Baldi, Pierre; Brunak, Søren
medicine will be particularly affected by the new results and the increased understanding of life at the molecular level. Bioinformatics is the development and application of computer methods for analysis, interpretation, and prediction, as well as for the design of experiments. It has emerged as a...
As a newborn interdisciplinary field, bioinformatics is receiving increasing attention from biologists, computer scientists, statisticians, mathematicians and engineers. This paper briefly introduces the birth, importance, and extensive applications of bioinformatics in the different fields of biological research. A major challenge in bioinformatics - the unraveling of gene regulation - is discussed in detail.
Min, Seonwoo; Lee, Byunghan; Yoon, Sungroh
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 res...
Thampi, Sabu M.
Bioinformatics is a new discipline that addresses the need to manage and interpret the data that in the past decade was massively generated by genomic research. This discipline represents the convergence of genomics, biotechnology and information technology, and encompasses analysis and interpretation of data, modeling of biological phenomena, and development of algorithms and statistics. This article presents an introduction to bioinformatics
Mitchell John; Murray-Rust Peter; Rzepa Henry
Abstract 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 auth...
Full Text Available Abstract 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.
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…
Wang, May Dongmei
During 2012, next generation sequencing (NGS) has attracted great attention in the biomedical research community, especially for personalized medicine. Also, third generation sequencing has become available. Therefore, state-of-art sequencing technology and analysis are reviewed in this Bioinformatics spotlight on 2012. Next-generation sequencing (NGS) is high-throughput nucleic acid sequencing technology with wide dynamic range and single base resolution. The full promise of NGS depends on the optimization of NGS platforms, sequence alignment and assembly algorithms, data analytics, novel algorithms for integrating NGS data with existing genomic, proteomic, or metabolomic data, and quantitative assessment of NGS technology in comparing to more established technologies such as microarrays. NGS technology has been predicated to become a cornerstone of personalized medicine. It is argued that NGS is a promising field for motivated young researchers who are looking for opportunities in bioinformatics. PMID:23192635
Johnson, Kathy A.
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.
Cohen-Boulakia, Sarah; Valduriez, Patrick
The volumes of bioinformatics data available on the Web are constantly increasing.Access and joint exploitation of these highly distributed data (i.e, available in distributed Webdata sources) and highly heterogeneous (in text or tabulated les including images, in dierentformats, described with dierent levels of detail and dierent levels of quality ...) is essential forthe biological knowledge to progress. The purpose of this short report is to present in a simpleway the problems of the joint...
Burr, Tom L [Los Alamos National Laboratory
Genetic data is often used to infer evolutionary relationships among a collection of viruses, bacteria, animal or plant species, or other operational taxonomic units (OTU). A phylogenetic tree depicts such relationships and provides a visual representation of the estimated branching order of the OTUs. Tree estimation is unique for several reasons, including: the types of data used to represent each OTU; the use ofprobabilistic nucleotide substitution models; the inference goals involving both tree topology and branch length, and the huge number of possible trees for a given sample of a very modest number of OTUs, which implies that fmding the best tree(s) to describe the genetic data for each OTU is computationally demanding. Bioinformatics is too large a field to review here. We focus on that aspect of bioinformatics that includes study of similarities in genetic data from multiple OTUs. Although research questions are diverse, a common underlying challenge is to estimate the evolutionary history of the OTUs. Therefore, this paper reviews the role of phylogenetic tree estimation in bioinformatics, available methods and software, and identifies areas for additional research and development.
Full Text Available Flow cytometry bioinformatics is the application of bioinformatics to flow cytometry data, which involves storing, retrieving, organizing, and analyzing flow cytometry data using extensive computational resources and tools. Flow cytometry bioinformatics requires extensive use of and contributes to the development of techniques from computational statistics and machine learning. Flow cytometry and related methods allow the quantification of multiple independent biomarkers on large numbers of single cells. The rapid growth in the multidimensionality and throughput of flow cytometry data, particularly in the 2000s, has led to the creation of a variety of computational analysis methods, data standards, and public databases for the sharing of results. Computational methods exist to assist in the preprocessing of flow cytometry data, identifying cell populations within it, matching those cell populations across samples, and performing diagnosis and discovery using the results of previous steps. For preprocessing, this includes compensating for spectral overlap, transforming data onto scales conducive to visualization and analysis, assessing data for quality, and normalizing data across samples and experiments. For population identification, tools are available to aid traditional manual identification of populations in two-dimensional scatter plots (gating, to use dimensionality reduction to aid gating, and to find populations automatically in higher dimensional space in a variety of ways. It is also possible to characterize data in more comprehensive ways, such as the density-guided binary space partitioning technique known as probability binning, or by combinatorial gating. Finally, diagnosis using flow cytometry data can be aided by supervised learning techniques, and discovery of new cell types of biological importance by high-throughput statistical methods, as part of pipelines incorporating all of the aforementioned methods. Open standards, data
Bioinformatics is an emerging interdisciplinary research field in which mathematics. computer science and biology meet. In this thesis. bioinformatic methods for analysis of functional and structural properties among proteins will be presented. I have developed and applied bioinformatic methods on the enzyme superfamily of short-chain dehydrogenases/reductases (SDRs), coenzyme-binding enzymes of the Rossmann fold type, and amyloid-forming proteins and peptides. The basis...
Kim, Ju Han
Bioinformatics is a rapidly emerging field of biomedical research. A flood of large-scale genomic and postgenomic data means that many of the challenges in biomedical research are now challenges in computational science. Clinical informatics has long developed methodologies to improve biomedical research and clinical care by integrating experimental and clinical information systems. The informatics revolution in both bioinformatics and clinical informatics will eventually change the current practice of medicine, including diagnostics, therapeutics, and prognostics. Postgenome informatics, powered by high-throughput technologies and genomic-scale databases, is likely to transform our biomedical understanding forever, in much the same way that biochemistry did a generation ago. This paper describes how these technologies will impact biomedical research and clinical care, emphasizing recent advances in biochip-based functional genomics and proteomics. Basic data preprocessing with normalization and filtering, primary pattern analysis, and machine-learning algorithms are discussed. Use of integrative biochip informatics technologies, including multivariate data projection, gene-metabolic pathway mapping, automated biomolecular annotation, text mining of factual and literature databases, and the integrated management of biomolecular databases, are also discussed. PMID:12544491
Tolvanen, Martti; Vihinen, Mauno
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…
@@ With the completion of human genome sequencing, a new era of bioinformatics st arts. On one hand, due to the advance of high throughput DNA microarray technol ogies, functional genomics such as gene expression information has increased exp onentially and will continue to do so for the foreseeable future. Conventional m eans of storing, analysing and comparing related data are already overburdened. Moreover, the rich information in genes , their functions and their associated wide biological implication requires new technologies of analysing data that employ sophisticated statistical and machine learning algorithms, powerful com puters and intensive interaction together different data sources such as seque nce data, gene expression data, proteomics data and metabolic pathway informati on to discover complex genomic structures and functional patterns with other bi ological process to gain a comprehensive understanding of cell physiology.
Emergent Computation is concerned with recent applications of Mathematical Linguistics or Automata Theory. This subject has a primary focus upon "Bioinformatics" (the Genome and arising interest in the Proteome), but the closing chapter also examines applications in Biology, Medicine, Anthropology, etc. The book is composed of an organized examination of DNA, RNA, and the assembly of amino acids into proteins. Rather than examine these areas from a purely mathematical viewpoint (that excludes much of the biochemical reality), the author uses scientific papers written mostly by biochemists based upon their laboratory observations. Thus while DNA may exist in its double stranded form, triple stranded forms are not excluded. Similarly, while bases exist in Watson-Crick complements, mismatched bases and abasic pairs are not excluded, nor are Hoogsteen bonds. Just as there are four bases naturally found in DNA, the existence of additional bases is not ignored, nor amino acids in addition to the usual complement of...
Abouelhoda, Mohamed; Ghanem, Moustafa
Sequence analysis is a major area in bioinformatics encompassing the methods and techniques for studying the biological sequences, DNA, RNA, and proteins, on the linear structure level. The focus of this area is generally on the identification of intra- and inter-molecular similarities. Identifying intra-molecular similarities boils down to detecting repeated segments within a given sequence, while identifying inter-molecular similarities amounts to spotting common segments among two or multiple sequences. From a data mining point of view, sequence analysis is nothing but string- or pattern mining specific to biological strings. For a long time, this point of view, however, has not been explicitly embraced neither in the data mining nor in the sequence analysis text books, which may be attributed to the co-evolution of the two apparently independent fields. In other words, although the word "data-mining" is almost missing in the sequence analysis literature, its basic concepts have been implicitly applied. Interestingly, recent research in biological sequence analysis introduced efficient solutions to many problems in data mining, such as querying and analyzing time series [49,53], extracting information from web pages , fighting spam mails , detecting plagiarism , and spotting duplications in software systems .
Pallen, Mark J
Microbial bioinformatics in 2020 will remain a vibrant, creative discipline, adding value to the ever-growing flood of new sequence data, while embracing novel technologies and fresh approaches. Databases and search strategies will struggle to cope and manual curation will not be sustainable during the scale-up to the million-microbial-genome era. Microbial taxonomy will have to adapt to a situation in which most microorganisms are discovered and characterised through the analysis of sequences. Genome sequencing will become a routine approach in clinical and research laboratories, with fresh demands for interpretable user-friendly outputs. The "internet of things" will penetrate healthcare systems, so that even a piece of hospital plumbing might have its own IP address that can be integrated with pathogen genome sequences. Microbiome mania will continue, but the tide will turn from molecular barcoding towards metagenomics. Crowd-sourced analyses will collide with cloud computing, but eternal vigilance will be the price of preventing the misinterpretation and overselling of microbial sequence data. Output from hand-held sequencers will be analysed on mobile devices. Open-source training materials will address the need for the development of a skilled labour force. As we boldly go into the third decade of the twenty-first century, microbial sequence space will remain the final frontier! PMID:27471065
Global computing, the collaboration of idle PCs via the Internet in a SETI@home style, emerges as a new way of massive parallel multiprocessing with potentially enormous CPU power. Its relations to the broader, fast-moving field of Grid computing are discussed without attempting a review of the latter. This review (i) includes a short table of milestones in global computing history, (ii) lists opportunities global computing offers for bioinformatics, (iii) describes the structure of problems well suited for such an approach, (iv) analyses the anatomy of successful projects and (v) points to existing software frameworks. Finally, an evaluation of the various costs shows that global computing indeed has merit, if the problem to be solved is already coded appropriately and a suitable global computing framework can be found. Then, either significant amounts of computing power can be recruited from the general public, or--if employed in an enterprise-wide Intranet for security reasons--idle desktop PCs can substitute for an expensive dedicated cluster. PMID:12511066
Lawlor, Brendan; Walsh, Paul
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
Muhammad Ali Masood
Full Text Available Dealing with data means to group information into a set of categories either in order to learn new artifacts or understand new domains. For this purpose researchers have always looked for the hidden patterns in data that can be defined and compared with other known notions based on the similarity or dissimilarity of their attributes according to well-defined rules. Data mining, having the tools of data classification and data clustering, is one of the most powerful techniques to deal with data in such a manner that it can help researchers identify the required information. As a step forward to address this challenge, experts have utilized clustering techniques as a mean of exploring hidden structure and patterns in underlying data. Improved stability, robustness and accuracy of unsupervised data classification in many fields including pattern recognition, machine learning, information retrieval, image analysis and bioinformatics, clustering has proven itself as a reliable tool. To identify the clusters in datasets algorithm are utilized to partition data set into several groups based on the similarity within a group. There is no specific clustering algorithm, but various algorithms are utilized based on domain of data that constitutes a cluster and the level of efficiency required. Clustering techniques are categorized based upon different approaches. This paper is a survey of few clustering techniques out of many in data mining. For the purpose five of the most common clustering techniques out of many have been discussed. The clustering techniques which have been surveyed are: K-medoids, K-means, Fuzzy C-means, Density-Based Spatial Clustering of Applications with Noise (DBSCAN and Self-Organizing Map (SOM clustering.
This article highlights some of the basic concepts of bioinformatics and data mining. The major research areas of bioinformatics are highlighted. The application of data mining in the domain of bioinformatics is explained. It also highlights some of the current challenges and opportunities of data mining in bioinformatics.
Schneider, Maria V.; Walter, Peter; Blatter, Marie-Claude;
to the development of ‘high-throughput biology’, the need for training in the field of bioinformatics, in particular, is seeing a resurgence: it has been defined as a key priority by many Institutions and research programmes and is now an important component of many grant proposals. Nevertheless, when it comes...... and clearly tagged in relation to target audiences, learning objectives, etc. Ideally, they would also be peer reviewed, and easily and efficiently accessible for downloading. Here, we present the Bioinformatics Training Network (BTN), a new enterprise that has been initiated to address these needs and review...
Bartlett, Andrew; Lewis, Jamie; Williams, Matthew L.
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
Weber, Tilmann; Kim, Hyun Uk
. In this context, this review gives a summary of tools and databases that currently are available to mine, identify and characterize natural product biosynthesis pathways and their producers based on ‘omics data. A web portal called Secondary Metabolite Bioinformatics Portal (SMBP at http...
Elwess, Nancy L.; Latourelle, Sandra M.; Cauthorn, Olivia
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…
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...
Maloney, Mark; Parker, Jeffrey; LeBlanc, Mark; Woodard, Craig T.; Glackin, Mary; Hanrahan, Michael
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…
Bioinformatics is a usage of information technology to help solve biological problems by designing novel and in-cisive algorithms and methods of analyses.Bioinformatics becomes a discipline vital in the era of post-genom-ics.In this review article,the application of bioinformatics in tropical medicine will be presented and dis-cussed.
Tammi Martti; Ranganathan Shoba; Gribskov Michael; Tan Tin Wee
Abstract In 1998, the Asia Pacific Bioinformatics Network (APBioNet), Asia's oldest bioinformatics organisation was set up to champion the advancement of bioinformatics in the Asia Pacific. By 2002, APBioNet was able to gain sufficient critical mass to initiate the first International Conference on Bioinformatics (InCoB) bringing together scientists working in the field of bioinformatics in the region. This year, the InCoB2006 Conference was organized as the 5th annual conference of the Asia-...
Schweighofer, Karl; Pohorille, Andrew
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.
Thomas K Karikari
Full Text Available Until recently, bioinformatics, an important discipline in the biological sciences, was largely limited to countries with advanced scientific resources. Nonetheless, several developing countries have lately been making progress in bioinformatics training and applications. In Africa, leading countries in the discipline include South Africa, Nigeria, and Kenya. However, one country that is less known when it comes to bioinformatics is Ghana. Here, I provide a first description of the development of bioinformatics activities in Ghana and how these activities contribute to the overall development of the discipline in Africa. Over the past decade, scientists in Ghana have been involved in publications incorporating bioinformatics analyses, aimed at addressing research questions in biomedical science and agriculture. Scarce research funding and inadequate training opportunities are some of the challenges that need to be addressed for Ghanaian scientists to continue developing their expertise in bioinformatics.
Full Text Available Abstract In 1998, the Asia Pacific Bioinformatics Network (APBioNet, Asia's oldest bioinformatics organisation was set up to champion the advancement of bioinformatics in the Asia Pacific. By 2002, APBioNet was able to gain sufficient critical mass to initiate the first International Conference on Bioinformatics (InCoB bringing together scientists working in the field of bioinformatics in the region. This year, the InCoB2006 Conference was organized as the 5th annual conference of the Asia-Pacific Bioinformatics Network, on Dec. 18–20, 2006 in New Delhi, India, following a series of successful events in Bangkok (Thailand, Penang (Malaysia, Auckland (New Zealand and Busan (South Korea. This Introduction provides a brief overview of the peer-reviewed manuscripts accepted for publication in this Supplement. It exemplifies a typical snapshot of the growing research excellence in bioinformatics of the region as we embark on a trajectory of establishing a solid bioinformatics research culture in the Asia Pacific that is able to contribute fully to the global bioinformatics community.
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…
Torres, Angela; Nieto, Juan J.
The purpose of this paper is to present a general view of the current applications of fuzzy logic in medicine and bioinformatics. We particularly review the medical literature using fuzzy logic. We then recall the geometrical interpretation of fuzzy sets as points in a fuzzy hypercube and present two concrete illustrations in medicine (drug addictions) and in bioinformatics (comparison of genomes).
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 RLK) genetic…
Heyer, Laurie J.
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…
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.
Zhong, Yang; Zhang, Xiaoyan; Ma, Jian; Zhang, Liang
As the Human Genome Project experiences remarkable success and a flood of biological data is produced, bioinformatics becomes a very "hot" cross-disciplinary field, yet experienced bioinformaticians are urgently needed worldwide. This paper summarises the rapid development of bioinformatics education in China, especially related undergraduate…
Full Text Available Abstract As advances in life sciences and information technology bring profound influences on bioinformatics due to its interdisciplinary nature, bioinformatics is experiencing a new leap-forward from in-house computing infrastructure into utility-supplied cloud computing delivered over the Internet, in order to handle the vast quantities of biological data generated by high-throughput experimental technologies. Albeit relatively new, cloud computing promises to address big data storage and analysis issues in the bioinformatics field. Here we review extant cloud-based services in bioinformatics, classify them into Data as a Service (DaaS, Software as a Service (SaaS, Platform as a Service (PaaS, and Infrastructure as a Service (IaaS, and present our perspectives on the adoption of cloud computing in bioinformatics. Reviewers This article was reviewed by Frank Eisenhaber, Igor Zhulin, and Sandor Pongor.
As advances in life sciences and information technology bring profound influences on bioinformatics due to its interdisciplinary nature, bioinformatics is experiencing a new leap-forward from in-house computing infrastructure into utility-supplied cloud computing delivered over the Internet, in order to handle the vast quantities of biological data generated by high-throughput experimental technologies. Albeit relatively new, cloud computing promises to address big data storage and analysis issues in the bioinformatics field. Here we review extant cloud-based services in bioinformatics, classify them into Data as a Service (DaaS), Software as a Service (SaaS), Platform as a Service (PaaS), and Infrastructure as a Service (IaaS), and present our perspectives on the adoption of cloud computing in bioinformatics.This article was reviewed by Frank Eisenhaber, Igor Zhulin, and Sandor Pongor. 2012 Dai et al.; licensee BioMed Central Ltd.
Segun A Fatumo
Full Text Available Over the past few decades, major advances in the field of molecular biology, coupled with advances in genomic technologies, have led to an explosive growth in the biological data generated by the scientific community. The critical need to process and analyze such a deluge of data and turn it into useful knowledge has caused bioinformatics to gain prominence and importance. Bioinformatics is an interdisciplinary research area that applies techniques, methodologies, and tools in computer and information science to solve biological problems. In Nigeria, bioinformatics has recently played a vital role in the advancement of biological sciences. As a developing country, the importance of bioinformatics is rapidly gaining acceptance, and bioinformatics groups comprised of biologists, computer scientists, and computer engineers are being constituted at Nigerian universities and research institutes. In this article, we present an overview of bioinformatics education and research in Nigeria. We also discuss professional societies and academic and research institutions that play central roles in advancing the discipline in Nigeria. Finally, we propose strategies that can bolster bioinformatics education and support from policy makers in Nigeria, with potential positive implications for other developing countries.
Sirintrapun, S Joseph; Zehir, Ahmet; Syed, Aijazuddin; Gao, JianJiong; Schultz, Nikolaus; Cheng, Donavan T
Translational bioinformatics and clinical research (biomedical) informatics are the primary domains related to informatics activities that support translational research. Translational bioinformatics focuses on computational techniques in genetics, molecular biology, and systems biology. Clinical research (biomedical) informatics involves the use of informatics in discovery and management of new knowledge relating to health and disease. This article details 3 projects that are hybrid applications of translational bioinformatics and clinical research (biomedical) informatics: The Cancer Genome Atlas, the cBioPortal for Cancer Genomics, and the Memorial Sloan Kettering Cancer Center clinical variants and results database, all designed to facilitate insights into cancer biology and clinical/therapeutic correlations. PMID:26851671
Gorodkin, Jan; Hofacker, Ivo L.; Ruzzo, Walter L.
RNA bioinformatics and computational RNA biology have emerged from implementing methods for predicting the secondary structure of single sequences. The field has evolved to exploit multiple sequences to take evolutionary information into account, such as compensating (and structure preserving) base...
Mudasser Fraz Wyne
Full Text Available Bioinformatics is a new field that is poorly served by any of the traditional science programs in Biology, Computer science or Biochemistry. Known to be a rapidly evolving discipline, Bioinformatics has emerged from experimental molecular biology and biochemistry as well as from the artificial intelligence, database, pattern recognition, and algorithms disciplines of computer science. While institutions are responding to this increased demand by establishing graduate programs in bioinformatics, entrance barriers for these programs are high, largely due to the significant prerequisite knowledge which is required, both in the fields of biochemistry and computer science. Although many schools currently have or are proposing graduate programs in bioinformatics, few are actually developing new undergraduate programs. In this paper I explore the blend of a multidisciplinary approach, discuss the response of academia and highlight challenges faced by this emerging field.
Systems integration is becoming the driving force for 21st century biology. Researchers are systematically tackling gene functions and complex regulatory processes by studying organisms at different levels of organization, from genomes and transcriptomes to proteomes and interactomes. To fully realize the value of such high-throughput data requires advanced bioinformatics for integration, mining, comparative analysis, and functional interpretation. We are developing a bioinformatics research ...
Dai Lin; Gao Xin; Guo Yan; Xiao Jingfa; Zhang Zhang
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 a...
Huang, Xiuzhen; Bruce, Barry; Buchan, Alison; Congdon, Clare Bates; Cramer, Carole L.; Jennings, Steven F; Jiang, Hongmei; Li, Zenglu; McClure, Gail; McMullen, Rick; Moore, Jason H.; Nanduri, Bindu; Peckham, Joan; Perkins, Andy; Polson, Shawn W.
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).
Ghulam A. PARRAY; Abdul G. Rather; Parvez Sofi; Shafiq A. Wani; Amjad M. Husaini; Asif B. Shikari; Javid I. Mir
Saffron (Crocus sativus L.) is a sterile triploid plant and belongs to the Iridaceae (Liliales, Monocots). Its genome is of relatively large size and is poorly characterized. Bioinformatics can play an enormous technical role in the sequence-level structural characterization of saffron genomic DNA. Bioinformatics tools can also help in appreciating the extent of diversity of various geographic or genetic groups of cultivated saffron to infer relationships between groups and accessions. The ch...
Tanaka Masahiro; Sasaki Kensaku; Mishima Hiroyuki; Tatebe Osamu; Yoshiura Koh-ichiro
Abstract 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 environm...
Full Text Available The drastic increase in the number of coronaviruses discovered and coronavirus genomes being sequenced have given us an unprecedented opportunity to perform genomics and bioinformatics analysis on this family of viruses. Coronaviruses possess the largest genomes (26.4 to 31.7 kb among all known RNA viruses, with G + C contents varying from 32% to 43%. Variable numbers of small ORFs are present between the various conserved genes (ORF1ab, spike, envelope, membrane and nucleocapsid and downstream to nucleocapsid gene in different coronavirus lineages. Phylogenetically, three genera, Alphacoronavirus, Betacoronavirus and Gammacoronavirus, with Betacoronavirus consisting of subgroups A, B, C and D, exist. A fourth genus, Deltacoronavirus, which includes bulbul coronavirus HKU11, thrush coronavirus HKU12 and munia coronavirus HKU13, is emerging. Molecular clock analysis using various gene loci revealed that the time of most recent common ancestor of human/civet SARS related coronavirus to be 1999-2002, with estimated substitution rate of 4´10-4 to 2´10-2 substitutions per site per year. Recombination in coronaviruses was most notable between different strains of murine hepatitis virus (MHV, between different strains of infectious bronchitis virus, between MHV and bovine coronavirus, between feline coronavirus (FCoV type I and canine coronavirus generating FCoV type II, and between the three genotypes of human coronavirus HKU1 (HCoV-HKU1. Codon usage bias in coronaviruses were observed, with HCoV-HKU1 showing the most extreme bias, and cytosine deamination and selection of CpG suppressed clones are the two major independent biological forces that shape such codon usage bias in coronaviruses.
Lu, Qiang; Hao, Pei; Curcin, Vasa; He, Weizhong; Li, Yuan-Yuan; Luo, Qing-Ming; Guo, Yi-Ke; Li, Yi-Xue
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. PMID:16260186
The thesis focuses on two bioinformatics research topics: the development of tools for an efficient and reliable identification of single nucleotides polymorphisms (SNPs) and polymorphic simple sequence repeats (SSRs) from expressed sequence tags (ESTs) (Chapter 2, 3 and 4), and the subsequent imple
Neerincx, P.B.T.; Leunissen, J.A.M.
Bioinformaticians have developed large collections of tools to make sense of the rapidly growing pool of molecular biological data. Biological systems tend to be complex and in order to understand them, it is often necessary to link many data sets and use more than one tool. Therefore, bioinformatic
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...
Kelley, Scott; Alger, Christianna; Deutschman, Douglas
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). The…
Ondrej, Vladan; Dvorak, Petr
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:…
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…
Boyle, John A.
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…
Wang, Bing; Zhang, Xiang
This chapter provides an overview of some bioinformatics tasks and the relevance of the evolutionary computation methods, especially GAs. There are two advantages of GA-based approaches. One is that GAs are easier to run in parallel than single trajectory search procedures, and therefore allow groups of processors to be utilized for a search. The other is
Full Text Available Abstract 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
Poe, D.; Venkatraman, N.; Hansen, C.; Singh, G.
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…
Lelieveld, Stefan H; Veltman, Joris A; Gilissen, Christian
With the widespread adoption of next generation sequencing technologies by the genetics community and the rapid decrease in costs per base, exome sequencing has become a standard within the repertoire of genetic experiments for both research and diagnostics. Although bioinformatics now offers standard solutions for the analysis of exome sequencing data, many challenges still remain; especially the increasing scale at which exome data are now being generated has given rise to novel challenges in how to efficiently store, analyze and interpret exome data of this magnitude. In this review we discuss some of the recent developments in bioinformatics for exome sequencing and the directions that this is taking us to. With these developments, exome sequencing is paving the way for the next big challenge, the application of whole genome sequencing. PMID:27075447
Ghulam A. Parray
Full Text Available Saffron (Crocus sativus L. is a sterile triploid plant and belongs to the Iridaceae (Liliales, Monocots. Its genome is of relatively large size and is poorly characterized. Bioinformatics can play an enormous technical role in the sequence-level structural characterization of saffron genomic DNA. Bioinformatics tools can also help in appreciating the extent of diversity of various geographic or genetic groups of cultivated saffron to infer relationships between groups and accessions. The characterization of the transcriptome of saffron stigmas is the most vital for throwing light on the molecular basis of flavor, color biogenesis, genomic organization and biology of gynoecium of saffron. The information derived can be utilized for constructing biological pathways involved in the biosynthesis of principal components of saffron i.e., crocin, crocetin, safranal, picrocrocin and safchiA
Rocco, D; Critchlow, T
The transition of the World Wide Web from a paradigm of static Web pages to one of dynamic Web services provides new and exciting opportunities for bioinformatics with respect to data dissemination, transformation, and integration. However, the rapid growth of bioinformatics services, coupled with non-standardized interfaces, diminish the potential that these Web services offer. To face this challenge, we examine the notion of a Web service class that defines the functionality provided by a collection of interfaces. These descriptions are an integral part of a larger framework that can be used to discover, classify, and wrapWeb services automatically. We discuss how this framework can be used in the context of the proliferation of sites offering BLAST sequence alignment services for specialized data sets.
LIU Wei; LI Dong; ZHU YunPing; HE FuChu
Research in signaling networks contributes to a deeper understanding of organism living activities. With the development of experimental methods in the signal transduction field, more and more mechanisms of signaling pathways have been discovered. This paper introduces such popular bioin-formatics analysis methods for signaling networks as the common mechanism of signaling pathways and database resource on the Internet, summerizes the methods of analyzing the structural properties of networks, including structural Motif finding and automated pathways generation, and discusses the modeling and simulation of signaling networks in detail, as well as the research situation and tendency in this area. Now the investigation of signal transduction is developing from small-scale experiments to large-scale network analysis, and dynamic simulation of networks is closer to the real system. With the investigation going deeper than ever, the bioinformatics analysis of signal transduction would have immense space for development and application.
Full Text Available Workflow systems are typical fit for in the explorative research of bioinformaticians. These systems can help bioinformaticians to design and run their experiments and to automatically capture and store the data generated at runtime. On the other hand, Web services are increasingly used as the preferred method for accessing and processing the information coming from the diverse life science sources. In this work we provide an efficient approach for creating bioinformatic workflow for all-service architecture systems (i.e., all system components are services . This architecture style simplifies the user interaction with workflow systems and facilitates both the change of individual components, and the addition of new components to adopt to other workflow tasks if required. We finally present a case study for the bioinformatics domain to elaborate the applicability of our proposed approach.
Greene, Anna C.; Giffin, Kristine A.; Greene, Casey S; Jason H Moore
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...
Bretonnel Cohen, K; Hunter, Lawrence E.
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. P...
In the past two decades genome sequencing has developed from a laborious and costly technology employed by large international consortia to a widely used, automated and affordable tool used worldwide by many individual research groups. Genome sequences of many food animals and crop plants have been deciphered and are being exploited for fundamental research and applied to improve their breeding programs. The developments in sequencing technologies have also impacted the associated bioinformat...
Biological sequence alignment is an important and challenging task in bioinformatics. Alignment may be defined as an arrangement of two or more DNA or protein sequences to highlight the regions of their similarity. Sequence alignment is used to infer the evolutionary relationship between a set of protein or DNA sequences. An accurate alignment can provide valuable information for experimentation on the newly found sequences. It is indispensable in basic research as well as in practical applic...
Casari, G; Daruvar, Dea; Sander, C.; Schneider, Reinhard
Scientific history was made in completing the yeast genuine sequence, yet its 13 Mb are a mere starting point. Two challenges loom large: to decipher the function of all genes and to describe the workings of the eukaryotic cell in full molecular detail. A combination of experimental and theoretical approaches will be brought to bear on these challenges. What will be next in yeast genome analysis from the point of view of bioinformatics?
Walaa Nagy; Hoda M.O. Mokhtar
Workflow systems are typical fit for in the explorative research of bioinformaticians. These systems can help bioinformaticians to design and run their experiments and to automatically capture and store the data generated at runtime. On the other hand, Web services are increasingly used as the preferred method for accessing and processing the information coming from the diverse life science sources. In this work we provide an efficient approach for creating bioinformatic workflow for all-serv...
Fang, Wai-Chi; Lue, Jaw-Chyng
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).
Sudhakar, R.; Gupta, Kuhu; Kumar, Sushant
Bioinformatics can be defined as conceptualization of biology, in specific- Molecular Biology and then application of certain techniques from multiple disciplines such as statistics, computer science and applied mathematics to analyze and understand the vast information related to molecular structures. Hence, its management becomes difficult. The manager must be thorough with the concepts of biology- genetic studies in particular, as well as information technology. Discussed below is the mana...
Napolitano, Francesco; Mariani-Costantini, Renato; Tagliaferri, Roberto
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...
Shanahan, Hugh P; Owen, Anne M; Harrison, Andrew P
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
Translational bioinformatics plays an indispensable role in transforming psychoneuroimmunology (PNI) into personalized medicine. It provides a powerful method to bridge the gaps between various knowledge domains in PNI and systems biology. Translational bioinformatics methods at various systems levels can facilitate pattern recognition, and expedite and validate the discovery of systemic biomarkers to allow their incorporation into clinical trials and outcome assessments. Analysis of the correlations between genotypes and phenotypes including the behavioral-based profiles will contribute to the transition from the disease-based medicine to human-centered medicine. Translational bioinformatics would also enable the establishment of predictive models for patient responses to diseases, vaccines, and drugs. In PNI research, the development of systems biology models such as those of the neurons would play a critical role. Methods based on data integration, data mining, and knowledge representation are essential elements in building health information systems such as electronic health records and computerized decision support systems. Data integration of genes, pathophysiology, and behaviors are needed for a broad range of PNI studies. Knowledge discovery approaches such as network-based systems biology methods are valuable in studying the cross-talks among pathways in various brain regions involved in disorders such as Alzheimer's disease. PMID:22933157
Greene, Anna C; Giffin, Kristine A; Greene, Casey S; Moore, Jason H
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
Ong, Quang; Nguyen, Phuc; Thao, Nguyen Phuong; Le, Ly
The advance in genomics technology leads to the dramatic change in plant biology research. Plant biologists now easily access to enormous genomic data to deeply study plant high-density genetic variation at molecular level. Therefore, fully understanding and well manipulating bioinformatics tools to manage and analyze these data are essential in current plant genome research. Many plant genome databases have been established and continued expanding recently. Meanwhile, analytical methods based on bioinformatics are also well developed in many aspects of plant genomic research including comparative genomic analysis, phylogenomics and evolutionary analysis, and genome-wide association study. However, constantly upgrading in computational infrastructures, such as high capacity data storage and high performing analysis software, is the real challenge for plant genome research. This review paper focuses on challenges and opportunities which knowledge and skills in bioinformatics can bring to plant scientists in present plant genomics era as well as future aspects in critical need for effective tools to facilitate the translation of knowledge from new sequencing data to enhancement of plant productivity. PMID:27499685
The general audience for these lectures is mainly physicists, computer scientists, engineers or the general public wanting to know more about what’s going on in the biosciences. What’s bioinformatics and why is all this fuss being made about it ? What’s this revolution triggered by the human genome project ? Are there any results yet ? What are the problems ? What new avenues of research have been opened up ? What about the technology ? These new developments will be compared with what happened at CERN earlier in its evolution, and it is hoped that the similiraties and contrasts will stimulate new curiosity and provoke new thoughts.
Lue, Jaw-Chyng L.; Fang, Wai-Chi
A microsystem architecture for real-time, on-site, robust bioinformatic patterns recognition and analysis has been proposed. This system is compatible with on-chip DNA analysis means such as polymerase chain reaction (PCR)amplification. A corresponding novel artificial neural network (ANN) learning algorithm using new sigmoid-logarithmic transfer function based on error backpropagation (EBP) algorithm is invented. Our results show the trained new ANN can recognize low fluorescence patterns better than the conventional sigmoidal ANN does. A differential logarithmic imaging chip is designed for calculating logarithm of relative intensities of fluorescence signals. The single-rail logarithmic circuit and a prototype ANN chip are designed, fabricated and characterized.
Magana, Alejandra J.; Taleyarkhan, Manaz; Alvarado, Daniela Rivera; Kane, Michael; Springer, John; Clase, Kari
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…
Nomi L Harris
Full Text Available 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.
@@ The Studio of Computational Biology & Bioinformatics (SCBB), IHBT, CSIR,Palampur, India organized one of the very first national workshop funded by DBT,Govt.of India, on the Bioinformatics issues associated with next generation sequencing approaches.The course structure was designed by SCBB, IHBT.The workshop took place in the IHBT premise on 17 and 18 June 2010.
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…
Ramlo, Susan E.; McConnell, David; Duan, Zhong-Hui; Moore, Francisco B.
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…
Howard, David R.; Miskowski, Jennifer A.; Grunwald, Sandra K.; Abler, Michael L.
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…
Olsen, Lars Rønn; Campos, Benito; Barnkob, Mike Stein;
cancer immunotherapies has yet to be fulfilled. The insufficient efficacy of existing treatments can be attributed to a number of biological and technical issues. In this review, we detail the current limitations of immunotherapy target selection and design, and review computational methods to streamline......The mechanisms of immune response to cancer have been studied extensively and great effort has been invested into harnessing the therapeutic potential of the immune system. Immunotherapies have seen significant advances in the past 20 years, but the full potential of protective and therapeutic...... and co-targets for single-epitope and multi-epitope strategies. We provide examples of application to the well-known tumor antigen HER2 and suggest bioinformatics methods to ameliorate therapy resistance and ensure efficient and lasting control of tumors....
Surangi W. Punyasena
Full Text Available Recent advances in microscopy, imaging, and data analyses have permitted both the greater application of quantitative methods and the collection of large data sets that can be used to investigate plant morphology. This special issue, the first for Applications in Plant Sciences, presents a collection of papers highlighting recent methods in the quantitative study of plant form. These emerging biometric and bioinformatic approaches to plant sciences are critical for better understanding how morphology relates to ecology, physiology, genotype, and evolutionary and phylogenetic history. From microscopic pollen grains and charcoal particles, to macroscopic leaves and whole root systems, the methods presented include automated classification and identification, geometric morphometrics, and skeleton networks, as well as tests of the limits of human assessment. All demonstrate a clear need for these computational and morphometric approaches in order to increase the consistency, objectivity, and throughput of plant morphological studies.
Multi-class classification is one of the fundamental tasks in bioinformatics and typically arises in cancer diagnosis studies by gene expression profiling. This article reviews two recent approaches to multi-class classification by combining multiple binary classifiers, which are formulated based on a unified framework of error-correcting output coding (ECOC). The first approach is to construct a multi-class classifier in which each binary classifier to be aggregated has a weight value to be optimally tuned based on the observed data. In the second approach, misclassification of each binary classifier is formulated as a bit inversion error with a probabilistic model by making an analogy to the context of information transmission theory. Experimental studies using various real-world datasets including cancer classification problems reveal that both of the new methods are superior or comparable to other multi-class classification methods
Handel, Adam E
Estrogen is a steroid hormone that plays critical roles in a myriad of intracellular pathways. The expression of many genes is regulated through the steroid hormone receptors ESR1 and ESR2. These bind to DNA and modulate the expression of target genes. Identification of estrogen target genes is greatly facilitated by the use of transcriptomic methods, such as RNA-seq and expression microarrays, and chromatin immunoprecipitation with massively parallel sequencing (ChIP-seq). Combining transcriptomic and ChIP-seq data enables a distinction to be drawn between direct and indirect estrogen target genes. This chapter discusses some methods of identifying estrogen target genes that do not require any expertise in programming languages or complex bioinformatics. PMID:26585125
ACADEMIC TRAINING LECTURE SERIES 27, 28 February 1, 2, 3 March 2006 from 11:00 to 12:00 - Auditorium, bldg. 500 Decoding the Genome A special series of 5 lectures on: Recent extraordinary advances in the life sciences arising through new detection technologies and bioinformatics The past five years have seen an extraordinary change in the information and tools available in the life sciences. The sequencing of the human genome, the discovery that we possess far fewer genes than foreseen, the measurement of the tiny changes in the genomes that differentiate us, the sequencing of the genomes of many pathogens that lead to diseases such as malaria are all examples of completely new information that is now available in the quest for improved healthcare. New tools have allowed similar strides in the discovery of the associated protein structures, providing invaluable information for those searching for new drugs. New DNA microarray chips permit simultaneous measurement of the state of expression of tens...
Next generation sequencing (NGS) has revolutionized the field of genomics and its wide range of applications has resulted in the genome-wide analysis of hundreds of species and the development of thousands of computational tools. This thesis represents my work on NGS analysis of four species, Lotus...... japonicus (Lotus), Vaccinium corymbosum (blueberry), Stegodyphus mimosarum (spider) and Trifolium occidentale (clover). From a bioinformatics data analysis perspective, my work can be divided into three parts; genome annotation, small RNA, and gene expression analysis. Lotus is a legume of significant...... agricultural and biological importance. Its capacity to form symbiotic relationships with rhizobia and microrrhizal fungi has fascinated researchers for years. Lotus has a small genome of approximately 470 Mb and a short life cycle of 2 to 3 months, which has made Lotus a model legume plant for many molecular...
Kristina M. Obom
Full Text Available The completely online Master of Science in Bioinformatics program differs from the onsite program only in the mode of content delivery. Analysis of student satisfaction indicates no statistically significant difference between most online and onsite student responses, however, online and onsite students do differ significantly in their responses to a few questions on the course evaluation queries. Analysis of student exam performance using three assessments indicates that there was no significant difference in grades earned by students in online and onsite courses. These results suggest that our model for online bioinformatics education provides students with a rigorous course of study that is comparable to onsite course instruction and possibly provides a more rigorous course load and more opportunities for participation.
Obom, Kristina. M.; Cummings, Patrick J.
The completely online Master of Science in Bioinformatics program differs from the onsite program only in the mode of content delivery. Analysis of student satisfaction indicates no statistically significant difference between most online and onsite student responses, however, online and onsite students do differ significantly in their responses to a few questions on the course evaluation queries. Analysis of student exam performance using three assessments indicates that there was no signifi...
Full Text Available ABSTRACT:The traditional methods for mining foods for bioactive peptides are tedious and long. Similar to the drug industry, the length of time to identify and deliver a commercial health ingredient that reduces disease symptoms can take anything between 5 to 10 years. Reducing this time and effort is crucial in order to create new commercially viable products with clear and important health benefits. In the past few years, bioinformatics, the science that brings together fast computational biology, and efficient genome mining, is appearing as the long awaited solution to this problem. By quickly mining food genomes for characteristics of certain food therapeutic ingredients, researchers can potentially find new ones in a matter of a few weeks. Yet, surprisingly, very little success has been achieved so far using bioinformatics in mining for food bioactives.The absence of food specific bioinformatic mining tools, the slow integration of both experimental mining and bioinformatics, and the important difference between different experimental platforms are some of the reasons for the slow progress of bioinformatics in the field of functional food and more specifically in bioactive peptide discovery.In this paper I discuss some methods that could be easily translated, using a rational peptide bioinformatics design, to food bioactive peptide mining. I highlight the need for an integrated food peptide database. I also discuss how to better integrate experimental work with bioinformatics in order to improve the mining of food for bioactive peptides, therefore achieving a higher success rates.
Brazas, Michelle D; Ouellette, B F Francis
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
Zou, Quan; Li, Xu-Bin; Jiang, Wen-Rui; Lin, Zi-Yu; Li, Gui-Lin; Chen, Ke
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. PMID:23396756
Gentleman, R.C.; Carey, V.J.; Bates, D.M.;
The Bioconductor project is an initiative for the collaborative creation of extensible software for computational biology and bioinformatics. The goals of the project include: fostering collaborative development and widespread use of innovative software, reducing barriers to entry into interdisci......The Bioconductor project is an initiative for the collaborative creation of extensible software for computational biology and bioinformatics. The goals of the project include: fostering collaborative development and widespread use of innovative software, reducing barriers to entry into...... interdisciplinary scientific research, and promoting the achievement of remote reproducibility of research results. We describe details of our aims and methods, identify current challenges, compare Bioconductor to other open bioinformatics projects, and provide working examples....
GAO; George; Fu
Highly pathogenic influenza A virus H5N1 has spread out worldwide and raised the public concerns. This increased the output of influenza virus sequence data as well as the research publication and other reports. In order to fight against H5N1 avian flu in a comprehensive way, we designed and started to set up the Website for Avian Flu Information (http://www.avian-flu.info) from 2004. Other than the influenza virus database available, the website is aiming to integrate diversified information for both researchers and the public. From 2004 to 2009, we collected information from all aspects, i.e. reports of outbreaks, scientific publications and editorials, policies for prevention, medicines and vaccines, clinic and diagnosis. Except for publications, all information is in Chinese. Till April 15, 2009, the cumulative news entries had been over 2000 and research papers were approaching 5000. By using the curated data from Influenza Virus Resource, we have set up an influenza virus sequence database and a bioinformatic platform, providing the basic functions for the sequence analysis of influenza virus. We will focus on the collection of experimental data and results as well as the integration of the data from the geological information system and avian influenza epidemiology.
LIU Di; LIU Quan-He; WU Lin-Huan; LIU Bin; WU Jun; LAO Yi-Mei; LI Xiao-Jing; GAO George Fu; MA Jun-Cai
Highly pathogenic influenza A virus H5N1 has spread out worldwide and raised the public concerns. This increased the output of influenza virus sequence data as well as the research publication and other reports. In order to fight against H5N1 avian flu in a comprehensive way, we designed and started to set up the Website for Avian Flu Information (http://www.avian-flu.info) from 2004. Other than the influenza virus database available, the website is aiming to integrate diversified information for both researchers and the public. From 2004 to 2009, we collected information from all aspects, i.e. reports of outbreaks, scientific publications and editorials, policies for prevention, medicines and vaccines, clinic and diagnosis. Except for publications, all information is in Chinese. Till April 15, 2009, the cumulative news entries had been over 2000 and research papers were approaching 5000. By using the curated data from Influenza Virus Resource, we have set up an influenza virus sequence database and a bioin-formatic platform, providing the basic functions for the sequence analysis of influenza virus. We will focus on the collection of experimental data and results as well as the integration of the data from the geological information system and avian influenza epidemiology.
One of the mechanisms of external signal transduction (ionizing radiation, toxicants, stress) to the target cell is the existence of membrane and intracellular proteins with intrinsic tyrosine kinase activity. No wonder that etiology of malignant growth links to abnormalities in signal transduction through tyrosine kinases. The epidermal growth factor receptor (EGFR) tyrosine kinases play fundamental roles in development, proliferation and differentiation of tissues of epithelial, mesenchymal and neuronal origin. There are four types of EGFR: EGF receptor (ErbB1/HER1), ErbB2/Neu/HER2, ErbB3/HER3 and ErbB4/HER4. Abnormal expression of EGFR, appearance of receptor mutants with changed ability to protein-protein interactions or increased tyrosine kinase activity have been implicated in the malignancy of different types of human tumors. Bioinformatics is currently using in investigation on design and selection of drugs that can make alterations in structure or competitively bind with receptors and so display antagonistic characteristics. (authors)
Zeng, Zhiqiang; Shi, Hua; Wu, Yun; Hong, Zhiling
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. PMID:26525745
Full Text Available 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.
Hiraoka, Satoshi; Yang, Ching-chia; Iwasaki, Wataru
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. PMID:27383682
Computational workflows in bioinformatics are becoming increasingly important in the achievement of scientific advances. These workflows generally require access to multiple, distributed data sources and analytic tools. The requisite data sources may include large public data repositories, community...
Li, Xin; Ma, Li; Wang, Jinjia; Zhao, Chun
Feature selection (FS) techniques have become an important tool in bioinformatics field. The core algorithm of it is to select the hidden significant data with low-dimension from high-dimensional data space, and thus to analyse the basic built-in rule of the data. The data of bioinformatics fields are always with high-dimension and small samples, so the research of FS algorithm in the bioinformatics fields has great foreground. In this article, we make the interested reader aware of the possibilities of feature selection, provide basic properties of feature selection techniques, and discuss their uses in the sequence analysis, microarray analysis, mass spectra analysis etc. Finally, the current problems and the prospects of feature selection algorithm in the application of bioinformatics is also discussed. PMID:21604512
Reviews the development of scalable pattern recognition algorithms for computational biology and bioinformatics Includes numerous examples and experimental results to support the theoretical concepts described Concludes each chapter with directions for future research and a comprehensive bibliography
Zhiqiang Zeng; Hua Shi; Yun Wu; Zhiling Hong
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 ...
Kashyap, Hirak; Ahmed, Hasin Afzal; Hoque, Nazrul; Roy, Swarup; Bhattacharyya, Dhruba Kumar
Bioinformatics research is characterized by voluminous and incremental datasets and complex data analytics methods. The machine learning methods used in bioinformatics are iterative and parallel. These methods can be scaled to handle big data using the distributed and parallel computing technologies. Usually big data tools perform computation in batch-mode and are not optimized for iterative processing and high data dependency among operations. In the recent years, parallel, incremental, and ...
Schneider, M.V.; Watson, J.; Attwood, T.;
services, and discuss successful training strategies shared by a diverse set of bioinformatics trainers. We also identify steps that trainers in bioinformatics could take together to advance the state of the art in current training practices. The ideas presented in this article derive from the first...... Trainer Networking Session held under the auspices of the EU-funded SLING Integrating Activity, which took place in November 2009....
Keane, Thomas M; Page, Andrew J.; McInerney, James O.; Naughton, Thomas J
In the past number of years the demand for high performance computing has greatly increased in the area of bioinformatics. The huge increase in size of many genomic databases has meant that many common tasks in bioinformatics are not possible to complete in a reasonable amount of time on a single processor. Recently distributed computing has emerged as an inexpensive alternative to dedicated parallel computing. We have developed a general-purpose distributed computing platform ...
Full Text Available Abstract Background Recent advances in experimental and computational technologies have fueled the development of many sophisticated bioinformatics programs. The correctness of such programs is crucial as incorrectly computed results may lead to wrong biological conclusion or misguide downstream experimentation. Common software testing procedures involve executing the target program with a set of test inputs and then verifying the correctness of the test outputs. However, due to the complexity of many bioinformatics programs, it is often difficult to verify the correctness of the test outputs. Therefore our ability to perform systematic software testing is greatly hindered. Results We propose to use a novel software testing technique, metamorphic testing (MT, to test a range of bioinformatics programs. Instead of requiring a mechanism to verify whether an individual test output is correct, the MT technique verifies whether a pair of test outputs conform to a set of domain specific properties, called metamorphic relations (MRs, thus greatly increases the number and variety of test cases that can be applied. To demonstrate how MT is used in practice, we applied MT to test two open-source bioinformatics programs, namely GNLab and SeqMap. In particular we show that MT is simple to implement, and is effective in detecting faults in a real-life program and some artificially fault-seeded programs. Further, we discuss how MT can be applied to test programs from various domains of bioinformatics. Conclusion This paper describes the application of a simple, effective and automated technique to systematically test a range of bioinformatics programs. We show how MT can be implemented in practice through two real-life case studies. Since many bioinformatics programs, particularly those for large scale simulation and data analysis, are hard to test systematically, their developers may benefit from using MT as part of the testing strategy. Therefore our work
Stringer-Calvert David WJ; Gupta Priyanka; Wagner Valerie; Pouliot Yannick; Lee Thomas J; Tenenbaum Jessica D; Karp Peter D
Abstract Background This article addresses the problem of interoperation of heterogeneous bioinformatics databases. Results We introduce BioWarehouse, an open source toolkit for constructing bioinformatics database warehouses using the MySQL and Oracle relational database managers. BioWarehouse integrates its component databases into a common representational framework within a single database management system, thus enabling multi-database queries using the Structured Query Language (SQL) bu...
Ilzins, Olaf; Isea, Raul; Hoebeke, Johan
The objective of this short report is to reconsider the subject of bioinformatics as just being a tool of experimental biological science. To do that, we introduce three examples to show how bioinformatics could be considered as an experimental science. These examples show how the development of theoretical biological models generates experimentally verifiable computer hypotheses, which necessarily must be validated by experiments in vitro or in vivo.
Bülow, Lorenz; Hehl, Reinhard
Bioinformatics tools can be employed to identify conserved cis-sequences in sets of coregulated plant genes because more and more gene expression and genomic sequence data become available. Knowledge on the specific cis-sequences, their enrichment and arrangement within promoters, facilitates the design of functional synthetic plant promoters that are responsive to specific stresses. The present chapter illustrates an example for the bioinformatic identification of conserved Arabidopsis thaliana cis-sequences enriched in drought stress-responsive genes. This workflow can be applied for the identification of cis-sequences in any sets of coregulated genes. The workflow includes detailed protocols to determine sets of coregulated genes, to extract the corresponding promoter sequences, and how to install and run a software package to identify overrepresented motifs. Further bioinformatic analyses that can be performed with the results are discussed. PMID:27557771
Zales, Charlotte Rappe; Cronin, Susan J.
Sixteen high school women participated in a 5-week residential summer program designed to encourage female and minority students to choose careers in scientific fields. Students gained expertise in bioinformatics through problem-based learning in a complex learning environment of content instruction, speakers, labs, and trips. Innovative hands-on activities filled the program. Students learned biological principles in context and sophisticated bioinformatics tools for processing data. Students additionally mastered a variety of information-searching techniques. Students completed creative individual and group projects, demonstrating the successful integration of biology, information technology, and bioinformatics. Discussions with female scientists allowed students to see themselves in similar roles. Summer residential aspects fostered an atmosphere in which students matured in interacting with others and in their views of diversity.
Om Prakash Sharma
Full Text Available This review article discusses the current scenario of the national and international burden due to lymphatic filariasis (LF and describes the active elimination programmes for LF and their achievements to eradicate this most debilitating disease from the earth. Since, bioinformatics is a rapidly growing field of biological study, and it has an increasingly significant role in various fields of biology. We have reviewed its leading involvement in the filarial research using different approaches of bioinformatics and have summarized available existing drugs and their targets to re-examine and to keep away from the resisting conditions. Moreover, some of the novel drug targets have been assembled for further study to design fresh and better pharmacological therapeutics. Various bioinformatics-based web resources, and databases have been discussed, which may enrich the filarial research.
DENG You-ping; AI Jun-mei; XIAO Pei-gen
One important purpose to investigate medicinal plants is to understand genes and enzymes that govern the biological metabolic process to produce bioactive compounds.Genome wide high throughput technologies such as genomics,transcriptomics,proteomics and metabolomics can help reach that goal.Such technologies can produce a vast amount of data which desperately need bioinformatics and systems biology to process,manage,distribute and understand these data.By dealing with the"omics"data,bioinformatics and systems biology can also help improve the quality of traditional medicinal materials,develop new approaches for the classification and authentication of medicinal plants,identify new active compounds,and cultivate medicinal plant species that tolerate harsh environmental conditions.In this review,the application of bioinformatics and systems biology in medicinal plants is briefly introduced.
Trias Thireou; George Spyrou; Vassilis Atlamazoglou
The explosive growth of the bioinformatics field has led to a large amount of data and software applications publicly available as web resources. However, the lack of persistence of web references is a barrier to a comprehensive shared access. We conducted a study of the current availability and other features of primary bioinformatics web resources (such as software tools and databases). The majority (95%) of the examined bioinformatics web resources were found running on UNIX/Linux operating systems, and the most widely used web server was found to be Apache (or Apache-related products). Of the overall 1,130 Uniform Resource Locators (URLs) examined, 91% were highly available (more than 90% of the time), while only 4% showed low accessibility (less than 50% of the time) during the survey. Furthermore, the most common URL failure modes are presented and analyzed.
Structural bioinformatics is concerned with the molecular structure of biomacromolecules on a genomic scale, using computational methods. Classic problems in structural bioinformatics include the prediction of protein and RNA structure from sequence, the design of artificial proteins or enzymes...... and experimental determination of macromolecular structure that are based on such methods. These developments include generative models of protein structure, the estimation of the parameters of energy functions that are used in structure prediction, the superposition of macromolecules and structure...... bioinformatics. Recently, probabilistic models and machine learning methods based on Bayesian principles are providing efficient and rigorous solutions to challenging problems that were long regarded as intractable. In this review, I will highlight some important recent developments in the prediction, analysis...
Phillips, J. C.
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.
Approaches in Integrative Bioinformatics provides a basic introduction to biological information systems, as well as guidance for the computational analysis of systems biology. This book also covers a range of issues and methods that reveal the multitude of omics data integration types and the relevance that integrative bioinformatics has today. Topics include biological data integration and manipulation, modeling and simulation of metabolic networks, transcriptomics and phenomics, and virtual cell approaches, as well as a number of applications of network biology. It helps to illustrat
Recent developments in computer science enable algorithms previously perceived as too time-consuming to now be efficiently used for applications in bioinformatics and life sciences. This work focuses on proteins and their structures, protein structure similarity searching at main representation levels and various techniques that can be used to accelerate similarity searches. Divided into four parts, the first part provides a formal model of 3D protein structures for functional genomics, comparative bioinformatics and molecular modeling. The second part focuses on the use of multithreading for
Heiges, Mark; Wang, Haiming; Robinson, Edward; Aurrecoechea, Cristina; Gao, Xin; Kaluskar, Nivedita; Rhodes, Philippa; Wang, Sammy; He, Cong-Zhou; Su, Yanqi; Miller, John; Kraemer, Eileen; Kissinger, Jessica C
The database, CryptoDB (), is a community bioinformatics resource for the AIDS-related apicomplexan-parasite, Cryptosporidium. CryptoDB integrates whole genome sequence and annotation with expressed sequence tag and genome survey sequence data and provides supplemental bioinformatics analyses and data-mining tools. A simple, yet comprehensive web interface is available for mining and visualizing the data. CryptoDB is allied with the databases PlasmoDB and ToxoDB via ApiDB, an NIH/NIAID-funded...
Ditty, Jayna L.; Kvaal, Christopher A.; Goodner, Brad; Freyermuth, Sharyn K.; Bailey, Cheryl; Britton, Robert A.; Gordon, Stuart G.; Heinhorst, Sabine; Reed, Kelynne; Xu, Zhaohui; Sanders-Lorenz, Erin R.; Axen, Seth; Kim, Edwin; Johns, Mitrick; Scott, Kathleen; Kerfeld, Cheryl A.
Undergraduate life sciences education needs an overhaul, as clearly described in the National Research Council of the National Academies publication BIO 2010: Transforming Undergraduate Education for Future Research Biologists. Among BIO 2010's top recommendations is the need to involve students in working with real data and tools that reflect the nature of life sciences research in the 21st century. Education research studies support the importance of utilizing primary literature, designing and implementing experiments, and analyzing results in the context of a bona fide scientific question in cultivating the analytical skills necessary to become a scientist. Incorporating these basic scientific methodologies in undergraduate education leads to increased undergraduate and post-graduate retention in the sciences. Toward this end, many undergraduate teaching organizations offer training and suggestions for faculty to update and improve their teaching approaches to help students learn as scientists, through design and discovery (e.g., Council of Undergraduate Research [www.cur.org] and Project Kaleidoscope [www.pkal.org]). With the advent of genome sequencing and bioinformatics, many scientists now formulate biological questions and interpret research results in the context of genomic information. Just as the use of bioinformatic tools and databases changed the way scientists investigate problems, it must change how scientists teach to create new opportunities for students to gain experiences reflecting the influence of genomics, proteomics, and bioinformatics on modern life sciences research. Educators have responded by incorporating bioinformatics into diverse life science curricula. While these published exercises in, and guidelines for, bioinformatics curricula are helpful and inspirational, faculty new to the area of bioinformatics inevitably need training in the theoretical underpinnings of the algorithms. Moreover, effectively integrating bioinformatics
Full Text Available Abstract Reversible protein phosphorylation is one of the most important forms of cellular regulation. Thus, phosphoproteomic analysis of protein phosphorylation in cells is a powerful tool to evaluate cell functional status. The importance of protein kinase-regulated signal transduction pathways in human cancer has led to the development of drugs that inhibit protein kinases at the apex or intermediary levels of these pathways. Phosphoproteomic analysis of these signalling pathways will provide important insights for operation and connectivity of these pathways to facilitate identification of the best targets for cancer therapies. Enrichment of phosphorylated proteins or peptides from tissue or bodily fluid samples is required. The application of technologies such as phosphoenrichments, mass spectrometry (MS coupled to bioinformatics tools is crucial for the identification and quantification of protein phosphorylation sites for advancing in such relevant clinical research. A combination of different phosphopeptide enrichments, quantitative techniques and bioinformatic tools is necessary to achieve good phospho-regulation data and good structural analysis of protein studies. The current and most useful proteomics and bioinformatics techniques will be explained with research examples. Our aim in this article is to be helpful for cancer research via detailing proteomics and bioinformatic tools.
López, Elena; Wesselink, Jan-Jaap; López, Isabel; Mendieta, Jesús; Gómez-Puertas, Paulino; Muñoz, Sarbelio Rodríguez
Reversible protein phosphorylation is one of the most important forms of cellular regulation. Thus, phosphoproteomic analysis of protein phosphorylation in cells is a powerful tool to evaluate cell functional status. The importance of protein kinase-regulated signal transduction pathways in human cancer has led to the development of drugs that inhibit protein kinases at the apex or intermediary levels of these pathways. Phosphoproteomic analysis of these signalling pathways will provide important insights for operation and connectivity of these pathways to facilitate identification of the best targets for cancer therapies. Enrichment of phosphorylated proteins or peptides from tissue or bodily fluid samples is required. The application of technologies such as phosphoenrichments, mass spectrometry (MS) coupled to bioinformatics tools is crucial for the identification and quantification of protein phosphorylation sites for advancing in such relevant clinical research. A combination of different phosphopeptide enrichments, quantitative techniques and bioinformatic tools is necessary to achieve good phospho-regulation data and good structural analysis of protein studies. The current and most useful proteomics and bioinformatics techniques will be explained with research examples. Our aim in this article is to be helpful for cancer research via detailing proteomics and bioinformatic tools. PMID:21967744
Goto, N.; Prins, J.C.P.; Nakao, M.; Bonnal, R.; Aerts, J.; Katayama, A.
The BioRuby software toolkit contains a comprehensive set of free development tools and libraries for bioinformatics and molecular biology, written in the Ruby programming language. BioRuby has components for sequence analysis, pathway analysis, protein modelling and phylogenetic analysis; it suppor
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...
Rasmussen, Morten; Thaysen-Andersen, Morten; Højrup, Peter
We have developed "GLYCANthrope " - CROSSWORKS for glycans: a bioinformatics tool, which assists in identifying N-linked glycosylated peptides as well as their glycan moieties from MS2 data of enzymatically digested glycoproteins. The program runs either as a stand-alone application or as a plug...
Lima, Andre O. S.; Garces, Sergio P. S.
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…
Gelbart, Hadas; Yarden, Anat
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…
Whyte, Barry James
The Virginia Bioinformatics Institute (VBI) at Virginia Tech has announced the appointment of Joao Setubal as the institute's deputy director. As deputy director, Setubal will act on behalf of VBI's executive and scientific director, Bruno Sobral, handling internal administrative functions, as well as scientific decision making.
As the sequencing stage of human genome project is near the end, the work has begun for discovering novel genes from genome sequences and annotating their biological functions. Here are reviewed current major bioinformatics tools and technologies available for large scale gene discovery and annotation from human genome sequences. Some ideas about possible future development are also provided.
Verheggen, Kenneth; Maddelein, Davy; Hulstaert, Niels; Martens, Lennart; Barsnes, Harald; Vaudel, Marc
The use of proteomics bioinformatics substantially contributes to an improved understanding of proteomes, but this novel and in-depth knowledge comes at the cost of increased computational complexity. Parallelization across multiple computers, a strategy termed distributed computing, can be used to handle this increased complexity; however, setting up and maintaining a distributed computing infrastructure requires resources and skills that are not readily available to most research groups. Here we propose a free and open-source framework named Pladipus that greatly facilitates the establishment of distributed computing networks for proteomics bioinformatics tools. Pladipus is straightforward to install and operate thanks to its user-friendly graphical interface, allowing complex bioinformatics tasks to be run easily on a network instead of a single computer. As a result, any researcher can benefit from the increased computational efficiency provided by distributed computing, hence empowering them to tackle more complex bioinformatics challenges. Notably, it enables any research group to perform large-scale reprocessing of publicly available proteomics data, thus supporting the scientific community in mining these data for novel discoveries. PMID:26510693
Stringer-Calvert David WJ
Full Text Available Abstract Background This article addresses the problem of interoperation of heterogeneous bioinformatics databases. Results We introduce BioWarehouse, an open source toolkit for constructing bioinformatics database warehouses using the MySQL and Oracle relational database managers. BioWarehouse integrates its component databases into a common representational framework within a single database management system, thus enabling multi-database queries using the Structured Query Language (SQL but also facilitating a variety of database integration tasks such as comparative analysis and data mining. BioWarehouse currently supports the integration of a pathway-centric set of databases including ENZYME, KEGG, and BioCyc, and in addition the UniProt, GenBank, NCBI Taxonomy, and CMR databases, and the Gene Ontology. Loader tools, written in the C and JAVA languages, parse and load these databases into a relational database schema. The loaders also apply a degree of semantic normalization to their respective source data, decreasing semantic heterogeneity. The schema supports the following bioinformatics datatypes: chemical compounds, biochemical reactions, metabolic pathways, proteins, genes, nucleic acid sequences, features on protein and nucleic-acid sequences, organisms, organism taxonomies, and controlled vocabularies. As an application example, we applied BioWarehouse to determine the fraction of biochemically characterized enzyme activities for which no sequences exist in the public sequence databases. The answer is that no sequence exists for 36% of enzyme activities for which EC numbers have been assigned. These gaps in sequence data significantly limit the accuracy of genome annotation and metabolic pathway prediction, and are a barrier for metabolic engineering. Complex queries of this type provide examples of the value of the data warehousing approach to bioinformatics research. Conclusion BioWarehouse embodies significant progress on the
Nehm, Ross H.; Budd, Ann F.
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 …
Shachak, Aviv; Ophir, Ron; Rubin, Eitan
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…
Miskowski, Jennifer A.; Howard, David R.; Abler, Michael L.; Grunwald, Sandra K.
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…
Inlow, Jennifer K.; Miller, Paige; Pittman, Bethany
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'…
Attwood, Terri K.; Selimas, Ioannis; Buis, Rob; Altenburg, Ruud; Herzog, Robert; Ledent, Valerie; Ghita, Viorica; Fernandes, Pedro; Marques, Isabel; Brugman, Marc
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…
Furge, Laura Lowe; Stevens-Truss, Regina; Moore, D. Blaine; Langeland, James A.
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.…
Accardi, L.; Freudenberg, Wolfgang; Ohya, Masanori
/ H. Kamimura -- Massive collection of full-length complementary DNA clones and microarray analyses: keys to rice transcriptome analysis / S. Kikuchi -- Changes of influenza A(H5) viruses by means of entropic chaos degree / K. Sato and M. Ohya -- Basics of genome sequence analysis in bioinformatics - its fundamental ideas and problems / T. Suzuki and S. Miyazaki -- A basic introduction to gene expression studies using microarray expression data analysis / D. Wanke and J. Kilian -- Integrating biological perspectives: a quantum leap for microarray expression analysis / D. Wanke ... [et al.].
Xiao Li; Yizheng Zhang
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 biological 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.
Haibo WANG; Junyun GUO
[Objective] This study aimed to perform the bioinformatics analysis of Zinc transporter (ZnT) from Baoding Alfalfa. [Method] Based on the amino acid sequence, the physical and chemical properties, hydrophilicity/hydrophobicity, secondary structure of ZnT from Baoding alfalfa were predicted by a series of bioinformatics software. And the transmembrane domains were predicted by using different online tools. [Result] ZnT is a hydrophobic protein containing 408 amino acids with the theoretical pl of 5.94, and it has 7 potential transmembrane hydrophobic regions. In the sec- ondary structure, co-helix (Hh) accounted for 48.04%, extended strand (Ee) for 9.56%, random coil (Cc) for 42.40%, which was accored with the characteristic of transmembrane protein. [Conclusion] mZnT is a member of CDF family, responsible for transporting Zn^2+ out of the cell membrane to reduce the concentration and toxicity of Zn^2+.
Via, Allegra; Blicher, Thomas; Bongcam-Rudloff, Erik;
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......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...... 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...
Full Text Available The application of whole-genome shotgun sequencing to microbial communities represents a major development in metagenomics, the study of uncultured microbes via the tools of modern genomic analysis. In the past year, whole-genome shotgun sequencing projects of prokaryotic communities from an acid mine biofilm, the Sargasso Sea, Minnesota farm soil, three deep-sea whale falls, and deep-sea sediments have been reported, adding to previously published work on viral communities from marine and fecal samples. The interpretation of this new kind of data poses a wide variety of exciting and difficult bioinformatics problems. The aim of this review is to introduce the bioinformatics community to this emerging field by surveying existing techniques and promising new approaches for several of the most interesting of these computational problems.
Research for the biological systems has reached to the stage that clarifies an organism as a whole from genome, a set of genes. To accomplish the researches, one needs to face a lot of data retrieved from genome sequences. Conventional methods, namely experiments in wet-labs, are, however not designed for dealing with genome scale data. For those data analyses, computer based researches, such as data mining and simulation, are suitable. As a result, bioinformatics, a new discipline combining expertise of biology and information science, is emerging. Here, we report a development of a data base and a web based system for application execution (Execution of Application on web system). Those are one of the efforts to support bioinformatics research by Office of ITBL Promotion. (author)
Calabrese, Barbara; Cannataro, Mario
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. PMID:25863787
This book presents selected papers on statistical model development related mainly to the fields of Biostatistics and Bioinformatics. The coverage of the material falls squarely into the following categories: (a) Survival analysis and multivariate survival analysis, (b) Time series and longitudinal data analysis, (c) Statistical model development and (d) Applied statistical modelling. Innovations in statistical modelling are presented throughout each of the four areas, with some intriguing new ideas on hierarchical generalized non-linear models and on frailty models with structural dispersion, just to mention two examples. The contributors include distinguished international statisticians such as Philip Hougaard, John Hinde, Il Do Ha, Roger Payne and Alessandra Durio, among others, as well as promising newcomers. Some of the contributions have come from researchers working in the BIO-SI research programme on Biostatistics and Bioinformatics, centred on the Universities of Limerick and Galway in Ireland and fu...
Varma, B Sharat Chandra; Balakrishnan, M
This book presents an evaluation methodology to design future FPGA fabrics incorporating hard embedded blocks (HEBs) to accelerate applications. This methodology will be useful for selection of blocks to be embedded into the fabric and for evaluating the performance gain that can be achieved by such an embedding. The authors illustrate the use of their methodology by studying the impact of HEBs on two important bioinformatics applications: protein docking and genome assembly. The book also explains how the respective HEBs are designed and how hardware implementation of the application is done using these HEBs. It shows that significant speedups can be achieved over pure software implementations by using such FPGA-based accelerators. The methodology presented in this book may also be used for designing HEBs for accelerating software implementations in other domains besides bioinformatics. This book will prove useful to students, researchers, and practicing engineers alike.
Cristancho, Marco; Isaza, Gustavo; Pinzón, Andrés; Rodríguez, Juan
This volume compiles accepted contributions for the 2nd Edition of the Colombian Computational Biology and Bioinformatics Congress CCBCOL, after a rigorous review process in which 54 papers were accepted for publication from 119 submitted contributions. Bioinformatics and Computational Biology are areas of knowledge that have emerged due to advances that have taken place in the Biological Sciences and its integration with Information Sciences. The expansion of projects involving the study of genomes has led the way in the production of vast amounts of sequence data which needs to be organized, analyzed and stored to understand phenomena associated with living organisms related to their evolution, behavior in different ecosystems, and the development of applications that can be derived from this analysis. .
Holland, R. C. G.; Down, T. A.; Pocock, M.; Prlić, A.; Huen, D; James, K.; Foisy, S.; Dräger, A.; Yates, A; Heuer, M.; Schreiber, M. J.
Summary: BioJava is a mature open-source project that provides a framework for processing of biological data. BioJava contains powerful analysis and statistical routines, tools for parsing common file formats and packages for manipulating sequences and 3D structures. It enables rapid bioinformatics application development in the Java programming language. Availability: BioJava is an open-source project distributed under the Lesser GPL (LGPL). BioJava can be downloaded from the BioJava website...
Many bioinformatics problems, such as sequence alignment, gene prediction, phylogenetic tree estimation and RNA secondary structure prediction, are often affected by the "uncertainty" of a solution; that is, the probability of the solution is extremely small. This situation arises for estimation problems on high-dimensional discrete spaces in which the number of possible discrete solutions is immense. In the analysis of biological data or the development of prediction algorithms, this uncerta...
Full Text Available Abstract Background Molecular biologists need sophisticated analytical tools which often demand extensive computational resources. While finding, installing, and using these tools can be challenging, pipelining data from one program to the next is particularly awkward, especially when using web-based programs. At the same time, system administrators tasked with maintaining these tools do not always appreciate the needs of research biologists. Results BIRCH (Biological Research Computing Hierarchy is an organizational framework for delivering bioinformatics resources to a user group, scaling from a single lab to a large institution. The BIRCH core distribution includes many popular bioinformatics programs, unified within the GDE (Genetic Data Environment graphic interface. Of equal importance, BIRCH provides the system administrator with tools that simplify the job of managing a multiuser bioinformatics system across different platforms and operating systems. These include tools for integrating locally-installed programs and databases into BIRCH, and for customizing the local BIRCH system to meet the needs of the user base. BIRCH can also act as a front end to provide a unified view of already-existing collections of bioinformatics software. Documentation for the BIRCH and locally-added programs is merged in a hierarchical set of web pages. In addition to manual pages for individual programs, BIRCH tutorials employ step by step examples, with screen shots and sample files, to illustrate both the important theoretical and practical considerations behind complex analytical tasks. Conclusion BIRCH provides a versatile organizational framework for managing software and databases, and making these accessible to a user base. Because of its network-centric design, BIRCH makes it possible for any user to do any task from anywhere.
ABSTRACT:The traditional methods for mining foods for bioactive peptides are tedious and long. Similar to the drug industry, the length of time to identify and deliver a commercial health ingredient that reduces disease symptoms can take anything between 5 to 10 years. Reducing this time and effort is crucial in order to create new commercially viable products with clear and important health benefits. In the past few years, bioinformatics, the science that brings together fast computational b...
Knox Barry E; Qin Maochun; McIlvain Vera A; Danko Charles G; Pertsov Arkady M
Abstract Background Cell specific gene expression is largely regulated by different combinations of transcription factors that bind cis-elements in the upstream promoter sequence. However, experimental detection of cis-elements is difficult, expensive, and time-consuming. This provides a motivation for developing bioinformatic methods to identify cis-elements that could prioritize future experimental studies. Here, we use motif discovery algorithms to predict transcription factor binding site...
Yang, Jack Y; Yang, Mary Qu; Zhu, Mengxia (Michelle); Arabnia, Hamid R; Deng, Youping
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 personali...
Om Prakash Sharma; Yellamandaya Vadlamudi; Arun Gupta Kota; Vikrant Kumar Sinha; Muthuvel Suresh Kumar
This review article discusses the current scenario of the national and international burden due to lymphatic filariasis (LF) and describes the active elimination programmes for LF and their achievements to eradicate this most debilitating disease from the earth. Since, bioinformatics is a rapidly growing field of biological study, and it has an increasingly significant role in various fields of biology. We have reviewed its leading involvement in the filarial research using different approach...
Karikari, Thomas K.; Emmanuel Quansah; Wael M.Y. Mohamed
Research in bioinformatics has a central role in helping to advance biomedical research. However, its introduction to Africa has been met with some challenges (such as inadequate infrastructure, training opportunities, research funding, human resources, biorepositories and databases) that have contributed to the slow pace of development in this field across the continent. Fortunately, recent improvements in areas such as research funding, infrastructural support and capacity building are help...
Brooksbank, Catherine; Cameron, Graham; Thornton, Janet
The wide uptake of next-generation sequencing and other ultra-high throughput technologies by life scientists with a diverse range of interests, spanning fundamental biological research, medicine, agriculture and environmental science, has led to unprecedented growth in the amount of data generated. It has also put the need for unrestricted access to biological data at the centre of biology. The European Bioinformatics Institute (EMBL-EBI) is unique in Europe and is one of only two organisati...
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
"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
Arabnia Hamid R; Zhu Mengxia; Yang Mary Qu; Yang Jack Y; Deng Youping
Abstract 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 ...
Structural bioinformatics deals with the analysis, classification and prediction of three-dimensional structures of biomacromolecules. It is becoming increasingly important as the number of structures is growing rapidly. This thesis describes three studies concerned with protein-function prediction and two studies about protein structure validation. New protein structures are often compared to known structures to find out if they have a known fold, which may provide hints about their function...
Siva Kiran RR; Setty MVN; Hanumatha Rao G
Database of Biological/Bioinformatics Databases (DBD) is a collection of 1669 databases and online resources collected from NAR Database Summary Papers (http://www.oxfordjournals.org/nar/database/a/) & Internet search engines. The database has been developed based on 437 keywords (Glossary) available in http://falcon.roswellpark.org/labweb/glossary.html. Keywords with their relevant databases are arranged in alphabetic order which enables quick accession of databases by researchers. Dat...
Wightman, Bruce; Hark, Amy T
The development of fields such as bioinformatics and genomics has created new challenges and opportunities for undergraduate biology curricula. Students preparing for careers in science, technology, and medicine need more intensive study of bioinformatics and more sophisticated training in the mathematics on which this field is based. In this study, we deliberately integrated bioinformatics instruction at multiple course levels into an existing biology curriculum. Students in an introductory biology course, intermediate lab courses, and advanced project-oriented courses all participated in new course components designed to sequentially introduce bioinformatics skills and knowledge, as well as computational approaches that are common to many bioinformatics applications. In each course, bioinformatics learning was embedded in an existing disciplinary instructional sequence, as opposed to having a single course where all bioinformatics learning occurs. We designed direct and indirect assessment tools to follow student progress through the course sequence. Our data show significant gains in both student confidence and ability in bioinformatics during individual courses and as course level increases. Despite evidence of substantial student learning in both bioinformatics and mathematics, students were skeptical about the link between learning bioinformatics and learning mathematics. While our approach resulted in substantial learning gains, student "buy-in" and engagement might be better in longer project-based activities that demand application of skills to research problems. Nevertheless, in situations where a concentrated focus on project-oriented bioinformatics is not possible or desirable, our approach of integrating multiple smaller components into an existing curriculum provides an alternative. PMID:22987552
Full Text Available Abstract The availability of bioinformatics web-based services is rapidly proliferating, for their interoperability and ease of use. The next challenge is in the integration of these services in the form of workflows, and several projects are already underway, standardizing the syntax, semantics, and user interfaces. In order to deploy the advantages of web services with locally installed tools, here we describe a collection of proxy client tools for 42 major bioinformatics web services in the form of European Molecular Biology Open Software Suite (EMBOSS UNIX command-line tools. EMBOSS provides sophisticated means for discoverability and interoperability for hundreds of tools, and our package, named the Keio Bioinformatics Web Service (KBWS, adds functionalities of local and multiple alignment of sequences, phylogenetic analyses, and prediction of cellular localization of proteins and RNA secondary structures. This software implemented in C is available under GPL from http://www.g-language.org/kbws/ and GitHub repository http://github.com/cory-ko/KBWS. Users can utilize the SOAP services implemented in Perl directly via WSDL file at http://soap.g-language.org/kbws.wsdl (RPC Encoded and http://soap.g-language.org/kbws_dl.wsdl (Document/literal.
Hack, Catherine; Kendall, Gary
It is widely predicted that the application of high-throughput technologies to the quantification and identification of biological molecules will cause a paradigm shift in the life sciences. However, if the biosciences are to evolve from a predominantly descriptive discipline to an information science, practitioners will require enhanced skills in mathematics, computing, and statistical analysis. Universities have responded to the widely perceived skills gap primarily by developing masters programs in bioinformatics, resulting in a rapid expansion in the provision of postgraduate bioinformatics education. There is, however, a clear need to improve the quantitative and analytical skills of life science undergraduates. This article reviews the response of academia in the United Kingdom and proposes the learning outcomes that graduates should achieve to cope with the new biology. While the analysis discussed here uses the development of bioinformatics education in the United Kingdom as an illustrative example, it is hoped that the issues raised will resonate with all those involved in curriculum development in the life sciences. PMID:21638550
Gillings Michael R
Full Text Available Abstract Background 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. Results 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/ Conclusion 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.
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.
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
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
Xu, Joshua; Kelly, Reagan; Zhou, Guangxu; Turner, Steven A; Ding, Don; Harris, Stephen C; Hong, Huixiao; Fang, Hong; Tong, Weida
A genetic association study is a complicated process that involves collecting phenotypic data, generating genotypic data, analyzing associations between genotypic and phenotypic data, and interpreting genetic biomarkers identified. SNPTrack is an integrated bioinformatics system developed by the US Food and Drug Administration (FDA) to support the review and analysis of pharmacogenetics data resulting from FDA research or submitted by sponsors. The system integrates data management, analysis, and interpretation in a single platform for genetic association studies. Specifically, it stores genotyping data and single-nucleotide polymorphism (SNP) annotations along with study design data in an Oracle database. It also integrates popular genetic analysis tools, such as PLINK and Haploview. SNPTrack provides genetic analysis capabilities and captures analysis results in its database as SNP lists that can be cross-linked for biological interpretation to gene/protein annotations, Gene Ontology, and pathway analysis data. With SNPTrack, users can do the entire stream of bioinformatics jobs for genetic association studies. SNPTrack is freely available to the public at http://www.fda.gov/ScienceResearch/BioinformaticsTools/SNPTrack/default.htm. PMID:23245293
Full Text Available Bioinformatics is the permutation and mishmash of biological science and 4IT. The discipline covers every computational tools and techniques used to administer, examine and manipulate huge sets of biological statistics. The discipline also helps in creation of databases to store up and supervise biological statistics, improvement of computer algorithms to find out relations in these databases and use of computer tools for the study and understanding of biological information, including DNA, RNA, protein sequences, gene expression profiles, protein structures, and biochemical pathways. The study of this paper implements an integrative solution. As we know that solution to a problem in a specific discipline may be a solution to another problem in a different discipline. For example entropy that has been rented from physical sciences is solution to most of the problems and issues in computer science. Another example is bioinformatics, where computing method and applications are implemented over biological information. This paper shows an initiative step towards that and will discuss upon the needs for integration of multiple discipline and sciences. Similarly green chemistry gives birth to a new kind of computing i.e. green computing. In next versions of this paper we will study biological fuel cell and will discuss to develop a mobile battery that will be life time charged using the concepts of biological fuel cell. Another issue that we are going to discuss in our series is brain tumor detection. This paper is a review on BI i.e. bioinformatics to start with.
Attwood, Teresa K; Atwood, Teresa K; Bongcam-Rudloff, Erik; Brazas, Michelle E; Corpas, Manuel; Gaudet, Pascale; Lewitter, Fran; Mulder, Nicola; Palagi, Patricia M; Schneider, Maria Victoria; van Gelder, Celia W G
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
Bansal Arvind K
Full Text Available Abstract The revolutionary growth in the computation speed and memory storage capability has fueled a new era in the analysis of biological data. Hundreds of microbial genomes and many eukaryotic genomes including a cleaner draft of human genome have been sequenced raising the expectation of better control of microorganisms. The goals are as lofty as the development of rational drugs and antimicrobial agents, development of new enhanced bacterial strains for bioremediation and pollution control, development of better and easy to administer vaccines, the development of protein biomarkers for various bacterial diseases, and better understanding of host-bacteria interaction to prevent bacterial infections. In the last decade the development of many new bioinformatics techniques and integrated databases has facilitated the realization of these goals. Current research in bioinformatics can be classified into: (i genomics – sequencing and comparative study of genomes to identify gene and genome functionality, (ii proteomics – identification and characterization of protein related properties and reconstruction of metabolic and regulatory pathways, (iii cell visualization and simulation to study and model cell behavior, and (iv application to the development of drugs and anti-microbial agents. In this article, we will focus on the techniques and their limitations in genomics and proteomics. Bioinformatics research can be classified under three major approaches: (1 analysis based upon the available experimental wet-lab data, (2 the use of mathematical modeling to derive new information, and (3 an integrated approach that integrates search techniques with mathematical modeling. The major impact of bioinformatics research has been to automate the genome sequencing, automated development of integrated genomics and proteomics databases, automated genome comparisons to identify the genome function, automated derivation of metabolic pathways, gene
Full Text Available Language WorkBenches (LWBs are software engineering tools that help domain experts develop solutions to various classes of problems. Some of these tools focus on non-technical users and provide languages to help organize knowledge while other workbenches provide means to create new programming languages. A key advantage of language workbenches is that they support the seamless composition of independently developed languages. This capability is useful when developing programs that can benefit from different levels of abstraction. We reasoned that language workbenches could be useful to develop bioinformatics software solutions. In order to evaluate the potential of language workbenches in bioinformatics, we tested a prominent workbench by developing an alternative to shell scripting. To illustrate what LWBs and Language Composition can bring to bioinformatics, we report on our design and development of NYoSh (Not Your ordinary Shell. NYoSh was implemented as a collection of languages that can be composed to write programs as expressive and concise as shell scripts. This manuscript offers a concrete illustration of the advantages and current minor drawbacks of using the MPS LWB. For instance, we found that we could implement an environment-aware editor for NYoSh that can assist the programmers when developing scripts for specific execution environments. This editor further provides semantic error detection and can be compiled interactively with an automatic build and deployment system. In contrast to shell scripts, NYoSh scripts can be written in a modern development environment, supporting context dependent intentions and can be extended seamlessly by end-users with new abstractions and language constructs. We further illustrate language extension and composition with LWBs by presenting a tight integration of NYoSh scripts with the GobyWeb system. The NYoSh Workbench prototype, which implements a fully featured integrated development environment
Simi, Manuele; Campagne, Fabien
Language WorkBenches (LWBs) are software engineering tools that help domain experts develop solutions to various classes of problems. Some of these tools focus on non-technical users and provide languages to help organize knowledge while other workbenches provide means to create new programming languages. A key advantage of language workbenches is that they support the seamless composition of independently developed languages. This capability is useful when developing programs that can benefit from different levels of abstraction. We reasoned that language workbenches could be useful to develop bioinformatics software solutions. In order to evaluate the potential of language workbenches in bioinformatics, we tested a prominent workbench by developing an alternative to shell scripting. To illustrate what LWBs and Language Composition can bring to bioinformatics, we report on our design and development of NYoSh (Not Your ordinary Shell). NYoSh was implemented as a collection of languages that can be composed to write programs as expressive and concise as shell scripts. This manuscript offers a concrete illustration of the advantages and current minor drawbacks of using the MPS LWB. For instance, we found that we could implement an environment-aware editor for NYoSh that can assist the programmers when developing scripts for specific execution environments. This editor further provides semantic error detection and can be compiled interactively with an automatic build and deployment system. In contrast to shell scripts, NYoSh scripts can be written in a modern development environment, supporting context dependent intentions and can be extended seamlessly by end-users with new abstractions and language constructs. We further illustrate language extension and composition with LWBs by presenting a tight integration of NYoSh scripts with the GobyWeb system. The NYoSh Workbench prototype, which implements a fully featured integrated development environment for NYoSh is
Jayaraman, V. K.; Sundararajan, V.
Conventional linear & nonlinear tools for classification, regression & data driven modeling are being replaced on a rapid scale by newer techniques & tools based on artificial intelligence and machine learning. While the linear techniques are not applicable for inherently nonlinear problems, newer methods serve as attractive alternatives for solving real life problems. Support Vector Machine (SVM) classifiers are a set of universal feed-forward network based classification algorithms that have been formulated from statistical learning theory and structural risk minimization principle. SVM regression closely follows the classification methodology. In this work recent applications of SVM in Chemo & Bioinformatics will be described with suitable illustrative examples.
Tusch, Guenter; Bretl, Chris; O'Connor, Martin; Connor, Martin; Das, Amar
Mining large clinical and bioinformatics databases often includes exploration of temporal data. E.g., in liver transplantation, researchers might look for patients with an unusual time pattern of potential complications of the liver. In Knowledge-based Temporal Abstraction time-stamped data points are transformed into an interval-based representation. We extended this framework by creating an open-source platform, SPOT. It supports the R statistical package and knowledge representation standards (OWL, SWRL) using the open source Semantic Web tool Protégé-OWL. PMID:18999225
Salmonellas are the main responsible agent for the frequent food-borne gastrointestinal diseases. Their detection using classical methods are laborious and their results take a lot of time to be revealed. In this context, we tried to set up a revealing technique of the invA virulence gene, found in the majority of Salmonella species. After amplification with PCR using specific primers created and verified by bioinformatics programs, two couples of primers were set up and they appeared to be very specific and sensitive for the detection of invA gene. (Author)
Lopez, Rodrigo; Silventoinen, Ville; Robinson, Stephen; Kibria, Asif; Gish, Warren
Since 1995, the WU-BLAST programs (http://blast.wustl.edu) have provided a fast, flexible and reliable method for similarity searching of biological sequence databases. The software is in use at many locales and web sites. The European Bioinformatics Institute's WU-Blast2 (http://www.ebi.ac.uk/blast2/) server has been providing free access to these search services since 1997 and today supports many features that both enhance the usability and expand on the scope of the software.
Due to rapid accumulation of biological data, bioinformatics has become a very important branch of biological research. In this thesis, we develop novel bioinformatic approaches and aid design of biological experiments by using ideas and methods from statistical physics. Identification of transcription factor binding sites within the regulatory segments of genomic DNA is an important step towards understanding of the regulatory circuits that control expression of genes. We propose a novel, biophysics based algorithm, for the supervised detection of transcription factor (TF) binding sites. The method classifies potential binding sites by explicitly estimating the sequence-specific binding energy and the chemical potential of a given TF. In contrast with the widely used information theory based weight matrix method, our approach correctly incorporates saturation in the transcription factor/DNA binding probability. This results in a significant reduction in the number of expected false positives, and in the explicit appearance---and determination---of a binding threshold. The new method was used to identify likely genomic binding sites for the Escherichia coli TFs, and to examine the relationship between TF binding specificity and degree of pleiotropy (number of regulatory targets). We next address how parameters of protein-DNA interactions can be obtained from data on protein binding to random oligos under controlled conditions (SELEX experiment data). We show that 'robust' generation of an appropriate data set is achieved by a suitable modification of the standard SELEX procedure, and propose a novel bioinformatic algorithm for analysis of such data. Finally, we use quantitative data analysis, bioinformatic methods and kinetic modeling to analyze gene expression strategies of bacterial viruses. We study bacteriophage Xp10 that infects rice pathogen Xanthomonas oryzae. Xp10 is an unusual bacteriophage, which has morphology and genome organization that most closely
Skarzyńska, Agnieszka; Pawełkowicz, Magdalena; Krzywkowski, Tomasz; Świerkula, Katarzyna; PlÄ der, Wojciech; Przybecki, Zbigniew
The new sequencing methods, called Next Generation Sequencing gives an opportunity to possess a vast amount of data in short time. This data requires structural and functional annotation. Functional identification and characterization of predicted proteins could be done by in silico approches, thanks to a numerous computational tools available nowadays. However, there is a need to confirm the results of proteins function prediction using different programs and comparing the results or confirm experimentally. Here we present a bioinformatics pipeline for structural and functional annotation of proteins.
Wiwanitkit, Somsri; Wiwanitkit, Viroj
The role of microRNA in the pathogenesis of pulmonary tuberculosis is the interesting topic in chest medicine at present. Recently, it was proposed that the microRNA can be a useful biomarker for monitoring of pulmonary tuberculosis and might be the important part in pathogenesis of disease. Here, the authors perform a bioinformatics study to assess the microRNA within known tuberculosis RNA. The microRNA part can be detected and this can be important key information in further study of the p...
Greenwood, M.; Goble, C.A.; Stevens, R. D.; Zhao, J.(Central China Normal University (HZNU), Wuhan, 430079, China); Addis, M; Marvin, D; Moreau, L; Oinn, T.
Like experiments performed at a laboratory bench, the data associated with an e-Science experiment are of reduced value if other scientists are not able to identify the origin, or provenance, of those data. Provenance information is essential if experiments are to be validated and verified by others, or even by those who originally performed them. In this article, we give an overview of our initial work on the provenance of bioinformatics e-Science experiments within myGrid. We use two kinds ...
Alva, V.; Nam, S.; Söding, J.; Lupas, A.
The MPI Bioinformatics Toolkit (http://toolkit.tuebingen.mpg.de) is an open, interactive web service for comprehensive and collaborative protein bioinformatic analysis. It offers a wide array of interconnected, state-of-the-art bioinformatics tools to experts and non-experts alike, developed both externally (e.g. BLAST+, HMMER3, MUSCLE) and internally (e.g. HHpred, HHblits, PCOILS). While a beta version of the Toolkit was released 10 years ago, the current production-level release has been av...
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...
Qiao, Li-An; Zhu, Jing; Liu, Qingyan; Zhu, Tao; Song, Chi; Lin, Wei; Wei, Guozhu; Mu, Lisen; Tao, Jiang; Zhao, Nanming; Yang, Guangwen; Liu, Xiangjun
The integration of bioinformatics resources worldwide is one of the major concerns of the biological community. We herein established the BOD (Bioinformatics on demand) system to use Grid computing technology to set up a virtual workbench via a web-based platform, to assist researchers performing customized comprehensive bioinformatics work. Users will be able to submit entire search queries and computation requests, e.g. from DNA assembly to gene prediction and finally protein folding, from ...
Machanick, Philip; Bishop, Ozlem Tastan
The Research Unit in Bioinformatics at Rhodes University (RUBi), South Africa offers a Masters of Science in Bioinformatics. Growing demand for Bioinformatics qualifications results in applications from across Africa. Courses aim to bridge gaps in the diverse backgrounds of students who range from biologists with no prior computing exposure to computer scientists with no biology background. The programme is evenly split between coursework and research, with diverse modules from a range of dep...
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.
Yang, Mary Qu; Niemierko, Andrzej; Yang, Jack Y; Jin, Yufang
Bioinformatics and systems biology are two booming research areas studying live organisms. Though having different focuses, bioinformatics and systems biology often share same or similar engineering and computer science methods to elucidate the mechanisms of multi-level biological systems. Regulatory mechanisms underlying biological processes involve interactions at cellular, sub-cellular, genomic and genetic levels. Accordingly, we need to bridge the gaps of biomedical researches at different levels of studies and foster the interdisciplinary and multidisciplinary research between both bioinformatics and systems biology domains. The synergic research on integrating bioinformatics and systems biology facilitates the advances in biology and medicine. PMID:20090160
Song, Min; Yang, Christopher C; Tang, Xuning
Bioinformatics is an interdisciplinary research field that applies advanced computational techniques to biological data. Bibliometrics analysis has recently been adopted to understand the knowledge structure of a research field by citation pattern. In this paper, we explore the knowledge structure of Bioinformatics from the perspective of a core open access Bioinformatics journal, BMC Bioinformatics with trend analysis, the content and co-authorship network similarity, and principal component analysis. Publications in four core journals including Bioinformatics - Oxford Journal and four conferences in Bioinformatics were harvested from DBLP. After converting publications into TF-IDF term vectors, we calculate the content similarity, and we also calculate the social network similarity based on the co-authorship network by utilizing the overlap measure between two co-authorship networks. Key terms is extracted and analyzed with PCA, visualization of the co-authorship network is conducted. The experimental results show that Bioinformatics is fast-growing, dynamic and diversified. The content analysis shows that there is an increasing overlap among Bioinformatics journals in terms of topics and more research groups participate in researching Bioinformatics according to the co-authorship network similarity. PMID:23710427
McWilliam, Hamish; Valentin, Franck; Goujon, Mickael; Li, Weizhong; Narayanasamy, Menaka; Martin, Jenny; Miyar, Teresa; Lopez, Rodrigo
The European Bioinformatics Institute (EMBL-EBI) has been providing access to mainstream databases and tools in bioinformatics since 1997. In addition to the traditional web form based interfaces, APIs exist for core data resources such as EMBL-Bank, Ensembl, UniProt, InterPro, PDB and ArrayExpress. These APIs are based on Web Services (SOAP/REST) interfaces that allow users to systematically access databases and analytical tools. From the user's point of view, these Web Services provide the same functionality as the browser-based forms. However, using the APIs frees the user from web page constraints and are ideal for the analysis of large batches of data, performing text-mining tasks and the casual or systematic evaluation of mathematical models in regulatory networks. Furthermore, these services are widespread and easy to use; require no prior knowledge of the technology and no more than basic experience in programming. In the following we wish to inform of new and updated services as well as briefly describe planned developments to be made available during the course of 2009-2010. PMID:19435877
Pei-Ming Song; Yang Zhang; Yu-Fei He; Hui-Min Bao; Jian-Hua Luo; Yin-Kun Liu; Peng-Yuan Yang; Xian Chen
AIM: To analyze the metastasis-related proteins in hepatocellular carcinoma (HCC) and discover the biomark-er candidates for diagnosis and therapeutic intervention of HCC metastasis with bioinformatics tools.METHODS: Metastasis-related proteins were determined by stable isotope labeling and MS analysis and analyzed with bioinformatics resources, including Phobius, Kyoto encyclopedia of genes and genomes (KEGG), online mendelian inheritance in man (OHIH) and human protein reference database (HPRD).RESULTS: All the metastasis-related proteins were linked to 83 pathways in KEGG, including MAPK and p53 signal pathways. Protein-protein interaction network showed that all the metastasis-related proteins were categorized into 19 function groups, including cell cycle, apoptosis and signal transcluction. OMIM analysis linked these proteins to 186 OMIM entries.CONCLUSION: Metastasis-related proteins provide HCC cells with biological advantages in cell proliferation, migration and angiogenesis, and facilitate metastasis of HCC cells. The bird's eye view can reveal a global charac-teristic of metastasis-related proteins and many differen-tially expressed proteins can be identified as candidates for diagnosis and treatment of HCC.
Korhonen, Pasi K; Young, Neil D; Gasser, Robin B
Billions of people and animals are infected with parasitic worms (helminths). Many of these worms cause diseases that have a major socioeconomic impact worldwide, and are challenging to control because existing treatment methods are often inadequate. There is, therefore, a need to work toward developing new intervention methods, built on a sound understanding of parasitic worms at molecular level, the relationships that they have with their animal hosts and/or the diseases that they cause. Decoding the genomes and transcriptomes of these parasites brings us a step closer to this goal. The key focus of this article is to critically review and discuss bioinformatic tools used for the assembly and annotation of these genomes and transcriptomes, as well as various post-genomic analyses of transcription profiles, biological pathways, synteny, phylogeny, biogeography and the prediction and prioritisation of drug target candidates. Bioinformatic pipelines implemented and established recently provide practical and efficient tools for the assembly and annotation of genomes of parasitic worms, and will be applicable to a wide range of other parasites and eukaryotic organisms. Future research will need to assess the utility of long-read sequence data sets for enhanced genomic assemblies, and develop improved algorithms for gene prediction and post-genomic analyses, to enable comprehensive systems biology explorations of parasitic organisms. PMID:26956711
Full Text Available We propose the formation of an International PsychoSocial and Cultural Bioinformatics Project (IPCBP to explore the research foundations of Integrative Medical Insights (IMI on all levels from the molecular-genomic to the psychological, cultural, social, and spiritual. Just as The Human Genome Project identified the molecular foundations of modern medicine with the new technology of sequencing DNA during the past decade, the IPCBP would extend and integrate this neuroscience knowledge base with the technology of gene expression via DNA/proteomic microarray research and brain imaging in development, stress, healing, rehabilitation, and the psychotherapeutic facilitation of existentional wellness. We anticipate that the IPCBP will require a unique international collaboration of, academic institutions, researchers, and clinical practioners for the creation of a new neuroscience of mind-body communication, brain plasticity, memory, learning, and creative processing during optimal experiential states of art, beauty, and truth. We illustrate this emerging integration of bioinformatics with medicine with a videotape of the classical 4-stage creative process in a neuroscience approach to psychotherapy.
Yuen Macaire MS
Full Text Available Abstract Background We present a biological data warehouse called Atlas that locally stores and integrates biological sequences, molecular interactions, homology information, functional annotations of genes, and biological ontologies. The goal of the system is to provide data, as well as a software infrastructure for bioinformatics research and development. Description The Atlas system is based on relational data models that we developed for each of the source data types. Data stored within these relational models are managed through Structured Query Language (SQL calls that are implemented in a set of Application Programming Interfaces (APIs. The APIs include three languages: C++, Java, and Perl. The methods in these API libraries are used to construct a set of loader applications, which parse and load the source datasets into the Atlas database, and a set of toolbox applications which facilitate data retrieval. Atlas stores and integrates local instances of GenBank, RefSeq, UniProt, Human Protein Reference Database (HPRD, Biomolecular Interaction Network Database (BIND, Database of Interacting Proteins (DIP, Molecular Interactions Database (MINT, IntAct, NCBI Taxonomy, Gene Ontology (GO, Online Mendelian Inheritance in Man (OMIM, LocusLink, Entrez Gene and HomoloGene. The retrieval APIs and toolbox applications are critical components that offer end-users flexible, easy, integrated access to this data. We present use cases that use Atlas to integrate these sources for genome annotation, inference of molecular interactions across species, and gene-disease associations. Conclusion The Atlas biological data warehouse serves as data infrastructure for bioinformatics research and development. It forms the backbone of the research activities in our laboratory and facilitates the integration of disparate, heterogeneous biological sources of data enabling new scientific inferences. Atlas achieves integration of diverse data sets at two levels. First
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…
Background: Scientific research in bio-informatics is often data-driven and supported by biolog- ical databases. In a growing number of research projects, researchers like to ask questions that require the combination of information from more than one database. Most bio-informatics papers do not det
Likic, Vladimir A.
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…
Floraino, Wely B.
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…
Sutcliffe, Iain C.; Cummings, Stephen P.
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…
Wightman, Bruce; Hark, Amy T.
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…
Krilowicz, Beverly; Johnston, Wendie; Sharp, Sandra B.; Warter-Perez, Nancy; Momand, Jamil
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…
Gammeltoft, Steen; Christensen, Søren Tvorup; Joachimiak, Marcin;
Tetrahymena, bioinformatics, cilia, evolution, signaling, TtPTK1, PTK, Grb2, SH-PTP 2, Plcy, Src, PTP, PI3K, SH2, SH3, PH......Tetrahymena, bioinformatics, cilia, evolution, signaling, TtPTK1, PTK, Grb2, SH-PTP 2, Plcy, Src, PTP, PI3K, SH2, SH3, PH...
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…
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…
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...
Wefer, Stephen H.; Sheppard, Keith
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…
Grisham, William; Schottler, Natalie A.; Valli-Marill, Joanne; Beck, Lisa; Beatty, Jackson
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…
Effective tools for presenting and sharing data are necessary for collaborative projects, typical for bioinformatics. In order to facilitate sharing our data with other genomics, molecular biology, and bioinformatics researchers, we have developed software to export our data to GenBank and combined ...
Lim, Yun Ping; Hoog, Jan-Olov; Gardner, Phyllis; Ranganathan, Shoba; Andersson, Siv; Subbiah, Subramanian; Tan, Tin Wee; Hide, Winston; Weiss, Anthony S.
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…
Andrew F. Hill
Full Text Available Extracellular vesicles (EVs are the collective term for the various vesicles that are released by cells into the extracellular space. Such vesicles include exosomes and microvesicles, which vary by their size and/or protein and genetic cargo. With the discovery that EVs contain genetic material in the form of RNA (evRNA has come the increased interest in these vesicles for their potential use as sources of disease biomarkers and potential therapeutic agents. Rapid developments in the availability of deep sequencing technologies have enabled the study of EV-related RNA in detail. In October 2012, the International Society for Extracellular Vesicles (ISEV held a workshop on “evRNA analysis and bioinformatics.” Here, we report the conclusions of one of the roundtable discussions where we discussed evRNA analysis technologies and provide some guidelines to researchers in the field to consider when performing such analysis.
Zhou, Yinhua; Datta, Saheli; Salter, Charlotte
The governments of China, India, and the United Kingdom are unanimous in their belief that bioinformatics should supply the link between basic life sciences research and its translation into health benefits for the population and the economy. Yet at the same time, as ambitious states vying for position in the future global bioeconomy they differ considerably in the strategies adopted in pursuit of this goal. At the heart of these differences lies the interaction between epistemic change within the scientific community itself and the apparatus of the state. Drawing on desk-based research and thirty-two interviews with scientists and policy makers in the three countries, this article analyzes the politics that shape this interaction. From this analysis emerges an understanding of the variable capacities of different kinds of states and political systems to work with science in harnessing the potential of new epistemic territories in global life sciences innovation.
Block, Jeremy N.
The overall goal of this project is to enhance the physical accuracy of individual models in macromolecular NMR (Nuclear Magnetic Resonance) structures and the realism of variation within NMR ensembles of models, while improving agreement with the experimental data. A secondary overall goal is to combine synergistically the best aspects of NMR and crystallographic methodologies to better illuminate the underlying joint molecular reality. This is accomplished by using the powerful method of all-atom contact analysis (describing detailed sterics between atoms, including hydrogens); new graphical representations and interactive tools in 3D and virtual reality; and structural bioinformatics approaches to the expanded and enhanced data now available. The resulting better descriptions of macromolecular structure and its dynamic variation enhances the effectiveness of the many biomedical applications that depend on detailed molecular structure, such as mutational analysis, homology modeling, molecular simulations, protein design, and drug design.
Edgar Wingender; Torsten Crass; Jennifer D Hogan; Alexander E Kel; Olga V Kel-Margoulis; Anatolij P Potapov
Bioinformatics has delivered great contributions to genome and genomics research, without which the world-wide success of this and other global (‘omics’) approaches would not have been possible. More recently, it has developed further towards the analysis of different kinds of networks thus laying the foundation for comprehensive description, analysis and manipulation of whole living systems in modern ``systems biology”. The next step which is necessary for developing a systems biology that deals with systemic phenomena is to expand the existing and develop new methodologies that are appropriate to characterize intercellular processes and interactions without omitting the causal underlying molecular mechanisms. Modelling the processes on the different levels of complexity involved requires a comprehensive integration of information on gene regulatory events, signal transduction pathways, protein interaction and metabolic networks as well as cellular functions in the respective tissues/organs.
Walaa N. Ismail
Full Text Available Workflow systems by it’s nature can help bioin-formaticians to plan for their experiments, store, capture and analysis of the runtime generated data. On the other hand, the life science research usually produces new knowledge at an increasing speed; Knowledge such as papers, databases and other systems knowledge that a researcher needs to deal with is actually a complex task that needs much of efforts and time. Thus the management of knowledge is therefore an important issue for life scientists. Approaches has been developed to organize biological knowledge sources and to record provenance knowledge of an experiment into a readily resource are presently being carried out. This article focuses on the knowledge management of in silico experimentation in bioinformatics workflow systems.
Full Text Available Abstract Background Identifying the molecular interactions using bioinformatics tools before venturing into wet lab studies saves the energy and time considerably. The present study summarizes, molecular interactions and binding energy calculations made for major structural protein, collagen of Type I and Type III with the chosen cross-linkers, namely, coenzyme Q10, dopaquinone, embelin, embelin complex-1 & 2, idebenone, 5-O-methyl embelin, potassium embelate and vilangin. Results Molecular descriptive analyses suggest, dopaquinone, embelin, idebenone, 5-O-methyl embelin, and potassium embelate display nil violations. And results of docking analyses revealed, best affinity for Type I (- 4.74 kcal/mol and type III (-4.94 kcal/mol collagen was with dopaquinone. Conclusions Among the selected cross-linkers, dopaquinone, embelin, potassium embelate and 5-O-methyl embelin were the suitable cross-linkers for both Type I and Type III collagen and stabilizes the collagen at the expected level.
Cook, Charles E; Bergman, Mary Todd; Finn, Robert D; Cochrane, Guy; Birney, Ewan; Apweiler, Rolf
New technologies are revolutionising biological research and its applications by making it easier and cheaper to generate ever-greater volumes and types of data. In response, the services and infrastructure of the European Bioinformatics Institute (EMBL-EBI, www.ebi.ac.uk) are continually expanding: total disk capacity increases significantly every year to keep pace with demand (75 petabytes as of December 2015), and interoperability between resources remains a strategic priority. Since 2014 we have launched two new resources: the European Variation Archive for genetic variation data and EMPIAR for two-dimensional electron microscopy data, as well as a Resource Description Framework platform. We also launched the Embassy Cloud service, which allows users to run large analyses in a virtual environment next to EMBL-EBI's vast public data resources. PMID:26673705
Sequence alignment algorithms such as the Smith-Waterman algorithm are among the most important applications in the development of bioinformatics. Sequence alignment algorithms must process large amounts of data which may take a long time. Here, we introduce our Adaptive Hybrid Multiprocessor technique to accelerate the implementation of the Smith-Waterman algorithm. Our technique utilizes both the graphics processing unit (GPU) and the central processing unit (CPU). It adapts to the implementation according to the number of CPUs given as input by efficiently distributing the workload between the processing units. Using existing resources (GPU and CPU) in an efficient way is a novel approach. The peak performance achieved for the platforms GPU + CPU, GPU + 2CPUs, and GPU + 3CPUs is 10.4 GCUPS, 13.7 GCUPS, and 18.6 GCUPS, respectively (with the query length of 511 amino acid). © 2010 IEEE.
Kisiela, Michael; Skarka, Adam; Ebert, Bettina; Maser, Edmund
Steroidal compounds including cholesterol, bile acids and steroid hormones play a central role in various physiological processes such as cell signaling, growth, reproduction, and energy homeostasis. Hydroxysteroid dehydrogenases (HSDs), which belong to the superfamily of short-chain dehydrogenases/reductases (SDR) or aldo-keto reductases (AKR), are important enzymes involved in the steroid hormone metabolism. HSDs function as an enzymatic switch that controls the access of receptor-active steroids to nuclear hormone receptors and thereby mediate a fine-tuning of the steroid response. The aim of this study was the identification of classified functional HSDs and the bioinformatic annotation of these proteins in all complete sequenced bacterial genomes followed by a phylogenetic analysis. For the bioinformatic annotation we constructed specific hidden Markov models in an iterative approach to provide a reliable identification for the specific catalytic groups of HSDs. Here, we show a detailed phylogenetic analysis of 3α-, 7α-, 12α-HSDs and two further functional related enzymes (3-ketosteroid-Δ(1)-dehydrogenase, 3-ketosteroid-Δ(4)(5α)-dehydrogenase) from the superfamily of SDRs. For some bacteria that have been previously reported to posses a specific HSD activity, we could annotate the corresponding HSD protein. The dominating phyla that were identified to express HSDs were that of Actinobacteria, Proteobacteria, and Firmicutes. Moreover, some evolutionarily more ancient microorganisms (e.g., Cyanobacteria and Euryachaeota) were found as well. A large number of HSD-expressing bacteria constitute the normal human gastro-intestinal flora. Another group of bacteria were originally isolated from natural habitats like seawater, soil, marine and permafrost sediments. These bacteria include polycyclic aromatic hydrocarbons-degrading species such as Pseudomonas, Burkholderia and Rhodococcus. In conclusion, HSDs are found in a wide variety of microorganisms including
Gardner, S; Slezak, T
We summarize four of our group's high-risk/high-payoff research projects funded by the Intelligence Technology Innovation Center (ITIC) in conjunction with our DHS-funded pathogen informatics activities. These are (1) quantitative assessment of genomic sequencing needs to predict high quality DNA and protein signatures for detection, and comparison of draft versus finished sequences for diagnostic signature prediction; (2) development of forensic software to identify SNP and PCR-RFLP variations from a large number of viral pathogen sequences and optimization of the selection of markers for maximum discrimination of those sequences; (3) prediction of signatures for the detection of virulence, antibiotic resistance, and toxin genes and genetic engineering markers in bacteria; (4) bioinformatic characterization of virulence factors to rapidly screen genomic data for potential genes with similar functions and to elucidate potential health threats in novel organisms. The results of (1) are being used by policy makers to set national sequencing priorities. Analyses from (2) are being used in collaborations with the CDC to genotype and characterize many variola strains, and reports from these collaborations have been made to the President. We also determined SNPs for serotype and strain discrimination of 126 foot and mouth disease virus (FMDV) genomes. For (3), currently >1000 probes have been predicted for the specific detection of >4000 virulence, antibiotic resistance, and genetic engineering vector sequences, and we expect to complete the bioinformatic design of a comprehensive ''virulence detection chip'' by August 2005. Results of (4) will be a system to rapidly predict potential virulence pathways and phenotypes in organisms based on their genomic sequences.
Yalcin, Dicle; Hakguder, Zeynep M; Otu, Hasan H
Individual cells within the same population show various degrees of heterogeneity, which may be better handled with single-cell analysis to address biological and clinical questions. Single-cell analysis is especially important in developmental biology as subtle spatial and temporal differences in cells have significant associations with cell fate decisions during differentiation and with the description of a particular state of a cell exhibiting an aberrant phenotype. Biotechnological advances, especially in the area of microfluidics, have led to a robust, massively parallel and multi-dimensional capturing, sorting, and lysis of single-cells and amplification of related macromolecules, which have enabled the use of imaging and omics techniques on single cells. There have been improvements in computational single-cell image analysis in developmental biology regarding feature extraction, segmentation, image enhancement and machine learning, handling limitations of optical resolution to gain new perspectives from the raw microscopy images. Omics approaches, such as transcriptomics, genomics and epigenomics, targeting gene and small RNA expression, single nucleotide and structural variations and methylation and histone modifications, rely heavily on high-throughput sequencing technologies. Although there are well-established bioinformatics methods for analysis of sequence data, there are limited bioinformatics approaches which address experimental design, sample size considerations, amplification bias, normalization, differential expression, coverage, clustering and classification issues, specifically applied at the single-cell level. In this review, we summarize biological and technological advancements, discuss challenges faced in the aforementioned data acquisition and analysis issues and present future prospects for application of single-cell analyses to developmental biology. PMID:26358759
Rocha, Miguel; Fdez-Riverola, Florentino; Paz, Juan
This proceedings presents recent practical applications of Computational Biology and Bioinformatics. It contains the proceedings of the 9th International Conference on Practical Applications of Computational Biology & Bioinformatics held at University of Salamanca, Spain, at June 3rd-5th, 2015. The International Conference on Practical Applications of Computational Biology & Bioinformatics (PACBB) is an annual international meeting dedicated to emerging and challenging applied research in Bioinformatics and Computational Biology. Biological and biomedical research are increasingly driven by experimental techniques that challenge our ability to analyse, process and extract meaningful knowledge from the underlying data. The impressive capabilities of next generation sequencing technologies, together with novel and ever evolving distinct types of omics data technologies, have put an increasingly complex set of challenges for the growing fields of Bioinformatics and Computational Biology. The analysis o...
Kouskoumvekaki, Irene; Shublaq, Nour; Brunak, Søren
access to user-friendly solutions to navigate, integrate and extract information out of biological databases, as well as to combine tools and data resources in bioinformatics workflows. In this review, we present services that assist biomedical scientists in incorporating bioinformatics tools...... that facilitate the integration of biomedical ontologies and bioinformatics tools in computational workflows....
Römer, Michael; Eichner, Johannes; Dräger, Andreas; Wrzodek, Clemens; Wrzodek, Finja; Zell, Andreas
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
Full Text Available 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/.
Smith, David Roy
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
Cheung David W
Full Text Available Abstract Background Very often genome-wide data analysis requires the interoperation of multiple databases and analytic tools. A large number of genome databases and bioinformatics applications are available through the web, but it is difficult to automate interoperation because: 1 the platforms on which the applications run are heterogeneous, 2 their web interface is not machine-friendly, 3 they use a non-standard format for data input and output, 4 they do not exploit standards to define application interface and message exchange, and 5 existing protocols for remote messaging are often not firewall-friendly. To overcome these issues, web services have emerged as a standard XML-based model for message exchange between heterogeneous applications. Web services engines have been developed to manage the configuration and execution of a web services workflow. Results To demonstrate the benefit of using web services over traditional web interfaces, we compare the two implementations of HAPI, a gene expression analysis utility developed by the University of California San Diego (UCSD that allows visual characterization of groups or clusters of genes based on the biomedical literature. This utility takes a set of microarray spot IDs as input and outputs a hierarchy of MeSH Keywords that correlates to the input and is grouped by Medical Subject Heading (MeSH category. While the HTML output is easy for humans to visualize, it is difficult for computer applications to interpret semantically. To facilitate the capability of machine processing, we have created a workflow of three web services that replicates the HAPI functionality. These web services use document-style messages, which means that messages are encoded in an XML-based format. We compared three approaches to the implementation of an XML-based workflow: a hard coded Java application, Collaxa BPEL Server and Taverna Workbench. The Java program functions as a web services engine and interoperates
Full Text Available Bioinformatics emerged as a new discipline dedicated to the answer the queries about life science using computational approaches. The basic aim of bioinformatics is to create databases, analyse data sets and managing data generated through large-scale projects such as Human Genome project (HGP. It covers a wide variety of traditional computer science domains, such as data modeling, data retrieval, data mining, data integration, data managing, data warehousing, and simulation of biological information generated through laboratory and field experiments. Due to varied form, nature, and activities in the field of bioinformatics, presenting the information in cohesive fashion is major challenge. The bioinformatics information resources are heterogeneous in nature. Integration and interoperability of information is one of the biggest challenges in this field. Bioinformatics, as an emerging field, needs attention towards metadata application for resource discovery. This paper discusses the metadata element set description framework for integration of various information resources related to the field of bioinformatics available over internet. A web-based tool iBIRA: Integrated Bioinformatics Information Resources Access has been designed and developed for integration of bioinformatics information resources. Dublin Core metadata element set has been used for description of information resources and XML schema has been used for interoperability of information resources with others. A database has been designed using structure query language (SQL–database management system and hypertext preprocessor (PHP–as web programming languages for integration of bioinformatics resources. The database is designated to categorise various resources into biological database, institutions, journals, patents, software tools, web-servers, etc., and the search result is presented in the form of ‘tree view’. Each of these categories of the resources has been analysed
In this editorial preface,I briefly review cancer bioinformatics and introduce the four articles in this special issue highlighting important applications of the field:detection of chromatin states; detection of SNP-containing motifs and association with transcription factor-binding sites; improvements in functional enrichment modules; and gene association studies on aging and cancer.We expect this issue to provide bioinformatics scientists,cancer biologists,and clinical doctors with a better understanding of how cancer bioinformatics can be used to identify candidate biomarkers and targets and to conduct functional analysis.
Stockinger, Heinz; Altenhoff, Adrian M; Arnold, Konstantin; Bairoch, Amos; Bastian, Frederic; Bergmann, Sven; Bougueleret, Lydie; Bucher, Philipp; Delorenzi, Mauro; Lane, Lydie; Le Mercier, Philippe; Lisacek, Frédérique; Michielin, Olivier; Palagi, Patricia M; Rougemont, Jacques; Schwede, Torsten; von Mering, Christian; van Nimwegen, Erik; Walther, Daniel; Xenarios, Ioannis; Zavolan, Mihaela; Zdobnov, Evgeny M; Zoete, Vincent; Appel, Ron D
The SIB Swiss Institute of Bioinformatics (www.isb-sib.ch) was created in 1998 as an institution to foster excellence in bioinformatics. It is renowned worldwide for its databases and software tools, such as UniProtKB/Swiss-Prot, PROSITE, SWISS-MODEL, STRING, etc, that are all accessible on ExPASy.org, SIB's Bioinformatics Resource Portal. This article provides an overview of the scientific and training resources SIB has consistently been offering to the life science community for more than 15 years. PMID:24792157
Marcos R. Silva
Full Text Available This paper will discuss the development and role of the Convention’s Clearing-House Mechanism (CHM, its synergies with the Biosafety Clearing-House (BCH, and its support for bioinformatic initiatives in light of the Convention’s programme areas and cross-cutting issues. Within this context, the paper will also examine the significance of bioinformatics in assisting Parties to implement obligations under the Convention and the role of the CHM in facilitating activities by Parties and Governments to exploit the benefits arising from the evolving bioinformatics global infrastructure.
Full Text Available In this editorial preface, I briefly review cancer bioinformatics and introduce the four articles in this special issue highlighting important applications of the field: detection of chromatin states; detection of SNP-containing motifs and association with transcription factor-binding sites; improvements in functional enrichment modules; and gene association studies on aging and cancer. We expect this issue to provide bioinformatics scientists, cancer biologists, and clinical doctors with a better understanding of how cancer bioinformatics can be used to identify candidate biomarkers and targets and to conduct functional analysis.
Full Text Available WSSV is one of the most dangerous pathogens in shrimp aquaculture. However, the molecular mechanism of how WSSV interacts with shrimp is still not very clear. In the present study, bioinformatic approaches were used to predict interactions between proteins from WSSV and shrimp. The genome data of WSSV (NC_003225.1 and the constructed transcriptome data of F. chinensis were used to screen potentially interacting proteins by searching in protein interaction databases, including STRING, Reactome, and DIP. Forty-four pairs of proteins were suggested to have interactions between WSSV and the shrimp. Gene ontology analysis revealed that 6 pairs of these interacting proteins were classified into “extracellular region” or “receptor complex” GO-terms. KEGG pathway analysis showed that they were involved in the “ECM-receptor interaction pathway.” In the 6 pairs of interacting proteins, an envelope protein called “collagen-like protein” (WSSV-CLP encoded by an early virus gene “wsv001” in WSSV interacted with 6 deduced proteins from the shrimp, including three integrin alpha (ITGA, two integrin beta (ITGB, and one syndecan (SDC. Sequence analysis on WSSV-CLP, ITGA, ITGB, and SDC revealed that they possessed the sequence features for protein-protein interactions. This study might provide new insights into the interaction mechanisms between WSSV and shrimp.
Arancio, Walter; Pizzolanti, Giuseppe; Genovese, Swonild Ilenia; Baiamonte, Concetta; Giordano, Carla
We present a classic interactome bioinformatic analysis and a study on competing endogenous (ce) RNAs for hTERT. The hTERT gene codes for the catalytic subunit and limiting component of the human telomerase complex. Human telomerase reverse transcriptase (hTERT) is essential for the integrity of telomeres. Telomere dysfunctions have been widely reported to be involved in aging, cancer, and cellular senescence. The hTERT gene network has been analyzed using the BioGRID interaction database (http://thebiogrid.org/) and related analysis tools such as Osprey (http://biodata.mshri.on.ca/osprey/servlet/Index) and GeneMANIA (http://genemania.org/). The network of interaction of hTERT transcripts has been further analyzed following the competing endogenous (ce) RNA hypotheses (messenger [m] RNAs cross-talk via micro [mi] RNAs) using the miRWalk database and tools (www.ma.uni-heidelberg.de/apps/zmf/mirwalk/). These analyses suggest a role for Akt, nuclear factor-κB (NF-κB), heat shock protein 90 (HSP90), p70/p80 autoantigen, 14-3-3 proteins, and dynein in telomere functions. Roles for histone acetylation/deacetylation and proteoglycan metabolism are also proposed. PMID:24713059
Cutts, Rosalind J; Guerra-Assunção, José Afonso; Gadaleta, Emanuela; Dayem Ullah, Abu Z; Chelala, Claude
BCCTBbp (http://bioinformatics.breastcancertissue bank.org) was initially developed as the data-mining portal of the Breast Cancer Campaign Tissue Bank (BCCTB), a vital resource of breast cancer tissue for researchers to support and promote cutting-edge research. BCCTBbp is dedicated to maximising research on patient tissues by initially storing genomics, methylomics, transcriptomics, proteomics and microRNA data that has been mined from the literature and linking to pathways and mechanisms involved in breast cancer. Currently, the portal holds 146 datasets comprising over 227,795 expression/genomic measurements from various breast tissues (e.g. normal, malignant or benign lesions), cell lines and body fluids. BCCTBbp can be used to build on breast cancer knowledge and maximise the value of existing research. By recording a large number of annotations on samples and studies, and linking to other databases, such as NCBI, Ensembl and Reactome, a wide variety of different investigations can be carried out. Additionally, BCCTBbp has a dedicated analytical layer allowing researchers to further analyse stored datasets. A future important role for BCCTBbp is to make available all data generated on BCCTB tissues thus building a valuable resource of information on the tissues in BCCTB that will save repetition of experiments and expand scientific knowledge. PMID:25332396
Payne, Joshua L; Sinnott-Armstrong, Nicholas A; Moore, Jason H
Advances in the video gaming industry have led to the production of low-cost, high-performance graphics processing units (GPUs) that possess more memory bandwidth and computational capability than central processing units (CPUs), the standard workhorses of scientific computing. With the recent release of generalpurpose GPUs and NVIDIA's GPU programming language, CUDA, graphics engines are being adopted widely in scientific computing applications, particularly in the fields of computational biology and bioinformatics. The goal of this article is to concisely present an introduction to GPU hardware and programming, aimed at the computational biologist or bioinformaticist. To this end, we discuss the primary differences between GPU and CPU architecture, introduce the basics of the CUDA programming language, and discuss important CUDA programming practices, such as the proper use of coalesced reads, data types, and memory hierarchies. We highlight each of these topics in the context of computing the all-pairs distance between instances in a dataset, a common procedure in numerous disciplines of scientific computing. We conclude with a runtime analysis of the GPU and CPU implementations of the all-pairs distance calculation. We show our final GPU implementation to outperform the CPU implementation by a factor of 1700. PMID:20658333
Full Text Available Microsomes are derived mostly from endoplasmic reticulum and are an ideal target to investigate compound metabolism, membrane-bound enzyme functions, lipid-protein interactions, and drug-drug interactions. To better understand the molecular mechanisms of the liver and its diseases, mouse liver microsomes were isolated and enriched with differential centrifugation and sucrose gradient centrifugation, and microsome membrane proteins were further extracted from isolated microsomal fractions by the carbonate method. The enriched microsome proteins were arrayed with two-dimensional gel electrophoresis (2DE and carbonate-extracted microsome membrane proteins with one-dimensional gel electrophoresis (1DE. A total of 183 2DE-arrayed proteins and 99 1DE-separated proteins were identified with tandem mass spectrometry. A total of 259 nonredundant microsomal proteins were obtained and represent the proteomic profile of mouse liver microsomes, including 62 definite microsome membrane proteins. The comprehensive bioinformatics analyses revealed the functional categories of those microsome proteins and provided clues into biological functions of the liver. The systematic analyses of the proteomic profile of mouse liver microsomes not only reveal essential, valuable information about the biological function of the liver, but they also provide important reference data to analyze liver disease-related microsome proteins for biomarker discovery and mechanism clarification of liver disease.
A comprehensive range of mass spectrometric tools is required to investigate todays life science applications and a strong focus is on addressing the needs of functional proteomics. Application examples are given showing the streamlined process of protein identification from low femtomole amounts of digests. Sample preparation is achieved with a convertible robot for automated 2D gel picking, and MALDI target dispensing. MALDI-TOF or ESI-MS subsequent to enzymatic digestion. A choice of mass spectrometers including Q-q-TOF with multipass capability, MALDI-MS/MS with unsegmented PSD, Ion Trap and FT-MS are discussed for their respective strengths and applications. Bioinformatics software that allows both database work and novel peptide mass spectra interpretation is reviewed. The automated database searching uses either entire digest LC-MSn ESI Ion Trap data or MALDI MS and MS/MS spectra. It is shown how post translational modifications are interactively uncovered and de-novo sequencing of peptides is facilitated
Full Text Available As is well known, soil is a complex ecosystem harboring the most prokaryotic biodiversity on the Earth. In recent years, the advent of high-throughput sequencing techniques has greatly facilitated the progress of soil ecological studies. However, how to effectively understand the underlying biological features of large-scale sequencing data is a new challenge. In the present study, we used 33 publicly available metagenomes from diverse soil sites (i.e. grassland, forest soil, desert, Arctic soil, and mangrove sediment and integrated some state-of-the-art computational tools to explore the phylogenetic and functional characterizations of the microbial communities in soil. Microbial composition and metabolic potential in soils were comprehensively illustrated at the metagenomic level. A spectrum of metagenomic biomarkers containing 46 taxa and 33 metabolic modules were detected to be significantly differential that could be used as indicators to distinguish at least one of five soil communities. The co-occurrence associations between complex microbial compositions and functions were inferred by network-based approaches. Our results together with the established bioinformatic pipelines should provide a foundation for future research into the relation between soil biodiversity and ecosystem function.
Xu, Zhuofei; Hansen, Martin Asser; Hansen, Lars H; Jacquiod, Samuel; Sørensen, Søren J
As is well known, soil is a complex ecosystem harboring the most prokaryotic biodiversity on the Earth. In recent years, the advent of high-throughput sequencing techniques has greatly facilitated the progress of soil ecological studies. However, how to effectively understand the underlying biological features of large-scale sequencing data is a new challenge. In the present study, we used 33 publicly available metagenomes from diverse soil sites (i.e. grassland, forest soil, desert, Arctic soil, and mangrove sediment) and integrated some state-of-the-art computational tools to explore the phylogenetic and functional characterizations of the microbial communities in soil. Microbial composition and metabolic potential in soils were comprehensively illustrated at the metagenomic level. A spectrum of metagenomic biomarkers containing 46 taxa and 33 metabolic modules were detected to be significantly differential that could be used as indicators to distinguish at least one of five soil communities. The co-occurrence associations between complex microbial compositions and functions were inferred by network-based approaches. Our results together with the established bioinformatic pipelines should provide a foundation for future research into the relation between soil biodiversity and ecosystem function. PMID:24691166
Full Text Available We have applied bioinformatic approaches to identify pathways common to chemical leukemogens and to determine whether leukemogens could be distinguished from non-leukemogenic carcinogens. From all known and probable carcinogens classified by IARC and NTP, we identified 35 carcinogens that were associated with leukemia risk in human studies and 16 non-leukemogenic carcinogens. Using data on gene/protein targets available in the Comparative Toxicogenomics Database (CTD for 29 of the leukemogens and 11 of the non-leukemogenic carcinogens, we analyzed for enrichment of all 250 human biochemical pathways in the Kyoto Encyclopedia of Genes and Genomes (KEGG database. The top pathways targeted by the leukemogens included metabolism of xenobiotics by cytochrome P450, glutathione metabolism, neurotrophin signaling pathway, apoptosis, MAPK signaling, Toll-like receptor signaling and various cancer pathways. The 29 leukemogens formed 18 distinct clusters comprising 1 to 3 chemicals that did not correlate with known mechanism of action or with structural similarity as determined by 2D Tanimoto coefficients in the PubChem database. Unsupervised clustering and one-class support vector machines, based on the pathway data, were unable to distinguish the 29 leukemogens from 11 non-leukemogenic known and probable IARC carcinogens. However, using two-class random forests to estimate leukemogen and non-leukemogen patterns, we estimated a 76% chance of distinguishing a random leukemogen/non-leukemogen pair from each other.
Full Text Available Abstract Background Recent advances in genomic sequencing have enabled the use of genome sequencing in standard biological and biotechnological research projects. The challenge is how to integrate the large amount of data in order to gain novel biological insights. One way to leverage sequence data is to use genome-scale metabolic models. We have therefore designed and implemented a bioinformatics platform which supports the development of such metabolic models. Results MEMOSys (MEtabolic MOdel research and development System is a versatile platform for the management, storage, and development of genome-scale metabolic models. It supports the development of new models by providing a built-in version control system which offers access to the complete developmental history. Moreover, the integrated web board, the authorization system, and the definition of user roles allow collaborations across departments and institutions. Research on existing models is facilitated by a search system, references to external databases, and a feature-rich comparison mechanism. MEMOSys provides customizable data exchange mechanisms using the SBML format to enable analysis in external tools. The web application is based on the Java EE framework and offers an intuitive user interface. It currently contains six annotated microbial metabolic models. Conclusions We have developed a web-based system designed to provide researchers a novel application facilitating the management and development of metabolic models. The system is freely available at http://www.icbi.at/MEMOSys.
Full Text Available Mitogen‐activated protein kinase kinase kinase (MAPKKK is a component of the MAPK cascade pathway that plays an important role in plant growth, development, and response to abiotic stress, the functions of which have been well characterized in several plant species, such as Arabidopsis, rice, and maize. In this study, we performed genome‐wide and systemic bioinformatics analysis of MAPKKK family genes in Medicago truncatula. In total, there were 73 MAPKKK family members identified by search of homologs, and they were classified into three subfamilies, MEKK, ZIK, and RAF. Based on the genomic duplication function, 72 MtMAPKKK genes were located throughout all chromosomes, but they cluster in different chromosomes. Using microarray data and high‐throughput sequencing‐data, we assessed their expression profiles in growth and development processes; these results provided evidence for exploring their important functions in developmental regulation, especially in the nodulation process. Furthermore, we investigated their expression in abiotic stresses by RNA‐seq, which confirmed their critical roles in signal transduction and regulation processes under stress. In summary, our genome‐wide, systemic characterization and expressional analysis of MtMAPKKK genes will provide insights that will be useful for characterizing the molecular functions of these genes in M. truncatula.
Chen, Yian A.; Almeida, Jonas S.; Chou, Lien-Siang
Animal songs are frequently analyzed using discrete hierarchical units, such as units, themes and songs. Because animal songs and bio-sequences may be understood as analogous, bioinformatics analysis tools DNA/protein sequence alignment and alignment-free methods are proposed to quantify the theme similarities of the songs of false killer whales recorded off northeast Taiwan. The eighteen themes with discrete units that were identified in an earlier study [Y. A. Chen, masters thesis, University of Charleston, 2001] were compared quantitatively using several distance metrics. These metrics included the scores calculated using the Smith-Waterman algorithm with the repeated procedure; the standardized Euclidian distance and the angle metrics based on word frequencies. The theme classifications based on different metrics were summarized and compared in dendrograms using cluster analyses. The results agree with earlier classifications derived by human observation qualitatively. These methods further quantify the similarities among themes. These methods could be applied to the analyses of other animal songs on a larger scale. For instance, these techniques could be used to investigate song evolution and cultural transmission quantifying the dissimilarities of humpback whale songs across different seasons, years, populations, and geographic regions. [Work supported by SC Sea Grant, and Ilan County Government, Taiwan.
Zarzycki, Jan; Erbilgin, Onur; Kerfeld, Cheryl A
Bacterial microcompartments (BMCs) are proteinaceous organelles encapsulating enzymes that catalyze sequential reactions of metabolic pathways. BMCs are phylogenetically widespread; however, only a few BMCs have been experimentally characterized. Among them are the carboxysomes and the propanediol- and ethanolamine-utilizing microcompartments, which play diverse metabolic and ecological roles. The substrate of a BMC is defined by its signature enzyme. In catabolic BMCs, this enzyme typically generates an aldehyde. Recently, it was shown that the most prevalent signature enzymes encoded by BMC loci are glycyl radical enzymes, yet little is known about the function of these BMCs. Here we characterize the glycyl radical enzyme-associated microcompartment (GRM) loci using a combination of bioinformatic analyses and active-site and structural modeling to show that the GRMs comprise five subtypes. We predict distinct functions for the GRMs, including the degradation of choline, propanediol, and fuculose phosphate. This is the first family of BMCs for which identification of the signature enzyme is insufficient for predicting function. The distinct GRM functions are also reflected in differences in shell composition and apparently different assembly pathways. The GRMs are the counterparts of the vitamin B12-dependent propanediol- and ethanolamine-utilizing BMCs, which are frequently associated with virulence. This study provides a comprehensive foundation for experimental investigations of the diverse roles of GRMs. Understanding this plasticity of function within a single BMC family, including characterization of differences in permeability and assembly, can inform approaches to BMC bioengineering and the design of therapeutics. PMID:26407889