereby speeding up the selection of targets for further analysis. The designed pipeline constitutes a new automatic approach to obtaining and administrating relevant biological data from high-throughput investigations of cDNAs in order to systematically identify and characterize novel genes, as well as to comprehensively describe the function of the encoded proteins. PMID:14762202
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Controlling new knowledge: Genomic science, governance and the politics of bioinformatics.
Salter, Brian; Salter, Charlotte
2017-04-01
The rise of bioinformatics is a direct response to the political difficulties faced by genomics in its quest to be a new biomedical innovation, and the value of bioinformatics lies in its role as the bridge between the promise of genomics and its realization in the form of health benefits. Western scientific elites are able to use their close relationship with the state to control and facilitate the emergence of new domains compatible with the existing distribution of epistemic power - all within the embrace of public trust. The incorporation of bioinformatics as the saviour of genomics had to be integrated with the operation of two key aspects of governance in this field: the definition and ownership of the new knowledge. This was achieved mainly by the development of common standards and by the promotion of the values of communality, open access and the public ownership of data to legitimize and maintain the governance power of publicly funded genomic science. Opposition from industry advocating the private ownership of knowledge has been largely neutered through the institutions supporting the science-state concordat. However, in order for translation into health benefits to occur and public trust to be assured, genomic and clinical data have to be integrated and knowledge ownership agreed upon across the separate and distinct governance territories of scientist, clinical medicine and society. Tensions abound as science seeks ways of maintaining its control of knowledge production through the negotiation of new forms of governance with the institutions and values of clinicians and patients.
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Field of genes: using Apache Kafka as a bioinformatic data repository
Lynch, Richard; Walsh, Paul
2018-01-01
Abstract Background Bioinformatic research is increasingly dependent on large-scale datasets, accessed either from private or public repositories. An example of a public repository is National Center for Biotechnology Information's (NCBI’s) Reference Sequence (RefSeq). These repositories must decide in what form to make their data available. Unstructured data can be put to almost any use but are limited in how access to them can be scaled. Highly structured data offer improved performance for specific algorithms but limit the wider usefulness of the data. We present an alternative: lightly structured data stored in Apache Kafka in a way that is amenable to parallel access and streamed processing, including subsequent transformations into more highly structured representations. We contend that this approach could provide a flexible and powerful nexus of bioinformatic data, bridging the gap between low structure on one hand, and high performance and scale on the other. To demonstrate this, we present a proof-of-concept version of NCBI’s RefSeq database using this technology. We measure the performance and scalability characteristics of this alternative with respect to flat files. Results The proof of concept scales almost linearly as more compute nodes are added, outperforming the standard approach using files. Conclusions Apache Kafka merits consideration as a fast and more scalable but general-purpose way to store and retrieve bioinformatic data, for public, centralized reference datasets such as RefSeq and for private clinical and experimental data. PMID:29635394
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Bio-Docklets: virtualization containers for single-step execution of NGS pipelines
Kim, Baekdoo; Ali, Thahmina; Lijeron, Carlos; Afgan, Enis
2017-01-01
Abstract Processing of next-generation sequencing (NGS) data requires significant technical skills, involving installation, configuration, and execution of bioinformatics data pipelines, in addition to specialized postanalysis visualization and data mining software. In order to address some of these challenges, developers have leveraged virtualization containers toward seamless deployment of preconfigured bioinformatics software and pipelines on any computational platform. We present an approach for abstracting the complex data operations of multistep, bioinformatics pipelines for NGS data analysis. As examples, we have deployed 2 pipelines for RNA sequencing and chromatin immunoprecipitation sequencing, preconfigured within Docker virtualization containers we call Bio-Docklets. Each Bio-Docklet exposes a single data input and output endpoint and from a user perspective, running the pipelines as simply as running a single bioinformatics tool. This is achieved using a “meta-script” that automatically starts the Bio-Docklets and controls the pipeline execution through the BioBlend software library and the Galaxy Application Programming Interface. The pipeline output is postprocessed by integration with the Visual Omics Explorer framework, providing interactive data visualizations that users can access through a web browser. Our goal is to enable easy access to NGS data analysis pipelines for nonbioinformatics experts on any computing environment, whether a laboratory workstation, university computer cluster, or a cloud service provider. Beyond end users, the Bio-Docklets also enables developers to programmatically deploy and run a large number of pipeline instances for concurrent analysis of multiple datasets. PMID:28854616
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Rahpeyma, Mehdi; Fotouhi, Fatemeh; Makvandi, Manouchehr; Ghadiri, Ata; Samarbaf-Zadeh, Alireza
2015-01-01
Background Crimean-Congo hemorrhagic fever virus (CCHFV) is a member of the nairovirus, a genus in the Bunyaviridae family, which causes a life threatening disease in human. Currently, there is no vaccine against CCHFV and detailed structural analysis of CCHFV proteins remains undefined. The CCHFV M RNA segment encodes two viral surface glycoproteins known as Gn and Gc. Viral glycoproteins can be considered as key targets for vaccine development. Objectives The current study aimed to investigate structural bioinformatics of CCHFV Gn protein and design a construct to make a recombinant bacmid to express by baculovirus system. Materials and Methods To express the Gn protein in insect cells that can be used as antigen in animal model vaccine studies. Bioinformatic analysis of CCHFV Gn protein was performed and designed a construct and cloned into pFastBacHTb vector and a recombinant Gn-bacmid was generated by Bac to Bac system. Results Primary, secondary, and 3D structure of CCHFV Gn were obtained and PCR reaction with M13 forward and reverse primers confirmed the generation of recombinant bacmid DNA harboring Gn coding region under polyhedron promoter. Conclusions Characterization of the detailed structure of CCHFV Gn by bioinformatics software provides the basis for development of new experiments and construction of a recombinant bacmid harboring CCHFV Gn, which is valuable for designing a recombinant vaccine against deadly pathogens like CCHFV. PMID:26862379
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BioXSD: the common data-exchange format for everyday bioinformatics web services.
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.
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Wang, Qinghua; Arighi, Cecilia N; King, Benjamin L; Polson, Shawn W; Vincent, James; Chen, Chuming; Huang, Hongzhan; Kingham, Brewster F; Page, Shallee T; Rendino, Marc Farnum; Thomas, William Kelley; Udwary, Daniel W; Wu, Cathy H
2012-01-01
Recent advances in high-throughput DNA sequencing technologies have equipped biologists with a powerful new set of tools for advancing research goals. The resulting flood of sequence data has made it critically important to train the next generation of scientists to handle the inherent bioinformatic challenges. The North East Bioinformatics Collaborative (NEBC) is undertaking the genome sequencing and annotation of the little skate (Leucoraja erinacea) to promote advancement of bioinformatics infrastructure in our region, with an emphasis on practical education to create a critical mass of informatically savvy life scientists. In support of the Little Skate Genome Project, the NEBC members have developed several annotation workshops and jamborees to provide training in genome sequencing, annotation and analysis. Acting as a nexus for both curation activities and dissemination of project data, a project web portal, SkateBase (http://skatebase.org) has been developed. As a case study to illustrate effective coupling of community annotation with workforce development, we report the results of the Mitochondrial Genome Annotation Jamborees organized to annotate the first completely assembled element of the Little Skate Genome Project, as a culminating experience for participants from our three prior annotation workshops. We are applying the physical/virtual infrastructure and lessons learned from these activities to enhance and streamline the genome annotation workflow, as we look toward our continuing efforts for larger-scale functional and structural community annotation of the L. erinacea genome.
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Wang, Qinghua; Arighi, Cecilia N.; King, Benjamin L.; Polson, Shawn W.; Vincent, James; Chen, Chuming; Huang, Hongzhan; Kingham, Brewster F.; Page, Shallee T.; Farnum Rendino, Marc; Thomas, William Kelley; Udwary, Daniel W.; Wu, Cathy H.
2012-01-01
Recent advances in high-throughput DNA sequencing technologies have equipped biologists with a powerful new set of tools for advancing research goals. The resulting flood of sequence data has made it critically important to train the next generation of scientists to handle the inherent bioinformatic challenges. The North East Bioinformatics Collaborative (NEBC) is undertaking the genome sequencing and annotation of the little skate (Leucoraja erinacea) to promote advancement of bioinformatics infrastructure in our region, with an emphasis on practical education to create a critical mass of informatically savvy life scientists. In support of the Little Skate Genome Project, the NEBC members have developed several annotation workshops and jamborees to provide training in genome sequencing, annotation and analysis. Acting as a nexus for both curation activities and dissemination of project data, a project web portal, SkateBase (http://skatebase.org) has been developed. As a case study to illustrate effective coupling of community annotation with workforce development, we report the results of the Mitochondrial Genome Annotation Jamborees organized to annotate the first completely assembled element of the Little Skate Genome Project, as a culminating experience for participants from our three prior annotation workshops. We are applying the physical/virtual infrastructure and lessons learned from these activities to enhance and streamline the genome annotation workflow, as we look toward our continuing efforts for larger-scale functional and structural community annotation of the L. erinacea genome. PMID:22434832
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The Enzyme Portal: a case study in applying user-centred design methods in bioinformatics.
de Matos, Paula; Cham, Jennifer A; Cao, Hong; Alcántara, Rafael; Rowland, Francis; Lopez, Rodrigo; Steinbeck, Christoph
2013-03-20
User-centred design (UCD) is a type of user interface design in which the needs and desires of users are taken into account at each stage of the design process for a service or product; often for software applications and websites. Its goal is to facilitate the design of software that is both useful and easy to use. To achieve this, you must characterise users' requirements, design suitable interactions to meet their needs, and test your designs using prototypes and real life scenarios.For bioinformatics, there is little practical information available regarding how to carry out UCD in practice. To address this we describe a complete, multi-stage UCD process used for creating a new bioinformatics resource for integrating enzyme information, called the Enzyme Portal (http://www.ebi.ac.uk/enzymeportal). This freely-available service mines and displays data about proteins with enzymatic activity from public repositories via a single search, and includes biochemical reactions, biological pathways, small molecule chemistry, disease information, 3D protein structures and relevant scientific literature.We employed several UCD techniques, including: persona development, interviews, 'canvas sort' card sorting, user workflows, usability testing and others. Our hope is that this case study will motivate the reader to apply similar UCD approaches to their own software design for bioinformatics. Indeed, we found the benefits included more effective decision-making for design ideas and technologies; enhanced team-working and communication; cost effectiveness; and ultimately a service that more closely meets the needs of our target audience.
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Microbial bioinformatics for food safety and production
Alkema, Wynand; Boekhorst, Jos; Wels, Michiel
2016-01-01
In the production of fermented foods, microbes play an important role. Optimization of fermentation processes or starter culture production traditionally was a trial-and-error approach inspired by expert knowledge of the fermentation process. Current developments in high-throughput ‘omics’ technologies allow developing more rational approaches to improve fermentation processes both from the food functionality as well as from the food safety perspective. Here, the authors thematically review typical bioinformatics techniques and approaches to improve various aspects of the microbial production of fermented food products and food safety. PMID:26082168
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Using EMBL-EBI services via Web interface and programmatically via Web Services
Lopez, Rodrigo; Cowley, Andrew; Li, Weizhong; McWilliam, Hamish
2015-01-01
The European Bioinformatics Institute (EMBL-EBI) provides access to a wide range of databases and analysis tools that are of key importance in bioinformatics. As well as providing Web interfaces to these resources, Web Services are available using SOAP and REST protocols that enable programmatic access to our resources and allow their integration into other applications and analytical workflows. This unit describes the various options available to a typical researcher or bioinformatician who wishes to use our resources via Web interface or programmatically via a range of programming languages. PMID:25501941
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Translational Biomedical Informatics in the Cloud: Present and Future
Chen, Jiajia; Qian, Fuliang; Yan, Wenying; Shen, Bairong
2013-01-01
Next generation sequencing and other high-throughput experimental techniques of recent decades have driven the exponential growth in publicly available molecular and clinical data. This information explosion has prepared the ground for the development of translational bioinformatics. The scale and dimensionality of data, however, pose obvious challenges in data mining, storage, and integration. In this paper we demonstrated the utility and promise of cloud computing for tackling the big data problems. We also outline our vision that cloud computing could be an enabling tool to facilitate translational bioinformatics research. PMID:23586054
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Biopython: freely available Python tools for computational molecular biology and bioinformatics.
Cock, Peter J A; Antao, Tiago; Chang, Jeffrey T; Chapman, Brad A; Cox, Cymon J; Dalke, Andrew; Friedberg, Iddo; Hamelryck, Thomas; Kauff, Frank; Wilczynski, Bartek; de Hoon, Michiel J L
2009-06-01
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. Biopython is freely available, with documentation and source code at (www.biopython.org) under the Biopython license.
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Modern Computational Techniques for the HMMER Sequence Analysis
2013-01-01
This paper focuses on the latest research and critical reviews on modern computing architectures, software and hardware accelerated algorithms for bioinformatics data analysis with an emphasis on one of the most important sequence analysis applications—hidden Markov models (HMM). We show the detailed performance comparison of sequence analysis tools on various computing platforms recently developed in the bioinformatics society. The characteristics of the sequence analysis, such as data and compute-intensive natures, make it very attractive to optimize and parallelize by using both traditional software approach and innovated hardware acceleration technologies. PMID:25937944
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KMC 3: counting and manipulating k-mer statistics.
Kokot, Marek; Dlugosz, Maciej; Deorowicz, Sebastian
2017-09-01
Counting all k -mers in a given dataset is a standard procedure in many bioinformatics applications. We introduce KMC3, a significant improvement of the former KMC2 algorithm together with KMC tools for manipulating k -mer databases. Usefulness of the tools is shown on a few real problems. Program is freely available at http://sun.aei.polsl.pl/REFRESH/kmc . sebastian.deorowicz@polsl.pl. 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
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PatGen--a consolidated resource for searching genetic patent sequences.
Rouse, Richard J D; Castagnetto, Jesus; Niedner, Roland H
2005-04-15
Compared to the wealth of online resources covering genomic, proteomic and derived data the Bioinformatics community is rather underserved when it comes to patent information related to biological sequences. The current online resources are either incomplete or rather expensive. This paper describes, PatGen, an integrated database containing data from bioinformatic and patent resources. This effort addresses the inconsistency of publicly available genetic patent data coverage by providing access to a consolidated dataset. PatGen can be searched at http://www.patgendb.com rjdrouse@patentinformatics.com.
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NASA Astrophysics Data System (ADS)
Kintsakis, Athanassios M.; Psomopoulos, Fotis E.; Symeonidis, Andreas L.; Mitkas, Pericles A.
Hermes introduces a new "describe once, run anywhere" paradigm for the execution of bioinformatics workflows in hybrid cloud environments. It combines the traditional features of parallelization-enabled workflow management systems and of distributed computing platforms in a container-based approach. It offers seamless deployment, overcoming the burden of setting up and configuring the software and network requirements. Most importantly, Hermes fosters the reproducibility of scientific workflows by supporting standardization of the software execution environment, thus leading to consistent scientific workflow results and accelerating scientific output.
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Multiobjective optimization in bioinformatics and computational biology.
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.
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Promoting synergistic research and education in genomics and bioinformatics.
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 scientific achievements by bridging these two very important disciplines into an interactive and attractive forum. Keeping this objective in mind, Biocomp 2007 aims to promote interdisciplinary and multidisciplinary education and research. 25 high quality peer-reviewed papers were selected from 400+ submissions for this supplementary issue of BMC Genomics. Those papers contributed to a wide-range of important research fields including gene expression data analysis and applications, high-throughput genome mapping, sequence analysis, gene regulation, protein structure prediction, disease prediction by machine learning techniques, systems biology, database and biological software development. We always encourage participants submitting proposals for genomics sessions, special interest research sessions, workshops and tutorials to Professor Hamid R. Arabnia (hra@cs.uga.edu) in order to ensure that Biocomp continuously plays the leadership role in promoting inter/multidisciplinary research and education in the fields. Biocomp received top conference ranking with a high score of 0.95/1.00. Biocomp is academically co-sponsored by the International Society of Intelligent Biological Medicine and the Research Laboratories and Centers of Harvard University--Massachusetts Institute of Technology, Indiana University--Purdue University, Georgia Tech--Emory University, UIUC, UCLA, Columbia University, University of Texas at Austin and University of Iowa etc. Biocomp--Worldcomp brings leading scientists together across the nation and all over the world and aims to promote synergistic components such as keynote lectures, special interest sessions, workshops and tutorials in response to the advances of cutting-edge research.
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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 manipulation of sequences, alignments, and phylogenetic trees, unavailable in existing utilities (e.g., EMBOSS, Newick Utilities, and FAST), are provided. Bioinformaticians should find BpWrapper useful for rapid prototyping of workflows on the command-line without creating custom scripts for comparative genomics and other bioinformatics applications.
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Biowep: a workflow enactment portal for bioinformatics applications.
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 effective workflows can significantly improve automation of in-silico analysis. Biowep is available for interested researchers as a reference portal. They are invited to submit their workflows to the workflow repository. Biowep is further being developed in the sphere of the Laboratory of Interdisciplinary Technologies in Bioinformatics - LITBIO.
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Biowep: a workflow enactment portal for bioinformatics applications
Romano, Paolo; Bartocci, Ezio; Bertolini, Guglielmo; De Paoli, Flavio; Marra, Domenico; Mauri, Giancarlo; Merelli, Emanuela; Milanesi, Luciano
2007-01-01
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 databases and analysis software and the creation of effective workflows can significantly improve automation of in-silico analysis. Biowep is available for interested researchers as a reference portal. They are invited to submit their workflows to the workflow repository. Biowep is further being developed in the sphere of the Laboratory of Interdisciplinary Technologies in Bioinformatics – LITBIO. PMID:17430563
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Trindade, Fábio; Ferreira, Rita; Magalhães, Beatriz; Leite-Moreira, Adelino; Falcão-Pires, Inês; Vitorino, Rui
2018-01-16
Nowadays we are surrounded by a plethora of bioinformatics tools, powerful enough to deal with the large amounts of data arising from proteomic studies, but whose application is sometimes hard to find. Therefore, we used a specific clinical problem - to discriminate pathophysiology and potential biomarkers between two similar cardiovascular diseases, aortic valve stenosis (AVS) and coronary artery disease (CAD) - to make a step-by-step guide through four bioinformatics tools: STRING, DisGeNET, Cytoscape and ClueGO. Proteome data was collected from articles available on PubMed centered on proteomic studies enrolling subjects with AVS or CAD. Through the analysis of gene ontology provided by STRING and ClueGO we could find specific biological phenomena associated with AVS, such as down-regulation of elastic fiber assembly, and with CAD, such as up-regulation of plasminogen activation. Moreover, through Cytoscape and DisGeNET we could pinpoint surrogate markers either for AVS (e.g. popeye domain containing protein 2 and 28S ribosomal protein S36, mitochondrial) or for CAD (e.g. ankyrin repeat and SOCS box protein 7) which deserve future validation. Data recycling and integration as well as research orientation are among the main advantages of resorting to bioinformatics analysis, hence these tutorials can be of great convenience for proteomics investigators. As we saw for aortic valve stenosis and coronary artery disease, it can be of great relevance to perform preliminary bioinformatics analysis with already published proteomics data. It not only saves us time in the lab (avoiding work duplication) as it points out new hypothesis to explain the phenotypical presentation of the diseases as well as new surrogate markers with clinical relevance, deserving future scrutiny. These essential steps can be easily overcome if one follows the steps proposed in our tutorial for STRING, DisGeNET, Cytoscape and ClueGO utilization. Copyright © 2017 Elsevier B.V. All rights reserved.
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NASA Astrophysics Data System (ADS)
Serve, Kinta M.
Part I. Pleural fibrosis, a non-malignant, asbestos-related respiratory disease characterized by excessive collagen deposition, is progressive, debilitating, and potentially fatal. Disease severity may be influenced by the type of asbestos fiber inhaled, with Libby amphibole (LA) a seemingly more potent mediator of pleural fibrosis than chrysotile (CH) asbestos. This difference in severity may be due to the reported immunological component associated with LA but not CH related diseases. Here, we report the potential mechanisms by which asbestos-associated mesothelial cell autoantibodies (MCAAs) contribute to pleural fibrosis development. MCAAs are shown to bind cultured human pleural mesothelial cells and induce the deposition of type I collagen proteins in the absence of phenotypic changes typically associated with fibrosis development. However, additional extracellular proteins seem to differentially contribute to LA and CH MCAA-associated collagen deposition. Our data also suggest that IgG subclass distributions differ between LA and CH MCAAs, potentially altering the antibody effector functions. Differences in MCAA mechanisms of action and effector functions may help explain the disparate clinical disease phenotypes noted between LA and CH-exposed populations and may provide insights for development of novel therapeutic strategies. Part II. As scientific research becomes increasingly reliant on computational tools, it is more important than ever before to train students to use these tools. While educators agree that biology students should gain experience with bioinformatics, there exists no consensus as to how to integrate these concepts into the already demanding undergraduate curriculum. The Portal-21 project offers a solution by utilizing on-line learning case studies to allow flexibility for classroom integration. Presented here are the results from two field tests of a case study developed to introduce the common bioinformatics tools pBLAST and PubMed to undergraduate students while reinforcing concepts of protein function. Data suggest positive gains in student learning and confidence with using bioinformatics tools following use of the case study. These results indicate that on-line case studies are a useful tool for introducing bioinformatics into undergraduate classrooms.
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Jiang, Xiao-Sheng; Dai, Jie; Sheng, Quan-Hu; Zhang, Lei; Xia, Qi-Chang; Wu, Jia-Rui; Zeng, Rong
2005-01-01
Subcellular proteomics, as an important step to functional proteomics, has been a focus in proteomic research. However, the co-purification of "contaminating" proteins has been the major problem in all the subcellular proteomic research including all kinds of mitochondrial proteome research. It is often difficult to conclude whether these "contaminants" represent true endogenous partners or artificial associations induced by cell disruption or incomplete purification. To solve such a problem, we applied a high-throughput comparative proteome experimental strategy, ICAT approach performed with two-dimensional LC-MS/MS analysis, coupled with combinational usage of different bioinformatics tools, to study the proteome of rat liver mitochondria prepared with traditional centrifugation (CM) or further purified with a Nycodenz gradient (PM). A total of 169 proteins were identified and quantified convincingly in the ICAT analysis, in which 90 proteins have an ICAT ratio of PM:CM>1.0, while another 79 proteins have an ICAT ratio of PM:CM<1.0. Almost all the proteins annotated as mitochondrial according to Swiss-Prot annotation, bioinformatics prediction, and literature reports have a ratio of PM:CM>1.0, while proteins annotated as extracellular or secreted, cytoplasmic, endoplasmic reticulum, ribosomal, and so on have a ratio of PM:CM<1.0. Catalase and AP endonuclease 1, which have been known as peroxisomal and nuclear, respectively, have shown a ratio of PM:CM>1.0, confirming the reports about their mitochondrial location. Moreover, the 125 proteins with subcellular location annotation have been used as a testing dataset to evaluate the efficiency for ascertaining mitochondrial proteins by ICAT analysis and the bioinformatics tools such as PSORT, TargetP, SubLoc, MitoProt, and Predotar. The results indicated that ICAT analysis coupled with combinational usage of different bioinformatics tools could effectively ascertain mitochondrial proteins and distinguish contaminant proteins and even multilocation proteins. Using such a strategy, many novel proteins, known proteins without subcellular location annotation, and even known proteins that have been annotated as other locations have been strongly indicated for their mitochondrial location.