Deep learning in bioinformatics.

Science.gov (United States)

Min, Seonwoo; Lee, Byunghan; Yoon, Sungroh

2017-09-01

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

Mathematics and evolutionary biology make bioinformatics education comprehensible

Science.gov (United States)

Weisstein, Anton E.

2013-01-01

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

Mathematics and evolutionary biology make bioinformatics education comprehensible.

Science.gov (United States)

Jungck, John R; Weisstein, Anton E

2013-09-01

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

Meeting review: 2002 O'Reilly Bioinformatics Technology Conference.

Science.gov (United States)

Counsell, Damian

2002-01-01

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

Biggest challenges in bioinformatics.

Science.gov (United States)

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

2013-04-01

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

Biggest challenges in bioinformatics

OpenAIRE

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

2013-01-01

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

Establishing bioinformatics research in the Asia Pacific

Directory of Open Access Journals (Sweden)

Tammi Martti

2006-12-01

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

An innovative approach for testing bioinformatics programs using metamorphic testing

Directory of Open Access Journals (Sweden)

Liu Huai

2009-01-01

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

Gold nanoparticle-based beacon to detect STAT5b mRNA expression in living cells: a case optimized by bioinformatics screen.

Science.gov (United States)

Deng, Dawei; Li, Yang; Xue, Jianpeng; Wang, Jie; Ai, Guanhua; Li, Xin; Gu, Yueqing

2015-01-01

Messenger RNA (mRNA), a single-strand ribonucleic acid with functional gene information is usually abnormally expressed in cancer cells and has become a promising biomarker for the study of tumor progress. Hairpin DNA-coated gold nanoparticle (hDAuNP) beacon containing a bare gold nanoparticle (AuNP) as fluorescence quencher and thiol-terminated fluorescently labeled stem-loop-stem oligonucleotide sequences attached by Au-S bond is currently a new nanoscale biodiagnostic platform capable of mRNA detection, in which the design of the loop region sequence is crucial for hybridizing with the target mRNA. Hence, in this study, to improve the sensitivity and selectivity of hDAuNP beacon simultaneously, the loop region of hairpin DNA was screened by bioinformatics strategy. Here, signal transducer and activator of transcription 5b (STAT5b) mRNA was selected and used as a practical example. The results from the combined characterizations using optical techniques, flow cytometry assay, and cell microscopic imaging showed that after optimization, the as-prepared hDAuNP beacon had higher selectivity and sensitivity for the detection of STAT5b mRNA in living cells, as compared with our previous beacon. Thus, the bioinformatics method may be a promising new strategy for assisting in the designing of the hDAuNP beacon, extending its application in the detection of mRNA expression and the resultant mRNA-based biological processes and disease pathogenesis.

Preface to Introduction to Structural Bioinformatics

NARCIS (Netherlands)

Feenstra, K. Anton; Abeln, Sanne

2018-01-01

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

Detecting Microsatellites in Genome Data: Variance in Definitions and Bioinformatic Approaches Cause Systematic Bias

Directory of Open Access Journals (Sweden)

Angelika Merkel

2008-01-01

Full Text Available Microsatellites are currently one of the most commonly used genetic markers. The application of bioinformatic tools has become common practice in the study of these short tandem repeats (STR. However, in silico studies can suffer from study bias. Using a meta-analysis on microsatellite distribution in yeast we show that estimates of numbers of repeats reported by different studies can differ in the order of several magnitudes, even within a single genome. These differences arise because varying definitions of microsatellites, spanning repeat size, array length and array composition, are used in different search paradigms, with minimum array length being the main influencing factor. Structural differences in the implemented search algorithm additionally contribute to variation in the number of repeats detected. We suggest that for future studies a consistent approach to STR searches is adopted in order to improve the power of intra- and interspecific comparisons

COMPARISON OF POPULAR BIOINFORMATICS DATABASES

OpenAIRE

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

2016-01-01

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

A Reference Viral Database (RVDB) To Enhance Bioinformatics Analysis of High-Throughput Sequencing for Novel Virus Detection.

Science.gov (United States)

Goodacre, Norman; Aljanahi, Aisha; Nandakumar, Subhiksha; Mikailov, Mike; Khan, Arifa S

2018-01-01

Detection of distantly related viruses by high-throughput sequencing (HTS) is bioinformatically challenging because of the lack of a public database containing all viral sequences, without abundant nonviral sequences, which can extend runtime and obscure viral hits. Our reference viral database (RVDB) includes all viral, virus-related, and virus-like nucleotide sequences (excluding bacterial viruses), regardless of length, and with overall reduced cellular sequences. Semantic selection criteria (SEM-I) were used to select viral sequences from GenBank, resulting in a first-generation viral database (VDB). This database was manually and computationally reviewed, resulting in refined, semantic selection criteria (SEM-R), which were applied to a new download of updated GenBank sequences to create a second-generation VDB. Viral entries in the latter were clustered at 98% by CD-HIT-EST to reduce redundancy while retaining high viral sequence diversity. The viral identity of the clustered representative sequences (creps) was confirmed by BLAST searches in NCBI databases and HMMER searches in PFAM and DFAM databases. The resulting RVDB contained a broad representation of viral families, sequence diversity, and a reduced cellular content; it includes full-length and partial sequences and endogenous nonretroviral elements, endogenous retroviruses, and retrotransposons. Testing of RVDBv10.2, with an in-house HTS transcriptomic data set indicated a significantly faster run for virus detection than interrogating the entirety of the NCBI nonredundant nucleotide database, which contains all viral sequences but also nonviral sequences. RVDB is publically available for facilitating HTS analysis, particularly for novel virus detection. It is meant to be updated on a regular basis to include new viral sequences added to GenBank. IMPORTANCE To facilitate bioinformatics analysis of high-throughput sequencing (HTS) data for the detection of both known and novel viruses, we have

Establishing bioinformatics research in the Asia Pacific

OpenAIRE

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

2006-01-01

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

Bioinformatics: A History of Evolution "In Silico"

Science.gov (United States)

Ondrej, Vladan; Dvorak, Petr

2012-01-01

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

Generalized Centroid Estimators in Bioinformatics

Science.gov (United States)

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

2011-01-01

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

Introduction to bioinformatics.

Science.gov (United States)

Can, Tolga

2014-01-01

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

Bioinformatics clouds for big data manipulation.

Science.gov (United States)

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

2012-11-28

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

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

Science.gov (United States)

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

2016-12-22

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

Designing XML schemas for bioinformatics.

Science.gov (United States)

Bruhn, Russel Elton; Burton, Philip John

2003-06-01

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

Bioinformatics

DEFF Research Database (Denmark)

Baldi, Pierre; Brunak, Søren

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

Bioinformatics clouds for big data manipulation

Directory of Open Access Journals (Sweden)

Dai Lin

2012-11-01

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

Bioinformatics clouds for big data manipulation

KAUST Repository

Dai, Lin

2012-11-28

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

Group spike-and-slab lasso generalized linear models for disease prediction and associated genes detection by incorporating pathway information.

Science.gov (United States)

Tang, Zaixiang; Shen, Yueping; Li, Yan; Zhang, Xinyan; Wen, Jia; Qian, Chen'ao; Zhuang, Wenzhuo; Shi, Xinghua; Yi, Nengjun

2018-03-15

Large-scale molecular data have been increasingly used as an important resource for prognostic prediction of diseases and detection of associated genes. However, standard approaches for omics data analysis ignore the group structure among genes encoded in functional relationships or pathway information. We propose new Bayesian hierarchical generalized linear models, called group spike-and-slab lasso GLMs, for predicting disease outcomes and detecting associated genes by incorporating large-scale molecular data and group structures. The proposed model employs a mixture double-exponential prior for coefficients that induces self-adaptive shrinkage amount on different coefficients. The group information is incorporated into the model by setting group-specific parameters. We have developed a fast and stable deterministic algorithm to fit the proposed hierarchal GLMs, which can perform variable selection within groups. We assess the performance of the proposed method on several simulated scenarios, by varying the overlap among groups, group size, number of non-null groups, and the correlation within group. Compared with existing methods, the proposed method provides not only more accurate estimates of the parameters but also better prediction. We further demonstrate the application of the proposed procedure on three cancer datasets by utilizing pathway structures of genes. Our results show that the proposed method generates powerful models for predicting disease outcomes and detecting associated genes. The methods have been implemented in a freely available R package BhGLM (http://www.ssg.uab.edu/bhglm/). nyi@uab.edu. Supplementary data are available at Bioinformatics online.

Interdisciplinary Introductory Course in Bioinformatics

Science.gov (United States)

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

2010-01-01

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

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

Science.gov (United States)

Brazas, Michelle D; Ouellette, B F Francis

2013-09-01

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

Bioinformatics for Next Generation Sequencing Data

Directory of Open Access Journals (Sweden)

Alberto Magi

2010-09-01

Full Text Available The emergence of next-generation sequencing (NGS platforms imposes increasing demands on statistical methods and bioinformatic tools for the analysis and the management of the huge amounts of data generated by these technologies. Even at the early stages of their commercial availability, a large number of softwares already exist for analyzing NGS data. These tools can be fit into many general categories including alignment of sequence reads to a reference, base-calling and/or polymorphism detection, de novo assembly from paired or unpaired reads, structural variant detection and genome browsing. This manuscript aims to guide readers in the choice of the available computational tools that can be used to face the several steps of the data analysis workflow.

Taking Bioinformatics to Systems Medicine.

Science.gov (United States)

van Kampen, Antoine H C; Moerland, Perry D

2016-01-01

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

Crowdsourcing for bioinformatics.

Science.gov (United States)

Good, Benjamin M; Su, Andrew I

2013-08-15

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

Is there room for ethics within bioinformatics education?

Science.gov (United States)

Taneri, Bahar

2011-07-01

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

EURASIP journal on bioinformatics & systems biology

National Research Council Canada - National Science Library

2006-01-01

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

Virtual Bioinformatics Distance Learning Suite

Science.gov (United States)

Tolvanen, Martti; Vihinen, Mauno

2004-01-01

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

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

Science.gov (United States)

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

2010-11-27

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

Bioinformatics in translational drug discovery.

Science.gov (United States)

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

2017-08-31

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

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

Science.gov (United States)

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

2015-04-01

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

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

Science.gov (United States)

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

2015-01-01

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

Navigating the changing learning landscape: perspective from bioinformatics.ca

OpenAIRE

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

2013-01-01

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

A Bioinformatics Analysis Reveals a Group of MocR Bacterial Transcriptional Regulators Linked to a Family of Genes Coding for Membrane Proteins

Directory of Open Access Journals (Sweden)

Teresa Milano

2016-01-01

Full Text Available The MocR bacterial transcriptional regulators are characterized by an N-terminal domain, 60 residues long on average, possessing the winged-helix-turn-helix (wHTH architecture responsible for DNA recognition and binding, linked to a large C-terminal domain (350 residues on average that is homologous to fold type-I pyridoxal 5′-phosphate (PLP dependent enzymes like aspartate aminotransferase (AAT. These regulators are involved in the expression of genes taking part in several metabolic pathways directly or indirectly connected to PLP chemistry, many of which are still uncharacterized. A bioinformatics analysis is here reported that studied the features of a distinct group of MocR regulators predicted to be functionally linked to a family of homologous genes coding for integral membrane proteins of unknown function. This group occurs mainly in the Actinobacteria and Gammaproteobacteria phyla. An analysis of the multiple sequence alignments of their wHTH and AAT domains suggested the presence of specificity-determining positions (SDPs. Mapping of SDPs onto a homology model of the AAT domain hinted at possible structural/functional roles in effector recognition. Likewise, SDPs in wHTH domain suggested the basis of specificity of Transcription Factor Binding Site recognition. The results reported represent a framework for rational design of experiments and for bioinformatics analysis of other MocR subgroups.

Bioinformatics for cancer immunotherapy target discovery

DEFF Research Database (Denmark)

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

2014-01-01

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

Bioinformatics for Exploration

Science.gov (United States)

Johnson, Kathy A.

2006-01-01

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

The GMOD Drupal bioinformatic server framework.

Science.gov (United States)

Papanicolaou, Alexie; Heckel, David G

2010-12-15

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

Development and evaluation of a bioinformatics approach for designing molecular assays for viral detection.

Directory of Open Access Journals (Sweden)

Pierre H H Schneeberger

Full Text Available Viruses belonging to the Flaviviridae and Bunyaviridae families show considerable genetic diversity. However, this diversity is not necessarily taken into account when developing diagnostic assays, which are often based on the pairwise alignment of a limited number of sequences. Our objective was to develop and evaluate a bioinformatics workflow addressing two recurrent issues of molecular assay design: (i the high intraspecies genetic diversity in viruses and (ii the potential for cross-reactivity with close relatives.The workflow developed herein was based on two consecutive BLASTn steps; the first was utilized to select highly conserved regions among the viral taxon of interest, and the second was employed to assess the degree of similarity of these highly-conserved regions to close relatives. Subsequently, the workflow was tested on a set of eight viral species, including various strains from the Flaviviridae and Bunyaviridae families.The genetic diversity ranges from as low as 0.45% variable sites over the complete genome of the Japanese encephalitis virus to more than 16% of variable sites on segment L of the Crimean-Congo hemorrhagic fever virus. Our proposed bioinformatics workflow allowed the selection-based on computing scores-of the best target for a diagnostic molecular assay for the eight viral species investigated.Our bioinformatics workflow allowed rapid selection of highly conserved and specific genomic fragments among the investigated viruses, while considering up to several hundred complete genomic sequences. The pertinence of this workflow will increase in parallel to the number of sequences made publicly available. We hypothesize that our workflow might be utilized to select diagnostic molecular markers for higher organisms with more complex genomes, provided the sequences are made available.

[Pharmacogenetics II. Research molecular methods, bioinformatics and ethical concerns].

Science.gov (United States)

Daudén, E

2007-01-01

Pharmacogenetics refers to the study of the individual pharmacological response based on the genotype. Its objective is to optimize treatment in an individual basis, thereby creating a more efficient and safe personalized therapy. In the second part of this review, the molecular methods of study in pharmacogenetics, including microarray technology or DNA chips, are discussed. Among them we highlight the microarrays used to determine the gene expression that detect specific RNA sequences, and the microarrays employed to determine the genotype that detect specific DNA sequences, including polymorphisms, particularly single nucleotide polymorphisms (SNPs). The relationship between pharmacogenetics, bioinformatics and ethical concerns is reviewed.

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

Science.gov (United States)

Fristensky, Brian

2007-01-01

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

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

Directory of Open Access Journals (Sweden)

Fristensky Brian

2007-02-01

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

Component-Based Approach for Educating Students in Bioinformatics

Science.gov (United States)

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

2009-01-01

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

Phylogenetic trees in bioinformatics

Energy Technology Data Exchange (ETDEWEB)

Burr, Tom L [Los Alamos National Laboratory

2008-01-01

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

The GMOD Drupal Bioinformatic Server Framework

Science.gov (United States)

Papanicolaou, Alexie; Heckel, David G.

2010-01-01

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

Bioinformatics analysis identifies several intrinsically disordered human E3 ubiquitin-protein ligases

DEFF Research Database (Denmark)

Boomsma, Wouter Krogh; Nielsen, Sofie Vincents; Lindorff-Larsen, Kresten

2016-01-01

conduct a bioinformatics analysis to examine >600 human and S. cerevisiae E3 ligases to identify enzymes that are similar to San1 in terms of function and/or mechanism of substrate recognition. An initial sequence-based database search was found to detect candidates primarily based on the homology...

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

Science.gov (United States)

Nogaj, Luiza A.

2014-01-01

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

A Mathematical Optimization Problem in Bioinformatics

Science.gov (United States)

Heyer, Laurie J.

2008-01-01

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

Bioinformatics and Cancer

Science.gov (United States)

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

Biology in 'silico': The Bioinformatics Revolution.

Science.gov (United States)

Bloom, Mark

2001-01-01

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

Bioinformatics research in the Asia Pacific: a 2007 update.

Science.gov (United States)

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

2008-01-01

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

A Quick Guide for Building a Successful Bioinformatics Community

Science.gov (United States)

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

2015-01-01

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

MicroRNA from tuberculosis RNA: A bioinformatics study

OpenAIRE

Wiwanitkit, Somsri; Wiwanitkit, Viroj

2012-01-01

The role of microRNA in the pathogenesis of pulmonary tuberculosis is the interesting topic in chest medicine at present. Recently, it was proposed that the microRNA can be a useful biomarker for monitoring of pulmonary tuberculosis and might be the important part in pathogenesis of disease. Here, the authors perform a bioinformatics study to assess the microRNA within known tuberculosis RNA. The microRNA part can be detected and this can be important key information in further study of the p...

Challenge: A Multidisciplinary Degree Program in Bioinformatics

Directory of Open Access Journals (Sweden)

Mudasser Fraz Wyne

2006-06-01

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

When cloud computing meets bioinformatics: a review.

Science.gov (United States)

Zhou, Shuigeng; Liao, Ruiqi; Guan, Jihong

2013-10-01

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

Application of machine learning methods in bioinformatics

Science.gov (United States)

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

2018-05-01

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

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

DEFF Research Database (Denmark)

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

2010-01-01

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

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

Science.gov (United States)

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

2016-06-13

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

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

DEFF Research Database (Denmark)

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

2012-01-01

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

Planning bioinformatics workflows using an expert system

Science.gov (United States)

Chen, Xiaoling; Chang, Jeffrey T.

2017-01-01

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

Continuing Education Workshops in Bioinformatics Positively Impact Research and Careers.

Science.gov (United States)

Brazas, Michelle D; Ouellette, B F Francis

2016-06-01

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

Bioinformatics education dissemination with an evolutionary problem solving perspective.

Science.gov (United States)

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

2010-11-01

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

Using "Arabidopsis" Genetic Sequences to Teach Bioinformatics

Science.gov (United States)

Zhang, Xiaorong

2009-01-01

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

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

Science.gov (United States)

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

2017-09-01

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

Development of Bioinformatics Infrastructure for Genomics Research.

Science.gov (United States)

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

2017-06-01

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

Fuzzy Logic in Medicine and Bioinformatics

Directory of Open Access Journals (Sweden)

Angela Torres

2006-01-01

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

Online Bioinformatics Tutorials | Office of Cancer Genomics

Science.gov (United States)

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

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

Science.gov (United States)

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

2018-02-01

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

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

Science.gov (United States)

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

2018-01-01

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

4273π: bioinformatics education on low cost ARM hardware.

Science.gov (United States)

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

2013-08-12

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

OpenHelix: bioinformatics education outside of a different box.

Science.gov (United States)

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

2010-11-01

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

Translational Bioinformatics and Clinical Research (Biomedical) Informatics.

Science.gov (United States)

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

2015-06-01

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

Development of a cloud-based Bioinformatics Training Platform.

Science.gov (United States)

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

2017-05-01

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

Microsoft Biology Initiative: .NET Bioinformatics Platform and Tools

Science.gov (United States)

Diaz Acosta, B.

2011-01-01

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

Concepts and introduction to RNA bioinformatics

DEFF Research Database (Denmark)

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

2014-01-01

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

Adapting bioinformatics curricula for big data

Science.gov (United States)

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

2016-01-01

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

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

Science.gov (United States)

Rein, Diane C

2006-07-01

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

[Bioinformatics Analysis of Clustered Regularly Interspaced Short Palindromic Repeats in the Genomes of Shigella].

Science.gov (United States)

Wang, Pengfei; Wang, Yingfang; Duan, Guangcai; Xue, Zerun; Wang, Linlin; Guo, Xiangjiao; Yang, Haiyan; Xi, Yuanlin

2015-04-01

This study was aimed to explore the features of clustered regularly interspaced short palindromic repeats (CRISPR) structures in Shigella by using bioinformatics. We used bioinformatics methods, including BLAST, alignment and RNA structure prediction, to analyze the CRISPR structures of Shigella genomes. The results showed that the CRISPRs existed in the four groups of Shigella, and the flanking sequences of upstream CRISPRs could be classified into the same group with those of the downstream. We also found some relatively conserved palindromic motifs in the leader sequences. Repeat sequences had the same group with corresponding flanking sequences, and could be classified into two different types by their RNA secondary structures, which contain "stem" and "ring". Some spacers were found to homologize with part sequences of plasmids or phages. The study indicated that there were correlations between repeat sequences and flanking sequences, and the repeats might act as a kind of recognition mechanism to mediate the interaction between foreign genetic elements and Cas proteins.

Concepts Of Bioinformatics And Its Application In Veterinary ...

African Journals Online (AJOL)

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

Bioinformatics analysis of differentially expressed proteins in prostate cancer based on proteomics data

Directory of Open Access Journals (Sweden)

Chen C

2016-03-01

Full Text Available Chen Chen,1 Li-Guo Zhang,1 Jian Liu,1 Hui Han,1 Ning Chen,1 An-Liang Yao,1 Shao-San Kang,1 Wei-Xing Gao,1 Hong Shen,2 Long-Jun Zhang,1 Ya-Peng Li,1 Feng-Hong Cao,1 Zhi-Guo Li3 1Department of Urology, North China University of Science and Technology Affiliated Hospital, 2Department of Modern Technology and Education Center, 3Department of Medical Research Center, International Science and Technology Cooperation Base of Geriatric Medicine, North China University of Science and Technology, Tangshan, People’s Republic of China Abstract: We mined the literature for proteomics data to examine the occurrence and metastasis of prostate cancer (PCa through a bioinformatics analysis. We divided the differentially expressed proteins (DEPs into two groups: the group consisting of PCa and benign tissues (P&b and the group presenting both high and low PCa metastatic tendencies (H&L. In the P&b group, we found 320 DEPs, 20 of which were reported more than three times, and DES was the most commonly reported. Among these DEPs, the expression levels of FGG, GSN, SERPINC1, TPM1, and TUBB4B have not yet been correlated with PCa. In the H&L group, we identified 353 DEPs, 13 of which were reported more than three times. Among these DEPs, MDH2 and MYH9 have not yet been correlated with PCa metastasis. We further confirmed that DES was differentially expressed between 30 cancer and 30 benign tissues. In addition, DEPs associated with protein transport, regulation of actin cytoskeleton, and the extracellular matrix (ECM–receptor interaction pathway were prevalent in the H&L group and have not yet been studied in detail in this context. Proteins related to homeostasis, the wound-healing response, focal adhesions, and the complement and coagulation pathways were overrepresented in both groups. Our findings suggest that the repeatedly reported DEPs in the two groups may function as potential biomarkers for detecting PCa and predicting its aggressiveness. Furthermore

The secondary metabolite bioinformatics portal

DEFF Research Database (Denmark)

Weber, Tilmann; Kim, Hyun Uk

2016-01-01

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

BioWarehouse: a bioinformatics database warehouse toolkit.

Science.gov (United States)

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

2006-03-23

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

Bioinformatics approaches for identifying new therapeutic bioactive peptides in food

Directory of Open Access Journals (Sweden)

Nora Khaldi

2012-10-01

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

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

Science.gov (United States)

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

2009-01-01

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

A bioinformatics approach for identifying transgene insertion sites using whole genome sequencing data.

Science.gov (United States)

Park, Doori; Park, Su-Hyun; Ban, Yong Wook; Kim, Youn Shic; Park, Kyoung-Cheul; Kim, Nam-Soo; Kim, Ju-Kon; Choi, Ik-Young

2017-08-15

Genetically modified crops (GM crops) have been developed to improve the agricultural traits of modern crop cultivars. Safety assessments of GM crops are of paramount importance in research at developmental stages and before releasing transgenic plants into the marketplace. Sequencing technology is developing rapidly, with higher output and labor efficiencies, and will eventually replace existing methods for the molecular characterization of genetically modified organisms. To detect the transgenic insertion locations in the three GM rice gnomes, Illumina sequencing reads are mapped and classified to the rice genome and plasmid sequence. The both mapped reads are classified to characterize the junction site between plant and transgene sequence by sequence alignment. Herein, we present a next generation sequencing (NGS)-based molecular characterization method, using transgenic rice plants SNU-Bt9-5, SNU-Bt9-30, and SNU-Bt9-109. Specifically, using bioinformatics tools, we detected the precise insertion locations and copy numbers of transfer DNA, genetic rearrangements, and the absence of backbone sequences, which were equivalent to results obtained from Southern blot analyses. NGS methods have been suggested as an effective means of characterizing and detecting transgenic insertion locations in genomes. Our results demonstrate the use of a combination of NGS technology and bioinformatics approaches that offers cost- and time-effective methods for assessing the safety of transgenic plants.

Adapting bioinformatics curricula for big data.

Science.gov (United States)

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

2016-01-01

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

Application of Bioinformatics in Chronobiology Research

Directory of Open Access Journals (Sweden)

Robson da Silva Lopes

2013-01-01

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

Skate Genome Project: Cyber-Enabled Bioinformatics Collaboration

Science.gov (United States)

Vincent, J.

2011-01-01

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

BioWarehouse: a bioinformatics database warehouse toolkit

Directory of Open Access Journals (Sweden)

Stringer-Calvert David WJ

2006-03-01

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

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

Science.gov (United States)

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

2005-09-01

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

Evaluating an Inquiry-Based Bioinformatics Course Using Q Methodology

Science.gov (United States)

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

2008-01-01

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

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

Science.gov (United States)

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

2005-01-01

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

An Overview of Bioinformatics Tools and Resources in Allergy.

Science.gov (United States)

Fu, Zhiyan; Lin, Jing

2017-01-01

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

3D modelling of the pathogenic Leptospira protein LipL32: A bioinformatics approach.

Science.gov (United States)

Kumaran, Sharmilah Kumari; Bakar, Mohd Faizal Abu; Mohd-Padil, Hirzahida; Mat-Sharani, Shuhaila; Sakinah, S; Poorani, K; Alsaeedy, Hiba; Peli, Amira; Wei, Teh Seoh; Ling, Mok Pooi; Hamat, Rukman Awang; Neela, Vasantha Kumari; Higuchi, Akon; Alarfaj, Abdullah A; Rajan, Mariappan; Benelli, Giovanni; Arulselvan, Palanisamy; Kumar, S Suresh

2017-12-01

Leptospirosis is a widespread zoonotic disease caused by pathogenic Leptospira species (Leptospiraceae). LipL32 is an abundant lipoprotein from the outer membrane proteins (OMPs) group, highly conserved among pathogenic and intermediate Leptospira species. Several studies used LipL32 as a specific gene to identify the presence of leptospires. This research was aimed to study the characteristics of LipL32 protein gene code, to fill the knowledge gap concerning the most appropriate gene that can be used as antigen to detect the Leptospira. Here, we investigated the features of LipL32 in fourteen Leptospira pathogenic strains based on comparative analyses of their primary, secondary structures and 3D modeling using a bioinformatics approach. Furthermore, the physicochemical properties of LipL32 in different strains were studied, shedding light on the identity of signal peptides, as well as on the secondary and tertiary structure of the LipL32 protein, supported by 3D modelling assays. The results showed that the LipL32 gene was present in all the fourteen pathogenic Leptospira strains used in this study, with limited diversity in terms of sequence conservation, hydrophobic group, hydrophilic group and number of turns (random coil). Overall, these results add basic knowledge to the characteristics of LipL32 protein, contributing to the identification of potential antigen candidates in future research, in order to ensure prompt and reliable detection of pathogenic Leptospira species. Copyright © 2017 Elsevier B.V. All rights reserved.

Recent developments in life sciences research: Role of bioinformatics

African Journals Online (AJOL)

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

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

African Journals Online (AJOL)

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

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

Science.gov (United States)

Smith, David Roy

2015-07-01

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

Bioinformatics of cardiovascular miRNA biology.

Science.gov (United States)

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

2015-12-01

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

Assessment of a Bioinformatics across Life Science Curricula Initiative

Science.gov (United States)

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

2007-01-01

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

Incorporating Genomics and Bioinformatics across the Life Sciences Curriculum

Energy Technology Data Exchange (ETDEWEB)

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

2011-08-01

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

Bioinformatics-Aided Venomics

Directory of Open Access Journals (Sweden)

Quentin Kaas

2015-06-01

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

A Bioinformatics Facility for NASA

Science.gov (United States)

Schweighofer, Karl; Pohorille, Andrew

2006-01-01

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

Comprehensive decision tree models in bioinformatics.

Directory of Open Access Journals (Sweden)

Gregor Stiglic

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

Comprehensive decision tree models in bioinformatics.

Science.gov (United States)

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

2012-01-01

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

When process mining meets bioinformatics

NARCIS (Netherlands)

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

2011-01-01

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

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

CERN Document Server

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

2015-01-01

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

Bioconductor: open software development for computational biology and bioinformatics

DEFF Research Database (Denmark)

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

2004-01-01

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

PubData: search engine for bioinformatics databases worldwide

OpenAIRE

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

2016-01-01

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

Towards Detecting Group Identities in Complex Artificial Societies

DEFF Research Database (Denmark)

Grappiolo, Corrado; Yannakakis, Georgios N.

2012-01-01

This paper presents a framework for modelling group struc- tures and dynamics in both artificial societies and human-populated vir- tual environments such as computer games. The group modelling (GM) framework proposed focuses on the detection of existing, pre-defined group structures and is compo......This paper presents a framework for modelling group struc- tures and dynamics in both artificial societies and human-populated vir- tual environments such as computer games. The group modelling (GM) framework proposed focuses on the detection of existing, pre-defined group structures...

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

African Journals Online (AJOL)

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

Academic Training - Bioinformatics: Decoding the Genome

CERN Multimedia

Chris Jones

2006-01-01

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

Assessment of Data Reliability of Wireless Sensor Network for Bioinformatics

Directory of Open Access Journals (Sweden)

Ting Dong

2017-09-01

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

Reproducible Bioinformatics Research for Biologists

Science.gov (United States)

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

Bioinformatics of genomic association mapping

NARCIS (Netherlands)

Vaez Barzani, Ahmad

2015-01-01

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

Bioinformatic tools for PCR Primer design

African Journals Online (AJOL)

ES

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

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

NARCIS (Netherlands)

Wanders, B.

2012-01-01

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

Expression and Bioinformatic Analysis of Ornithine Aminotransferase 
in Non-small Cell Lung Cancer

Directory of Open Access Journals (Sweden)

Danfei ZHOU

2012-09-01

Full Text Available Background and objective It has been proven that ornithine aminotransferase (OAT might play an important role in the oncogenesis and progression of numerous malignant tumors. The aim of this study is to detect the mRNA and protein expression of OAT in non-small cell lung cancer (NSCLC, as well as to analyze the bioinformatic features and binary interactions. Methods OAT mRNA expression was detected in A549 and 16HBE cell lines by reverse transcription-polymerase chain reaction. OAT protein expression was determined in 55 cases of NSCLC and 17 cases of adjacent non-tumor lung tissues by immunohistochemical staining. The bioinformatic features and binary interactions of OAT were analyzed. Gene ontology annotation and signal pathway analysis were performed. Results OAT mRNA expression in A549 cells was 2.85-fold lower than that in 16HBE cells. OAT protein expression was significantly higher in NSCLC tissues than that in adjacent non-tumor lung tissues. A significant difference of OAT protein expression was existed between squamous cell lung cancer and adenocarcinoma (P<0.05, but was not correlated with the gender, age, lymph node metastasis, tumor size, and TNM stages. Bioinformatic analysis suggested that OAT was a highly homologous and stable protein located in the mitochondria. An aminotran-3 domain and several sites of phosphorylation, which may function in signal transduction, gene transcription, and molecular transit, were found. In the 54 selected binary interactions of OAT, TNF and TRAF6 play roles in the NF-κB pathway. Conclusion OAT may play an important role in the oncogenesis and progression of NSCLC. Thus, OAT may be a novel biomarker for the diagnosis of NSCLC or a new target for its treatment.

Generative Topic Modeling in Image Data Mining and Bioinformatics Studies

Science.gov (United States)

Chen, Xin

2012-01-01

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

Taking Bioinformatics to Systems Medicine

NARCIS (Netherlands)

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

2016-01-01

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

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

Science.gov (United States)

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

2016-09-29

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

Bioinformatics Education in Pathology Training: Current Scope and Future Direction

Directory of Open Access Journals (Sweden)

Michael R Clay

2017-04-01

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

Best practices in bioinformatics training for life scientists

DEFF Research Database (Denmark)

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

2013-01-01

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

Teaching Bioinformatics and Neuroinformatics by Using Free Web-Based Tools

Science.gov (United States)

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

2010-01-01

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

Bioinformatics and the Undergraduate Curriculum

Science.gov (United States)

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

2010-01-01

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

Bringing Web 2.0 to bioinformatics.

Science.gov (United States)

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

2009-01-01

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

Accounting for imperfect detection of groups and individuals when estimating abundance.

Science.gov (United States)

Clement, Matthew J; Converse, Sarah J; Royle, J Andrew

2017-09-01

If animals are independently detected during surveys, many methods exist for estimating animal abundance despite detection probabilities account for imperfect detection of groups, while assuming that individuals within groups are detected perfectly. However, this assumption is often unsupported. We introduce an abundance estimator for grouped animals when detection of groups is imperfect and group size may be under-counted, but not over-counted. The estimator combines an MRDS model with an N-mixture model to account for imperfect detection of individuals. The new MRDS-Nmix model requires the same data as an MRDS model (independent detection histories, an estimate of distance to transect, and an estimate of group size), plus a second estimate of group size provided by the second observer. We extend the model to situations in which detection of individuals within groups declines with distance. We simulated 12 data sets and used Bayesian methods to compare the performance of the new MRDS-Nmix model to an MRDS model. Abundance estimates generated by the MRDS-Nmix model exhibited minimal bias and nominal coverage levels. In contrast, MRDS abundance estimates were biased low and exhibited poor coverage. Many species of conservation interest reside in groups and could benefit from an estimator that better accounts for imperfect detection. Furthermore, the ability to relax the assumption of perfect detection of individuals within detected groups may allow surveyors to re-allocate resources toward detection of new groups instead of extensive surveys of known groups. We believe the proposed estimator is feasible because the only additional field data required are a second estimate of group size.

Bioinformatics meets user-centred design: a perspective.

Directory of Open Access Journals (Sweden)

Katrina Pavelin

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

Bioinformatics on the Cloud Computing Platform Azure

Science.gov (United States)

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

2014-01-01

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

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

Science.gov (United States)

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

2011-11-01

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

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

Science.gov (United States)

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

2015-01-01

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

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

NARCIS (Netherlands)

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

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

Fundamentals of bioinformatics and computational biology methods and exercises in matlab

CERN Document Server

Singh, Gautam B

2015-01-01

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

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

NARCIS (Netherlands)

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

2014-01-01

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

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

Science.gov (United States)

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

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

Science.gov (United States)

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

2014-01-01

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

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

Science.gov (United States)

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

2017-11-27

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

The growing need for microservices in bioinformatics

Directory of Open Access Journals (Sweden)

Christopher L Williams

2016-01-01

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

The growing need for microservices in bioinformatics.

Science.gov (United States)

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

2016-01-01

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

The growing need for microservices in bioinformatics

Science.gov (United States)

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

2016-01-01

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

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

Science.gov (United States)

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

2016-01-01

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

A density-based clustering model for community detection in complex networks

Science.gov (United States)

Zhao, Xiang; Li, Yantao; Qu, Zehui

2018-04-01

Network clustering (or graph partitioning) is an important technique for uncovering the underlying community structures in complex networks, which has been widely applied in various fields including astronomy, bioinformatics, sociology, and bibliometric. In this paper, we propose a density-based clustering model for community detection in complex networks (DCCN). The key idea is to find group centers with a higher density than their neighbors and a relatively large integrated-distance from nodes with higher density. The experimental results indicate that our approach is efficient and effective for community detection of complex networks.

[Expression profiles and bioinformatic analysis of miRNA in human dental pulp cells during endothelial differentiation].

Science.gov (United States)

Gong, Qimei; Jiang, Hongwei; Wang, Jinming; Ling, Junqi

2014-05-01

To investigate the differential expression profile and bioinformatic analysis of microRNA (miRNA) in human dental pulp cells (DPC) during endothelial differentiation. DPC were cultured in endothelial induction medium (50 µg/L vascular endothelial growth factor, 10 µg/L basic fibroblast growth factor and 2% fetal calf serum) for 7 days. Meanwhile non-induced DPC were used as control.Quantitative real-time PCR (qRT-PCR) was applied to detect vascular endothelial marker genes [CD31, von Willebrand factor (vWF) and vascular endothelial-cadherin (VE-cadherin)] and in vitro tube formation on matrigel was used to analyze the angiogenic ability of differentiated cells. And then miRNA expression profiles of DPC were examined using miRNA microarray and then the differentially expressed miRNA were validated by qRT-PCR. Furthermore, bioinformatic analysis was employed to predict the target genes of miRNA and to analyze the possible biological functions and signaling pathways that were involved in DPC after induction. The relative mRNA level of CD31, vWF and VE-cadherin in the control group were (3.48 ± 0.22) ×10(-4), (3.13 ± 0.31) ×10(-4) and (39.60 ± 2.36) ×10(-4), and (19.57 ± 2.20) ×10(-4), (48.13 ± 0.54) ×10(-4) and (228.00 ± 8.89) ×10(-4) in the induced group. The expressions of CD31, vWF and VE-cadherin were increased significantly in endothelial induced DPC compared to the control group (P functions, such as the regulation of transcription, cell motion, blood vessel morphogenesis, angiogenesis and cytoskeletal protein, and signaling pathways including the mitogen-activated protein kinase (MAPK) and the Wnt signaling pathway. The differential miRNA expression identified in this study may be involved in governing DPC endothelial differentiation, thus contributing to the future research on regulatory mechanisms in dental pulp angiogenesis.

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

Science.gov (United States)

Floraino, Wely B.

2008-01-01

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

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

Science.gov (United States)

Likic, Vladimir A.

2006-01-01

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

Temporal Patterns in Sheep Fetal Heart Rate Variability Correlate to Systemic Cytokine Inflammatory Response: A Methodological Exploration of Monitoring Potential Using Complex Signals Bioinformatics.

Directory of Open Access Journals (Sweden)

Christophe L Herry

Full Text Available Fetal inflammation is associated with increased risk for postnatal organ injuries. No means of early detection exist. We hypothesized that systemic fetal inflammation leads to distinct alterations of fetal heart rate variability (fHRV. We tested this hypothesis deploying a novel series of approaches from complex signals bioinformatics. In chronically instrumented near-term fetal sheep, we induced an inflammatory response with lipopolysaccharide (LPS injected intravenously (n = 10 observing it over 54 hours; seven additional fetuses served as controls. Fifty-one fHRV measures were determined continuously every 5 minutes using Continuous Individualized Multi-organ Variability Analysis (CIMVA. CIMVA creates an fHRV measures matrix across five signal-analytical domains, thus describing complementary properties of fHRV. We implemented, validated and tested methodology to obtain a subset of CIMVA fHRV measures that matched best the temporal profile of the inflammatory cytokine IL-6. In the LPS group, IL-6 peaked at 3 hours. For the LPS, but not control group, a sharp increase in standardized difference in variability with respect to baseline levels was observed between 3 h and 6 h abating to baseline levels, thus tracking closely the IL-6 inflammatory profile. We derived fHRV inflammatory index (FII consisting of 15 fHRV measures reflecting the fetal inflammatory response with prediction accuracy of 90%. Hierarchical clustering validated the selection of 14 out of 15 fHRV measures comprising FII. We developed methodology to identify a distinctive subset of fHRV measures that tracks inflammation over time. The broader potential of this bioinformatics approach is discussed to detect physiological responses encoded in HRV measures.

Chapter 16: text mining for translational bioinformatics.

Science.gov (United States)

Cohen, K Bretonnel; Hunter, Lawrence E

2013-04-01

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

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

Science.gov (United States)

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

2012-07-01

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

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

Science.gov (United States)

Shachak, Aviv; Ophir, Ron; Rubin, Eitan

2005-01-01

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

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

Science.gov (United States)

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

2015-06-02

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

SPECIES DATABASES AND THE BIOINFORMATICS REVOLUTION.

Science.gov (United States)

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

BioSmalltalk: a pure object system and library for bioinformatics.

Science.gov (United States)

Morales, Hernán F; Giovambattista, Guillermo

2013-09-15

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

Bioclipse: an open source workbench for chemo- and bioinformatics

Directory of Open Access Journals (Sweden)

Wagener Johannes

2007-02-01

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

Bioinformatics in New Generation Flavivirus Vaccines

Directory of Open Access Journals (Sweden)

Penelope Koraka

2010-01-01

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

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

Science.gov (United States)

Wren, Jonathan D

2016-09-01

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

A Bioinformatic Pipeline for Monitoring of the Mutational Stability of Viral Drug Targets with Deep-Sequencing Technology.

Science.gov (United States)

Kravatsky, Yuri; Chechetkin, Vladimir; Fedoseeva, Daria; Gorbacheva, Maria; Kravatskaya, Galina; Kretova, Olga; Tchurikov, Nickolai

2017-11-23

The efficient development of antiviral drugs, including efficient antiviral small interfering RNAs (siRNAs), requires continuous monitoring of the strict correspondence between a drug and the related highly variable viral DNA/RNA target(s). Deep sequencing is able to provide an assessment of both the general target conservation and the frequency of particular mutations in the different target sites. The aim of this study was to develop a reliable bioinformatic pipeline for the analysis of millions of short, deep sequencing reads corresponding to selected highly variable viral sequences that are drug target(s). The suggested bioinformatic pipeline combines the available programs and the ad hoc scripts based on an original algorithm of the search for the conserved targets in the deep sequencing data. We also present the statistical criteria for the threshold of reliable mutation detection and for the assessment of variations between corresponding data sets. These criteria are robust against the possible sequencing errors in the reads. As an example, the bioinformatic pipeline is applied to the study of the conservation of RNA interference (RNAi) targets in human immunodeficiency virus 1 (HIV-1) subtype A. The developed pipeline is freely available to download at the website http://virmut.eimb.ru/. Brief comments and comparisons between VirMut and other pipelines are also presented.

Genetic and bioinformatics analysis of four novel GCK missense variants detected in Caucasian families with GCK-MODY phenotype.

Science.gov (United States)

Costantini, S; Malerba, G; Contreas, G; Corradi, M; Marin Vargas, S P; Giorgetti, A; Maffeis, C

2015-05-01

Heterozygous loss-of-function mutations in the glucokinase (GCK) gene cause maturity-onset diabetes of the young (MODY) subtype GCK (GCK-MODY/MODY2). GCK sequencing revealed 16 distinct mutations (13 missense, 1 nonsense, 1 splice site, and 1 frameshift-deletion) co-segregating with hyperglycaemia in 23 GCK-MODY families. Four missense substitutions (c.718A>G/p.Asn240Asp, c.757G>T/p.Val253Phe, c.872A>C/p.Lys291Thr, and c.1151C>T/p.Ala384Val) were novel and a founder effect for the nonsense mutation (c.76C>T/p.Gln26*) was supposed. We tested whether an accurate bioinformatics approach could strengthen family-genetic evidence for missense variant pathogenicity in routine diagnostics, where wet-lab functional assays are generally unviable. In silico analyses of the novel missense variants, including orthologous sequence conservation, amino acid substitution (AAS)-pathogenicity predictors, structural modeling and splicing predictors, suggested that the AASs and/or the underlying nucleotide changes are likely to be pathogenic. This study shows how a careful bioinformatics analysis could provide effective suggestions to help molecular-genetic diagnosis in absence of wet-lab validations. © 2014 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

mORCA: sailing bioinformatics world with mobile devices.

Science.gov (United States)

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

2018-03-01

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

p3d--Python module for structural bioinformatics.

Science.gov (United States)

Fufezan, Christian; Specht, Michael

2009-08-21

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

Best practices in bioinformatics training for life scientists.

KAUST Repository

Via, Allegra

2013-06-25

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

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

Science.gov (United States)

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

2017-08-29

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

Bioinformatic tools for PCR Primer design

African Journals Online (AJOL)

ES

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

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

Science.gov (United States)

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

2007-01-01

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

Advance in structural bioinformatics

CERN Document Server

Wei, Dongqing; Zhao, Tangzhen; Dai, Hao

2014-01-01

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

Bioinformatics Analysis Reveals Genes Involved in the Pathogenesis of Ameloblastoma and Keratocystic Odontogenic Tumor.

Science.gov (United States)

Santos, Eliane Macedo Sobrinho; Santos, Hércules Otacílio; Dos Santos Dias, Ivoneth; Santos, Sérgio Henrique; Batista de Paula, Alfredo Maurício; Feltenberger, John David; Sena Guimarães, André Luiz; Farias, Lucyana Conceição

2016-01-01

Pathogenesis of odontogenic tumors is not well known. It is important to identify genetic deregulations and molecular alterations. This study aimed to investigate, through bioinformatic analysis, the possible genes involved in the pathogenesis of ameloblastoma (AM) and keratocystic odontogenic tumor (KCOT). Genes involved in the pathogenesis of AM and KCOT were identified in GeneCards. Gene list was expanded, and the gene interactions network was mapped using the STRING software. "Weighted number of links" (WNL) was calculated to identify "leader genes" (highest WNL). Genes were ranked by K-means method and Kruskal-Wallis test was used (Preview data was used to corroborate the bioinformatics data. CDK1 was identified as leader gene for AM. In KCOT group, results show PCNA and TP53 . Both tumors exhibit a power law behavior. Our topological analysis suggested leader genes possibly important in the pathogenesis of AM and KCOT, by clustering coefficient calculated for both odontogenic tumors (0.028 for AM, zero for KCOT). The results obtained in the scatter diagram suggest an important relationship of these genes with the molecular processes involved in AM and KCOT. Ontological analysis for both AM and KCOT demonstrated different mechanisms. Bioinformatics analyzes were confirmed through literature review. These results may suggest the involvement of promising genes for a better understanding of the pathogenesis of AM and KCOT.

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

Science.gov (United States)

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

2017-09-15

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

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

Science.gov (United States)

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

2001-01-01

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

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

Science.gov (United States)

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

2016-01-01

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

"Extreme Programming" in a Bioinformatics Class

Science.gov (United States)

Kelley, Scott; Alger, Christianna; Deutschman, Douglas

2009-01-01

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

Bioinformatics in Undergraduate Education: Practical Examples

Science.gov (United States)

Boyle, John A.

2004-01-01

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

Modern bioinformatics meets traditional Chinese medicine.

Science.gov (United States)

Gu, Peiqin; Chen, Huajun

2014-11-01

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

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

Directory of Open Access Journals (Sweden)

Ernest Rossi

2006-01-01

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

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

Directory of Open Access Journals (Sweden)

Ernest Rossi

2006-01-01

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

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

Science.gov (United States)

Weisman, David

2010-01-01

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

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

Science.gov (United States)

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

2007-01-01

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

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

Science.gov (United States)

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

2012-01-01

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

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

Directory of Open Access Journals (Sweden)

Mladen Čudanov

2012-11-01

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

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

Science.gov (United States)

Wefer, Stephen H.; Sheppard, Keith

2008-01-01

The proliferation of bioinformatics in modern biology marks a modern revolution in science that promises to influence science education at all levels. This study analyzed secondary school science standards of 49 U.S. states (Iowa has no science framework) and the District of Columbia for content related to bioinformatics. The bioinformatics…

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

Science.gov (United States)

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

2006-11-06

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

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

Science.gov (United States)

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

2006-01-01

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

Genomics and bioinformatics resources for translational science in Rosaceae.

Science.gov (United States)

Jung, Sook; Main, Dorrie

2014-01-01

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

Implementing bioinformatic workflows within the bioextract server

Science.gov (United States)

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

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

Science.gov (United States)

Loucif, Samia

2014-01-01

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

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

Science.gov (United States)

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

2016-04-30

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

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

Science.gov (United States)

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

2012-03-01

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

A Bioinformatic Pipeline for Monitoring of the Mutational Stability of Viral Drug Targets with Deep-Sequencing Technology

Directory of Open Access Journals (Sweden)

Yuri Kravatsky

2017-11-01

Full Text Available The efficient development of antiviral drugs, including efficient antiviral small interfering RNAs (siRNAs, requires continuous monitoring of the strict correspondence between a drug and the related highly variable viral DNA/RNA target(s. Deep sequencing is able to provide an assessment of both the general target conservation and the frequency of particular mutations in the different target sites. The aim of this study was to develop a reliable bioinformatic pipeline for the analysis of millions of short, deep sequencing reads corresponding to selected highly variable viral sequences that are drug target(s. The suggested bioinformatic pipeline combines the available programs and the ad hoc scripts based on an original algorithm of the search for the conserved targets in the deep sequencing data. We also present the statistical criteria for the threshold of reliable mutation detection and for the assessment of variations between corresponding data sets. These criteria are robust against the possible sequencing errors in the reads. As an example, the bioinformatic pipeline is applied to the study of the conservation of RNA interference (RNAi targets in human immunodeficiency virus 1 (HIV-1 subtype A. The developed pipeline is freely available to download at the website http://virmut.eimb.ru/. Brief comments and comparisons between VirMut and other pipelines are also presented.

Combining medical informatics and bioinformatics toward tools for personalized medicine.

Science.gov (United States)

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

2003-01-01

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

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

Directory of Open Access Journals (Sweden)

Geraint Duck

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

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

Science.gov (United States)

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

2012-07-01

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

Using registries to integrate bioinformatics tools and services into workbench environments

DEFF Research Database (Denmark)

Ménager, Hervé; Kalaš, Matúš; Rapacki, Kristoffer

2016-01-01

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

p3d – Python module for structural bioinformatics

Directory of Open Access Journals (Sweden)

Fufezan Christian

2009-08-01

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

A comparison of common programming languages used in bioinformatics.

Science.gov (United States)

Fourment, Mathieu; Gillings, Michael R

2008-02-05

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

Bioinformatics process management: information flow via a computational journal

Directory of Open Access Journals (Sweden)

Lushington Gerald

2007-12-01

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

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

Science.gov (United States)

Cazals, Frédéric; Dreyfus, Tom

2017-04-01

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

Identification of Surface Protein Biomarkers of Listeria monocytogenes via Bioinformatics and Antibody-Based Protein Detection Tools

Science.gov (United States)

Zhang, Cathy X. Y.; Brooks, Brian W.; Huang, Hongsheng; Pagotto, Franco

2016-01-01

traditionally divided into at least 12 serotypes. Currently, there are no monoclonal antibodies (MAbs) available that are capable of binding to the surface of L. monocytogenes strains representing all 12 serotypes. Such antibodies would be useful and are needed for the development of methods to detect and isolate L. monocytogenes from food samples. In our study, we aimed to identify surface proteins that possess regions of well-conserved amino acid sequences among various serotypes and then to employ them as antigen targets (biomarkers) for the development of MAbs. Through bioinformatics and protein expression analysis, we identified one of the four putative surface protein candidates, LMOf2365_0639, encoded by the genome of the L. monocytogenes serotype 4b strain F2365, as a useful surface biomarker. Extensive assessment of 35 MAbs raised against LMOf2365_0639 in our study revealed three MAbs (M3643, M3644, and M3651) that recognized a wide range of L. monocytogenes isolates. PMID:27342549

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

OpenAIRE

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

2016-01-01

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

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

Science.gov (United States)

Rowe, Laura

2017-01-01

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

Rough-fuzzy pattern recognition applications in bioinformatics and medical imaging

CERN Document Server

Maji, Pradipta

2012-01-01

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

E-MSD: an integrated data resource for bioinformatics.

Science.gov (United States)

Velankar, S; McNeil, P; Mittard-Runte, V; Suarez, A; Barrell, D; Apweiler, R; Henrick, K

2005-01-01

The Macromolecular Structure Database (MSD) group (http://www.ebi.ac.uk/msd/) continues to enhance the quality and consistency of macromolecular structure data in the worldwide Protein Data Bank (wwPDB) and to work towards the integration of various bioinformatics data resources. One of the major obstacles to the improved integration of structural databases such as MSD and sequence databases like UniProt is the absence of up to date and well-maintained mapping between corresponding entries. We have worked closely with the UniProt group at the EBI to clean up the taxonomy and sequence cross-reference information in the MSD and UniProt databases. This information is vital for the reliable integration of the sequence family databases such as Pfam and Interpro with the structure-oriented databases of SCOP and CATH. This information has been made available to the eFamily group (http://www.efamily.org.uk/) and now forms the basis of the regular interchange of information between the member databases (MSD, UniProt, Pfam, Interpro, SCOP and CATH). This exchange of annotation information has enriched the structural information in the MSD database with annotation from wider sequence-oriented resources. This work was carried out under the 'Structure Integration with Function, Taxonomy and Sequences (SIFTS)' initiative (http://www.ebi.ac.uk/msd-srv/docs/sifts) in the MSD group.

Best practices in bioinformatics training for life scientists.

KAUST Repository

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

2013-01-01

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

Privacy Preserving PCA on Distributed Bioinformatics Datasets

Science.gov (United States)

Li, Xin

2011-01-01

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

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

Directory of Open Access Journals (Sweden)

Barbara J. May

2013-02-01

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

Rise and demise of bioinformatics? Promise and progress.

Directory of Open Access Journals (Sweden)

Christos A Ouzounis

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

Detecting groups of similar components in complex networks

International Nuclear Information System (INIS)

Wang Jiao; Lai, C-H

2008-01-01

We study how to detect groups in a complex network each of which consists of component nodes sharing a similar connection pattern. Based on the mixture models and the exploratory analysis set up by Newman and Leicht (2007 Proc. Natl. Acad. Sci. USA 104 9564), we develop an algorithm that is applicable to a network with any degree distribution. The partition of a network suggested by this algorithm also applies to its complementary network. In general, groups of similar components are not necessarily identical with the communities in a community network; thus partitioning a network into groups of similar components provides additional information of the network structure. The proposed algorithm can also be used for community detection when the groups and the communities overlap. By introducing a tunable parameter that controls the involved effects of the heterogeneity, we can also investigate conveniently how the group structure can be coupled with the heterogeneity characteristics. In particular, an interesting example shows a group partition can evolve into a community partition in some situations when the involved heterogeneity effects are tuned. The extension of this algorithm to weighted networks is discussed as well.

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

Directory of Open Access Journals (Sweden)

Cieślik Marcin

2011-02-01

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

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

Directory of Open Access Journals (Sweden)

Anjali Srivastava

2017-09-01

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

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

Science.gov (United States)

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

2013-09-01

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

Protein raftophilicity. How bioinformatics can help membranologists

DEFF Research Database (Denmark)

Nielsen, Henrik; Sperotto, Maria Maddalena

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

Development and implementation of a bioinformatics online ...

African Journals Online (AJOL)

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

Bioinformatics study of the mangrove actin genes

Science.gov (United States)

Basyuni, M.; Wasilah, M.; Sumardi

2017-01-01

This study describes the bioinformatics methods to analyze eight actin genes from mangrove plants on DDBJ/EMBL/GenBank as well as predicted the structure, composition, subcellular localization, similarity, and phylogenetic. The physical and chemical properties of eight mangroves showed variation among the genes. The percentage of the secondary structure of eight mangrove actin genes followed the order of a helix > random coil > extended chain structure for BgActl, KcActl, RsActl, and A. corniculatum Act. In contrast to this observation, the remaining actin genes were random coil > extended chain structure > a helix. This study, therefore, shown the prediction of secondary structure was performed for necessary structural information. The values of chloroplast or signal peptide or mitochondrial target were too small, indicated that no chloroplast or mitochondrial transit peptide or signal peptide of secretion pathway in mangrove actin genes. These results suggested the importance of understanding the diversity and functional of properties of the different amino acids in mangrove actin genes. To clarify the relationship among the mangrove actin gene, a phylogenetic tree was constructed. Three groups of mangrove actin genes were formed, the first group contains B. gymnorrhiza BgAct and R. stylosa RsActl. The second cluster which consists of 5 actin genes the largest group, and the last branch consist of one gene, B. sexagula Act. The present study, therefore, supported the previous results that plant actin genes form distinct clusters in the tree.

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

Science.gov (United States)

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

2016-01-01

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

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

Science.gov (United States)

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

2013-01-01

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

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

Science.gov (United States)

Balqis, Widodo, Lukiati, Betty; Amin, Mohamad

2017-05-01

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

A BIOINFORMATIC STRATEGY TO RAPIDLY CHARACTERIZE CDNA LIBRARIES

Science.gov (United States)

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

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

Science.gov (United States)

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

2012-01-01

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

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

Science.gov (United States)

Zhang, Xiaorong

2011-01-01

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

2nd Colombian Congress on Computational Biology and Bioinformatics

CERN Document Server

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

2014-01-01

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

Biowep: a workflow enactment portal for bioinformatics applications.

Science.gov (United States)

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

2007-03-08

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

Biowep: a workflow enactment portal for bioinformatics applications

Directory of Open Access Journals (Sweden)

Romano Paolo

2007-03-01

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

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

Science.gov (United States)

Oshita, Kazuki; Arakawa, Kazuharu; Tomita, Masaru

2011-04-29

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

KBWS: an EMBOSS associated package for accessing bioinformatics web services

Directory of Open Access Journals (Sweden)

Tomita Masaru

2011-04-01

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

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

Science.gov (United States)

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

2018-01-01

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

Statistical modelling in biostatistics and bioinformatics selected papers

CERN Document Server

Peng, Defen

2014-01-01

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

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

Science.gov (United States)

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

2013-01-01

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

Community detection in networks with unequal groups.

Science.gov (United States)

Zhang, Pan; Moore, Cristopher; Newman, M E J

2016-01-01

Recently, a phase transition has been discovered in the network community detection problem below which no algorithm can tell which nodes belong to which communities with success any better than a random guess. This result has, however, so far been limited to the case where the communities have the same size or the same average degree. Here we consider the case where the sizes or average degrees differ. This asymmetry allows us to assign nodes to communities with better-than-random success by examining their local neighborhoods. Using the cavity method, we show that this removes the detectability transition completely for networks with four groups or fewer, while for more than four groups the transition persists up to a critical amount of asymmetry but not beyond. The critical point in the latter case coincides with the point at which local information percolates, causing a global transition from a less-accurate solution to a more-accurate one.

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

Science.gov (United States)

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

2016-09-01

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

Bioboxes: standardised containers for interchangeable bioinformatics software.

Science.gov (United States)

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

2015-01-01

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

A Virtual Bioinformatics Knowledge Environment for Early Cancer Detection

Science.gov (United States)

Crichton, Daniel; Srivastava, Sudhir; Johnsey, Donald

2003-01-01

Discovery of disease biomarkers for cancer is a leading focus of early detection. The National Cancer Institute created a network of collaborating institutions focused on the discovery and validation of cancer biomarkers called the Early Detection Research Network (EDRN). Informatics plays a key role in enabling a virtual knowledge environment that provides scientists real time access to distributed data sets located at research institutions across the nation. The distributed and heterogeneous nature of the collaboration makes data sharing across institutions very difficult. EDRN has developed a comprehensive informatics effort focused on developing a national infrastructure enabling seamless access, sharing and discovery of science data resources across all EDRN sites. This paper will discuss the EDRN knowledge system architecture, its objectives and its accomplishments.

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

Science.gov (United States)

Sutcliffe, Iain C.; Cummings, Stephen P.

2007-01-01

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

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

DEFF Research Database (Denmark)

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

2005-01-01

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

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

Directory of Open Access Journals (Sweden)

Tilmann Weber

2016-06-01

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

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

DEFF Research Database (Denmark)

Kouskoumvekaki, Irene; Shublaq, Nour; Brunak, Søren

2014-01-01

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

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

Directory of Open Access Journals (Sweden)

Thoraval Samuel

2005-04-01

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

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

Science.gov (United States)

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

2017-05-31

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

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

OpenAIRE

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

2005-01-01

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

Bioinformatics for whole-genome shotgun sequencing of microbial communities.

Directory of Open Access Journals (Sweden)

Kevin Chen

2005-07-01

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

Promoting synergistic research and education in genomics and bioinformatics.

Science.gov (United States)

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

2008-01-01

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

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

Science.gov (United States)

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

2012-01-01

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

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

Science.gov (United States)

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

2017-06-30

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

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

Science.gov (United States)

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

2018-05-14

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

Bioinformatics and Microarray Data Analysis on the Cloud.

Science.gov (United States)

Calabrese, Barbara; Cannataro, Mario

2016-01-01

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

Protecting innovation in bioinformatics and in-silico biology.

Science.gov (United States)

Harrison, Robert

2003-01-01

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

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

NARCIS (Netherlands)

Wanders, B.

2012-01-01

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

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

Directory of Open Access Journals (Sweden)

François Moreews

2015-12-01

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

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

OpenAIRE

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

2014-01-01

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

An Adaptive Hybrid Multiprocessor technique for bioinformatics sequence alignment

KAUST Repository

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

2012-01-01

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

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

Science.gov (United States)

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

2017-01-01

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

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

Science.gov (United States)

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

A conceptual basis to encode and detect organic functional groups in XML.

Science.gov (United States)

Sankar, Punnaivanam; Krief, Alain; Vijayasarathi, Durairaj

2013-06-01

A conceptual basis to define and detect organic functional groups is developed. The basic model of a functional group is termed as a primary functional group and is characterized by a group center composed of one or more group center atoms bonded to terminal atoms and skeletal carbon atoms. The generic group center patterns are identified from the structures of known functional groups. Accordingly, a chemical ontology 'Font' is developed to organize the existing functional groups as well as the new ones to be defined by the chemists. The basic model is extended to accommodate various combinations of primary functional groups as functional group assemblies. A concept of skeletal group is proposed to define the characteristic groups composed of only carbon atoms to be regarded as equivalent to functional groups. The combination of primary functional groups with skeletal groups is categorized as skeletal group assembly. In order to make the model suitable for reaction modeling purpose, a Graphical User Interface (GUI) is developed to define the functional groups and to encode in XML format appropriate to detect them in chemical structures. The system is capable of detecting multiple instances of primary functional groups as well as the overlapping poly-functional groups as the respective assemblies. Copyright © 2013 Elsevier Inc. All rights reserved.

jORCA: easily integrating bioinformatics Web Services.

Science.gov (United States)

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

2010-02-15

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

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

Science.gov (United States)

Nehm, Ross H.; Budd, Ann F.

2006-01-01

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

G2LC: Resources Autoscaling for Real Time Bioinformatics Applications in IaaS

Directory of Open Access Journals (Sweden)

Rongdong Hu

2015-01-01

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

Penalized feature selection and classification in bioinformatics

OpenAIRE

Ma, Shuangge; Huang, Jian

2008-01-01

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

Assessing computational genomics skills: Our experience in the H3ABioNet African bioinformatics network.

Science.gov (United States)

Jongeneel, C Victor; Achinike-Oduaran, Ovokeraye; Adebiyi, Ezekiel; Adebiyi, Marion; Adeyemi, Seun; Akanle, Bola; Aron, Shaun; Ashano, Efejiro; Bendou, Hocine; Botha, Gerrit; Chimusa, Emile; Choudhury, Ananyo; Donthu, Ravikiran; Drnevich, Jenny; Falola, Oluwadamila; Fields, Christopher J; Hazelhurst, Scott; Hendry, Liesl; Isewon, Itunuoluwa; Khetani, Radhika S; Kumuthini, Judit; Kimuda, Magambo Phillip; Magosi, Lerato; Mainzer, Liudmila Sergeevna; Maslamoney, Suresh; Mbiyavanga, Mamana; Meintjes, Ayton; Mugutso, Danny; Mpangase, Phelelani; Munthali, Richard; Nembaware, Victoria; Ndhlovu, Andrew; Odia, Trust; Okafor, Adaobi; Oladipo, Olaleye; Panji, Sumir; Pillay, Venesa; Rendon, Gloria; Sengupta, Dhriti; Mulder, Nicola

2017-06-01

The H3ABioNet pan-African bioinformatics network, which is funded to support the Human Heredity and Health in Africa (H3Africa) program, has developed node-assessment exercises to gauge the ability of its participating research and service groups to analyze typical genome-wide datasets being generated by H3Africa research groups. We describe a framework for the assessment of computational genomics analysis skills, which includes standard operating procedures, training and test datasets, and a process for administering the exercise. We present the experiences of 3 research groups that have taken the exercise and the impact on their ability to manage complex projects. Finally, we discuss the reasons why many H3ABioNet nodes have declined so far to participate and potential strategies to encourage them to do so.

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

Science.gov (United States)

2016-10-01

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

Architecture exploration of FPGA based accelerators for bioinformatics applications

CERN Document Server

Varma, B Sharat Chandra; Balakrishnan, M

2016-01-01

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

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

Directory of Open Access Journals (Sweden)

Regina Augustin

2011-01-01

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

Cancer immunology, bioinformatics and chemokine evidence link vaccines contaminated with animal proteins to autoimmune disease: a detailed look at Crohn's disease and Vitiligo

OpenAIRE

Arumugham, Vinu

2017-01-01

Cancer research has demonstrated that immunization with homologous xenogeneic proteins (such as vaccines contaminated with animal proteins that resemble human proteins) results in autoimmunity. Bioinformatics analysis demonstrates that animal proteins have occasional amino acids differences compared to equivalent human proteins. So mutated human protein epitopes can be identical to animal protein derived epitopes. Low affinity self reactive T cells suited for detection of mutated human epitop...

Detection of group D and viridans streptococci in blood by radiometric methods

International Nuclear Information System (INIS)

Beckwith, D.G.

1979-01-01

A prospective study was conducted to evaluate the radiometric detection of group D and viridans streptococci in blood, using three media preparations, Bactec 6A and 6B isotonic media and 8B hypertonic medium. All enterococci tested were detected by the 6A and 6B media. However, the 6A medium failed to detect 76% of the Streptococcus bovis isolates and 57% of the viridans streptococci, whereas all S. bovis isolates and 95% of the viridans streptococci were detected with the 6B formulation. No improvement in detection was noted in comparing the 6B and the 8B hypertonic media. The importance of adequate detection of this group of organisms, especially in patients with endocarditis, is discussed

Staff Scientist - RNA Bioinformatics | Center for Cancer Research

Science.gov (United States)

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

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

Science.gov (United States)

Vetrivel, Umashankar; Pilla, Kalabharath

2008-01-01

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

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

Science.gov (United States)

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

2017-01-01

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

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

African Journals Online (AJOL)

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

Virginia Bioinformatics Institute to expand cyberinfrastructure education and outreach project

OpenAIRE

Whyte, Barry James

2008-01-01

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

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

CERN Document Server

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

2012-01-01

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

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

Science.gov (United States)

Wightman, Bruce; Hark, Amy T.

2012-01-01

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

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

Science.gov (United States)

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

2017-09-20

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

Assessing computational genomics skills: Our experience in the H3ABioNet African bioinformatics network.

Directory of Open Access Journals (Sweden)

C Victor Jongeneel

2017-06-01

Full Text Available The H3ABioNet pan-African bioinformatics network, which is funded to support the Human Heredity and Health in Africa (H3Africa program, has developed node-assessment exercises to gauge the ability of its participating research and service groups to analyze typical genome-wide datasets being generated by H3Africa research groups. We describe a framework for the assessment of computational genomics analysis skills, which includes standard operating procedures, training and test datasets, and a process for administering the exercise. We present the experiences of 3 research groups that have taken the exercise and the impact on their ability to manage complex projects. Finally, we discuss the reasons why many H3ABioNet nodes have declined so far to participate and potential strategies to encourage them to do so.

Detection of breast diseases in various age groups among women

International Nuclear Information System (INIS)

Vapnik, T.N.

1981-01-01

A comprehensive study among women in various age groups provided data on the detection of dyshormonal and tumorous diseases of the breast which are necessary for organizing preventive measures and identifying groups for screening. Data on the distribution of breast pathology in various age groups are presented. The highest percentage of pathology is marked in women aged 31 to 40, with focal lesions 4 times as many as in the previous age group [ru

Bioinformatics for Undergraduates: Steps toward a Quantitative Bioscience Curriculum

Science.gov (United States)

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

2006-01-01

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

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

African Journals Online (AJOL)

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

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

Science.gov (United States)

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

2013-01-01

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

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

African Journals Online (AJOL)

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

mockrobiota: a Public Resource for Microbiome Bioinformatics Benchmarking.

Science.gov (United States)

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

2016-01-01

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

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

Directory of Open Access Journals (Sweden)

Sarah Torres

2010-06-01

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

Bioinformatic approaches reveal metagenomic characterization of soil microbial community.

Directory of Open Access Journals (Sweden)

Zhuofei Xu

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.

Bioinformatics in the Netherlands : The value of a nationwide community

NARCIS (Netherlands)

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

2017-01-01

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

Correspondence regarding Zhong et al., BMC Bioinformatics 2013 Mar 7;14:89.

Science.gov (United States)

Kuhn, Alexandre

2014-11-28

Computational expression deconvolution aims to estimate the contribution of individual cell populations to expression profiles measured in samples of heterogeneous composition. Zhong et al. recently proposed Digital Sorting Algorithm (BMC Bioinformatics 2013 Mar 7;14:89) and showed that they could accurately estimate population-specific expression levels and expression differences between two populations. They compared DSA with Population-Specific Expression Analysis (PSEA), a previous deconvolution method that we developed to detect expression changes occurring within the same population between two conditions (e.g. disease versus non-disease). However, Zhong et al. compared PSEA-derived specific expression levels across different cell populations. Specific expression levels obtained with PSEA cannot be directly compared across different populations as they are on a relative scale. They are accurate as we demonstrate by deconvolving the same dataset used by Zhong et al. and, importantly, allow for comparison of population-specific expression across conditions.

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

International Nuclear Information System (INIS)

Taylor, Ronald C.

2010-01-01

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

[Comparison of gut microbiotal compositional analysis of patients with irritable bowel syndrome through different bioinformatics pipelines].

Science.gov (United States)

Zhu, S W; Liu, Z J; Li, M; Zhu, H Q; Duan, L P

2018-04-18

To assess whether the same biological conclusion, diagnostic or curative effects regarding microbial composition of irritable bowel syndrome (IBS) patients could be reached through different bioinformatics pipelines, we used two common bioinformatics pipelines (Uparse V2.0 and Mothur V1.39.5)to analyze the same fecal microbial 16S rRNA high-throughput sequencing data. The two pipelines were used to analyze the diversity and richness of fecal microbial 16S rRNA high-throughput sequencing data of 27 samples, including 9 healthy controls (HC group), 9 diarrhea IBS patients before (IBS group) and after Rifaximin treatment (IBS-treatment, IBSt group). Analyses such as microbial diversity, principal co-ordinates analysis (PCoA), nonmetric multidimensional scaling (NMDS) and linear discriminant analysis effect size (LEfSe) were used to find out the microbial differences among HC group vs. IBS group and IBS group vs. IBSt group. (1) Microbial composition comparison of the 27 samples in the two pipelines showed significant variations at both family and genera levels while no significant variations at phylum level; (2) There was no significant difference in the comparison of HC vs. IBS or IBS vs. IBSt (Uparse: HC vs. IBS, F=0.98, P=0.445; IBS vs. IBSt, F=0.47,P=0.926; Mothur: HC vs.IBS, F=0.82, P=0.646; IBS vs. IBSt, F=0.37, P=0.961). The Shannon index was significantly decreased in IBSt; (3) Both workshops distinguished the significantly enriched genera between HC and IBS groups. For example, Nitrosomonas and Paraprevotella increased while Pseudoalteromonadaceae and Anaerotruncus decreased in HC group through Uparse pipeline, nevertheless Roseburia 62 increased while Butyricicoccus and Moraxellaceae decreased in HC group through Mothur pipeline.Only Uparse pipeline could pick out significant genera between IBS and IBSt, such as Pseudobutyricibrio, Clostridiaceae 1 and Clostridiumsensustricto 1. There were taxonomic and phylogenetic diversity differences between the two

Learning Genetics through an Authentic Research Simulation in Bioinformatics

Science.gov (United States)

Gelbart, Hadas; Yarden, Anat

2006-01-01

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

Leak detection in turbo group condensers using helium

International Nuclear Information System (INIS)

Gomez Cores, C.; Lloret, J.

1997-01-01

This method allows a rapid location of leaks (small or not) in the pipelines of a turbo group condenser, before opening the condenser boxes and no need of stooping the turbo group operation. This operation can last two hours maximum depending on the volume of the box or semi box. The technique consists of injecting helium into the water side and detecting it in the steam side, in the outlet of not condensable gases of the ejector. In the same way, probable air inlet to the condenser can be proved (auxiliary systems, turbo group joints to the condenser, etc.) in order to improve the vacuum and/or reduce the quantity of oxygen dissolved in the water of the steam side. (author) [es

Atlas – a data warehouse for integrative bioinformatics

Directory of Open Access Journals (Sweden)

Yuen Macaire MS

2005-02-01

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

CirComPara: A Multi‐Method Comparative  Bioinformatics Pipeline to Detect and Study circRNAs from RNA‐seq Data

Directory of Open Access Journals (Sweden)

Enrico Gaffo

2017-02-01

Full Text Available Circular RNAs (circRNAs are generated by backsplicing of immature RNA forming covalently closed loops of intron/exon RNA molecules. Pervasiveness, evolutionary conservation, massive and regulated expression, and posttranscriptional regulatory roles of circRNAs in eukaryotes have been appreciated and described only recently. Moreover, being easily detectable disease markers, circRNAs undoubtedly represent a molecular class with high bearing on molecular pathobiology. CircRNAs can be detected from RNAseq data using appropriate computational methods to identify the sequence reads spanning backsplice junctions that do not colinearly map to the reference genome. To this end, several programs were developed and critical assessment of various strategies and tools suggested the combination of at least two methods as good practice to guarantee robust circRNA detection. Here,we present CirComPara (http://github.com/egaffo/CirComPara, an automated bioinformatics pipeline, to detect, quantify and annotate circRNAs from RNAseq data using in parallel four different methods for backsplice identification. CirComPara also provides quantification of linear RNAs and gene expression, ultimately comparing and correlating circRNA and gene/transcript expression level. We applied our method to RNAseqdata of monocyte and macrophage samples in relation to haploinsufficiency of the RNAbinding splicing factor Quaking (QKI. The biological relevance of the results, in terms of number, types and variations of circRNAs expressed, illustrates CirComPara potential to enlarge the knowledge of the transcriptome, adding details on the circRNAome, and facilitating further computational and experimental studies.

Bioinformatic analysis of Msx1 and Msx2 involved in craniofacial development.

Science.gov (United States)

Dai, Jiewen; Mou, Zhifang; Shen, Shunyao; Dong, Yuefu; Yang, Tong; Shen, Steve Guofang

2014-01-01

Msx1 and Msx2 were revealed to be candidate genes for some craniofacial deformities, such as cleft lip with/without cleft palate (CL/P) and craniosynostosis. Many other genes were demonstrated to have a cross-talk with MSX genes in causing these defects. However, there is no systematic evaluation for these MSX gene-related factors. In this study, we performed systematic bioinformatic analysis for MSX genes by combining using GeneDecks, DAVID, and STRING database, and the results showed that there were numerous genes related to MSX genes, such as Irf6, TP63, Dlx2, Dlx5, Pax3, Pax9, Bmp4, Tgf-beta2, and Tgf-beta3 that have been demonstrated to be involved in CL/P, and Fgfr2, Fgfr1, Fgfr3, and Twist1 that were involved in craniosynostosis. Many of these genes could be enriched into different gene groups involved in different signaling ways, different craniofacial deformities, and different biological process. These findings could make us analyze the function of MSX gens in a gene network. In addition, our findings showed that Sumo, a novel gene whose polymorphisms were demonstrated to be associated with nonsyndromic CL/P by genome-wide association study, has protein-protein interaction with MSX1, which may offer us an alternative method to perform bioinformatic analysis for genes found by genome-wide association study and can make us predict the disrupted protein function due to the mutation in a gene DNA sequence. These findings may guide us to perform further functional studies in the future.

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

Science.gov (United States)

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

2015-01-01

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

Intrageneric Primer Design: Bringing Bioinformatics Tools to the Class

Science.gov (United States)

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

2006-01-01

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

Rapid cloning and bioinformatic analysis of spinach Y chromosome ...

Indian Academy of Sciences (India)

Rapid cloning and bioinformatic analysis of spinach Y chromosome- specific EST sequences. Chuan-Liang Deng, Wei-Li Zhang, Ying Cao, Shao-Jing Wang, ... Arabidopsis thaliana mRNA for mitochondrial half-ABC transporter (STA1 gene). 389 2.31E-13. 98.96. SP3−12. Betula pendula histidine kinase 3 (HK3) mRNA, ...

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

Science.gov (United States)

Martin, Guillaume; Baurens, Franc-Christophe; Droc, Gaëtan; Rouard, Mathieu; Cenci, Alberto; Kilian, Andrzej; Hastie, Alex; Doležel, Jaroslav; Aury, Jean-Marc; Alberti, Adriana; Carreel, Françoise; D'Hont, Angélique

2016-03-16

Recent advances in genomics indicate functional significance of a majority of genome sequences and their long range interactions. As a detailed examination of genome organization and function requires very high quality genome sequence, the objective of this study was to improve reference genome assembly of banana (Musa acuminata). We have developed a modular bioinformatics pipeline to improve genome sequence assemblies, which can handle various types of data. The pipeline comprises several semi-automated tools. However, unlike classical automated tools that are based on global parameters, the semi-automated tools proposed an expert mode for a user who can decide on suggested improvements through local compromises. The pipeline was used to improve the draft genome sequence of Musa acuminata. Genotyping by sequencing (GBS) of a segregating population and paired-end sequencing were used to detect and correct scaffold misassemblies. Long insert size paired-end reads identified scaffold junctions and fusions missed by automated assembly methods. GBS markers were used to anchor scaffolds to pseudo-molecules with a new bioinformatics approach that avoids the tedious step of marker ordering during genetic map construction. Furthermore, a genome map was constructed and used to assemble scaffolds into super scaffolds. Finally, a consensus gene annotation was projected on the new assembly from two pre-existing annotations. This approach reduced the total Musa scaffold number from 7513 to 1532 (i.e. by 80%), with an N50 that increased from 1.3 Mb (65 scaffolds) to 3.0 Mb (26 scaffolds). 89.5% of the assembly was anchored to the 11 Musa chromosomes compared to the previous 70%. Unknown sites (N) were reduced from 17.3 to 10.0%. The release of the Musa acuminata reference genome version 2 provides a platform for detailed analysis of banana genome variation, function and evolution. Bioinformatics tools developed in this work can be used to improve genome sequence assemblies in

Novel approaches for bioinformatic analysis of salivary RNA sequencing data for development.

Science.gov (United States)

Kaczor-Urbanowicz, Karolina Elzbieta; Kim, Yong; Li, Feng; Galeev, Timur; Kitchen, Rob R; Gerstein, Mark; Koyano, Kikuye; Jeong, Sung-Hee; Wang, Xiaoyan; Elashoff, David; Kang, So Young; Kim, Su Mi; Kim, Kyoung; Kim, Sung; Chia, David; Xiao, Xinshu; Rozowsky, Joel; Wong, David T W

2018-01-01

Analysis of RNA sequencing (RNA-Seq) data in human saliva is challenging. Lack of standardization and unification of the bioinformatic procedures undermines saliva's diagnostic potential. Thus, it motivated us to perform this study. We applied principal pipelines for bioinformatic analysis of small RNA-Seq data of saliva of 98 healthy Korean volunteers including either direct or indirect mapping of the reads to the human genome using Bowtie1. Analysis of alignments to exogenous genomes by another pipeline revealed that almost all of the reads map to bacterial genomes. Thus, salivary exRNA has fundamental properties that warrant the design of unique additional steps while performing the bioinformatic analysis. Our pipelines can serve as potential guidelines for processing of RNA-Seq data of human saliva. Processing and analysis results of the experimental data generated by the exceRpt (v4.6.3) small RNA-seq pipeline (github.gersteinlab.org/exceRpt) are available from exRNA atlas (exrna-atlas.org). Alignment to exogenous genomes and their quantification results were used in this paper for the analyses of small RNAs of exogenous origin. dtww@ucla.edu. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com

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

Directory of Open Access Journals (Sweden)

Fernando González-Nilo

2011-01-01

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

CROSSWORK for Glycans: Glycan Identificatin Through Mass Spectrometry and Bioinformatics

DEFF Research Database (Denmark)

Rasmussen, Morten; Thaysen-Andersen, Morten; Højrup, Peter

  We have developed "GLYCANthrope " - CROSSWORKS for glycans:  a bioinformatics tool, which assists in identifying N-linked glycosylated peptides as well as their glycan moieties from MS2 data of enzymatically digested glycoproteins. The program runs either as a stand-alone application or as a plug...

Hidden in the Middle: Culture, Value and Reward in Bioinformatics

Science.gov (United States)

Lewis, Jamie; Bartlett, Andrew; Atkinson, Paul

2016-01-01

Bioinformatics--the so-called shotgun marriage between biology and computer science--is an interdiscipline. Despite interdisciplinarity being seen as a virtue, for having the capacity to solve complex problems and foster innovation, it has the potential to place projects and people in anomalous categories. For example, valorised…

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

Directory of Open Access Journals (Sweden)

Swainston Neil

2006-12-01

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

A middleware-based platform for the integration of bioinformatic services

Directory of Open Access Journals (Sweden)

Guzmán Llambías

2015-08-01

Full Text Available Performing Bioinformatic´s experiments involve an intensive access to distributed services and information resources through Internet. Although existing tools facilitate the implementation of workflow-oriented applications, they lack of capabilities to integrate services beyond low-scale applications, particularly integrating services with heterogeneous interaction patterns and in a larger scale. This is particularly required to enable a large-scale distributed processing of biological data generated by massive sequencing technologies. On the other hand, such integration mechanisms are provided by middleware products like Enterprise Service Buses (ESB, which enable to integrate distributed systems following a Service Oriented Architecture. This paper proposes an integration platform, based on enterprise middleware, to integrate Bioinformatics services. It presents a multi-level reference architecture and focuses on ESB-based mechanisms to provide asynchronous communications, event-based interactions and data transformation capabilities. The paper presents a formal specification of the platform using the Event-B model.

A Survey on Evolutionary Algorithm Based Hybrid Intelligence in Bioinformatics

Directory of Open Access Journals (Sweden)

Shan Li

2014-01-01

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

Introducing bioinformatics, the biosciences' genomic revolution

CERN Document Server

Zanella, Paolo

1999-01-01

The general audience for these lectures is mainly physicists, computer scientists, engineers or the general public wanting to know more about what’s going on in the biosciences. What’s bioinformatics and why is all this fuss being made about it ? What’s this revolution triggered by the human genome project ? Are there any results yet ? What are the problems ? What new avenues of research have been opened up ? What about the technology ? These new developments will be compared with what happened at CERN earlier in its evolution, and it is hoped that the similiraties and contrasts will stimulate new curiosity and provoke new thoughts.

Emergent Computation Emphasizing Bioinformatics

CERN Document Server

Simon, Matthew

2005-01-01

Emergent Computation is concerned with recent applications of Mathematical Linguistics or Automata Theory. This subject has a primary focus upon "Bioinformatics" (the Genome and arising interest in the Proteome), but the closing chapter also examines applications in Biology, Medicine, Anthropology, etc. The book is composed of an organized examination of DNA, RNA, and the assembly of amino acids into proteins. Rather than examine these areas from a purely mathematical viewpoint (that excludes much of the biochemical reality), the author uses scientific papers written mostly by biochemists based upon their laboratory observations. Thus while DNA may exist in its double stranded form, triple stranded forms are not excluded. Similarly, while bases exist in Watson-Crick complements, mismatched bases and abasic pairs are not excluded, nor are Hoogsteen bonds. Just as there are four bases naturally found in DNA, the existence of additional bases is not ignored, nor amino acids in addition to the usual complement of...

Evaluating the Effectiveness of a Practical Inquiry-Based Learning Bioinformatics Module on Undergraduate Student Engagement and Applied Skills

Science.gov (United States)

Brown, James A. L.

2016-01-01

A pedagogic intervention, in the form of an inquiry-based peer-assisted learning project (as a practical student-led bioinformatics module), was assessed for its ability to increase students' engagement, practical bioinformatic skills and process-specific knowledge. Elements assessed were process-specific knowledge following module completion,…

Neonatal Informatics: Transforming Neonatal Care Through Translational Bioinformatics

Science.gov (United States)

Palma, Jonathan P.; Benitz, William E.; Tarczy-Hornoch, Peter; Butte, Atul J.; Longhurst, Christopher A.

2012-01-01

The future of neonatal informatics will be driven by the availability of increasingly vast amounts of clinical and genetic data. The field of translational bioinformatics is concerned with linking and learning from these data and applying new findings to clinical care to transform the data into proactive, predictive, preventive, and participatory health. As a result of advances in translational informatics, the care of neonates will become more data driven, evidence based, and personalized. PMID:22924023

Cloud BioLinux: pre-configured and on-demand bioinformatics computing for the genomics community.

Science.gov (United States)

Krampis, Konstantinos; Booth, Tim; Chapman, Brad; Tiwari, Bela; Bicak, Mesude; Field, Dawn; Nelson, Karen E

2012-03-19

A steep drop in the cost of next-generation sequencing during recent years has made the technology affordable to the majority of researchers, but downstream bioinformatic analysis still poses a resource bottleneck for smaller laboratories and institutes that do not have access to substantial computational resources. Sequencing instruments are typically bundled with only the minimal processing and storage capacity required for data capture during sequencing runs. Given the scale of sequence datasets, scientific value cannot be obtained from acquiring a sequencer unless it is accompanied by an equal investment in informatics infrastructure. Cloud BioLinux is a publicly accessible Virtual Machine (VM) that enables scientists to quickly provision on-demand infrastructures for high-performance bioinformatics computing using cloud platforms. Users have instant access to a range of pre-configured command line and graphical software applications, including a full-featured desktop interface, documentation and over 135 bioinformatics packages for applications including sequence alignment, clustering, assembly, display, editing, and phylogeny. Each tool's functionality is fully described in the documentation directly accessible from the graphical interface of the VM. Besides the Amazon EC2 cloud, we have started instances of Cloud BioLinux on a private Eucalyptus cloud installed at the J. Craig Venter Institute, and demonstrated access to the bioinformatic tools interface through a remote connection to EC2 instances from a local desktop computer. Documentation for using Cloud BioLinux on EC2 is available from our project website, while a Eucalyptus cloud image and VirtualBox Appliance is also publicly available for download and use by researchers with access to private clouds. Cloud BioLinux provides a platform for developing bioinformatics infrastructures on the cloud. An automated and configurable process builds Virtual Machines, allowing the development of highly

Cloud BioLinux: pre-configured and on-demand bioinformatics computing for the genomics community

Science.gov (United States)

2012-01-01

Background A steep drop in the cost of next-generation sequencing during recent years has made the technology affordable to the majority of researchers, but downstream bioinformatic analysis still poses a resource bottleneck for smaller laboratories and institutes that do not have access to substantial computational resources. Sequencing instruments are typically bundled with only the minimal processing and storage capacity required for data capture during sequencing runs. Given the scale of sequence datasets, scientific value cannot be obtained from acquiring a sequencer unless it is accompanied by an equal investment in informatics infrastructure. Results Cloud BioLinux is a publicly accessible Virtual Machine (VM) that enables scientists to quickly provision on-demand infrastructures for high-performance bioinformatics computing using cloud platforms. Users have instant access to a range of pre-configured command line and graphical software applications, including a full-featured desktop interface, documentation and over 135 bioinformatics packages for applications including sequence alignment, clustering, assembly, display, editing, and phylogeny. Each tool's functionality is fully described in the documentation directly accessible from the graphical interface of the VM. Besides the Amazon EC2 cloud, we have started instances of Cloud BioLinux on a private Eucalyptus cloud installed at the J. Craig Venter Institute, and demonstrated access to the bioinformatic tools interface through a remote connection to EC2 instances from a local desktop computer. Documentation for using Cloud BioLinux on EC2 is available from our project website, while a Eucalyptus cloud image and VirtualBox Appliance is also publicly available for download and use by researchers with access to private clouds. Conclusions Cloud BioLinux provides a platform for developing bioinformatics infrastructures on the cloud. An automated and configurable process builds Virtual Machines, allowing the

Detecting groups of coevolving positions in a molecule: a clustering approach

Directory of Open Access Journals (Sweden)

Galtier Nicolas

2007-11-01

Full Text Available Abstract Background Although the patterns of co-substitutions in RNA is now well characterized, detection of coevolving positions in proteins remains a difficult task. It has been recognized that the signal is typically weak, due to the fact that (i amino-acid are characterized by various biochemical properties, so that distinct amino acids changes are not functionally equivalent, and (ii a given mutation can be compensated by more than one mutation, at more than one position. Results We present a new method based on phylogenetic substitution mapping. The two above-mentioned problems are addressed by (i the introduction of a weighted mapping, which accounts for the biochemical effects (volume, polarity, charge of amino-acid changes, (ii the use of a clustering approach to detect groups of coevolving sites of virtually any size, and (iii the distinction between biochemical compensation and other coevolutionary mechanisms. We apply this methodology to a previously studied data set of bacterial ribosomal RNA, and to three protein data sets (myoglobin of vertebrates, S-locus Receptor Kinase and Methionine Amino-Peptidase. Conclusion We succeed in detecting groups of sites which significantly depart the null hypothesis of independence. Group sizes range from pairs to groups of size ≃ 10, depending on the substitution weights used. The structural and functional relevance of these groups of sites are assessed, and the various evolutionary processes potentially generating correlated substitution patterns are discussed.

Multiobjective optimization in bioinformatics and computational biology.

Science.gov (United States)

Handl, Julia; Kell, Douglas B; Knowles, Joshua

2007-01-01

This paper reviews the application of multiobjective optimization in the fields of bioinformatics and computational biology. A survey of existing work, organized by application area, forms the main body of the review, following an introduction to the key concepts in multiobjective optimization. An original contribution of the review is the identification of five distinct "contexts," giving rise to multiple objectives: These are used to explain the reasons behind the use of multiobjective optimization in each application area and also to point the way to potential future uses of the technique.

Bioinformatics analysis of the predicted polyprenol reductase genes in higher plants

Science.gov (United States)

Basyuni, M.; Wati, R.

2018-03-01

The present study evaluates the bioinformatics methods to analyze twenty-four predicted polyprenol reductase genes from higher plants on GenBank as well as predicted the structure, composition, similarity, subcellular localization, and phylogenetic. The physicochemical properties of plant polyprenol showed diversity among the observed genes. The percentage of the secondary structure of plant polyprenol genes followed the ratio order of α helix > random coil > extended chain structure. The values of chloroplast but not signal peptide were too low, indicated that few chloroplast transit peptide in plant polyprenol reductase genes. The possibility of the potential transit peptide showed variation among the plant polyprenol reductase, suggested the importance of understanding the variety of peptide components of plant polyprenol genes. To clarify this finding, a phylogenetic tree was drawn. The phylogenetic tree shows several branches in the tree, suggested that plant polyprenol reductase genes grouped into divergent clusters in the tree.

Age group classification and gender detection based on forced expiratory spirometry.

Science.gov (United States)

Cosgun, Sema; Ozbek, I Yucel

2015-08-01

This paper investigates the utility of forced expiratory spirometry (FES) test with efficient machine learning algorithms for the purpose of gender detection and age group classification. The proposed method has three main stages: feature extraction, training of the models and detection. In the first stage, some features are extracted from volume-time curve and expiratory flow-volume loop obtained from FES test. In the second stage, the probabilistic models for each gender and age group are constructed by training Gaussian mixture models (GMMs) and Support vector machine (SVM) algorithm. In the final stage, the gender (or age group) of test subject is estimated by using the trained GMM (or SVM) model. Experiments have been evaluated on a large database from 4571 subjects. The experimental results show that average correct classification rate performance of both GMM and SVM methods based on the FES test is more than 99.3 % and 96.8 % for gender and age group classification, respectively.

A web services choreography scenario for interoperating bioinformatics applications

Directory of Open Access Journals (Sweden)

Cheung David W

2004-03-01

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

Group-focused morality is associated with limited conflict detection and resolution capacity: Neuroanatomical evidence.

Science.gov (United States)

Nash, Kyle; Baumgartner, Thomas; Knoch, Daria

2017-02-01

Group-focused moral foundations (GMFs) - moral values that help protect the group's welfare - sharply divide conservatives from liberals and religiously devout from non-believers. However, there is little evidence about what drives this divide. Moral foundations theory and the model of motivated social cognition both associate group-focused moral foundations with differences in conflict detection and resolution capacity, but in opposing directions. Individual differences in conflict detection and resolution implicate specific neuroanatomical differences. Examining neuroanatomy thus affords an objective and non-biased opportunity to contrast these influential theories. Here, we report that increased adherence to group-focused moral foundations was strongly associated (whole-brain corrected) with reduced gray matter volume in key regions of the conflict detection and resolution system (anterior cingulate cortex and lateral prefrontal cortex). Because reduced gray matter is reliably associated with reduced neural and cognitive capacity, these findings support the idea outlined in the model of motivated social cognition that belief in group-focused moral values is associated with reduced conflict detection and resolution capacity. Copyright © 2017 Elsevier B.V. All rights reserved.

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

Science.gov (United States)

2015-01-01

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

Computational Lipidomics and Lipid Bioinformatics: Filling In the Blanks.

Science.gov (United States)

Pauling, Josch; Klipp, Edda

2016-12-22

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

A review of bioinformatic methods for forensic DNA analyses.

Science.gov (United States)

Liu, Yao-Yuan; Harbison, SallyAnn

2018-03-01

Short tandem repeats, single nucleotide polymorphisms, and whole mitochondrial analyses are three classes of markers which will play an important role in the future of forensic DNA typing. The arrival of massively parallel sequencing platforms in forensic science reveals new information such as insights into the complexity and variability of the markers that were previously unseen, along with amounts of data too immense for analyses by manual means. Along with the sequencing chemistries employed, bioinformatic methods are required to process and interpret this new and extensive data. As more is learnt about the use of these new technologies for forensic applications, development and standardization of efficient, favourable tools for each stage of data processing is being carried out, and faster, more accurate methods that improve on the original approaches have been developed. As forensic laboratories search for the optimal pipeline of tools, sequencer manufacturers have incorporated pipelines into sequencer software to make analyses convenient. This review explores the current state of bioinformatic methods and tools used for the analyses of forensic markers sequenced on the massively parallel sequencing (MPS) platforms currently most widely used. Copyright © 2017 Elsevier B.V. All rights reserved.

A generally applicable lightweight method for calculating a value structure for tools and services in bioinformatics infrastructure projects.

Science.gov (United States)

Mayer, Gerhard; Quast, Christian; Felden, Janine; Lange, Matthias; Prinz, Manuel; Pühler, Alfred; Lawerenz, Chris; Scholz, Uwe; Glöckner, Frank Oliver; Müller, Wolfgang; Marcus, Katrin; Eisenacher, Martin

2017-10-30

Sustainable noncommercial bioinformatics infrastructures are a prerequisite to use and take advantage of the potential of big data analysis for research and economy. Consequently, funders, universities and institutes as well as users ask for a transparent value model for the tools and services offered. In this article, a generally applicable lightweight method is described by which bioinformatics infrastructure projects can estimate the value of tools and services offered without determining exactly the total costs of ownership. Five representative scenarios for value estimation from a rough estimation to a detailed breakdown of costs are presented. To account for the diversity in bioinformatics applications and services, the notion of service-specific 'service provision units' is introduced together with the factors influencing them and the main underlying assumptions for these 'value influencing factors'. Special attention is given on how to handle personnel costs and indirect costs such as electricity. Four examples are presented for the calculation of the value of tools and services provided by the German Network for Bioinformatics Infrastructure (de.NBI): one for tool usage, one for (Web-based) database analyses, one for consulting services and one for bioinformatics training events. Finally, from the discussed values, the costs of direct funding and the costs of payment of services by funded projects are calculated and compared. © The Author 2017. Published by Oxford University Press.

Kubernetes as an approach for solving bioinformatic problems.

OpenAIRE

Markstedt, Olof

2017-01-01

The cluster orchestration tool Kubernetes enables easy deployment and reproducibility of life science research by utilizing the advantages of the container technology. The container technology allows for easy tool creation, sharing and runs on any Linux system once it has been built. The applicability of Kubernetes as an approach to run bioinformatic workflows was evaluated and resulted in some examples of how Kubernetes and containers could be used within the field of life science and how th...

Using Bioinformatics to Develop and Test Hypotheses: E. coli-Specific Virulence Determinants

Directory of Open Access Journals (Sweden)

Joanna R. Klein

2012-09-01

Full Text Available Bioinformatics, the use of computer resources to understand biological information, is an important tool in research, and can be easily integrated into the curriculum of undergraduate courses. Such an example is provided in this series of four activities that introduces students to the field of bioinformatics as they design PCR based tests for pathogenic E. coli strains. A variety of computer tools are used including BLAST searches at NCBI, bacterial genome searches at the Integrated Microbial Genomes (IMG database, protein analysis at Pfam and literature research at PubMed. In the process, students also learn about virulence factors, enzyme function and horizontal gene transfer. Some or all of the four activities can be incorporated into microbiology or general biology courses taken by students at a variety of levels, ranging from high school through college. The activities build on one another as they teach and reinforce knowledge and skills, promote critical thinking, and provide for student collaboration and presentation. The computer-based activities can be done either in class or outside of class, thus are appropriate for inclusion in online or blended learning formats. Assessment data showed that students learned general microbiology concepts related to pathogenesis and enzyme function, gained skills in using tools of bioinformatics and molecular biology, and successfully developed and tested a scientific hypothesis.

Data mining in bioinformatics using Weka.

Science.gov (United States)

Frank, Eibe; Hall, Mark; Trigg, Len; Holmes, Geoffrey; Witten, Ian H

2004-10-12

The Weka machine learning workbench provides a general-purpose environment for automatic classification, regression, clustering and feature selection-common data mining problems in bioinformatics research. It contains an extensive collection of machine learning algorithms and data pre-processing methods complemented by graphical user interfaces for data exploration and the experimental comparison of different machine learning techniques on the same problem. Weka can process data given in the form of a single relational table. Its main objectives are to (a) assist users in extracting useful information from data and (b) enable them to easily identify a suitable algorithm for generating an accurate predictive model from it. http://www.cs.waikato.ac.nz/ml/weka.

Domain similarity based orthology detection

OpenAIRE

Bitard-Feildel, Tristan; Kemena, Carsten; Greenwood, Jenny M; Bornberg-Bauer, Erich

2015-01-01

Background Orthologous protein detection software mostly uses pairwise comparisons of amino-acid sequences to assert whether two proteins are orthologous or not. Accordingly, when the number of sequences for comparison increases, the number of comparisons to compute grows in a quadratic order. A current challenge of bioinformatic research, especially when taking into account the increasing number of sequenced organisms available, is to make this ever-growing number of comparisons computationa...

Video Bioinformatics Analysis of Human Embryonic Stem Cell Colony Growth

Science.gov (United States)

Lin, Sabrina; Fonteno, Shawn; Satish, Shruthi; Bhanu, Bir; Talbot, Prue

2010-01-01

Because video data are complex and are comprised of many images, mining information from video material is difficult to do without the aid of computer software. Video bioinformatics is a powerful quantitative approach for extracting spatio-temporal data from video images using computer software to perform dating mining and analysis. In this article, we introduce a video bioinformatics method for quantifying the growth of human embryonic stem cells (hESC) by analyzing time-lapse videos collected in a Nikon BioStation CT incubator equipped with a camera for video imaging. In our experiments, hESC colonies that were attached to Matrigel were filmed for 48 hours in the BioStation CT. To determine the rate of growth of these colonies, recipes were developed using CL-Quant software which enables users to extract various types of data from video images. To accurately evaluate colony growth, three recipes were created. The first segmented the image into the colony and background, the second enhanced the image to define colonies throughout the video sequence accurately, and the third measured the number of pixels in the colony over time. The three recipes were run in sequence on video data collected in a BioStation CT to analyze the rate of growth of individual hESC colonies over 48 hours. To verify the truthfulness of the CL-Quant recipes, the same data were analyzed manually using Adobe Photoshop software. When the data obtained using the CL-Quant recipes and Photoshop were compared, results were virtually identical, indicating the CL-Quant recipes were truthful. The method described here could be applied to any video data to measure growth rates of hESC or other cells that grow in colonies. In addition, other video bioinformatics recipes can be developed in the future for other cell processes such as migration, apoptosis, and cell adhesion. PMID:20495527

Bioinformatics and structural characterization of a hypothetical protein from Streptococcus mutans

DEFF Research Database (Denmark)

Nan, Jie; Brostromer, Erik; Liu, Xiang-Yu

2009-01-01

. From the interlinking structural and bioinformatics studies, we have concluded that SMU.440 could be involved in polyketide-like antibiotic resistance, providing a better understanding of this hypothetical protein. Besides, the combination of multiple methods in this study can be used as a general...

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

Directory of Open Access Journals (Sweden)

Emile R Chimusa

2015-11-01

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

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

Science.gov (United States)

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

2015-11-01

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

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

Science.gov (United States)

Vamathevan, J; Birney, E

2017-08-01

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

Bioinformatic and Comparative Localization of Rab Proteins Reveals Functional Insights into the Uncharacterized GTPases Ypt10p and Ypt11p†

OpenAIRE

Buvelot Frei, Stéphanie; Rahl, Peter B.; Nussbaum, Maria; Briggs, Benjamin J.; Calero, Monica; Janeczko, Stephanie; Regan, Andrew D.; Chen, Catherine Z.; Barral, Yves; Whittaker, Gary R.; Collins, Ruth N.

2006-01-01

A striking characteristic of a Rab protein is its steady-state localization to the cytosolic surface of a particular subcellular membrane. In this study, we have undertaken a combined bioinformatic and experimental approach to examine the evolutionary conservation of Rab protein localization. A comprehensive primary sequence classification shows that 10 out of the 11 Rab proteins identified in the yeast (Saccharomyces cerevisiae) genome can be grouped within a major subclass, each comprising ...

Databases and Associated Bioinformatic Tools in Studies of Food Allergens, Epitopes and Haptens – a Review

Directory of Open Access Journals (Sweden)

Bucholska Justyna

2018-06-01

Full Text Available Allergies and/or food intolerances are a growing problem of the modern world. Diffi culties associated with the correct diagnosis of food allergies result in the need to classify the factors causing allergies and allergens themselves. Therefore, internet databases and other bioinformatic tools play a special role in deepening knowledge of biologically-important compounds. Internet repositories, as a source of information on different chemical compounds, including those related to allergy and intolerance, are increasingly being used by scientists. Bioinformatic methods play a signifi cant role in biological and medical sciences, and their importance in food science is increasing. This study aimed at presenting selected databases and tools of bioinformatic analysis useful in research on food allergies, allergens (11 databases, epitopes (7 databases, and haptens (2 databases. It also presents examples of the application of computer methods in studies related to allergies.

Bioinformatics prediction of swine MHC class I epitopes from Porcine Reproductive and Respiratory Syndrome Virus

DEFF Research Database (Denmark)

Welner, Simon; Nielsen, Morten; Lund, Ole

an effective CTL response against PRRSV, we have taken a bioinformatics approach to identify common PRRSV epitopes predicted to react broadly with predominant swine MHC (SLA) alleles. First, the genomic integrity and sequencing method was examined for 334 available complete PRRSV type 2 genomes leaving 104...... by the PopCover algorithm, providing a final list of 54 epitopes prioritized according to maximum coverage of PRRSV strains and SLA alleles. This bioinformatics approach provides a rational strategy for selecting peptides for a CTL-activating vaccine with broad coverage of both virus and swine diversity...

Bioinformatics approach of salt tolerance gene in mangrove plant Rhizophora stylosa

Science.gov (United States)

Basyuni, M.; Sumardi

2017-01-01

This study descibes bioinformatics approach on the analyze of the salt tolerance genes in mangrove plant, Rhizophora stylosa on DDBJ/EMBL/GenBank as well as similarity, phylogenetic, potential peptide, and subcellular localization. The DNA sequence between salt tolerance gene from R. stylosa exhibited 42-11% between themselves The target peptide value of mitochondria varied from 0.163 to 0.430, indicated it was possible to exist. These results suggested the importance of understanding the diversity and functional of properties of the different amino acids in mangrove OSC genes. To clarify the relationship among the salt-tolerant genes in R. stylosa, a phylogenetic tree was constructed. The phylogenetic tree shows that there are three clusters, first branch of Cu/Zn SOD and reverse transcriptase genes, the second branch consists of the majority genes and the last group was MAP3K alpha protein kinase only. The present study, therefore, suggested that salt tolerance genes form distinct clusters in the tree.

Designing a course model for distance-based online bioinformatics training in Africa: The H3ABioNet experience

Science.gov (United States)

Panji, Sumir; Fernandes, Pedro L.; Judge, David P.; Ghouila, Amel; Salifu, Samson P.; Ahmed, Rehab; Kayondo, Jonathan; Ssemwanga, Deogratius

2017-01-01

Africa is not unique in its need for basic bioinformatics training for individuals from a diverse range of academic backgrounds. However, particular logistical challenges in Africa, most notably access to bioinformatics expertise and internet stability, must be addressed in order to meet this need on the continent. H3ABioNet (www.h3abionet.org), the Pan African Bioinformatics Network for H3Africa, has therefore developed an innovative, free-of-charge “Introduction to Bioinformatics” course, taking these challenges into account as part of its educational efforts to provide on-site training and develop local expertise inside its network. A multiple-delivery–mode learning model was selected for this 3-month course in order to increase access to (mostly) African, expert bioinformatics trainers. The content of the course was developed to include a range of fundamental bioinformatics topics at the introductory level. For the first iteration of the course (2016), classrooms with a total of 364 enrolled participants were hosted at 20 institutions across 10 African countries. To ensure that classroom success did not depend on stable internet, trainers pre-recorded their lectures, and classrooms downloaded and watched these locally during biweekly contact sessions. The trainers were available via video conferencing to take questions during contact sessions, as well as via online “question and discussion” forums outside of contact session time. This learning model, developed for a resource-limited setting, could easily be adapted to other settings. PMID:28981516

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

Science.gov (United States)

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

2013-01-01

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

GeneDig: a web application for accessing genomic and bioinformatics knowledge.

Science.gov (United States)

Suciu, Radu M; Aydin, Emir; Chen, Brian E

2015-02-28

With the exponential increase and widespread availability of genomic, transcriptomic, and proteomic data, accessing these '-omics' data is becoming increasingly difficult. The current resources for accessing and analyzing these data have been created to perform highly specific functions intended for specialists, and thus typically emphasize functionality over user experience. We have developed a web-based application, GeneDig.org, that allows any general user access to genomic information with ease and efficiency. GeneDig allows for searching and browsing genes and genomes, while a dynamic navigator displays genomic, RNA, and protein information simultaneously for co-navigation. We demonstrate that our application allows more than five times faster and efficient access to genomic information than any currently available methods. We have developed GeneDig as a platform for bioinformatics integration focused on usability as its central design. This platform will introduce genomic navigation to broader audiences while aiding the bioinformatics analyses performed in everyday biology research.

Host-parasite interactions and ecology of the malaria parasite-a bioinformatics approach.

Science.gov (United States)

Izak, Dariusz; Klim, Joanna; Kaczanowski, Szymon

2018-04-25

Malaria remains one of the highest mortality infectious diseases. Malaria is caused by parasites from the genus Plasmodium. Most deaths are caused by infections involving Plasmodium falciparum, which has a complex life cycle. Malaria parasites are extremely well adapted for interactions with their host and their host's immune system and are able to suppress the human immune system, erase immunological memory and rapidly alter exposed antigens. Owing to this rapid evolution, parasites develop drug resistance and express novel forms of antigenic proteins that are not recognized by the host immune system. There is an emerging need for novel interventions, including novel drugs and vaccines. Designing novel therapies requires knowledge about host-parasite interactions, which is still limited. However, significant progress has recently been achieved in this field through the application of bioinformatics analysis of parasite genome sequences. In this review, we describe the main achievements in 'malarial' bioinformatics and provide examples of successful applications of protein sequence analysis. These examples include the prediction of protein functions based on homology and the prediction of protein surface localization via domain and motif analysis. Additionally, we describe PlasmoDB, a database that stores accumulated experimental data. This tool allows data mining of the stored information and will play an important role in the development of malaria science. Finally, we illustrate the application of bioinformatics in the development of population genetics research on malaria parasites, an approach referred to as reverse ecology.

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

Science.gov (United States)

Kalas, Matús; Puntervoll, Pål; Joseph, Alexandre; Bartaseviciūte, Edita; Töpfer, Armin; Venkataraman, Prabakar; Pettifer, Steve; Bryne, Jan Christian; Ison, Jon; Blanchet, Christophe; Rapacki, Kristoffer; Jonassen, Inge

2010-09-15

The world-wide community of life scientists has access to a large number of public bioinformatics databases and tools, which are developed and deployed using diverse technologies and designs. More and more of the resources offer programmatic web-service interface. However, efficient use of the resources is hampered by the lack of widely used, standard data-exchange formats for the basic, everyday bioinformatics data types. BioXSD has been developed as a candidate for standard, canonical exchange format for basic bioinformatics data. BioXSD is represented by a dedicated XML Schema and defines syntax for biological sequences, sequence annotations, alignments and references to resources. We have adapted a set of web services to use BioXSD as the input and output format, and implemented a test-case workflow. This demonstrates that the approach is feasible and provides smooth interoperability. Semantics for BioXSD is provided by annotation with the EDAM ontology. We discuss in a separate section how BioXSD relates to other initiatives and approaches, including existing standards and the Semantic Web. The BioXSD 1.0 XML Schema is freely available at http://www.bioxsd.org/BioXSD-1.0.xsd under the Creative Commons BY-ND 3.0 license. The http://bioxsd.org web page offers documentation, examples of data in BioXSD format, example workflows with source codes in common programming languages, an updated list of compatible web services and tools and a repository of feature requests from the community.

Novel C16orf57 mutations in patients with Poikiloderma with Neutropenia: bioinformatic analysis of the protein and predicted effects of all reported mutations

Directory of Open Access Journals (Sweden)

Colombo Elisa A

2012-01-01

Full Text Available Abstract Background Poikiloderma with Neutropenia (PN is a rare autosomal recessive genodermatosis caused by C16orf57 mutations. To date 17 mutations have been identified in 31 PN patients. Results We characterize six PN patients expanding the clinical phenotype of the syndrome and the mutational repertoire of the gene. We detect the two novel C16orf57 mutations, c.232C>T and c.265+2T>G, as well as the already reported c.179delC, c.531delA and c.693+1G>T mutations. cDNA analysis evidences the presence of aberrant transcripts, and bioinformatic prediction of C16orf57 protein structure gauges the mutations effects on the folded protein chain. Computational analysis of the C16orf57 protein shows two conserved H-X-S/T-X tetrapeptide motifs marking the active site of a two-fold pseudosymmetric structure recalling the 2H phosphoesterase superfamily. Based on this model C16orf57 is likely a 2H-active site enzyme functioning in RNA processing, as a presumptive RNA ligase. According to bioinformatic prediction, all known C16orf57 mutations, including the novel mutations herein described, impair the protein structure by either removing one or both tetrapeptide motifs or by destroying the symmetry of the native folding. Finally, we analyse the geographical distribution of the recurrent mutations that depicts clusters featuring a founder effect. Conclusions In cohorts of patients clinically affected by genodermatoses with overlapping symptoms, the molecular screening of C16orf57 gene seems the proper way to address the correct diagnosis of PN, enabling the syndrome-specific oncosurveillance. The bioinformatic prediction of the C16orf57 protein structure denotes a very basic enzymatic function consistent with a housekeeping function. Detection of aberrant transcripts, also in cells from PN patients carrying early truncated mutations, suggests they might be translatable. Tissue-specific sensitivity to the lack of functionally correct protein accounts for the

Shared Bioinformatics Databases within the Unipro UGENE Platform

Directory of Open Access Journals (Sweden)

Protsyuk Ivan V.

2015-03-01

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

Robust Bioinformatics Recognition with VLSI Biochip Microsystem

Science.gov (United States)

Lue, Jaw-Chyng L.; Fang, Wai-Chi

2006-01-01

A microsystem architecture for real-time, on-site, robust bioinformatic patterns recognition and analysis has been proposed. This system is compatible with on-chip DNA analysis means such as polymerase chain reaction (PCR)amplification. A corresponding novel artificial neural network (ANN) learning algorithm using new sigmoid-logarithmic transfer function based on error backpropagation (EBP) algorithm is invented. Our results show the trained new ANN can recognize low fluorescence patterns better than the conventional sigmoidal ANN does. A differential logarithmic imaging chip is designed for calculating logarithm of relative intensities of fluorescence signals. The single-rail logarithmic circuit and a prototype ANN chip are designed, fabricated and characterized.

Molecular cloing and bioinformatics analysis of lactate dehydrogenase from Taenia multiceps.

Science.gov (United States)

Guo, Cheng; Wang, Yu; Huang, Xing; Wang, Ning; Yan, Ming; He, Ran; Gu, Xiaobin; Xie, Yue; Lai, Weimin; Jing, Bo; Peng, Xuerong; Yang, Guangyou

2017-10-01

Coenurus cerebralis, the larval stage (metacestode or coenurus) of Taenia multiceps, parasitizes sheep, goats, and other ruminants and causes coenurosis. In this study, we isolated and characterized complementary DNAs that encode lactate dehydrogenase A (Tm-LDHA) and B (Tm-LDHB) from the transcriptome of T. multiceps and expressed recombinant Tm-LDHB (rTm-LDHB) in Escherichia coli. Bioinformatic analysis showed that both Tm-LDH genes (LDHA and LDHB) contain a 996-bp open reading frame and encode a protein of 331 amino acids. After determination of the immunogenicity of the recombinant Tm-LDHB, an indirect enzyme-linked immunosorbent assay (ELISA) was developed for preliminary evaluation of the serodiagnostic potential of rTm-LDHB in goats. However, the rTm-LDHB-based indirect ELISA developed here exhibited specificity of only 71.42% (10/14) and sensitivity of 1:3200 in detection of goats infected with T. multiceps in the field. This study is the first to describe LDHA and LDHB of T. multiceps; meanwhile, our results indicate that rTm-LDHB is not a specific antigen candidate for immunodiagnosis of T. multiceps infection in goats.

Microbial bioinformatics 2020.

Science.gov (United States)

Pallen, Mark J

2016-09-01

Microbial bioinformatics in 2020 will remain a vibrant, creative discipline, adding value to the ever-growing flood of new sequence data, while embracing novel technologies and fresh approaches. Databases and search strategies will struggle to cope and manual curation will not be sustainable during the scale-up to the million-microbial-genome era. Microbial taxonomy will have to adapt to a situation in which most microorganisms are discovered and characterised through the analysis of sequences. Genome sequencing will become a routine approach in clinical and research laboratories, with fresh demands for interpretable user-friendly outputs. The "internet of things" will penetrate healthcare systems, so that even a piece of hospital plumbing might have its own IP address that can be integrated with pathogen genome sequences. Microbiome mania will continue, but the tide will turn from molecular barcoding towards metagenomics. Crowd-sourced analyses will collide with cloud computing, but eternal vigilance will be the price of preventing the misinterpretation and overselling of microbial sequence data. Output from hand-held sequencers will be analysed on mobile devices. Open-source training materials will address the need for the development of a skilled labour force. As we boldly go into the third decade of the twenty-first century, microbial sequence space will remain the final frontier! © 2016 The Author. Microbial Biotechnology published by John Wiley & Sons Ltd and Society for Applied Microbiology.

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

Directory of Open Access Journals (Sweden)

Sophie Depiereux

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

Tissue damage in organic rainbow trout muscle investigated by proteomics and bioinformatics

DEFF Research Database (Denmark)

Wulff, Tune; Silva, T.; Nielsen, Michael Engelbrecht

2013-01-01

and magnitude of the cellular response, in the context of a regenerative process. Using a bioinformatics approach, the main biological function of these proteins were assigned, showing the regulation of proteins involved in processes like apoptosis, iron homeostasis and regulation of muscular structure...

Why Choose This One? Factors in Scientists' Selection of Bioinformatics Tools

Science.gov (United States)

Bartlett, Joan C.; Ishimura, Yusuke; Kloda, Lorie A.

2011-01-01

Purpose: The objective was to identify and understand the factors involved in scientists' selection of preferred bioinformatics tools, such as databases of gene or protein sequence information (e.g., GenBank) or programs that manipulate and analyse biological data (e.g., BLAST). Methods: Eight scientists maintained research diaries for a two-week…

Application of virtual phase-shifting speckle-interferometry for detection of polymorphism in the Chlamydia trachomatis omp1 gene

Science.gov (United States)

Feodorova, Valentina A.; Saltykov, Yury V.; Zaytsev, Sergey S.; Ulyanov, Sergey S.; Ulianova, Onega V.

2018-04-01

Method of phase-shifting speckle-interferometry has been used as a new tool with high potency for modern bioinformatics. Virtual phase-shifting speckle-interferometry has been applied for detection of polymorphism in the of Chlamydia trachomatis omp1 gene. It has been shown, that suggested method is very sensitive to natural genetic mutations as single nucleotide polymorphism (SNP). Effectiveness of proposed method has been compared with effectiveness of the newest bioinformatic tools, based on nucleotide sequence alignment.

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

Science.gov (United States)

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

2013-01-01

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

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

Science.gov (United States)

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

2010-01-01

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

Detection of cytokine expression patterns in the peripheral blood of patients with acute leukemia by antibody microarray analysis.

Science.gov (United States)

Li, Qing; Li, Mei; Wu, Yao-hui; Zhu, Xiao-jian; Zeng, Chen; Zou, Ping; Chen, Zhi-chao

2014-04-01

The cytokines of acute leukemia (AL) patients have certain expression patterns, forming a complex network involved in diagnosis, progression, and prognosis. We collected the serum of different AL patients before and after complete remission (CR) for detection of cytokines by using an antibody chip. The expression patterns of cytokines were determined by using bioinformatics computational analysis. The results showed that there were significant differences in the cytokine expression patterns between AL patients and normal controls, as well as between acute myeloid leukemia (AML) and acute lymphoblastic leukemia (ALL). In confirmatory test, ELISA revealed the expression of uPAR in AL. Moreover, the bioinformatic analysis showed that the differentially expressed cytokines among the AL groups were involved in different biological behaviors and were closely related with the development of the disease. It was concluded that the cytokine expression pattern of AL patients is significantly different from that of healthy volunteers. Also, differences of cytokine expression patterns exist between AML and ALL, and between before and after CR in the same subtype of AL, which holds important clinical significance for revealing disease progression.

Bioinformatic analysis of functional differences between the immunoproteasome and the constitutive proteasome

DEFF Research Database (Denmark)

Kesmir, Can; van Noort, V.; de Boer, R.J.

2003-01-01

not yet been quantified how different the specificity of two forms of the proteasome are. The main question, which still lacks direct evidence, is whether the immunoproteasome generates more MHC ligands. Here we use bioinformatics tools to quantify these differences and show that the immunoproteasome...

In-depth analysis of the adipocyte proteome by mass spectrometry and bioinformatics

DEFF Research Database (Denmark)

Adachi, Jun; Kumar, Chanchal; Zhang, Yanling

2007-01-01

, mitochondria, membrane, and cytosol of 3T3-L1 adipocytes. We identified 3,287 proteins while essentially eliminating false positives, making this one of the largest high confidence proteomes reported to date. Comprehensive bioinformatics analysis revealed that the adipocyte proteome, despite its specialized...

Bioinformatics analysis of Brucella vaccines and vaccine targets using VIOLIN.

Science.gov (United States)

He, Yongqun; Xiang, Zuoshuang

2010-09-27

Brucella spp. are Gram-negative, facultative intracellular bacteria that cause brucellosis, one of the commonest zoonotic diseases found worldwide in humans and a variety of animal species. While several animal vaccines are available, there is no effective and safe vaccine for prevention of brucellosis in humans. VIOLIN (http://www.violinet.org) is a web-based vaccine database and analysis system that curates, stores, and analyzes published data of commercialized vaccines, and vaccines in clinical trials or in research. VIOLIN contains information for 454 vaccines or vaccine candidates for 73 pathogens. VIOLIN also contains many bioinformatics tools for vaccine data analysis, data integration, and vaccine target prediction. To demonstrate the applicability of VIOLIN for vaccine research, VIOLIN was used for bioinformatics analysis of existing Brucella vaccines and prediction of new Brucella vaccine targets. VIOLIN contains many literature mining programs (e.g., Vaxmesh) that provide in-depth analysis of Brucella vaccine literature. As a result of manual literature curation, VIOLIN contains information for 38 Brucella vaccines or vaccine candidates, 14 protective Brucella antigens, and 68 host response studies to Brucella vaccines from 97 peer-reviewed articles. These Brucella vaccines are classified in the Vaccine Ontology (VO) system and used for different ontological applications. The web-based VIOLIN vaccine target prediction program Vaxign was used to predict new Brucella vaccine targets. Vaxign identified 14 outer membrane proteins that are conserved in six virulent strains from B. abortus, B. melitensis, and B. suis that are pathogenic in humans. Of the 14 membrane proteins, two proteins (Omp2b and Omp31-1) are not present in B. ovis, a Brucella species that is not pathogenic in humans. Brucella vaccine data stored in VIOLIN were compared and analyzed using the VIOLIN query system. Bioinformatics curation and ontological representation of Brucella vaccines

Bioinformatics: Cheap and robust method to explore biomaterial from Indonesia biodiversity

Science.gov (United States)

Widodo

2015-02-01

Indonesia has a huge amount of biodiversity, which may contain many biomaterials for pharmaceutical application. These resources potency should be explored to discover new drugs for human wealth. However, the bioactive screening using conventional methods is very expensive and time-consuming. Therefore, we developed a methodology for screening the potential of natural resources based on bioinformatics. The method is developed based on the fact that organisms in the same taxon will have similar genes, metabolism and secondary metabolites product. Then we employ bioinformatics to explore the potency of biomaterial from Indonesia biodiversity by comparing species with the well-known taxon containing the active compound through published paper or chemical database. Then we analyze drug-likeness, bioactivity and the target proteins of the active compound based on their molecular structure. The target protein was examined their interaction with other proteins in the cell to determine action mechanism of the active compounds in the cellular level, as well as to predict its side effects and toxicity. By using this method, we succeeded to screen anti-cancer, immunomodulators and anti-inflammation from Indonesia biodiversity. For example, we found anticancer from marine invertebrate by employing the method. The anti-cancer was explore based on the isolated compounds of marine invertebrate from published article and database, and then identified the protein target, followed by molecular pathway analysis. The data suggested that the active compound of the invertebrate able to kill cancer cell. Further, we collect and extract the active compound from the invertebrate, and then examined the activity on cancer cell (MCF7). The MTT result showed that the methanol extract of marine invertebrate was highly potent in killing MCF7 cells. Therefore, we concluded that bioinformatics is cheap and robust way to explore bioactive from Indonesia biodiversity for source of drug and another

OralCard: a bioinformatic tool for the study of oral proteome.

Science.gov (United States)

Arrais, Joel P; Rosa, Nuno; Melo, José; Coelho, Edgar D; Amaral, Diana; Correia, Maria José; Barros, Marlene; Oliveira, José Luís

2013-07-01

The molecular complexity of the human oral cavity can only be clarified through identification of components that participate within it. However current proteomic techniques produce high volumes of information that are dispersed over several online databases. Collecting all of this data and using an integrative approach capable of identifying unknown associations is still an unsolved problem. This is the main motivation for this work. We present the online bioinformatic tool OralCard, which comprises results from 55 manually curated articles reflecting the oral molecular ecosystem (OralPhysiOme). It comprises experimental information available from the oral proteome both of human (OralOme) and microbial origin (MicroOralOme) structured in protein, disease and organism. This tool is a key resource for researchers to understand the molecular foundations implicated in biology and disease mechanisms of the oral cavity. The usefulness of this tool is illustrated with the analysis of the oral proteome associated with diabetes melitus type 2. OralCard is available at http://bioinformatics.ua.pt/oralcard. Copyright © 2013 Elsevier Ltd. All rights reserved.

Efficient Feature Selection and Classification of Protein Sequence Data in Bioinformatics

Science.gov (United States)

Faye, Ibrahima; Samir, Brahim Belhaouari; Md Said, Abas

2014-01-01

Bioinformatics has been an emerging area of research for the last three decades. The ultimate aims of bioinformatics were to store and manage the biological data, and develop and analyze computational tools to enhance their understanding. The size of data accumulated under various sequencing projects is increasing exponentially, which presents difficulties for the experimental methods. To reduce the gap between newly sequenced protein and proteins with known functions, many computational techniques involving classification and clustering algorithms were proposed in the past. The classification of protein sequences into existing superfamilies is helpful in predicting the structure and function of large amount of newly discovered proteins. The existing classification results are unsatisfactory due to a huge size of features obtained through various feature encoding methods. In this work, a statistical metric-based feature selection technique has been proposed in order to reduce the size of the extracted feature vector. The proposed method of protein classification shows significant improvement in terms of performance measure metrics: accuracy, sensitivity, specificity, recall, F-measure, and so forth. PMID:25045727

MOWServ: a web client for integration of bioinformatic resources

Science.gov (United States)

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

2010-01-01

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

Extending Abdominal Aortic Aneurysm Detection to Older Age Groups

DEFF Research Database (Denmark)

Makrygiannis, Georgios; Labalue, Philippe; Erpicum, Marie

2016-01-01

. Current screening policies (e.g., men aged 65-74 years), however, do not account for aging and increased life expectancy of Western populations. This study investigated AAA detection by extending the target population to older age groups (75-85 years). METHODS: AAA screening was conducted in the County......-74 age group but rose to 7.3% in the age-extended group (75-85 years). Further in addition to age, height, current smoking, history of coronary artery disease, hypercholesterolemia, peripheral artery disease of the lower limbs, and varicose veins were significantly associated with the presence of AAA......BACKGROUND: There is evident benefit in terms of reduced aneurysm-related mortality from screening programs of abdominal aortic aneurysm (AAA) in men aged 65 years and more. Recent studies in the United Kingdom and Sweden have shown a decline of the prevalence of AAA in the general population...

Single-Cell Transcriptomics Bioinformatics and Computational Challenges

Directory of Open Access Journals (Sweden)

Lana Garmire

2016-09-01

Full Text Available The emerging single-cell RNA-Seq (scRNA-Seq technology holds the promise to revolutionize our understanding of diseases and associated biological processes at an unprecedented resolution. It opens the door to reveal the intercellular heterogeneity and has been employed to a variety of applications, ranging from characterizing cancer cells subpopulations to elucidating tumor resistance mechanisms. Parallel to improving experimental protocols to deal with technological issues, deriving new analytical methods to reveal the complexity in scRNA-Seq data is just as challenging. Here we review the current state-of-the-art bioinformatics tools and methods for scRNA-Seq analysis, as well as addressing some critical analytical challenges that the field faces.

Analysis of microRNA profile of Anopheles sinensis by deep sequencing and bioinformatic approaches.

Science.gov (United States)

Feng, Xinyu; Zhou, Xiaojian; Zhou, Shuisen; Wang, Jingwen; Hu, Wei

2018-03-12

microRNAs (miRNAs) are small non-coding RNAs widely identified in many mosquitoes. They are reported to play important roles in development, differentiation and innate immunity. However, miRNAs in Anopheles sinensis, one of the Chinese malaria mosquitoes, remain largely unknown. We investigated the global miRNA expression profile of An. sinensis using Illumina Hiseq 2000 sequencing. Meanwhile, we applied a bioinformatic approach to identify potential miRNAs in An. sinensis. The identified miRNA profiles were compared and analyzed by two approaches. The selected miRNAs from the sequencing result and the bioinformatic approach were confirmed with qRT-PCR. Moreover, target prediction, GO annotation and pathway analysis were carried out to understand the role of miRNAs in An. sinensis. We identified 49 conserved miRNAs and 12 novel miRNAs by next-generation high-throughput sequencing technology. In contrast, 43 miRNAs were predicted by the bioinformatic approach, of which two were assigned as novel. Comparative analysis of miRNA profiles by two approaches showed that 21 miRNAs were shared between them. Twelve novel miRNAs did not match any known miRNAs of any organism, indicating that they are possibly species-specific. Forty miRNAs were found in many mosquito species, indicating that these miRNAs are evolutionally conserved and may have critical roles in the process of life. Both the selected known and novel miRNAs (asi-miR-281, asi-miR-184, asi-miR-14, asi-miR-nov5, asi-miR-nov4, asi-miR-9383, and asi-miR-2a) could be detected by quantitative real-time PCR (qRT-PCR) in the sequenced sample, and the expression patterns of these miRNAs measured by qRT-PCR were in concordance with the original miRNA sequencing data. The predicted targets for the known and the novel miRNAs covered many important biological roles and pathways indicating the diversity of miRNA functions. We also found 21 conserved miRNAs and eight counterparts of target immune pathway genes in An. sinensis

Bioinformatics approach of three partial polyprenol reductase genes in Kandelia obovata

Science.gov (United States)

Basyuni, M.; Wati, R.; Sagami, H.; Oku, H.; Baba, S.

2018-03-01

This present study describesthe bioinformatics approach to analyze three partial polyprenol reductase genes from mangrove plant, Kandeliaobovataas well aspredictedphysical and chemical properties, potential peptide, subcellular localization, and phylogenetic. The diversity was noted in the physical and chemical properties of three partial polyprenol reductase genes. The values of chloroplast were relatively high, showed that chloroplast transit peptide occurred in mangrove polyprenol reductase. The target peptide value of mitochondria varied from 0.088 to 0.198 indicated it was possible to be present. These results suggested the importance of understanding the diversity of physicochemical properties of the different amino acids in polyprenol reductase. The subcellular localization of two partial genes located in the plasma membrane. To confirm the homology among the polyprenol reductase in the database, a dendrogram was drawn. The phylogenetic tree depicts that there are three clusters, the partial genes of K. obovata joined the largest one: C23157 was close to Ricinus communis polyprenol reductase. Whereas, C23901 and C24171 were grouped with Ipomoea nil polyprenol reductase, suggested that these polyprenol reductase genes form distinct separation into tropical habitat plants.

Synergy between Medical Informatics and Bioinformatics: Facilitating Genomic Medicine for Future Health Care

Czech Academy of Sciences Publication Activity Database

Martin-Sanchez, F.; Iakovidis, I.; Norager, S.; Maojo, V.; de Groen, P.; Van der Lei, J.; Jones, T.; Abraham-Fuchs, K.; Apweiler, R.; Babic, A.; Baud, R.; Breton, V.; Cinquin, P.; Doupi, P.; Dugas, M.; Eils, R.; Engelbrecht, R.; Ghazal, P.; Jehenson, P.; Kulikowski, C.; Lampe, K.; De Moor, G.; Orphanoudakis, S.; Rossing, N.; Sarachan, B.; Sousa, A.; Spekowius, G.; Thireos, G.; Zahlmann, G.; Zvárová, Jana; Hermosilla, I.; Vicente, F. J.

2004-01-01

Roč. 37, - (2004), s. 30-42 ISSN 1532-0464 Institutional research plan: CEZ:AV0Z1030915 Keywords : bioinformatics * medical informatics * genomics * genomic medicine * biomedical informatics Subject RIV: BD - Theory of Information Impact factor: 1.013, year: 2004

Strategies for Using Peer-Assisted Learning Effectively in an Undergraduate Bioinformatics Course

Science.gov (United States)

Shapiro, Casey; Ayon, Carlos; Moberg-Parker, Jordan; Levis-Fitzgerald, Marc; Sanders, Erin R.

2013-01-01

This study used a mixed methods approach to evaluate hybrid peer-assisted learning approaches incorporated into a bioinformatics tutorial for a genome annotation research project. Quantitative and qualitative data were collected from undergraduates who enrolled in a research-based laboratory course during two different academic terms at UCLA.…

Serological and molecular detection of spotted fever group Rickettsia in a group of pet dogs from Luanda, Angola.

Science.gov (United States)

Barradas, Patrícia F; Vilhena, Hugo; Oliveira, Ana Cristina; Granada, Sara; Amorim, Irina; Ferreira, Paula; Cardoso, Luís; Gärtner, Fátima; de Sousa, Rita

2017-05-31

Infections with tick-borne rickettsiae can cause diseases well known in humans but still not so well characterized in dogs. Susceptibility to infection depends on the virulence of Rickettsia spp. and only a few of them have been described to cause disease in dogs. The aim of this study was to investigate the exposure to Rickettsia spp. among a group of pet dogs from Luanda, Angola. Out of 103 dogs included in the study, 62 (60.2%) were infested with ticks. Plasma specimens tested for serology by an immunofluorescence assay (IFA) revealed that six (5.8%) dogs had detectable immunoglobulin G (IgG) antibodies to spotted fever group Rickettsia (SFGR), with endpoint titers of 64 for two dogs, 128 for three dogs and 1024 for one dog. From the seropositive group of dogs, five (83%) of them were males, with their age ranging from 1 to 8 years old. Among the seropositive dogs, four (66.7%) were parasitized with ticks and no breed (or cross) was found to be associated with specific antibodies. Rickettsia spp. DNA was detected by nested-polymerase chain reaction (PCR) in two (1.9%) dogs that were found to be seronegative. Seroprevalence and molecular detection of Rickettsia spp. infection in this group of pet dogs from Luanda is low compared with other studies performed in the same type of hosts in other areas. Although many dogs were parasitized with ticks, a low prevalence of Rickettsia spp. could be related with the hypothesis of a low rickettsial prevalence in the infesting ticks. This study provides evidence that dogs in Luanda are exposed to Rickettsia spp., but further studies are needed to better characterize the bacterial infections in dogs and in their ectoparasites.

Combining multiple decisions: applications to bioinformatics

International Nuclear Information System (INIS)

Yukinawa, N; Ishii, S; Takenouchi, T; Oba, S

2008-01-01

Multi-class classification is one of the fundamental tasks in bioinformatics and typically arises in cancer diagnosis studies by gene expression profiling. This article reviews two recent approaches to multi-class classification by combining multiple binary classifiers, which are formulated based on a unified framework of error-correcting output coding (ECOC). The first approach is to construct a multi-class classifier in which each binary classifier to be aggregated has a weight value to be optimally tuned based on the observed data. In the second approach, misclassification of each binary classifier is formulated as a bit inversion error with a probabilistic model by making an analogy to the context of information transmission theory. Experimental studies using various real-world datasets including cancer classification problems reveal that both of the new methods are superior or comparable to other multi-class classification methods

Secretome Analysis of Lipid-Induced Insulin Resistance in Skeletal Muscle Cells by a Combined Experimental and Bioinformatics Workflow

DEFF Research Database (Denmark)

Deshmukh, Atul S; Cox, Juergen; Jensen, Lars Juhl

2015-01-01

, in principle, allows an unbiased and comprehensive analysis of cellular secretomes; however, the distinction of bona fide secreted proteins from proteins released upon lysis of a small fraction of dying cells remains challenging. Here we applied highly sensitive MS and streamlined bioinformatics to analyze......-resistant conditions. Our study demonstrates an efficient combined experimental and bioinformatics workflow to identify putative secreted proteins from insulin-resistant skeletal muscle cells, which could easily be adapted to other cellular models....

Group-based Motion Detection for Energy-Efficient Localisation

Directory of Open Access Journals (Sweden)

Alban Cotillon

2012-10-01

Full Text Available Long-term outdoor localization remains challenging due to the high energy profiles of GPS modules. Duty cycling the GPS module combined with inertial sensors can improve energy consumption. However, inertial sensors that are kept active all the time can also drain mobile node batteries. This paper proposes duty cycling strategies for inertial sensors to maintain a target position accuracy and node lifetime. We present a method for duty cycling motion sensors according to features of movement events, and evaluate its energy and accuracy profile for an empirical data trace of cattle movement. We further introduce the concept of group-based duty cycling, where nodes that cluster together can share the burden of motion detection to reduce their duty cycles. Our evaluation shows that both variants of motion sensor duty cycling yield up to 78% improvement in overall node power consumption, and that the group-based method yields an additional 20% power reduction during periods of low mobility.

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

Science.gov (United States)

Campbell, Chad E.; Nehm, Ross H.

2013-01-01

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

Bioinformatic Analysis of Potential Biomarkers for Spinal Cord Injured Patients With Intractable Neuropathic Pain.

Science.gov (United States)

Wang, Yimin; Ye, Fang; Huang, Chanyan; Xue, Faling; Li, Yingyuan; Gao, Shaowei; Qiu, Zeting; Li, Si; Chen, Qinchang; Zhou, Huaqiang; Song, Yiyan; Huang, Wenqi; Tan, Wulin; Wang, Zhongxing

2018-03-15

Neuropathic pain is one of the common complications after spinal cord injury (SCI), affecting patients' life quality. The molecular mechanism for neuropathic pain after SCI is still unclear. We aimed to discover potential genes and MicroRNAs(miRNAs) related to neuropathic pain by bioinformatics method. Microarray data of GSE69901 were obtained from Gene Expression Omnibus (GEO) database. Peripheral blood samples from patients with or without neuropathic pain after spinal cord injury (SCI) were collected. 12 samples with neuropathic pain and 13 samples without pain as control were included in the downloaded microarray. Differentially expressed genes (DEGs) between neuropathic pain group and control group were detected using GEO2R online tool. Functional enrichment analysis of DEGs was performed using DAVID database. Protein-protein interaction (PPI) network was constructed from STRING database. MiRNAs targeting these DEGs were obtained from miRNet database. A merged miRNA-DEG network was constructed and analyzed with Cytoscape software. Total 1134 DEGs were identified between patients with or without neuropathic pain(case and control) and 454 biological processes were enriched. We identified 4 targeted miRNAs, including mir-204-5p, mir-519d-3p, mir-20b-5p, mir-6838-5p, which may be the potential biomarker for SCI patients. Protein modification and regulation biological process of central nervous system may be a risk factor of in SCI patients. Certain genes and miRNAs may be potential biomarkers for the prediction of and potential targets for prevention and treatment of neuropathic pain after SCI.This is an open-access article distributed under the terms of the Creative Commons Attribution-Non Commercial-No Derivatives License 4.0 (CCBY-NC-ND), where it is permissible to download and share the work provided it is properly cited. The work cannot be changed in any way or used commercially without permission from the journal. http

Creating a specialist protein resource network: a meeting report for the protein bioinformatics and community resources retreat

DEFF Research Database (Denmark)

Babbitt, Patricia C.; Bagos, Pantelis G.; Bairoch, Amos

2015-01-01

During 11–12 August 2014, a Protein Bioinformatics and Community Resources Retreat was held at the Wellcome Trust Genome Campus in Hinxton, UK. This meeting brought together the principal investigators of several specialized protein resources (such as CAZy, TCDB and MEROPS) as well as those from...... protein databases from the large Bioinformatics centres (including UniProt and RefSeq). The retreat was divided into five sessions: (1) key challenges, (2) the databases represented, (3) best practices for maintenance and curation, (4) information flow to and from large data centers and (5) communication...

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

Science.gov (United States)

Karlin, Samuel

2004-01-01

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

Cluster Flow: A user-friendly bioinformatics workflow tool [version 1; referees: 3 approved

Directory of Open Access Journals (Sweden)

Philip Ewels

2016-12-01

Full Text Available Pipeline tools are becoming increasingly important within the field of bioinformatics. Using a pipeline manager to manage and run workflows comprised of multiple tools reduces workload and makes analysis results more reproducible. Existing tools require significant work to install and get running, typically needing pipeline scripts to be written from scratch before running any analysis. We present Cluster Flow, a simple and flexible bioinformatics pipeline tool designed to be quick and easy to install. Cluster Flow comes with 40 modules for common NGS processing steps, ready to work out of the box. Pipelines are assembled using these modules with a simple syntax that can be easily modified as required. Core helper functions automate many common NGS procedures, making running pipelines simple. Cluster Flow is available with an GNU GPLv3 license on GitHub. Documentation, examples and an online demo are available at http://clusterflow.io.

Domain similarity based orthology detection.

Science.gov (United States)

Bitard-Feildel, Tristan; Kemena, Carsten; Greenwood, Jenny M; Bornberg-Bauer, Erich

2015-05-13

Orthologous protein detection software mostly uses pairwise comparisons of amino-acid sequences to assert whether two proteins are orthologous or not. Accordingly, when the number of sequences for comparison increases, the number of comparisons to compute grows in a quadratic order. A current challenge of bioinformatic research, especially when taking into account the increasing number of sequenced organisms available, is to make this ever-growing number of comparisons computationally feasible in a reasonable amount of time. We propose to speed up the detection of orthologous proteins by using strings of domains to characterize the proteins. We present two new protein similarity measures, a cosine and a maximal weight matching score based on domain content similarity, and new software, named porthoDom. The qualities of the cosine and the maximal weight matching similarity measures are compared against curated datasets. The measures show that domain content similarities are able to correctly group proteins into their families. Accordingly, the cosine similarity measure is used inside porthoDom, the wrapper developed for proteinortho. porthoDom makes use of domain content similarity measures to group proteins together before searching for orthologs. By using domains instead of amino acid sequences, the reduction of the search space decreases the computational complexity of an all-against-all sequence comparison. We demonstrate that representing and comparing proteins as strings of discrete domains, i.e. as a concatenation of their unique identifiers, allows a drastic simplification of search space. porthoDom has the advantage of speeding up orthology detection while maintaining a degree of accuracy similar to proteinortho. The implementation of porthoDom is released using python and C++ languages and is available under the GNU GPL licence 3 at http://www.bornberglab.org/pages/porthoda .

Agonist Binding to Chemosensory Receptors: A Systematic Bioinformatics Analysis

Directory of Open Access Journals (Sweden)

Fabrizio Fierro

2017-09-01

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

MAPI: towards the integrated exploitation of bioinformatics Web Services.

Science.gov (United States)

Ramirez, Sergio; Karlsson, Johan; Trelles, Oswaldo

2011-10-27

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

PipeCraft: Flexible open-source toolkit for bioinformatics analysis of custom high-throughput amplicon sequencing data.

Science.gov (United States)

Anslan, Sten; Bahram, Mohammad; Hiiesalu, Indrek; Tedersoo, Leho

2017-11-01

High-throughput sequencing methods have become a routine analysis tool in environmental sciences as well as in public and private sector. These methods provide vast amount of data, which need to be analysed in several steps. Although the bioinformatics may be applied using several public tools, many analytical pipelines allow too few options for the optimal analysis for more complicated or customized designs. Here, we introduce PipeCraft, a flexible and handy bioinformatics pipeline with a user-friendly graphical interface that links several public tools for analysing amplicon sequencing data. Users are able to customize the pipeline by selecting the most suitable tools and options to process raw sequences from Illumina, Pacific Biosciences, Ion Torrent and Roche 454 sequencing platforms. We described the design and options of PipeCraft and evaluated its performance by analysing the data sets from three different sequencing platforms. We demonstrated that PipeCraft is able to process large data sets within 24 hr. The graphical user interface and the automated links between various bioinformatics tools enable easy customization of the workflow. All analytical steps and options are recorded in log files and are easily traceable. © 2017 John Wiley & Sons Ltd.

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

Science.gov (United States)

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

2010-01-01

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

A novel reduced-complexity group detection structure in MIMO frequency selective fading channels

KAUST Repository

Qaraqe, Khalid A.; Ahimian, Nariman R.; Alouini, Mohamed-Slim

2010-01-01

In this paper a novel reduced complexity detection method named modified symbol flipping method is introduced and its advantages on reducing the burden of the calculations at the receiver compared to the optimum maximum likelihood detection method on multiple input- multiple output frequency selective fading channels are explained. The initial concept of the symbol flipping method is derived from a preliminary detection scheme named bit flipping which was introduced in [1]. The detection structure employed in this paper is ing, detection, and cancellation. On the detection stage, the proposed method is employed and the results are compared to the group maximum likelihood detection scheme proposed in [2]. Simulation results show that a 6 dB performance gain can be achieved at the expense of a slight increase in complexity in comparison with the conventional symbol flipping scheme. © 2010 Crown.

A novel reduced-complexity group detection structure in MIMO frequency selective fading channels

KAUST Repository

Qaraqe, Khalid A.

2010-09-01

In this paper a novel reduced complexity detection method named modified symbol flipping method is introduced and its advantages on reducing the burden of the calculations at the receiver compared to the optimum maximum likelihood detection method on multiple input- multiple output frequency selective fading channels are explained. The initial concept of the symbol flipping method is derived from a preliminary detection scheme named bit flipping which was introduced in [1]. The detection structure employed in this paper is ing, detection, and cancellation. On the detection stage, the proposed method is employed and the results are compared to the group maximum likelihood detection scheme proposed in [2]. Simulation results show that a 6 dB performance gain can be achieved at the expense of a slight increase in complexity in comparison with the conventional symbol flipping scheme. © 2010 Crown.

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

NARCIS (Netherlands)

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

2010-01-01

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

Polymerase chain reaction assay for the detection of Bacillus cereus group cells

DEFF Research Database (Denmark)

Hansen, Bjarne Munk; Leser, Thomas D.; Hendriksen, Niels Bohse

2001-01-01

of the B. cereus group in food and in the environment. Using 16S rDNA as target, a PCR assay for the detection of B. cereus group cells has been developed. Primers specific for the 16S rDNA of the B. cereus group bacteria were selected and used in combination with consensus primers for 165 rDNA as internal...... PCR procedure control. The PCR procedure was optimized with respect to annealing temperature. When DNA from the B. cereus group bacteria was present, the PCR assay yielded a B. cereus specific fragment, while when non-B. cereus prokaryotic DNA was present, the consensus 165 rDNA primers directed...

Performance Analysis of Hierarchical Group Key Management Integrated with Adaptive Intrusion Detection in Mobile ad hoc Networks

Science.gov (United States)

2016-04-05

applications in wireless networks such as military battlefields, emergency response, mobile commerce , online gaming, and collaborative work are based on the...www.elsevier.com/locate/peva Performance analysis of hierarchical group key management integrated with adaptive intrusion detection in mobile ad hoc...Accepted 19 September 2010 Available online 26 September 2010 Keywords: Mobile ad hoc networks Intrusion detection Group communication systems Group

Bioinformatic prediction and functional characterization of human KIAA0100 gene

Directory of Open Access Journals (Sweden)

He Cui

2017-02-01

Full Text Available Our previous study demonstrated that human KIAA0100 gene was a novel acute monocytic leukemia-associated antigen (MLAA gene. But the functional characterization of human KIAA0100 gene has remained unknown to date. Here, firstly, bioinformatic prediction of human KIAA0100 gene was carried out using online softwares; Secondly, Human KIAA0100 gene expression was downregulated by the clustered regularly interspaced short palindromic repeats (CRISPR/CRISPR-associated (Cas 9 system in U937 cells. Cell proliferation and apoptosis were next evaluated in KIAA0100-knockdown U937 cells. The bioinformatic prediction showed that human KIAA0100 gene was located on 17q11.2, and human KIAA0100 protein was located in the secretory pathway. Besides, human KIAA0100 protein contained a signalpeptide, a transmembrane region, three types of secondary structures (alpha helix, extended strand, and random coil , and four domains from mitochondrial protein 27 (FMP27. The observation on functional characterization of human KIAA0100 gene revealed that its downregulation inhibited cell proliferation, and promoted cell apoptosis in U937 cells. To summarize, these results suggest human KIAA0100 gene possibly comes within mitochondrial genome; moreover, it is a novel anti-apoptotic factor related to carcinogenesis or progression in acute monocytic leukemia, and may be a potential target for immunotherapy against acute monocytic leukemia.

BioQueue: a novel pipeline framework to accelerate bioinformatics analysis.

Science.gov (United States)

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

2017-10-15

With the rapid development of Next-Generation Sequencing, a large amount of data is now available for bioinformatics research. Meanwhile, the presence of many pipeline frameworks makes it possible to analyse these data. However, these tools concentrate mainly on their syntax and design paradigms, and dispatch jobs based on users' experience about the resources needed by the execution of a certain step in a protocol. As a result, it is difficult for these tools to maximize the potential of computing resources, and avoid errors caused by overload, such as memory overflow. Here, we have developed BioQueue, a web-based framework that contains a checkpoint before each step to automatically estimate the system resources (CPU, memory and disk) needed by the step and then dispatch jobs accordingly. BioQueue possesses a shell command-like syntax instead of implementing a new script language, which means most biologists without computer programming background can access the efficient queue system with ease. BioQueue is freely available at https://github.com/liyao001/BioQueue. The extensive documentation can be found at http://bioqueue.readthedocs.io. li_yao@outlook.com or gcsui@nefu.edu.cn. Supplementary data are available at Bioinformatics online. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com

Bicycle: a bioinformatics pipeline to analyze bisulfite sequencing data.

Science.gov (United States)

Graña, Osvaldo; López-Fernández, Hugo; Fdez-Riverola, Florentino; González Pisano, David; Glez-Peña, Daniel

2018-04-15

High-throughput sequencing of bisulfite-converted DNA is a technique used to measure DNA methylation levels. Although a considerable number of computational pipelines have been developed to analyze such data, none of them tackles all the peculiarities of the analysis together, revealing limitations that can force the user to manually perform additional steps needed for a complete processing of the data. This article presents bicycle, an integrated, flexible analysis pipeline for bisulfite sequencing data. Bicycle analyzes whole genome bisulfite sequencing data, targeted bisulfite sequencing data and hydroxymethylation data. To show how bicycle overtakes other available pipelines, we compared them on a defined number of features that are summarized in a table. We also tested bicycle with both simulated and real datasets, to show its level of performance, and compared it to different state-of-the-art methylation analysis pipelines. Bicycle is publicly available under GNU LGPL v3.0 license at http://www.sing-group.org/bicycle. Users can also download a customized Ubuntu LiveCD including bicycle and other bisulfite sequencing data pipelines compared here. In addition, a docker image with bicycle and its dependencies, which allows a straightforward use of bicycle in any platform (e.g. Linux, OS X or Windows), is also available. ograna@cnio.es or dgpena@uvigo.es. Supplementary data are available at Bioinformatics online.

Social Fingerprinting: detection of spambot groups through DNA-inspired behavioral modeling

DEFF Research Database (Denmark)

Cresci, Stefano; Di Pietro, Roberto; Petrocchi, Marinella

2017-01-01

Spambot detection in online social networks is a long-lasting challenge involving the study and design of detection techniques capable of efficiently identifying ever-evolving spammers. Recently, a new wave of social spambots has emerged, with advanced human-like characteristics that allow them...... to go undetected even by current state-of-the-art algorithms. In this paper, we show that efficient spambots detection can be achieved via an in-depth analysis of their collective behaviors exploiting the digital DNA technique for modeling the behaviors of social network users. Inspired by its...... biological counterpart, in the digital DNA representation the behavioral lifetime of a digital account is encoded in a sequence of characters. Then, we define a similarity measure for such digital DNA sequences. We build upon digital DNA and the similarity between groups of users to characterize both genuine...

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

Science.gov (United States)

Greene, Kathleen; Donovan, Sam

2005-01-01

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

Bioinformatic Analysis of Strawberry GSTF12 Gene

Science.gov (United States)

Wang, Xiran; Jiang, Leiyu; Tang, Haoru

2018-01-01

GSTF12 has always been known as a key factor of proanthocyanins accumulate in plant testa. Through bioinformatics analysis of the nucleotide and encoded protein sequence of GSTF12, it is more advantageous to the study of genes related to anthocyanin biosynthesis accumulation pathway. Therefore, we chosen GSTF12 gene of 11 kinds species, downloaded their nucleotide and protein sequence from NCBI as the research object, found strawberry GSTF12 gene via bioinformation analyse, constructed phylogenetic tree. At the same time, we analysed the strawberry GSTF12 gene of physical and chemical properties and its protein structure and so on. The phylogenetic tree showed that Strawberry and petunia were closest relative. By the protein prediction, we found that the protein owed one proper signal peptide without obvious transmembrane regions.

Bioinformatics-Driven Identification and Examination of Candidate Genes for Non-Alcoholic Fatty Liver Disease

DEFF Research Database (Denmark)

Banasik, Karina; Justesen, Johanne M.; Hornbak, Malene

2011-01-01

Objective: Candidate genes for non-alcoholic fatty liver disease (NAFLD) identified by a bioinformatics approach were examined for variant associations to quantitative traits of NAFLD-related phenotypes. Research Design and Methods: By integrating public database text mining, trans-organism protein...

Rhesus monkeys (Macaca mulatta) detect rhythmic groups in music, but not the beat.

Science.gov (United States)

Honing, Henkjan; Merchant, Hugo; Háden, Gábor P; Prado, Luis; Bartolo, Ramón

2012-01-01

It was recently shown that rhythmic entrainment, long considered a human-specific mechanism, can be demonstrated in a selected group of bird species, and, somewhat surprisingly, not in more closely related species such as nonhuman primates. This observation supports the vocal learning hypothesis that suggests rhythmic entrainment to be a by-product of the vocal learning mechanisms that are shared by several bird and mammal species, including humans, but that are only weakly developed, or missing entirely, in nonhuman primates. To test this hypothesis we measured auditory event-related potentials (ERPs) in two rhesus monkeys (Macaca mulatta), probing a well-documented component in humans, the mismatch negativity (MMN) to study rhythmic expectation. We demonstrate for the first time in rhesus monkeys that, in response to infrequent deviants in pitch that were presented in a continuous sound stream using an oddball paradigm, a comparable ERP component can be detected with negative deflections in early latencies (Experiment 1). Subsequently we tested whether rhesus monkeys can detect gaps (omissions at random positions in the sound stream; Experiment 2) and, using more complex stimuli, also the beat (omissions at the first position of a musical unit, i.e. the 'downbeat'; Experiment 3). In contrast to what has been shown in human adults and newborns (using identical stimuli and experimental paradigm), the results suggest that rhesus monkeys are not able to detect the beat in music. These findings are in support of the hypothesis that beat induction (the cognitive mechanism that supports the perception of a regular pulse from a varying rhythm) is species-specific and absent in nonhuman primates. In addition, the findings support the auditory timing dissociation hypothesis, with rhesus monkeys being sensitive to rhythmic grouping (detecting the start of a rhythmic group), but not to the induced beat (detecting a regularity from a varying rhythm).

Rhesus monkeys (Macaca mulatta detect rhythmic groups in music, but not the beat.

Directory of Open Access Journals (Sweden)

Henkjan Honing

Full Text Available It was recently shown that rhythmic entrainment, long considered a human-specific mechanism, can be demonstrated in a selected group of bird species, and, somewhat surprisingly, not in more closely related species such as nonhuman primates. This observation supports the vocal learning hypothesis that suggests rhythmic entrainment to be a by-product of the vocal learning mechanisms that are shared by several bird and mammal species, including humans, but that are only weakly developed, or missing entirely, in nonhuman primates. To test this hypothesis we measured auditory event-related potentials (ERPs in two rhesus monkeys (Macaca mulatta, probing a well-documented component in humans, the mismatch negativity (MMN to study rhythmic expectation. We demonstrate for the first time in rhesus monkeys that, in response to infrequent deviants in pitch that were presented in a continuous sound stream using an oddball paradigm, a comparable ERP component can be detected with negative deflections in early latencies (Experiment 1. Subsequently we tested whether rhesus monkeys can detect gaps (omissions at random positions in the sound stream; Experiment 2 and, using more complex stimuli, also the beat (omissions at the first position of a musical unit, i.e. the 'downbeat'; Experiment 3. In contrast to what has been shown in human adults and newborns (using identical stimuli and experimental paradigm, the results suggest that rhesus monkeys are not able to detect the beat in music. These findings are in support of the hypothesis that beat induction (the cognitive mechanism that supports the perception of a regular pulse from a varying rhythm is species-specific and absent in nonhuman primates. In addition, the findings support the auditory timing dissociation hypothesis, with rhesus monkeys being sensitive to rhythmic grouping (detecting the start of a rhythmic group, but not to the induced beat (detecting a regularity from a varying rhythm.

[Factors affecting the adoption of ICT tools in experiments with bioinformatics in biopharmaceutical organizations: a case study in the Brazilian Cancer Institute].

Science.gov (United States)

Pitassi, Claudio; Gonçalves, Antonio Augusto; Moreno Júnior, Valter de Assis

2014-01-01

The scope of this article is to identify and analyze the factors that influence the adoption of ICT tools in experiments with bioinformatics at the Brazilian Cancer Institute (INCA). It involves a descriptive and exploratory qualitative field study. Evidence was collected mainly based on in-depth interviews with the management team at the Research Center and the IT Division. The answers were analyzed using the categorical content method. The categories were selected from the scientific literature and consolidated in the Technology-Organization-Environment (TOE) framework created for this study. The model proposed made it possible to demonstrate how the factors selected impacted INCA´s adoption of bioinformatics systems and tools, contributing to the investigation of two critical areas for the development of the health industry in Brazil, namely technological innovation and bioinformatics. Based on the evidence collected, a research question was posed: to what extent can the alignment of the factors related to the adoption of ICT tools in experiments with bioinformatics increase the innovation capacity of a Brazilian biopharmaceutical organization?

Detection of Group B Streptococcus in Brazilian pregnant women and antimicrobial susceptibility patterns

Directory of Open Access Journals (Sweden)

Didier Silveira Castellano-Filho

2010-12-01

Full Text Available Group B Streptococcus (GBS is still not routinely screened during pregnancy in Brazil, being prophylaxis and empirical treatment based on identification of risk groups. This study aimed to investigate GBS prevalence in Brazilian pregnant women by culture or polymerase chain reaction (PCR associated to the enrichment culture, and to determine the antimicrobial susceptibility patterns of isolated bacteria, so as to support public health policies and empirical prophylaxis. After an epidemiological survey, vaginal and anorectal specimens were collected from 221 consenting laboring women. Each sample was submitted to enrichment culture and sheep blood agar was used to isolate suggestive GBS. Alternatively, specific PCR was performed from enrichment cultures. Antimicrobial susceptibility patterns were determined for isolated bacteria by agar diffusion method. No risk groups were identified. Considering the culture-based methodology, GBS was detected in 9.5% of the donors. Twenty five bacterial strains were isolated and identified. Through the culture-PCR methodology, GBS was detected in 32.6% specimens. Bacterial resistance was not detected against ampicillin, cephazolin, vancomycin and ciprofloxacin, whereas 22.7% were resistant to erythromycin and 50% were resistant to clindamycin. GBS detection may be improved by the association of PCR and enrichment culture. Considering that colony selection in agar plates may be laboring and technician-dependent, it may not reflect the real prevalence of streptococci. As in Brazil prevention strategies to reduce the GBS associated diseases have not been adopted, prospective studies are needed to anchor public health policies especially considering the regional GBS antimicrobial susceptibility patterns.

Alu Insertions and Genetic Diversity: A Preliminary Investigation by an Undergraduate Bioinformatics Class

Science.gov (United States)

Elwess, Nancy L.; Duprey, Stephen L.; Harney, Lindesay A.; Langman, Jessie E.; Marino, Tara C.; Martinez, Carolina; McKeon, Lauren L.; Moss, Chantel I. E.; Myrie, Sasha S.; Taylor, Luke Ryan

2008-01-01

"Alu"-insertion polymorphisms were used by an undergraduate Bioinformatics class to study how these insertion sites could be the basis for an investigation in human population genetics. Based on the students' investigation, both allele and genotype "Alu" frequencies were determined for African-American and Japanese populations as well as a…

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

Science.gov (United States)

Medin, Carey L.; Nolin, Katie L.

2011-01-01

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

TMTI Task 1.6 Genetic Engineering Methods and Detection

Energy Technology Data Exchange (ETDEWEB)

Slezak, T; Lenhoff, R; Allen, J; Borucki, M; Vitalis, E; Gardner, S

2009-12-04

A large number of GE techniques can be adapted from other microorganisms to biothreat bacteria and viruses. Detection of GE in a microorganism increases in difficulty as the size of the genetic change decreases. In addition to the size of the engineered change, the consensus genomic sequence of the microorganism can impact the difficulty of detecting an engineered change in genomes that are highly variable from strain to strain. This problem will require comprehensive databases of whole genome sequences for more genetically variable biothreat bacteria and viruses. Preliminary work with microarrays for detecting synthetic elements or virulence genes and analytic bioinformatic approaches for whole genome sequence comparison to detect genetic engineering show promise for attacking this difficult problem but a large amount of future work remains.

Quantum Bio-Informatics:From Quantum Information to Bio-Informatics

CERN Document Server

Freudenberg, W; Ohya, M

2008-01-01

The purpose of this volume is examine bio-informatics and quantum information, which are growing rapidly at present, and to attempt to connect the two, with a view to enumerating and solving the many fundamental problems they entail. To this end, we look for interdisciplinary bridges in mathematics, physics, and information and life sciences. In particular, research into a new paradigm for information science and life science on the basis of quantum theory is emphasized. Sample Chapter(s). Markov Fields on Graphs (599 KB). Contents: Markov Fields on Graphs (L Accardi & H Ohno); Some Aspects of

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

Science.gov (United States)

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

2016-03-01

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

A Small-Group Activity Introducing the Use and Interpretation of BLAST

Directory of Open Access Journals (Sweden)

Peter D. Newell

2013-08-01

Full Text Available As biological sequence data are generated at an ever increasing rate, the role of bioinformatics in biological research also grows. Students must be trained to complete and interpret bioinformatic searches to enable them to effectively utilize the trove of sequence data available. A key bioinformatic tool for sequence comparison and genome database searching is BLAST (Basic Local Alignment Search Tool. BLAST identifies sequences in a database that are similar to the entered query sequence, and ranks them based on the length and quality of the alignment. Our goal was to introduce sophomore and junior level undergraduate students to the basic functions and uses of BLAST with a small group activity lasting a single class period. The activity provides students an opportunity to perform a BLAST search, interpret the data output, and use the data to make inferences about bacterial cell envelope structure. The activity consists of two parts. Part 1 is a handout to be completed prior to class, complete with video tutorial, that reviews cell envelope structure, introduces key terms, and allows students to familiarize themselves with the mechanics of a BLAST search. Part 2 consists of a hands-on, web-based small group activity to be completed during the class period. Evaluation of the activity through student performance assessments suggests that students who complete the activity can better interpret the BLAST output parameters % query coverage and % max identity. While the topic of the activity is bacterial cell wall structure, it could be adapted to address other biological concepts.

Artificial Evolution for the Detection of Group Identities in Complex Artificial Societies

DEFF Research Database (Denmark)

Grappiolo, Corrado; Togelius, Julian; Yannakakis, Georgios N.

2013-01-01

This paper aims at detecting the presence of group structures in complex artificial societies by solely observing and analysing the interactions occurring among the artificial agents. Our approach combines: (1) an unsupervised method for clustering interactions into two possible classes, namely in...

Read-Split-Run: an improved bioinformatics pipeline for identification of genome-wide non-canonical spliced regions using RNA-Seq data.

Science.gov (United States)

Bai, Yongsheng; Kinne, Jeff; Donham, Brandon; Jiang, Feng; Ding, Lizhong; Hassler, Justin R; Kaufman, Randal J

2016-08-22

Most existing tools for detecting next-generation sequencing-based splicing events focus on generic splicing events. Consequently, special types of non-canonical splicing events of short mRNA regions (IRE1α targeted) have not yet been thoroughly addressed at a genome-wide level using bioinformatics approaches in conjunction with next-generation technologies. During endoplasmic reticulum (ER) stress, the gene encoding the RNase Ire1α is known to splice out a short 26 nt region from the mRNA of the transcription factor Xbp1 non-canonically within the cytosol. This causes an open reading frame-shift that induces expression of many downstream genes in reaction to ER stress as part of the unfolded protein response (UPR). We previously published an algorithm termed "Read-Split-Walk" (RSW) to identify non-canonical splicing regions using RNA-Seq data and applied it to ER stress-induced Ire1α heterozygote and knockout mouse embryonic fibroblast cell lines. In this study, we have developed an improved algorithm "Read-Split-Run" (RSR) for detecting genome-wide Ire1α-targeted genes with non-canonical spliced regions at a faster speed. We applied the RSR algorithm using different combinations of several parameters to the previously RSW tested mouse embryonic fibroblast cells (MEF) and the human Encyclopedia of DNA Elements (ENCODE) RNA-Seq data. We also compared the performance of RSR with two other alternative splicing events identification tools (TopHat (Trapnell et al., Bioinformatics 25:1105-1111, 2009) and Alt Event Finder (Zhou et al., BMC Genomics 13:S10, 2012)) utilizing the context of the spliced Xbp1 mRNA as a positive control in the data sets we identified it to be the top cleavage target present in Ire1α (+/-) but absent in Ire1α (-/-) MEF samples and this comparison was also extended to human ENCODE RNA-Seq data. Proof of principle came in our results by the fact that the 26 nt non-conventional splice site in Xbp1 was detected as the top hit by our new RSR

Detection of shielded radionuclides from weak and poorly resolved spectra using group positive RIVAL

International Nuclear Information System (INIS)

Kump, Paul; Bai, Er-Wei; Chan, Kung-Sik; Eichinger, William

2013-01-01

This paper is concerned with the identification of nuclides from weak and poorly resolved spectra in the presence of unknown radiation shielding materials such as carbon, water, concrete and lead. Since a shield will attenuate lower energies more so than higher ones, isotope sub-spectra must be introduced into models and into detection algorithms. We propose a new algorithm for detection, called group positive RIVAL, that encourages the selection of groups of sub-spectra rather than the selection of individual sub-spectra that may be from the same parent isotope. Indeed, the proposed algorithm incorporates group positive LASSO, and, as such, we supply the consistency results of group positive LASSO and adaptive group positive LASSO. In an example employing various shielding materials and material thicknesses, group positive RIVAL is shown to perform well in all scenarios with the exception of ones in which the shielding material is lead. - Highlights: ► Identification of nuclides from weak and poorly resolved spectra. ► Shielding materials such as carbon, water, concrete, and lead are considered. ► Isotope spectra are decomposed into their sub-spectra. ► A variable selection algorithm is proposed that encourages group selection. ► Simulations demonstrate the proposed method's performance when nuclides have been shielded

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

Science.gov (United States)

Leonelli, Sabina

2010-01-01

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

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

Science.gov (United States)

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

2012-01-01

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

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

Science.gov (United States)

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

2012-01-01

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

Working Group 3: Greenhouse signal detection

International Nuclear Information System (INIS)

Barnett, T.; Ellsaesser, H.; Groisman, P.Ya.; Grotch, S.; Jenkins, G.; Karoly, D.; Riches, M.; Santer, B.; Schoenwiese, C.; Vinnikov, K.; Zwiers, F.

1990-01-01

Quantitative efforts to detect the greenhouse-gas signal (GHG) in nature are in their infancy. The reasons for this state of affairs are numerous. It is only in the last few years that GCMs have advanced to the point where their simulations of GHG signals might be marginally believable. Without reasonably good a priori predictions of expected GHG signals from the models, the detection problem is moot. The observational data sets describing changes in the global climate system over the last 50-100 years needed for adequate detection studies have also only come into existence in the last five years. Finally, no coherent, generally-agreed-on detection strategy has been developed by the scientific community interested in the GHG problem. The lack of adequate model predictions and observational sets are largely responsible for this latter condition. The rudimentary detection efforts that have been conducted have generally been based on recognizing the fingerprint of GHG signals in the oceans and atmosphere. GCM results for 1 x 2 x CO 2 equilibrium runs have been used to search for GHG effects induced in tropospheric air and ocean surface temperature fields since the early 1900s. No significant effect has been found

Biogem: an effective tool based approach for scaling up open source software development in bioinformatics

NARCIS (Netherlands)

Bonnal, R.J.P.; Smant, G.; Prins, J.C.P.

2012-01-01

Biogem provides a software development environment for the Ruby programming language, which encourages community-based software development for bioinformatics while lowering the barrier to entry and encouraging best practices. Biogem, with its targeted modular and decentralized approach, software

Challenging a bioinformatic tool's ability to detect microbial contaminants using in silico whole genome sequencing data.

Science.gov (United States)

Olson, Nathan D; Zook, Justin M; Morrow, Jayne B; Lin, Nancy J

2017-01-01

High sensitivity methods such as next generation sequencing and polymerase chain reaction (PCR) are adversely impacted by organismal and DNA contaminants. Current methods for detecting contaminants in microbial materials (genomic DNA and cultures) are not sensitive enough and require either a known or culturable contaminant. Whole genome sequencing (WGS) is a promising approach for detecting contaminants due to its sensitivity and lack of need for a priori assumptions about the contaminant. Prior to applying WGS, we must first understand its limitations for detecting contaminants and potential for false positives. Herein we demonstrate and characterize a WGS-based approach to detect organismal contaminants using an existing metagenomic taxonomic classification algorithm. Simulated WGS datasets from ten genera as individuals and binary mixtures of eight organisms at varying ratios were analyzed to evaluate the role of contaminant concentration and taxonomy on detection. For the individual genomes the false positive contaminants reported depended on the genus, with Staphylococcus , Escherichia , and Shigella having the highest proportion of false positives. For nearly all binary mixtures the contaminant was detected in the in-silico datasets at the equivalent of 1 in 1,000 cells, though F. tularensis was not detected in any of the simulated contaminant mixtures and Y. pestis was only detected at the equivalent of one in 10 cells. Once a WGS method for detecting contaminants is characterized, it can be applied to evaluate microbial material purity, in efforts to ensure that contaminants are characterized in microbial materials used to validate pathogen detection assays, generate genome assemblies for database submission, and benchmark sequencing methods.

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

Directory of Open Access Journals (Sweden)

Asia Majidi

2015-01-01

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

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

Directory of Open Access Journals (Sweden)

Marci D. Brandenburg, MS, MSI

2017-04-01

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

Bioinformatics Education in High School: Implications for Promoting Science, Technology, Engineering, and Mathematics Careers

Science.gov (United States)

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

2013-01-01

We investigated the effects of our Bio-ITEST teacher professional development model and bioinformatics curricula on cognitive traits (awareness, engagement, self-efficacy, and relevance) in high school teachers and students that are known to accompany a developing interest in science, technology, engineering, and mathematics (STEM) careers. The…

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

Directory of Open Access Journals (Sweden)

Valerio Ferrario

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

Bioinformatic identification and characterization of human endothelial cell-restricted genes

Directory of Open Access Journals (Sweden)

Keskin Derin B

2010-05-01

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

A bioinformatics roadmap for the human vaccines project.

Science.gov (United States)

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

2017-06-01

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

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

International Nuclear Information System (INIS)

Roche-Lima, Abiel; Thulasiram, Ruppa K

2012-01-01

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

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

Czech Academy of Sciences Publication Activity Database

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

2016-01-01

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

Parallel evolutionary computation in bioinformatics applications.

Science.gov (United States)

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

2013-05-01

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

Bioinformatic and Biometric Methods in Plant Morphology

Directory of Open Access Journals (Sweden)

Surangi W. Punyasena

2014-08-01

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.

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

Science.gov (United States)

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

2018-03-02

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

Possible Biomarkers for the Early Detection of HIV-associated Heart Diseases: A Proteomics and Bioinformatics Prediction

Directory of Open Access Journals (Sweden)

Suraiya Rasheed

2015-01-01

Full Text Available The frequency of cardiovascular disorders is increasing in HIV-infected individuals despite a significant reduction in the viral load by antiretroviral therapies (ART. Since the CD4+ T-cells are responsible for the viral load as well as immunological responses, we hypothesized that chronic HIV-infection of T-cells produces novel proteins/enzymes that cause cardiac dysfunctions. To identify specific factors that might cause cardiac disorders without the influence of numerous cofactors produced by other pathogenic microorganisms that co-inhabit most HIV-infected individuals, we analyzed genome-wide proteomes of a CD4+ T-cell line at different stages of HIV replication and cell growth over >6 months. Subtractive analyses of several hundred differentially regulated proteins from HIV-infected and uninfected counterpart cells and comparisons with proteins expressed from the same cells after treating with the antiviral drug Zidovudine/AZT and inhibiting virus replication, identified a well-coordinated network of 12 soluble/diffusible proteins in HIV-infected cells. Functional categorization, bioinformatics and statistical analyses of each protein predicted that the expression of cardiac-specific Ca2+ kinase together with multiple Ca2+ release channels causes a sustained overload of Ca2+ in the heart which induces fetal/cardiac myosin heavy chains (MYH6 and MYH7 and a myosin light-chain kinase. Each of these proteins has been shown to cause cardiac stress, arrhythmia, hypertrophic signaling, cardiomyopathy and heart failure (p = 8 × 10−11. Translational studies using the newly discovered proteins produced by HIV infection alone would provide additional biomarkers that could be added to the conventional markers for an early diagnosis and/or development of specific therapeutic interventions for heart diseases in HIV-infected individuals.

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

Science.gov (United States)

Eisenhaber, Frank; Sherman, Westley Arthur

2014-06-01

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

Grouped fuzzy SVM with EM-based partition of sample space for clustered microcalcification detection.

Science.gov (United States)

Wang, Huiya; Feng, Jun; Wang, Hongyu

2017-07-20

Detection of clustered microcalcification (MC) from mammograms plays essential roles in computer-aided diagnosis for early stage breast cancer. To tackle problems associated with the diversity of data structures of MC lesions and the variability of normal breast tissues, multi-pattern sample space learning is required. In this paper, a novel grouped fuzzy Support Vector Machine (SVM) algorithm with sample space partition based on Expectation-Maximization (EM) (called G-FSVM) is proposed for clustered MC detection. The diversified pattern of training data is partitioned into several groups based on EM algorithm. Then a series of fuzzy SVM are integrated for classification with each group of samples from the MC lesions and normal breast tissues. From DDSM database, a total of 1,064 suspicious regions are selected from 239 mammography, and the measurement of Accuracy, True Positive Rate (TPR), False Positive Rate (FPR) and EVL = TPR* 1-FPR are 0.82, 0.78, 0.14 and 0.72, respectively. The proposed method incorporates the merits of fuzzy SVM and multi-pattern sample space learning, decomposing the MC detection problem into serial simple two-class classification. Experimental results from synthetic data and DDSM database demonstrate that our integrated classification framework reduces the false positive rate significantly while maintaining the true positive rate.

A New Strategy to Reduce Influenza Escape: Detecting Therapeutic Targets Constituted of Invariance Groups

Directory of Open Access Journals (Sweden)

Julie Lao

2017-03-01

Full Text Available The pathogenicity of the different flu species is a real public health problem worldwide. To combat this scourge, we established a method to detect drug targets, reducing the possibility of escape. Besides being able to attach a drug candidate, these targets should have the main characteristic of being part of an essential viral function. The invariance groups that are sets of residues bearing an essential function can be detected genetically. They consist of invariant and synthetic lethal residues (interdependent residues not varying or slightly varying when together. We analyzed an alignment of more than 10,000 hemagglutinin sequences of influenza to detect six invariance groups, close in space, and on the protein surface. In parallel we identified five potential pockets on the surface of hemagglutinin. By combining these results, three potential binding sites were determined that are composed of invariance groups located respectively in the vestigial esterase domain, in the bottom of the stem and in the fusion area. The latter target is constituted of residues involved in the spring-loaded mechanism, an essential step in the fusion process. We propose a model describing how this potential target could block the reorganization of the hemagglutinin HA2 secondary structure and prevent viral entry into the host cell.

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

DEFF Research Database (Denmark)

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

2009-01-01

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

Fast Photo-detection in Phototransistors based on Group III-VI Layered Materials.

Science.gov (United States)

Patil, Prasanna; Ghosh, Sujoy; Wasala, Milinda; Lei, Sidong; Vajtai, Robert; Ajayan, Pulickel; Talapatra, Saikat

Response time of a photo detector is one of the crucial aspect of photo-detection. Recently it has been shown that direct band gap of few layered group III-VI materials helps in increased absorption of light thereby enhancing the photo responsive properties of these materials. Ternary system of Copper Indium Selenide has been extensively used in optoelectronics industry and it is expected that 2D layered structure of Copper Indium Selenide will be a key component of future optoelectronics devices based on 2D materials. Here we report fast photo detection in few layers of Copper Indium Selenide (CuIn7Se11) phototransistor. Few-layers of CuIn7Se11 flakes were exfoliated from crystals grown using chemical vapor transport technique. Our photo response characterization indicates responsivity of 104 mA/W with external quantum efficiency exceeding 103. We have found response time of few μs which is one of the fastest response among photodetectors based on 2D materials. We also found specific detectivity of 1012 Jones which is an order higher than conventional photodetectors. A comparison between response times of various layered group III-VI materials will be presented and discussed. This work is supported by the U.S. Army Research Office through a MURI Grant # W911NF-11-1-0362.

Detecting concealed information from groups using a dynamic questioning approach: simultaneous skin conductance measurement and immediate feedback

Directory of Open Access Journals (Sweden)

Ewout H Meijer

2013-02-01

Full Text Available Lie detection procedures typically aim at determining the guilt or innocence of a single suspect. The Concealed Information Test (CIT, for example, has been shown to be highly successful in detecting the presence or absence of crime-related information in a suspect’s memory. Many of today’s security threats, however, do not come from individuals, but from organized groups such as criminal organizations or terrorist networks. In this study, we tested whether a plan of an upcoming mock terrorist attack could be extracted from a group of suspects using a dynamic questioning approach. One-hundred participants were tested in 20 groups of 5. Each group was asked to plan a mock terrorist attack based on a list of potential countries, cities and streets. Next, three questions referring to the country, city, and street were presented, each with 5 options. Skin conductance in all 5 members of the group was measured simultaneously during this presentation. The dynamic questioning approach entailed direct analysis of the data, and if the average skin conductance of the group to a certain option exceeded a threshold, this option was followed up. E.g., if the reaction to the option ‘Italy’ exceeded the threshold, this was followed up by presenting 5 cities in Italy. Results showed that in 19 of the 20 groups the country was correctly detected using this procedure. In 13 of these remaining 19 groups the city was correctly detected. In 7 of these 13, the street was also correctly detected. The question about the country resulted in no false positives (out of 20, the question about the city resulted in 2 false positives (out of 19, while the question about the streets resulted in 2 false positives (out of 13. Furthermore, the 2 false positives at the city level also yielded a false positive at the street level. Taken together these results indicate our dynamic questioning approach can help to unveil plans about a mock terrorist attack.

Discriminating response groups in metabolic and regulatory pathway networks.

Science.gov (United States)

Van Hemert, John L; Dickerson, Julie A

2012-04-01

Analysis of omics experiments generates lists of entities (genes, metabolites, etc.) selected based on specific behavior, such as changes in response to stress or other signals. Functional interpretation of these lists often uses category enrichment tests using functional annotations like Gene Ontology terms and pathway membership. This approach does not consider the connected structure of biochemical pathways or the causal directionality of events. The Omics Response Group (ORG) method, described in this work, interprets omics lists in the context of metabolic pathway and regulatory networks using a statistical model for flow within the networks. Statistical results for all response groups are visualized in a novel Pathway Flow plot. The statistical tests are based on the Erlang distribution model under the assumption of independent and identically Exponential-distributed random walk flows through pathways. As a proof of concept, we applied our method to an Escherichia coli transcriptomics dataset where we confirmed common knowledge of the E.coli transcriptional response to Lipid A deprivation. The main response is related to osmotic stress, and we were also able to detect novel responses that are supported by the literature. We also applied our method to an Arabidopsis thaliana expression dataset from an abscisic acid study. In both cases, conventional pathway enrichment tests detected nothing, while our approach discovered biological processes beyond the original studies. We created a prototype for an interactive ORG web tool at http://ecoserver.vrac.iastate.edu/pathwayflow (source code is available from https://subversion.vrac.iastate.edu/Subversion/jlv/public/jlv/pathwayflow). The prototype is described along with additional figures and tables in Supplementary Material. julied@iastate.edu Supplementary data are available at Bioinformatics online.

Divide and Conquer: Sub-Grouping of ASD Improves ASD Detection Based on Brain Morphometry

Science.gov (United States)

Baum, Stefi A.; Cahill, Nathan D.; Michael, Andrew M.

2016-01-01

Low success (ASD) classification using brain morphometry from the large multi-site ABIDE dataset and inconsistent findings on brain morphometric abnormalities in ASD can be attributed to the ASD heterogeneity. In this study, we show that ASD brain morphometry is highly heterogeneous, and demonstrate that the heterogeneity can be mitigated and classification improved if autism severity (AS), verbal IQ (VIQ) and age are used with morphometric features. Morphometric features from structural MRIs (sMRIs) of 734 males (ASD: 361, controls: 373) of ABIDE were derived using FreeSurfer. Applying the Random Forest classifier, an AUC of 0.61 was achieved. Adding VIQ and age to morphometric features, AUC improved to 0.68. Sub-grouping the subjects by AS, VIQ and age improved the classification with the highest AUC of 0.8 in the moderate-AS sub-group (AS = 7–8). Matching subjects on age and/or VIQ in each sub-group further improved the classification with the highest AUC of 0.92 in the low AS sub-group (AS = 4–5). AUC decreased with AS and VIQ, and was the lowest in the mid-age sub-group (13–18 years). The important features were mainly from the frontal, temporal, ventricular, right hippocampal and left amygdala regions. However, they highly varied with AS, VIQ and age. The curvature and folding index features from frontal, temporal, lingual and insular regions were dominant in younger subjects suggesting their importance for early detection. When the experiments were repeated using the Gradient Boosting classifier similar results were obtained. Our findings suggest that identifying brain biomarkers in sub-groups of ASD can yield more robust and insightful results than searching across the whole spectrum. Further, it may allow identification of sub-group specific brain biomarkers that are optimized for early detection and monitoring, increasing the utility of sMRI as an important tool for early detection of ASD. PMID:27065101

Bioinformatics Database Tools in Analysis of Genetics of Neurodevelopmental Disorders

Directory of Open Access Journals (Sweden)

Dibyashree Mallik

2017-10-01

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

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

Science.gov (United States)

Dalpé, Gratien; Joly, Yann

2014-09-01

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

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

Science.gov (United States)

Campbell, Chad E.; Nehm, Ross H.

2013-01-01

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

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

Science.gov (United States)

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

2016-01-01

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

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

Science.gov (United States)

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

2015-01-01

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

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

Science.gov (United States)

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

2014-06-01

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

Bioinformatics approaches to single-cell analysis in developmental biology.

Science.gov (United States)

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

2016-03-01

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

REDItools: high-throughput RNA editing detection made easy.

Science.gov (United States)

Picardi, Ernesto; Pesole, Graziano

2013-07-15

The reliable detection of RNA editing sites from massive sequencing data remains challenging and, although several methodologies have been proposed, no computational tools have been released to date. Here, we introduce REDItools a suite of python scripts to perform high-throughput investigation of RNA editing using next-generation sequencing data. REDItools are in python programming language and freely available at http://code.google.com/p/reditools/. ernesto.picardi@uniba.it or graziano.pesole@uniba.it Supplementary data are available at Bioinformatics online.

A Brief Review of Bioinformatics Tools for Glycosylation Analysis by Mass Spectrometry

OpenAIRE

Tsai, Pei-Lun; Chen, Sung-Fang

2017-01-01

The purpose of this review is to provide updated information regarding bioinformatic software for the use in the characterization of glycosylated structures since 2013. A comprehensive review by Woodin et al. Analyst 138: 2793?2803, 2013 (ref. 1) described two main approaches that are introduced for starting researchers in this area; analysis of released glycans and the identification of glycopeptide in enzymatic digests, respectively. Complementary to that report, this review focuses on m...

Galaxy Workflows for Web-based Bioinformatics Analysis of Aptamer High-throughput Sequencing Data

Directory of Open Access Journals (Sweden)

William H Thiel

2016-01-01

Full Text Available Development of RNA and DNA aptamers for diagnostic and therapeutic applications is a rapidly growing field. Aptamers are identified through iterative rounds of selection in a process termed SELEX (Systematic Evolution of Ligands by EXponential enrichment. High-throughput sequencing (HTS revolutionized the modern SELEX process by identifying millions of aptamer sequences across multiple rounds of aptamer selection. However, these vast aptamer HTS datasets necessitated bioinformatics techniques. Herein, we describe a semiautomated approach to analyze aptamer HTS datasets using the Galaxy Project, a web-based open source collection of bioinformatics tools that were originally developed to analyze genome, exome, and transcriptome HTS data. Using a series of Workflows created in the Galaxy webserver, we demonstrate efficient processing of aptamer HTS data and compilation of a database of unique aptamer sequences. Additional Workflows were created to characterize the abundance and persistence of aptamer sequences within a selection and to filter sequences based on these parameters. A key advantage of this approach is that the online nature of the Galaxy webserver and its graphical interface allow for the analysis of HTS data without the need to compile code or install multiple programs.

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

Science.gov (United States)

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

2018-02-06

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

A P2P Framework for Developing Bioinformatics Applications in Dynamic Cloud Environments

Directory of Open Access Journals (Sweden)

Chun-Hung Richard Lin

2013-01-01

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

Dugong: a Docker image, based on Ubuntu Linux, focused on reproducibility and replicability for bioinformatics analyses.

Science.gov (United States)

Menegidio, Fabiano B; Jabes, Daniela L; Costa de Oliveira, Regina; Nunes, Luiz R

2018-02-01

This manuscript introduces and describes Dugong, a Docker image based on Ubuntu 16.04, which automates installation of more than 3500 bioinformatics tools (along with their respective libraries and dependencies), in alternative computational environments. The software operates through a user-friendly XFCE4 graphic interface that allows software management and installation by users not fully familiarized with the Linux command line and provides the Jupyter Notebook to assist in the delivery and exchange of consistent and reproducible protocols and results across laboratories, assisting in the development of open science projects. Source code and instructions for local installation are available at https://github.com/DugongBioinformatics, under the MIT open source license. Luiz.nunes@ufabc.edu.br. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com

Bioinformatics for Precision Medicine in Oncology: principles and application to the SHIVA clinical trial

Directory of Open Access Journals (Sweden)

Nicolas eServant

2014-05-01

Full Text Available Precision medicine (PM requires the delivery of individually adapted medical care based on the genetic characteristics of each patient and his/her tumor. The last decade witnessed the development of high-throughput technologies such as microarrays and next-generation sequencing which paved the way to PM in the field of oncology. While the cost of these technologies decreases, we are facing an exponential increase in the amount of data produced. Our ability to use this information in daily practice relies strongly on the availability of an efficient bioinformatics system that assists in the translation of knowledge from the bench towards molecular targeting and diagnosis. Clinical trials and routine diagnoses constitute different approaches, both requiring a strong bioinformatics environment capable of i warranting the integration and the traceability of data, ii ensuring the correct processing and analyses of genomic data and iii applying well-defined and reproducible procedures for workflow management and decision-making. To address the issues, a seamless information system was developed at Institut Curie which facilitates the data integration and tracks in real-time the processing of individual samples. Moreover, computational pipelines were developed to identify reliably genomic alterations and mutations from the molecular profiles of each patient. After a rigorous quality control, a meaningful report is delivered to the clinicians and biologists for the therapeutic decision. The complete bioinformatics environment and the key points of its implementation are presented in the context of the SHIVA clinical trial, a multicentric randomized phase II trial comparing targeted therapy based on tumor molecular profiling versus conventional therapy in patients with refractory cancer. The numerous challenges faced in practice during the setting up and the conduct of this trial are discussed as an illustration of PM application.

Bioinformatics in cancer therapy and drug design

International Nuclear Information System (INIS)

Horbach, D.Y.; Usanov, S.A.

2005-01-01

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)

Bioinformatics in cancer therapy and drug design

Energy Technology Data Exchange (ETDEWEB)

Horbach, D Y [International A. Sakharov environmental univ., Minsk (Belarus); Usanov, S A [Inst. of bioorganic chemistry, National academy of sciences of Belarus, Minsk (Belarus)

2005-05-15

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)

The OAuth 2.0 Web Authorization Protocol for the Internet Addiction Bioinformatics (IABio) Database.

Science.gov (United States)

Choi, Jeongseok; Kim, Jaekwon; Lee, Dong Kyun; Jang, Kwang Soo; Kim, Dai-Jin; Choi, In Young

2016-03-01

Internet addiction (IA) has become a widespread and problematic phenomenon as smart devices pervade society. Moreover, internet gaming disorder leads to increases in social expenditures for both individuals and nations alike. Although the prevention and treatment of IA are getting more important, the diagnosis of IA remains problematic. Understanding the neurobiological mechanism of behavioral addictions is essential for the development of specific and effective treatments. Although there are many databases related to other addictions, a database for IA has not been developed yet. In addition, bioinformatics databases, especially genetic databases, require a high level of security and should be designed based on medical information standards. In this respect, our study proposes the OAuth standard protocol for database access authorization. The proposed IA Bioinformatics (IABio) database system is based on internet user authentication, which is a guideline for medical information standards, and uses OAuth 2.0 for access control technology. This study designed and developed the system requirements and configuration. The OAuth 2.0 protocol is expected to establish the security of personal medical information and be applied to genomic research on IA.

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

NARCIS (Netherlands)

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

2007-01-01

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

A bioinformatics approach to the development of immunoassays for specified risk material in canned meat products

NARCIS (Netherlands)

Reece, P.; Bremer, M.G.E.G.; Stones, R.; Danks, C.; Baumgartner, S.; Tomkies, V.; Hemetsberger, C.; Smits, N.G.E.; Lubbe, W.

2009-01-01

A bioinformatics approach to developing antibodies to specific proteins has been evaluated for the production of antibodies to heat-processed specified risk tissues from ruminants (brain and eye tissue). The approach involved the identification of proteins specific to ruminant tissues by

DNA microarray technique for detecting food-borne pathogens

Directory of Open Access Journals (Sweden)

Xing GAO

2012-08-01

Full Text Available Objective To study the application of DNA microarray technique for screening and identifying multiple food-borne pathogens. Methods The oligonucleotide probes were designed by Clustal X and Oligo 6.0 at the conserved regions of specific genes of multiple food-borne pathogens, and then were validated by bioinformatic analyses. The 5' end of each probe was modified by amino-group and 10 Poly-T, and the optimized probes were synthesized and spotted on aldehyde-coated slides. The bacteria DNA template incubated with Klenow enzyme was amplified by arbitrarily primed PCR, and PCR products incorporated into Aminoallyl-dUTP were coupled with fluorescent dye. After hybridization of the purified PCR products with DNA microarray, the hybridization image and fluorescence intensity analysis was acquired by ScanArray and GenePix Pro 5.1 software. A series of detection conditions such as arbitrarily primed PCR and microarray hybridization were optimized. The specificity of this approach was evaluated by 16 different bacteria DNA, and the sensitivity and reproducibility were verified by 4 food-borne pathogens DNA. The samples of multiple bacteria DNA and simulated water samples of Shigella dysenteriae were detected. Results Nine different food-borne bacteria were successfully discriminated under the same condition. The sensitivity of genomic DNA was 102 －103pg/ μl, and the coefficient of variation (CV of the reproducibility of assay was less than 15%. The corresponding specific hybridization maps of the multiple bacteria DNA samples were obtained, and the detection limit of simulated water sample of Shigella dysenteriae was 3.54×105cfu/ml. Conclusions The DNA microarray detection system based on arbitrarily primed PCR can be employed for effective detection of multiple food-borne pathogens, and this assay may offer a new method for high-throughput platform for detecting bacteria.

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

Science.gov (United States)

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

2015-07-01

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

Identification of differentially expressed genes and signaling pathways in ovarian cancer by integrated bioinformatics analysis

Directory of Open Access Journals (Sweden)

Yang X

2018-03-01

Full Text Available Xiao Yang,1 Shaoming Zhu,2 Li Li,3 Li Zhang,1 Shu Xian,1 Yanqing Wang,1 Yanxiang Cheng1 1Department of Obstetrics and Gynecology, 2Department of Urology, Renmin Hospital of Wuhan University, 3Department of Pharmacology, Wuhan University Health Science Center, Wuhan, Hubei, People’s Republic of China Background: The mortality rate associated with ovarian cancer ranks the highest among gynecological malignancies. However, the cause and underlying molecular events of ovarian cancer are not clear. Here, we applied integrated bioinformatics to identify key pathogenic genes involved in ovarian cancer and reveal potential molecular mechanisms. Results: The expression profiles of GDS3592, GSE54388, and GSE66957 were downloaded from the Gene Expression Omnibus (GEO database, which contained 115 samples, including 85 cases of ovarian cancer samples and 30 cases of normal ovarian samples. The three microarray datasets were integrated to obtain differentially expressed genes (DEGs and were deeply analyzed by bioinformatics methods. The gene ontology (GO and Kyoto Encyclopedia of Genes and Genomes (KEGG pathway enrichments of DEGs were performed by DAVID and KOBAS online analyses, respectively. The protein–protein interaction (PPI networks of the DEGs were constructed from the STRING database. A total of 190 DEGs were identified in the three GEO datasets, of which 99 genes were upregulated and 91 genes were downregulated. GO analysis showed that the biological functions of DEGs focused primarily on regulating cell proliferation, adhesion, and differentiation and intracellular signal cascades. The main cellular components include cell membranes, exosomes, the cytoskeleton, and the extracellular matrix. The molecular functions include growth factor activity, protein kinase regulation, DNA binding, and oxygen transport activity. KEGG pathway analysis showed that these DEGs were mainly involved in the Wnt signaling pathway, amino acid metabolism, and the

Challenging a bioinformatic tool’s ability to detect microbial contaminants using in silico whole genome sequencing data

Directory of Open Access Journals (Sweden)

Nathan D. Olson

2017-09-01

Full Text Available High sensitivity methods such as next generation sequencing and polymerase chain reaction (PCR are adversely impacted by organismal and DNA contaminants. Current methods for detecting contaminants in microbial materials (genomic DNA and cultures are not sensitive enough and require either a known or culturable contaminant. Whole genome sequencing (WGS is a promising approach for detecting contaminants due to its sensitivity and lack of need for a priori assumptions about the contaminant. Prior to applying WGS, we must first understand its limitations for detecting contaminants and potential for false positives. Herein we demonstrate and characterize a WGS-based approach to detect organismal contaminants using an existing metagenomic taxonomic classification algorithm. Simulated WGS datasets from ten genera as individuals and binary mixtures of eight organisms at varying ratios were analyzed to evaluate the role of contaminant concentration and taxonomy on detection. For the individual genomes the false positive contaminants reported depended on the genus, with Staphylococcus, Escherichia, and Shigella having the highest proportion of false positives. For nearly all binary mixtures the contaminant was detected in the in-silico datasets at the equivalent of 1 in 1,000 cells, though F. tularensis was not detected in any of the simulated contaminant mixtures and Y. pestis was only detected at the equivalent of one in 10 cells. Once a WGS method for detecting contaminants is characterized, it can be applied to evaluate microbial material purity, in efforts to ensure that contaminants are characterized in microbial materials used to validate pathogen detection assays, generate genome assemblies for database submission, and benchmark sequencing methods.

Virulence Gene Pool Detected in Bovine Group C Streptococcus dysgalactiae subsp. dysgalactiae Isolates by Use of a Group A S. pyogenes Virulence Microarray ▿

Science.gov (United States)

Rato, Márcia G.; Nerlich, Andreas; Bergmann, René; Bexiga, Ricardo; Nunes, Sandro F.; Vilela, Cristina L.; Santos-Sanches, Ilda; Chhatwal, Gursharan S.

2011-01-01

A custom-designed microarray containing 220 virulence genes of Streptococcus pyogenes (group A Streptococcus [GAS]) was used to test group C Streptococcus dysgalactiae subsp. dysgalactiae (GCS) field strains causing bovine mastitis and group C or group G Streptococcus dysgalactiae subsp. equisimilis (GCS/GGS) isolates from human infections, with the latter being used for comparative purposes, for the presence of virulence genes. All bovine and all human isolates carried a fraction of the 220 genes (23% and 39%, respectively). The virulence genes encoding streptolysin S, glyceraldehyde-3-phosphate dehydrogenase, the plasminogen-binding M-like protein PAM, and the collagen-like protein SclB were detected in the majority of both bovine and human isolates (94 to 100%). Virulence factors, usually carried by human beta-hemolytic streptococcal pathogens, such as streptokinase, laminin-binding protein, and the C5a peptidase precursor, were detected in all human isolates but not in bovine isolates. Additionally, GAS bacteriophage-associated virulence genes encoding superantigens, DNase, and/or streptodornase were detected in bovine isolates (72%) but not in the human isolates. Determinants located in non-bacteriophage-related mobile elements, such as the gene encoding R28, were detected in all bovine and human isolates. Several virulence genes, including genes of bacteriophage origin, were shown to be expressed by reverse transcriptase PCR (RT-PCR). Phylogenetic analysis of superantigen gene sequences revealed a high level (>98%) of identity among genes of bovine GCS, of the horse pathogen Streptococcus equi subsp. equi, and of the human pathogen GAS. Our findings indicate that alpha-hemolytic bovine GCS, an important mastitis pathogen and considered to be a nonhuman pathogen, carries important virulence factors responsible for virulence and pathogenesis in humans. PMID:21525223

Detection of Electronic Anklet Wearers’ Groupings throughout Telematics Monitoring

Directory of Open Access Journals (Sweden)

Paulo Lima Machado

2017-01-01

Full Text Available Ankle bracelets (anklets imposed by law to track convicted individuals are being used in many countries as an alternative to overloaded prisons. There are many different systems for monitoring individuals wearing such devices, and these electronic anklet monitoring systems commonly detect violations of circulation areas permitted to holders. In spite of being able to monitor individual localization, such systems do not identify grouping activities of the monitored individuals, although this kind of event could represent a real risk of further offenses planned by those individuals. In order to address such a problem and to help monitoring systems to be able to have a proactive approach, this paper proposes sensor data fusion algorithms that are able to identify such groups based on data provided by anklet positioning devices. The results from the proposed algorithms can be applied to support risk assessment in the context of monitoring systems. The processing is performed using geographic points collected by a monitoring center, and as result, it produces a history of groups with their members, timestamps, locations and frequency of meetings. The proposed algorithms are validated in various serial and parallel computing scenarios, and the correspondent results are presented and discussed. The information produced by the proposed algorithms yields to a better characterization of the monitored individuals and can be adapted to support decision-making systems used by authorities that are responsible for planning decisions regarding actions affecting public security.

Achievements and challenges in structural bioinformatics and computational biophysics.

Science.gov (United States)

Samish, Ilan; Bourne, Philip E; Najmanovich, Rafael J

2015-01-01

The field of structural bioinformatics and computational biophysics has undergone a revolution in the last 10 years. Developments that are captured annually through the 3DSIG meeting, upon which this article reflects. An increase in the accessible data, computational resources and methodology has resulted in an increase in the size and resolution of studied systems and the complexity of the questions amenable to research. Concomitantly, the parameterization and efficiency of the methods have markedly improved along with their cross-validation with other computational and experimental results. The field exhibits an ever-increasing integration with biochemistry, biophysics and other disciplines. In this article, we discuss recent achievements along with current challenges within the field. © The Author 2014. Published by Oxford University Press.

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

NARCIS (Netherlands)

L. Shen (Lishuang); M.A. Diroma (Maria Angela); M. Gonzalez (Michael); D. Navarro-Gomez (Daniel); J. Leipzig (Jeremy); M.T. Lott (Marie T.); M. van Oven (Mannis); D.C. Wallace; C.C. Muraresku (Colleen Clarke); Z. Zolkipli-Cunningham (Zarazuela); P.F. Chinnery (Patrick); M. Attimonelli (Marcella); S. Zuchner (Stephan); M.J. Falk (Marni J.); X. Gai (Xiaowu)

2016-01-01

textabstractMSeqDR is the Mitochondrial Disease Sequence Data Resource, a centralized and comprehensive genome and phenome bioinformatics resource built by the mitochondrial disease community to facilitate clinical diagnosis and research investigations of individual patient phenotypes, genomes,

Improvements to PATRIC, the all-bacterial Bioinformatics Database and Analysis Resource Center

Science.gov (United States)

Wattam, Alice R.; Davis, James J.; Assaf, Rida; Boisvert, Sébastien; Brettin, Thomas; Bun, Christopher; Conrad, Neal; Dietrich, Emily M.; Disz, Terry; Gabbard, Joseph L.; Gerdes, Svetlana; Henry, Christopher S.; Kenyon, Ronald W.; Machi, Dustin; Mao, Chunhong; Nordberg, Eric K.; Olsen, Gary J.; Murphy-Olson, Daniel E.; Olson, Robert; Overbeek, Ross; Parrello, Bruce; Pusch, Gordon D.; Shukla, Maulik; Vonstein, Veronika; Warren, Andrew; Xia, Fangfang; Yoo, Hyunseung; Stevens, Rick L.

2017-01-01

The Pathosystems Resource Integration Center (PATRIC) is the bacterial Bioinformatics Resource Center (https://www.patricbrc.org). Recent changes to PATRIC include a redesign of the web interface and some new services that provide users with a platform that takes them from raw reads to an integrated analysis experience. The redesigned interface allows researchers direct access to tools and data, and the emphasis has changed to user-created genome-groups, with detailed summaries and views of the data that researchers have selected. Perhaps the biggest change has been the enhanced capability for researchers to analyze their private data and compare it to the available public data. Researchers can assemble their raw sequence reads and annotate the contigs using RASTtk. PATRIC also provides services for RNA-Seq, variation, model reconstruction and differential expression analysis, all delivered through an updated private workspace. Private data can be compared by ‘virtual integration’ to any of PATRIC's public data. The number of genomes available for comparison in PATRIC has expanded to over 80 000, with a special emphasis on genomes with antimicrobial resistance data. PATRIC uses this data to improve both subsystem annotation and k-mer classification, and tags new genomes as having signatures that indicate susceptibility or resistance to specific antibiotics. PMID:27899627

Group-specific multiplex PCR detection systems for the identification of flying insect prey.

Directory of Open Access Journals (Sweden)

Daniela Sint

Full Text Available The applicability of species-specific primers to study feeding interactions is restricted to those ecosystems where the targeted prey species occur. Therefore, group-specific primer pairs, targeting higher taxonomic levels, are often desired to investigate interactions in a range of habitats that do not share the same species but the same groups of prey. Such primers are also valuable to study the diet of generalist predators when next generation sequencing approaches cannot be applied beneficially. Moreover, due to the large range of prey consumed by generalists, it is impossible to investigate the breadth of their diet with species-specific primers, even if multiplexing them. However, only few group-specific primers are available to date and important groups of prey such as flying insects have rarely been targeted. Our aim was to fill this gap and develop group-specific primers suitable to detect and identify the DNA of common taxa of flying insects. The primers were combined in two multiplex PCR systems, which allow a time- and cost-effective screening of samples for DNA of the dipteran subsection Calyptratae (including Anthomyiidae, Calliphoridae, Muscidae, other common dipteran families (Phoridae, Syrphidae, Bibionidae, Chironomidae, Sciaridae, Tipulidae, three orders of flying insects (Hymenoptera, Lepidoptera, Plecoptera and coniferous aphids within the genus Cinara. The two PCR assays were highly specific and sensitive and their suitability to detect prey was confirmed by testing field-collected dietary samples from arthropods and vertebrates. The PCR assays presented here allow targeting prey at higher taxonomic levels such as family or order and therefore improve our ability to assess (trophic interactions with flying insects in terrestrial and aquatic habitats.

Creating a specialist protein resource network: a meeting report for the protein bioinformatics and community resources retreat.

Science.gov (United States)

Babbitt, Patricia C; Bagos, Pantelis G; Bairoch, Amos; Bateman, Alex; Chatonnet, Arnaud; Chen, Mark Jinan; Craik, David J; Finn, Robert D; Gloriam, David; Haft, Daniel H; Henrissat, Bernard; Holliday, Gemma L; Isberg, Vignir; Kaas, Quentin; Landsman, David; Lenfant, Nicolas; Manning, Gerard; Nagano, Nozomi; Srinivasan, Narayanaswamy; O'Donovan, Claire; Pruitt, Kim D; Sowdhamini, Ramanathan; Rawlings, Neil D; Saier, Milton H; Sharman, Joanna L; Spedding, Michael; Tsirigos, Konstantinos D; Vastermark, Ake; Vriend, Gerrit

2015-01-01

During 11-12 August 2014, a Protein Bioinformatics and Community Resources Retreat was held at the Wellcome Trust Genome Campus in Hinxton, UK. This meeting brought together the principal investigators of several specialized protein resources (such as CAZy, TCDB and MEROPS) as well as those from protein databases from the large Bioinformatics centres (including UniProt and RefSeq). The retreat was divided into five sessions: (1) key challenges, (2) the databases represented, (3) best practices for maintenance and curation, (4) information flow to and from large data centers and (5) communication and funding. An important outcome of this meeting was the creation of a Specialist Protein Resource Network that we believe will improve coordination of the activities of its member resources. We invite further protein database resources to join the network and continue the dialogue.

CNV-RF Is a Random Forest-Based Copy Number Variation Detection Method Using Next-Generation Sequencing.

Science.gov (United States)

Onsongo, Getiria; Baughn, Linda B; Bower, Matthew; Henzler, Christine; Schomaker, Matthew; Silverstein, Kevin A T; Thyagarajan, Bharat

2016-11-01

Simultaneous detection of small copy number variations (CNVs) (<0.5 kb) and single-nucleotide variants in clinically significant genes is of great interest for clinical laboratories. The analytical variability in next-generation sequencing (NGS) and artifacts in coverage data because of issues with mappability along with lack of robust bioinformatics tools for CNV detection have limited the utility of targeted NGS data to identify CNVs. We describe the development and implementation of a bioinformatics algorithm, copy number variation-random forest (CNV-RF), that incorporates a machine learning component to identify CNVs from targeted NGS data. Using CNV-RF, we identified 12 of 13 deletions in samples with known CNVs, two cases with duplications, and identified novel deletions in 22 additional cases. Furthermore, no CNVs were identified among 60 genes in 14 cases with normal copy number and no CNVs were identified in another 104 patients with clinical suspicion of CNVs. All positive deletions and duplications were confirmed using a quantitative PCR method. CNV-RF also detected heterozygous deletions and duplications with a specificity of 50% across 4813 genes. The ability of CNV-RF to detect clinically relevant CNVs with a high degree of sensitivity along with confirmation using a low-cost quantitative PCR method provides a framework for providing comprehensive NGS-based CNV/single-nucleotide variant detection in a clinical molecular diagnostics laboratory. Copyright © 2016 American Society for Investigative Pathology and the Association for Molecular Pathology. Published by Elsevier Inc. All rights reserved.

An internet-based bioinformatics toolkit for plant biosecurity diagnosis and surveillance of viruses and viroids.

Science.gov (United States)

Barrero, Roberto A; Napier, Kathryn R; Cunnington, James; Liefting, Lia; Keenan, Sandi; Frampton, Rebekah A; Szabo, Tamas; Bulman, Simon; Hunter, Adam; Ward, Lisa; Whattam, Mark; Bellgard, Matthew I

2017-01-11

Detection and preventing entry of exotic viruses and viroids at the border is critical for protecting plant industries trade worldwide. Existing post entry quarantine screening protocols rely on time-consuming biological indicators and/or molecular assays that require knowledge of infecting viral pathogens. Plants have developed the ability to recognise and respond to viral infections through Dicer-like enzymes that cleave viral sequences into specific small RNA products. Many studies reported the use of a broad range of small RNAs encompassing the product sizes of several Dicer enzymes involved in distinct biological pathways. Here we optimise the assembly of viral sequences by using specific small RNA subsets. We sequenced the small RNA fractions of 21 plants held at quarantine glasshouse facilities in Australia and New Zealand. Benchmarking of several de novo assembler tools yielded SPAdes using a kmer of 19 to produce the best assembly outcomes. We also found that de novo assembly using 21-25 nt small RNAs can result in chimeric assemblies of viral sequences and plant host sequences. Such non-specific assemblies can be resolved by using 21-22 nt or 24 nt small RNAs subsets. Among the 21 selected samples, we identified contigs with sequence similarity to 18 viruses and 3 viroids in 13 samples. Most of the viruses were assembled using only 21-22 nt long virus-derived siRNAs (viRNAs), except for one Citrus endogenous pararetrovirus that was more efficiently assembled using 24 nt long viRNAs. All three viroids found in this study were fully assembled using either 21-22 nt or 24 nt viRNAs. Optimised analysis workflows were customised within the Yabi web-based analytical environment. We present a fully automated viral surveillance and diagnosis web-based bioinformatics toolkit that provides a flexible, user-friendly, robust and scalable interface for the discovery and diagnosis of viral pathogens. We have implemented an automated viral surveillance and

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

Science.gov (United States)

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

2014-05-13

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

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

Science.gov (United States)

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

2016-05-01

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

The OAuth 2.0 Web Authorization Protocol for the Internet Addiction Bioinformatics (IABio Database

Directory of Open Access Journals (Sweden)

Jeongseok Choi

2016-03-01

Full Text Available Internet addiction (IA has become a widespread and problematic phenomenon as smart devices pervade society. Moreover, internet gaming disorder leads to increases in social expenditures for both individuals and nations alike. Although the prevention and treatment of IA are getting more important, the diagnosis of IA remains problematic. Understanding the neurobiological mechanism of behavioral addictions is essential for the development of specific and effective treatments. Although there are many databases related to other addictions, a database for IA has not been developed yet. In addition, bioinformatics databases, especially genetic databases, require a high level of security and should be designed based on medical information standards. In this respect, our study proposes the OAuth standard protocol for database access authorization. The proposed IA Bioinformatics (IABio database system is based on internet user authentication, which is a guideline for medical information standards, and uses OAuth 2.0 for access control technology. This study designed and developed the system requirements and configuration. The OAuth 2.0 protocol is expected to establish the security of personal medical information and be applied to genomic research on IA.

Detecting subnetwork-level dynamic correlations.

Science.gov (United States)

Yan, Yan; Qiu, Shangzhao; Jin, Zhuxuan; Gong, Sihong; Bai, Yun; Lu, Jianwei; Yu, Tianwei

2017-01-15

The biological regulatory system is highly dynamic. The correlations between many functionally related genes change over different biological conditions. Finding dynamic relations on the existing biological network may reveal important regulatory mechanisms. Currently no method is available to detect subnetwork-level dynamic correlations systematically on the genome-scale network. Two major issues hampered the development. The first is gene expression profiling data usually do not contain time course measurements to facilitate the analysis of dynamic relations, which can be partially addressed by using certain genes as indicators of biological conditions. Secondly, it is unclear how to effectively delineate subnetworks, and define dynamic relations between them. Here we propose a new method named LANDD (Liquid Association for Network Dynamics Detection) to find subnetworks that show substantial dynamic correlations, as defined by subnetwork A is concentrated with Liquid Association scouting genes for subnetwork B. The method produces easily interpretable results because of its focus on subnetworks that tend to comprise functionally related genes. Also, the collective behaviour of genes in a subnetwork is a much more reliable indicator of underlying biological conditions compared to using single genes as indicators. We conducted extensive simulations to validate the method's ability to detect subnetwork-level dynamic correlations. Using a real gene expression dataset and the human protein-protein interaction network, we demonstrate the method links subnetworks of distinct biological processes, with both confirmed relations and plausible new functional implications. We also found signal transduction pathways tend to show extensive dynamic relations with other functional groups. The R package is available at https://cran.r-project.org/web/packages/LANDD CONTACTS: yunba@pcom.edu, jwlu33@hotmail.com or tianwei.yu@emory.eduSupplementary information: Supplementary data

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

Science.gov (United States)

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

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

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

OpenAIRE

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

2013-01-01

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

Network-based group variable selection for detecting expression quantitative trait loci (eQTL

Directory of Open Access Journals (Sweden)

Zhang Xuegong

2011-06-01

Full Text Available Abstract Background Analysis of expression quantitative trait loci (eQTL aims to identify the genetic loci associated with the expression level of genes. Penalized regression with a proper penalty is suitable for the high-dimensional biological data. Its performance should be enhanced when we incorporate biological knowledge of gene expression network and linkage disequilibrium (LD structure between loci in high-noise background. Results We propose a network-based group variable selection (NGVS method for QTL detection. Our method simultaneously maps highly correlated expression traits sharing the same biological function to marker sets formed by LD. By grouping markers, complex joint activity of multiple SNPs can be considered and the dimensionality of eQTL problem is reduced dramatically. In order to demonstrate the power and flexibility of our method, we used it to analyze two simulations and a mouse obesity and diabetes dataset. We considered the gene co-expression network, grouped markers into marker sets and treated the additive and dominant effect of each locus as a group: as a consequence, we were able to replicate results previously obtained on the mouse linkage dataset. Furthermore, we observed several possible sex-dependent loci and interactions of multiple SNPs. Conclusions The proposed NGVS method is appropriate for problems with high-dimensional data and high-noise background. On eQTL problem it outperforms the classical Lasso method, which does not consider biological knowledge. Introduction of proper gene expression and loci correlation information makes detecting causal markers more accurate. With reasonable model settings, NGVS can lead to novel biological findings.

Meta-learning framework applied in bioinformatics inference system design.

Science.gov (United States)

Arredondo, Tomás; Ormazábal, Wladimir

2015-01-01

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

Bioinformatics Tools for the Discovery of New Nonribosomal Peptides

DEFF Research Database (Denmark)

Leclère, Valérie; Weber, Tilmann; Jacques, Philippe

2016-01-01

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

detectIR: a novel program for detecting perfect and imperfect inverted repeats using complex numbers and vector calculation.

Science.gov (United States)

Ye, Congting; Ji, Guoli; Li, Lei; Liang, Chun

2014-01-01

Inverted repeats are present in abundance in both prokaryotic and eukaryotic genomes and can form DNA secondary structures--hairpins and cruciforms that are involved in many important biological processes. Bioinformatics tools for efficient and accurate detection of inverted repeats are desirable, because existing tools are often less accurate and time consuming, sometimes incapable of dealing with genome-scale input data. Here, we present a MATLAB-based program called detectIR for the perfect and imperfect inverted repeat detection that utilizes complex numbers and vector calculation and allows genome-scale data inputs. A novel algorithm is adopted in detectIR to convert the conventional sequence string comparison in inverted repeat detection into vector calculation of complex numbers, allowing non-complementary pairs (mismatches) in the pairing stem and a non-palindromic spacer (loop or gaps) in the middle of inverted repeats. Compared with existing popular tools, our program performs with significantly higher accuracy and efficiency. Using genome sequence data from HIV-1, Arabidopsis thaliana, Homo sapiens and Zea mays for comparison, detectIR can find lots of inverted repeats missed by existing tools whose outputs often contain many invalid cases. detectIR is open source and its source code is freely available at: https://sourceforge.net/projects/detectir.

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

Directory of Open Access Journals (Sweden)

Athanassios M. Kintsakis

2017-01-01

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

bioalcidae, samjs and vcffilterjs: object-oriented formatters and filters for bioinformatics files.

Science.gov (United States)

Lindenbaum, Pierre; Redon, Richard

2018-04-01

Reformatting and filtering bioinformatics files are common tasks for bioinformaticians. Standard Linux tools and specific programs are usually used to perform such tasks but there is still a gap between using these tools and the programming interface of some existing libraries. In this study, we developed a set of tools namely bioalcidae, samjs and vcffilterjs that reformat or filter files using a JavaScript engine or a pure java expression and taking advantage of the java API for high-throughput sequencing data (htsjdk). https://github.com/lindenb/jvarkit. pierre.lindenbaum@univ-nantes.fr.

Bearing fault detection utilizing group delay and the Hilbert-Huang transform

International Nuclear Information System (INIS)

Jin, Shuai; Lee, Sang-Kwon

2017-01-01

Vibration signals measured from a mechanical system are useful to detect system faults. Signal processing has been used to extract fault information in bearing systems. However, a wide vibration signal frequency band often affects the ability to obtain the effective fault features. In addition, a few oscillation components are not useful at the entire frequency band in a vibration signal. By contrast, useful fatigue information can be embedded in the noise oscillation components. Thus, a method to estimate which frequency band contains fault information utilizing group delay was proposed in this paper. Group delay as a measure of phase distortion can indicate the phase structure relationship in the frequency domain between original (with noise) and denoising signals. We used the empirical mode decomposition of a Hilbert-Huang transform to sift the useful intrinsic mode functions based on the results of group delay after determining the valuable frequency band. Finally, envelope analysis and the energy distribution after the Hilbert transform were used to complete the fault diagnosis. The practical bearing fault data, which were divided into inner and outer race faults, were used to verify the efficiency and quality of the proposed method

Bearing fault detection utilizing group delay and the Hilbert-Huang transform

Energy Technology Data Exchange (ETDEWEB)

Jin, Shuai; Lee, Sang-Kwon [Inha University, Incheon (Korea, Republic of)

2017-03-15

Vibration signals measured from a mechanical system are useful to detect system faults. Signal processing has been used to extract fault information in bearing systems. However, a wide vibration signal frequency band often affects the ability to obtain the effective fault features. In addition, a few oscillation components are not useful at the entire frequency band in a vibration signal. By contrast, useful fatigue information can be embedded in the noise oscillation components. Thus, a method to estimate which frequency band contains fault information utilizing group delay was proposed in this paper. Group delay as a measure of phase distortion can indicate the phase structure relationship in the frequency domain between original (with noise) and denoising signals. We used the empirical mode decomposition of a Hilbert-Huang transform to sift the useful intrinsic mode functions based on the results of group delay after determining the valuable frequency band. Finally, envelope analysis and the energy distribution after the Hilbert transform were used to complete the fault diagnosis. The practical bearing fault data, which were divided into inner and outer race faults, were used to verify the efficiency and quality of the proposed method.

"Students-as-Partners" Scheme Enhances Postgraduate Students' Employability Skills While Addressing Gaps in Bioinformatics Education

Science.gov (United States)

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

2017-01-01

Teaching bioinformatics is a longstanding challenge for educators who need to demonstrate to students how skills developed in the classroom may be applied to real world research. This study employed an action research methodology which utilised student-staff partnership and peer-learning. It was centred on the experiences of peer-facilitators,…

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

Science.gov (United States)

Alyuruk, Hakan; Cavas, Levent

2014-01-01

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

miRToolsGallery: a tag-based and rankable microRNA bioinformatics resources database portal

Science.gov (United States)

Chen, Liang; Heikkinen, Liisa; Wang, ChangLiang; Yang, Yang; Knott, K Emily

2018-01-01

Abstract Hundreds of bioinformatics tools have been developed for MicroRNA (miRNA) investigations including those used for identification, target prediction, structure and expression profile analysis. However, finding the correct tool for a specific application requires the tedious and laborious process of locating, downloading, testing and validating the appropriate tool from a group of nearly a thousand. In order to facilitate this process, we developed a novel database portal named miRToolsGallery. We constructed the portal by manually curating > 950 miRNA analysis tools and resources. In the portal, a query to locate the appropriate tool is expedited by being searchable, filterable and rankable. The ranking feature is vital to quickly identify and prioritize the more useful from the obscure tools. Tools are ranked via different criteria including the PageRank algorithm, date of publication, number of citations, average of votes and number of publications. miRToolsGallery provides links and data for the comprehensive collection of currently available miRNA tools with a ranking function which can be adjusted using different criteria according to specific requirements. Database URL: http://www.mirtoolsgallery.org PMID:29688355

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

Science.gov (United States)

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

2009-02-01

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

PCOGR: Phylogenetic COG ranking as an online tool to judge the specificity of COGs with respect to freely definable groups of organisms

Directory of Open Access Journals (Sweden)

Kaufmann Michael

2004-10-01

Full Text Available Abstract Background The rapidly increasing number of completely sequenced genomes led to the establishment of the COG-database which, based on sequence homologies, assigns similar proteins from different organisms to clusters of orthologous groups (COGs. There are several bioinformatic studies that made use of this database to determine (hyperthermophile-specific proteins by searching for COGs containing (almost exclusively proteins from (hyperthermophilic genomes. However, public software to perform individually definable group-specific searches is not available. Results The tool described here exactly fills this gap. The software is accessible at http://www.uni-wh.de/pcogr and is linked to the COG-database. The user can freely define two groups of organisms by selecting for each of the (current 66 organisms to belong either to groupA, to the reference groupB or to be ignored by the algorithm. Then, for all COGs a specificity index is calculated with respect to the specificity to groupA, i. e. high scoring COGs contain proteins from the most of groupA organisms while proteins from the most organisms assigned to groupB are absent. In addition to ranking all COGs according to the user defined specificity criteria, a graphical visualization shows the distribution of all COGs by displaying their abundance as a function of their specificity indexes. Conclusions This software allows detecting COGs specific to a predefined group of organisms. All COGs are ranked in the order of their specificity and a graphical visualization allows recognizing (i the presence and abundance of such COGs and (ii the phylogenetic relationship between groupA- and groupB-organisms. The software also allows detecting putative protein-protein interactions, novel enzymes involved in only partially known biochemical pathways, and alternate enzymes originated by convergent evolution.

PCOGR: phylogenetic COG ranking as an online tool to judge the specificity of COGs with respect to freely definable groups of organisms.

Science.gov (United States)

Meereis, Florian; Kaufmann, Michael

2004-10-15

The rapidly increasing number of completely sequenced genomes led to the establishment of the COG-database which, based on sequence homologies, assigns similar proteins from different organisms to clusters of orthologous groups (COGs). There are several bioinformatic studies that made use of this database to determine (hyper)thermophile-specific proteins by searching for COGs containing (almost) exclusively proteins from (hyper)thermophilic genomes. However, public software to perform individually definable group-specific searches is not available. The tool described here exactly fills this gap. The software is accessible at http://www.uni-wh.de/pcogr and is linked to the COG-database. The user can freely define two groups of organisms by selecting for each of the (current) 66 organisms to belong either to groupA, to the reference groupB or to be ignored by the algorithm. Then, for all COGs a specificity index is calculated with respect to the specificity to groupA, i. e. high scoring COGs contain proteins from the most of groupA organisms while proteins from the most organisms assigned to groupB are absent. In addition to ranking all COGs according to the user defined specificity criteria, a graphical visualization shows the distribution of all COGs by displaying their abundance as a function of their specificity indexes. This software allows detecting COGs specific to a predefined group of organisms. All COGs are ranked in the order of their specificity and a graphical visualization allows recognizing (i) the presence and abundance of such COGs and (ii) the phylogenetic relationship between groupA- and groupB-organisms. The software also allows detecting putative protein-protein interactions, novel enzymes involved in only partially known biochemical pathways, and alternate enzymes originated by convergent evolution.

Shilling attack detection for recommender systems based on credibility of group users and rating time series.

Science.gov (United States)

Zhou, Wei; Wen, Junhao; Qu, Qiang; Zeng, Jun; Cheng, Tian

2018-01-01

Recommender systems are vulnerable to shilling attacks. Forged user-generated content data, such as user ratings and reviews, are used by attackers to manipulate recommendation rankings. Shilling attack detection in recommender systems is of great significance to maintain the fairness and sustainability of recommender systems. The current studies have problems in terms of the poor universality of algorithms, difficulty in selection of user profile attributes, and lack of an optimization mechanism. In this paper, a shilling behaviour detection structure based on abnormal group user findings and rating time series analysis is proposed. This paper adds to the current understanding in the field by studying the credibility evaluation model in-depth based on the rating prediction model to derive proximity-based predictions. A method for detecting suspicious ratings based on suspicious time windows and target item analysis is proposed. Suspicious rating time segments are determined by constructing a time series, and data streams of the rating items are examined and suspicious rating segments are checked. To analyse features of shilling attacks by a group user's credibility, an abnormal group user discovery method based on time series and time window is proposed. Standard testing datasets are used to verify the effect of the proposed method.

[Detection of CRSPR-Cas system in Streptococcus thermophiles].

Science.gov (United States)

Li, Wan; Liang, Hongzhang; Zhang, Danqing; Wang, Nana; Tang, Yaru; Li, Bailiang; Huo, Guicheng

2016-04-14

We aimed to detect the CRSPR-Cas system of six Streptococcus thermophilus. Bioinformatics method was used to predict CRSPR-Cas system of nine S. thermophilus that published in National Center for Biotechnology Information. Four primers were designed according to the flanking sequences of standard strains and the CRISPR-Cas system of six S. thermophilus have been detected by PCR method. S. thermophilus S4 had a Cas9 gene, others all had Cas9 gene, Cas10 gene and Cas9* gene. In addition, 79 and KLDS3.0207 still had Cas3 gene. Signature genes amplification of CRSPR-Cas system could predict the type of CRSPR-Cas system in unsequenced strains, these findings will help establish the foundation for the study of CRSPR-Cas system in lactic acid bacteria.

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

Energy Technology Data Exchange (ETDEWEB)

NONE

2000-04-01

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

Creating a specialist protein resource network: a meeting report for the protein bioinformatics and community resources retreat

NARCIS (Netherlands)

Babbitt, P.C.; Bagos, P.G.; Bairoch, A.; Bateman, A.; Chatonnet, A.; Chen, M.J.; Craik, D.J.; Finn, R.D.; Gloriam, D.; Haft, D.H.; Henrissat, B.; Holliday, G.L.; Isberg, V.; Kaas, Q.; Landsman, D.; Lenfant, N.; Manning, G.; Nagano, N.; Srinivasan, N.; O'Donovan, C.; Pruitt, K.D.; Sowdhamini, R.; Rawlings, N.D.; Saier, M.H., Jr.; Sharman, J.L.; Spedding, M.; Tsirigos, K.D.; Vastermark, A.; Vriend, G.

2015-01-01

During 11-12 August 2014, a Protein Bioinformatics and Community Resources Retreat was held at the Wellcome Trust Genome Campus in Hinxton, UK. This meeting brought together the principal investigators of several specialized protein resources (such as CAZy, TCDB and MEROPS) as well as those from

An Adaptive Hybrid Multiprocessor technique for bioinformatics sequence alignment

KAUST Repository

Bonny, Talal

2012-07-28

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.

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

Directory of Open Access Journals (Sweden)

Lei Wang

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