Relevant bibliographies by topics / Bioinformatics workflow

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Book chapters
  4. Conference papers

Academic literature on the topic 'Bioinformatics workflow'

Author: Grafiati
Published: 4 June 2021
Last updated: 1 February 2022

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Journal articles on the topic "Bioinformatics workflow"

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Jackson, Michael, Kostas Kavoussanakis, and Edward W. J. Wallace. "Using prototyping to choose a bioinformatics workflow management system." PLOS Computational Biology 17, no. 2 (2021): e1008622. http://dx.doi.org/10.1371/journal.pcbi.1008622.

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Workflow management systems represent, manage, and execute multistep computational analyses and offer many benefits to bioinformaticians. They provide a common language for describing analysis workflows, contributing to reproducibility and to building libraries of reusable components. They can support both incremental build and re-entrancy—the ability to selectively re-execute parts of a workflow in the presence of additional inputs or changes in configuration and to resume execution from where a workflow previously stopped. Many workflow management systems enhance portability by supporting the use of containers, high-performance computing (HPC) systems, and clouds. Most importantly, workflow management systems allow bioinformaticians to delegate how their workflows are run to the workflow management system and its developers. This frees the bioinformaticians to focus on what these workflows should do, on their data analyses, and on their science. RiboViz is a package to extract biological insight from ribosome profiling data to help advance understanding of protein synthesis. At the heart of RiboViz is an analysis workflow, implemented in a Python script. To conform to best practices for scientific computing which recommend the use of build tools to automate workflows and to reuse code instead of rewriting it, the authors reimplemented this workflow within a workflow management system. To select a workflow management system, a rapid survey of available systems was undertaken, and candidates were shortlisted: Snakemake, cwltool, Toil, and Nextflow. Each candidate was evaluated by quickly prototyping a subset of the RiboViz workflow, and Nextflow was chosen. The selection process took 10 person-days, a small cost for the assurance that Nextflow satisfied the authors’ requirements. The use of prototyping can offer a low-cost way of making a more informed selection of software to use within projects, rather than relying solely upon reviews and recommendations by others.
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Bedő, Justin. "BioShake: a Haskell EDSL for bioinformatics workflows." PeerJ 7 (July 9, 2019): e7223. http://dx.doi.org/10.7717/peerj.7223.

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Typical bioinformatics analyses comprise of long running computational workflows. An important part of reproducible research is the management and execution of these workflows to allow robust execution and to minimise errors. BioShake is an embedded domain specific language in Haskell for specifying and executing computational workflows for bioinformatics that significantly reduces the possibility of errors occurring. Unlike other workflow frameworks, BioShake raises many properties to the type level allowing the correctness of a workflow to be statically checked during compilation, catching errors before any lengthy execution process. BioShake builds on the Shake build tool to provide robust dependency tracking, parallel execution, reporting, and resumption capabilities. Finally, BioShake abstracts execution so that jobs can either be executed directly or submitted to a cluster. BioShake is available at http://github.com/PapenfussLab/bioshake.
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Kožusznik, Jan, Petr Bainar, Jana Klímová, et al. "SPIM workflow manager for HPC." Bioinformatics 35, no. 19 (2019): 3875–76. http://dx.doi.org/10.1093/bioinformatics/btz140.

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Abstract Summary Here we introduce a Fiji plugin utilizing the HPC-as-a-Service concept, significantly mitigating the challenges life scientists face when delegating complex data-intensive processing workflows to HPC clusters. We demonstrate on a common Selective Plane Illumination Microscopy image processing task that execution of a Fiji workflow on a remote supercomputer leads to improved turnaround time despite the data transfer overhead. The plugin allows the end users to conveniently transfer image data to remote HPC resources, manage pipeline jobs and visualize processed results directly from the Fiji graphical user interface. Availability and implementation The code is distributed free and open source under the MIT license. Source code: https://github.com/fiji-hpc/hpc-workflow-manager/, documentation: https://imagej.net/SPIM_Workflow_Manager_For_HPC. Supplementary information Supplementary data are available at Bioinformatics online.
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Conery, John S., Julian M. Catchen, and Michael Lynch. "Rule-based workflow management for bioinformatics." VLDB Journal 14, no. 3 (2005): 318–29. http://dx.doi.org/10.1007/s00778-005-0153-9.

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Köster, Johannes, and Sven Rahmann. "Snakemake—a scalable bioinformatics workflow engine." Bioinformatics 34, no. 20 (2018): 3600. http://dx.doi.org/10.1093/bioinformatics/bty350.

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Koster, J., and S. Rahmann. "Snakemake--a scalable bioinformatics workflow engine." Bioinformatics 28, no. 19 (2012): 2520–22. http://dx.doi.org/10.1093/bioinformatics/bts480.

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Simopoulos, Caitlin M. A., Zhibin Ning, Xu Zhang, et al. "pepFunk: a tool for peptide-centric functional analysis of metaproteomic human gut microbiome studies." Bioinformatics 36, no. 14 (2020): 4171–79. http://dx.doi.org/10.1093/bioinformatics/btaa289.

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Abstract Motivation Enzymatic digestion of proteins before mass spectrometry analysis is a key process in metaproteomic workflows. Canonical metaproteomic data processing pipelines typically involve matching spectra produced by the mass spectrometer to a theoretical spectra database, followed by matching the identified peptides back to parent-proteins. However, the nature of enzymatic digestion produces peptides that can be found in multiple proteins due to conservation or chance, presenting difficulties with protein and functional assignment. Results To combat this challenge, we developed pepFunk, a peptide-centric metaproteomic workflow focused on the analysis of human gut microbiome samples. Our workflow includes a curated peptide database annotated with Kyoto Encyclopedia of Genes and Genomes (KEGG) terms and a gene set variation analysis-inspired pathway enrichment adapted for peptide-level data. Analysis using our peptide-centric workflow is fast and highly correlated to a protein-centric analysis, and can identify more enriched KEGG pathways than analysis using protein-level data. Our workflow is open source and available as a web application or source code to be run locally. Availability and implementation pepFunk is available online as a web application at https://shiny.imetalab.ca/pepFunk/ with open-source code available from https://github.com/northomics/pepFunk. Contact dfigeys@uottawa.ca Supplementary information Supplementary data are available at Bioinformatics online.
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Bhardwaj, Vivek, Steffen Heyne, Katarzyna Sikora, et al. "snakePipes: facilitating flexible, scalable and integrative epigenomic analysis." Bioinformatics 35, no. 22 (2019): 4757–59. http://dx.doi.org/10.1093/bioinformatics/btz436.

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Abstract Summary Due to the rapidly increasing scale and diversity of epigenomic data, modular and scalable analysis workflows are of wide interest. Here we present snakePipes, a workflow package for processing and downstream analysis of data from common epigenomic assays: ChIP-seq, RNA-seq, Bisulfite-seq, ATAC-seq, Hi-C and single-cell RNA-seq. snakePipes enables users to assemble variants of each workflow and to easily install and upgrade the underlying tools, via its simple command-line wrappers and yaml files. Availability and implementation snakePipes can be installed via conda: `conda install -c mpi-ie -c bioconda -c conda-forge snakePipes’. Source code (https://github.com/maxplanck-ie/snakepipes) and documentation (https://snakepipes.readthedocs.io/en/latest/) are available online. Supplementary information Supplementary data are available at Bioinformatics online.
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Theil, Sebastien, and Etienne Rifa. "rANOMALY: AmplicoN wOrkflow for Microbial community AnaLYsis." F1000Research 10 (January 7, 2021): 7. http://dx.doi.org/10.12688/f1000research.27268.1.

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Bioinformatic tools for marker gene sequencing data analysis are continuously and rapidly evolving, thus integrating most recent techniques and tools is challenging. We present an R package for data analysis of 16S and ITS amplicons based sequencing. This workflow is based on several R functions and performs automatic treatments from fastq sequence files to diversity and differential analysis with statistical validation. The main purpose of this package is to automate bioinformatic analysis, ensure reproducibility between projects, and to be flexible enough to quickly integrate new bioinformatic tools or statistical methods. rANOMALY is an easy to install and customizable R package, that uses amplicon sequence variants (ASV) level for microbial community characterization. It integrates all assets of the latest bioinformatics methods, such as better sequence tracking, decontamination from control samples, use of multiple reference databases for taxonomic annotation, all main ecological analysis for which we propose advanced statistical tests, and a cross-validated differential analysis by four different methods. Our package produces ready to publish figures, and all of its outputs are made to be integrated in Rmarkdown code to produce automated reports.
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Dijkstra, Maurits J. J., Atze J. van der Ploeg, K. Anton Feenstra, Wan J. Fokkink, Sanne Abeln, and Jaap Heringa. "Tailor-made multiple sequence alignments using the PRALINE 2 alignment toolkit." Bioinformatics 35, no. 24 (2019): 5315–17. http://dx.doi.org/10.1093/bioinformatics/btz572.

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Abstract Summary PRALINE 2 is a toolkit for custom multiple sequence alignment workflows. It can be used to incorporate sequence annotations, such as secondary structure or (DNA) motifs, into the alignment scoring, as well as to customize many other aspects of a progressive multiple alignment workflow. Availability and implementation PRALINE 2 is implemented in Python and available as open source software on GitHub: https://github.com/ibivu/PRALINE/.
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Dissertations / Theses on the topic "Bioinformatics workflow"

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LEMOS, MELISSA. "WORKFLOW FOR BIOINFORMATICS." PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO, 2004. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=5928@1.

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CONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICO<br>Os projetos para estudo de genomas partem de uma fase de sequenciamento onde são gerados em laboratório dados brutos, ou seja, sequências de DNA sem significado biológico. As sequências de DNA possuem códigos responsáveis pela produção de proteínas e RNAs, enquanto que as proteínas participam de todos os fenômenos biológicos, como a replicação celular, produção de energia, defesa imunológica, contração muscular, atividade neurológica e reprodução. As sequências de DNA, RNA e proteínas são chamadas nesta tese de biossequências. Porém, o grande desafio destes projetos consiste em analisar essas biossequências, e obter informações biologicamente relevantes. Durante a fase de análise, os pesquisadores usam diversas ferramentas, programas de computador, e um grande volume de informações armazenadas em fontes de dados de Biologia Molecular. O crescente volume e a distribuição das fontes de dados e a implementação de novos processos em Bioinformática facilitaram enormemente a fase de análise, porém criaram uma demanda por ferramentas e sistemas semi-automáticos para lidar com tal volume e complexidade. Neste cenário, esta tese aborda o uso de workflows para compor processos de Bioinformática, facilitando a fase de análise. Inicialmente apresenta uma ontologia modelando processos e dados comumente utilizados em Bioinformática. Esta ontologia foi derivada de um estudo cuidadoso, resumido na tese, das principais tarefas feitas pelos pesquisadores em Bioinformática. Em seguida, a tese propõe um framework para um sistema de gerência de análises em biossequências, composto por dois sub-sistemas. O primeiro é um sistema de gerência de workflows de Bioinformática, que auxilia os pesquisadores na definição, validação, otimização e execução de workflows necessários para se realizar as análises. O segundo é um sistema de gerência de dados em Bioinformática, que trata do armazenamento e da manipulação dos dados envolvidos nestas análises. O framework inclui um gerente de ontologias, armazenando ontologias para Bioinformática, nos moldes da apresentada anteriormente. Por fim, a tese descreve instanciações do framework para três tipos de ambiente de trabalho comumente encontrados e sugestivamente chamados de ambiente pessoal, ambiente de laboratório e ambiente de comunidade. Para cada um destes ambientes, a tese discute em detalhe os aspectos particulares da execução e otimização de workflows.<br>Genome projects usually start with a sequencing phase, where experimental data, usually DNA sequences, is generated, without any biological interpretation. DNA sequences have codes which are responsible for the production of protein and RNA sequences, while protein sequences participate in all biological phenomena, such as cell replication, energy production, immunological defense, muscular contraction, neurological activity and reproduction. DNA, RNA and protein sequences are called biosequences in this thesis. The fundamental challenge researchers face lies exactly in analyzing these sequences to derive information that is biologically relevant. During the analysis phase, researchers use a variety of analysis programs and access large data sources holding Molecular Biology data. The growing number of Bioinformatics data sources and analysis programs indeed enormously facilitated the analysis phase. However, it creates a demand for systems that facilitate using such computational resources. Given this scenario, this thesis addresses the use of workflows to compose Bioinformatics analysis programs that access data sources, thereby facilitating the analysis phase. An ontology modeling the analysis program and data sources commonly used in Bioinformatics is first described. This ontology is derived from a careful study, also summarized in the thesis, of the computational resources researchers in Bioinformatics presently use. A framework for biosequence analysis management systems is next described. The system is divided into two major components. The first component is a Bioinformatics workflow management system that helps researchers define, validate, optimize and run workflows combining Bioinformatics analysis programs. The second component is a Bioinformatics data management system that helps researchers manage large volumes of Bioinformatics data. The framework includes an ontology manager that stores Bioinformatics ontologies, such as that previously described. Lastly, instantiations for the Bioinformatics workflow management system framework are described. The instantiations cover three types of working environments commonly found and suggestively called personal environment, laboratory environment and community environment. For each of these instantiations, aspects related to workflow optimization and execution are carefully discussed.
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Linke, Burkhard [Verfasser]. "Conveyor : a workflow engine for bioinformatics analyses / Burkhard Linke. Technische Fakultät." Bielefeld : Universitätsbibliothek Bielefeld, Hochschulschriften, 2012. http://d-nb.info/1020344385/34.

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Nyasulu, Jonas. "A Comparison of Vistrails and Taverna, and Workflow Interoperability." Thesis, Linköping University, Department of Computer and Information Science, 2009. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-21925.

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<p>In silico experiments in the field of bioinformatics generate large amounts of data since most of the tasks are done in an exploratory fashion. Workflows are one of the many tools used by scientists to model complex tasks.The interoperability of data generated from these tools plays an important role in improving the efficiency of such tools and also in verifying results from other experiments.We aim to compare workflow systems by integrating bioinformatics data in Vistrails and Taverna. We also look at how the two systems use the open provenance model that has been developed to bring provenance interoperability. We developed web services to perform similar functions of some workflows in Vistrails. With the services we were able to perform most of the tasks we planned using both systems. Differences in how lists of items are processed in the two systems results in differences in how workflows are composed in the two systems. In Taverna there is implicit iteration and Vistrails requires the use of additional modules to perform iteration.There are also differences in the execution times of workflows using web services, with workflows in Taverna taking longer than their counterparts in Vistrails. There are some similarities in the execution pattern of workflows if same workflow is invokedmultiple times, with the first invocation taking longer time than the subsequent ones.</p>
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Chatzou, Maria 1985. "Large-scale comparative bioinformatics analyses." Doctoral thesis, Universitat Pompeu Fabra, 2016. http://hdl.handle.net/10803/587086.

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One of the main and most recent challenges of modern biology is to keep-up with growing amount of biological data coming from next generation sequencing technologies. Keeping up with the growing volumes of experiments will be the only way to make sense of the data and extract actionable biological insights. Large-scale comparative bioinformatics analyses are an integral part of this procedure. When doing comparative bioinformatics, multiple sequence alignments (MSAs) are by far the most widely used models as they provide a unique insight into the accurate measure of sequence similarities and are therefore instrumental to revealing genetic and/or functional relationships among evolutionarily related species. Unfortunately, the well-established limitation of MSA methods when dealing with very large datasets potentially compromises all downstream analysis. In this thesis I expose the current relevance of multiple sequence aligners, I show how their current scaling up is leading to serious numerical stability issues and how they impact phylogenetic tree reconstruction. For this purpose, I have developed two new methods, MEGA-Coffee, a large scale aligner and Shootstrap a novel bootstrapping measure incorporating MSA instability with branch support estimates when computing trees. The large amount of computation required by these two projects was carried using Nextflow, a new computational framework that I have developed to improve computational efficiency and reproducibility of large-scale analyses like the one carried out in the context of these studies.<br>Uno de los principales y más recientes retos de la biología moderna es poder hacer frente a la creciente cantidad de datos biológicos procedentes de las tecnologías de secuenciación de alto rendimiento. Mantenerse al día con los crecientes volúmenes de datos experimentales es el único modo de poder interpretar estos datos y extraer conclusiones biológicos relevantes. Los análisis bioinformáticos comparativos a gran escala son una parte integral de este procedimiento. Al hacer bioinformática comparativa, los alineamientos múltiple de secuencias (MSA) son con mucho los modelos más utilizados, ya que proporcionan una visión única de la medida exacta de similitudes de secuencia y son, por tanto, fundamentales para inferir las relaciones genéticas y / o funcionales entre las especies evolutivamente relacionadas. Desafortunadamente, la conocida limitación de los métodos MSA para analizar grandes bases de datos, puede potencialmente comprometer todos los análisis realizados a continuación. En esta tesis expongo la relevancia actual de los métodos de alineamientos multiples de secuencia, muestro cómo su uso en datos masivos está dando lugar a serios problemas de estabilidad numérica y su impacto en la reconstrucción del árbol filogenético. Para este propósito, he desarrollado dos nuevos métodos, MEGA-café, un alineador de gran escala y Shootstrap una nueva medida de bootstrapping que incorpora la inestabilidad del MSA con las estimaciones de apoyo de rama en el cálculo de árboles filogéneticos. La gran cantidad de cálculo requerido por estos dos proyectos se realizó utilizando Nextflow, un nuevo marco computacional que se ha desarrollado para mejorar la eficiencia computacional y la reproducibilidad del análisis a gran escala como la que se lleva a cabo en el contexto de estos estudios.
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Marsolo, Keith Allen. "A workflow for the modeling and analysis of biomedical data." Columbus, Ohio : Ohio State University, 2007. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=osu1180309265.

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Frankhouser, David E. "Methylome Analysis: From Computation Workflow Development to Implementation in a Breast Cancer Prevention Trial." The Ohio State University, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=osu1512052081030923.

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Lamprecht, Anna-Lena, Tiziana Margaria, and Bernhard Steffen. "Bio-jETI : a framework for semantics-based service composition." Universität Potsdam, 2009. http://opus.kobv.de/ubp/volltexte/2010/4506/.

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Background: The development of bioinformatics databases, algorithms, and tools throughout the last years has lead to a highly distributedworld of bioinformatics services. Without adequatemanagement and development support, in silico researchers are hardly able to exploit the potential of building complex, specialized analysis processes from these services. The Semantic Web aims at thoroughly equipping individual data and services with machine-processable meta-information, while workflow systems support the construction of service compositions. However, even in this combination, in silico researchers currently would have to deal manually with the service interfaces, the adequacy of the semantic annotations, type incompatibilities, and the consistency of service compositions. Results: In this paper, we demonstrate by means of two examples how Semantic Web technology together with an adequate domain modelling frees in silico researchers from dealing with interfaces, types, and inconsistencies. In Bio-jETI, bioinformatics services can be graphically combined to complex services without worrying about details of their interfaces or about type mismatches of the composition. These issues are taken care of at the semantic level by Bio-jETI’s model checking and synthesis features. Whenever possible, they automatically resolve type mismatches in the considered service setting. Otherwise, they graphically indicate impossible/incorrect service combinations. In the latter case, the workflow developermay either modify his service composition using semantically similar services, or ask for help in developing the missing mediator that correctly bridges the detected type gap. Newly developed mediators should then be adequately annotated semantically, and added to the service library for later reuse in similar situations. Conclusion: We show the power of semantic annotations in an adequately modelled and semantically enabled domain setting. Using model checking and synthesis methods, users may orchestrate complex processes from a wealth of heterogeneous services without worrying about interfaces and (type) consistency. The success of this method strongly depends on a careful semantic annotation of the provided services and on its consequent exploitation for analysis, validation, and synthesis. We are convinced that these annotations will become standard, as they will become preconditions for the success and widespread use of (preferred) services in the Semantic Web
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Nagavaram, Ashish. "Cloud Based Dynamic Workflow with QOS For Mass Spectrometry Data Analysis." The Ohio State University, 2011. http://rave.ohiolink.edu/etdc/view?acc_num=osu1322681210.

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Socrates, Vimig. "Neuro-Integrative Connectivity: A Scientific Workflow-Based Neuroinformatics Platform For Brain Network Connectivity Studies Using EEG Data." Case Western Reserve University School of Graduate Studies / OhioLINK, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=case1561655750151063.

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Ba, Mouhamadou. "Composition guidée de services : application aux workflows d’analyse de données en bio-informatique." Thesis, Rennes, INSA, 2015. http://www.theses.fr/2015ISAR0024/document.

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Dans les domaines scientifiques, particulièrement en bioinformatique, des services élémentaires sont composés sous forme de workflows pour effectuer des expériences d’analyse de données complexes. À cause de l’hétérogénéité des ressources, la composition de services est une tâche difficile. Les utilisateurs, en composant des workflows, manquent d’assistance pour retrouver et interconnecter les services compatibles. Les solutions existantes utilisent des services spéciaux définis de manière manuelle pour gérer les conversions de formats de données entre les entrées et sorties des services dans les workflows. Cela est pénible pour un utilisateur final. Gérer les incompatibilités des services avec des convertisseurs manuels prend du temps et est lourd. Il existe des solutions automatisées pour faciliter la composition de workflows mais elles sont généralement limitées dans le guidage et l’adaptation des données entre services. La première contribution de cette thèse propose de détecter systématiquement la convertibilité des sorties vers les entrées des services. La détection de convertibilité repose sur un système de règles basé sur une abstraction des types d’entrée et sortie des services. L’abstraction de types permet de considérer la nature et la composition des données d’entrée et sortie. Les règles permettent la décomposition et la composition ainsi que la spécialisation et la généralisation de types. Elles permettent également de générer des convertisseurs de données à utiliser entre services dans les workflows. La deuxième contribution propose une approche interactive qui permet de guider des utilisateurs à composer des workflows en fournissant des suggestions de services et de liaisons compatibles basées sur la convertibilité de types d’entrée et sortie des services. L’approche est basée sur le modèle des Systèmes d’Information Logiques (LIS) qui permettent des requêtes et une navigation guidées et sûres sur des données représentées avec une logique uniforme. Avec notre approche, la composition de workflows est sûre et complète vis-à-vis de propriétés désirées. Les résultats et les expériences, effectués sur des services et des types de données en bioinformatique, montrent la pertinence de nos approches. Nos approches offrent des mécanismes adaptés pour gérer les incompatibilités de services dans les workflows, en prenant en compte la structure composite des données d’entrée et sortie. Elles permettent également de guider, étape par étape, des utilisateurs à définir des workflows bien formés à travers des suggestions pertinentes<br>In scientific domains, particularly in bioinformatics, elementary services are composed as workflows to perform complex data analysis experiments. Due to the heterogeneity of resources, the composition of services is a difficult task. Users, when composing workflows, lack assistance to find and interconnect compatible services. Existing solutions use special services manually defined to manage data format conversions between the inputs and outputs of services in workflows, it is difficult for an end user. Managing service incompatibilities with manual converters is time-consuming and heavy. There are automated solutions to facilitate composing workflows but they are generally limited in the guidance and the data adaptation between services they offer. The first contribution of this thesis proposes to systematically detect convertibility from outputs to inputs of services. Convertibility detection relies on a rule system based on an abstraction of input and output types of services. Type abstraction enables to consider the nature and the composition of input and output data. Rules enable decomposition and composition as well as specialization and generalization of types. They also enable to generate data converters to use between services in workflows. The second contribution proposes an interactive approach that enables to guide users to compose workflows by providing suggestions of compatible services and links based on convertibility of input and output types of services. The approach is based on the framework of Logical Information Systems (LIS) that enables safe and guided requests and navigation on data represented with a uniform logic. With our approach, composition of workflows is safe and complete w.r.t. desired properties. The results and experiences, conducted on bioinformatics services and datatypes, show the relevance of our approaches. Our approaches offer adapted mechanisms to manage service incompatibilities in workflows, by taking into account the composite structure of inputs and outputs data. They enable to guide, step by step, users to define well-formed workflows through relevant suggestions
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Book chapters on the topic "Bioinformatics workflow"

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El-Rami, Fadi E., and Aleksandra E. Sikora. "Bioinformatics Workflow for Gonococcal Proteomics." In Neisseria gonorrhoeae. Springer New York, 2019. http://dx.doi.org/10.1007/978-1-4939-9496-0_12.

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Guimarães, Milene Pereira, and Maria Cláudia Cavalcanti. "Enabling Annotation Provenance in Bioinformatics Workflow Applications." In Advances in Bioinformatics and Computational Biology. Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-15060-9_7.

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Meinl, Thorsten, Bernd Wiswedel, and Michael R. Berthold. "Workflow Tools for Managing Biological and Chemical Data." In Computational Approaches in Cheminformatics and Bioinformatics. John Wiley & Sons, Inc., 2011. http://dx.doi.org/10.1002/9781118131411.ch7.

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González Gayte, Isabel, Rocío Bautista Moreno, and M. Gonzalo Claros. "DEgenes Hunter - A Self-customised Gene Expression Analysis Workflow for Non-model Organisms." In Bioinformatics and Biomedical Engineering. Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-16480-9_31.

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Ozer, Hatice Gulcin, Doruk Bozdağ, Terry Camerlengo, et al. "A Comprehensive Analysis Workflow for Genome-Wide Screening Data from ChIP-Sequencing Experiments." In Bioinformatics and Computational Biology. Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-00727-9_30.

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Ahmed, Khaled S. "Medical Planning: Operating Theatre Design and Its Impact on Cost, Area and Workflow." In Bioinformatics and Biomedical Engineering. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-56148-6_28.

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Díaz, David, Sergio Gálvez, Juan Falgueras, et al. "Intuitive Bioinformatics for Genomics Applications: Omega-Brigid Workflow Framework." In Distributed Computing, Artificial Intelligence, Bioinformatics, Soft Computing, and Ambient Assisted Living. Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-02481-8_164.

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Ilnytskyy, Slava, and Andriy Bilichak. "Bioinformatics Analysis of Small RNA Transcriptomes: The Detailed Workflow." In Plant Epigenetics. Springer US, 2016. http://dx.doi.org/10.1007/978-1-4899-7708-3_16.

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Acuña, Ruben, Zoé Lacroix, and Jacques Chomilier. "A Workflow for the Prediction of the Effects of Residue Substitution on Protein Stability." In Pattern Recognition in Bioinformatics. Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-39159-0_23.

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Blazek, Pavel, Kamil Kuca, Jiri Krenek, and Ondrej Krejcar. "Increasing of Data Security and Workflow Optimization in Information and Management System for Laboratory." In Bioinformatics and Biomedical Engineering. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-56148-6_54.

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Conference papers on the topic "Bioinformatics workflow"

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Mondelli, Maria Luiza, Marcelo Monteiro Galheigo, V´ıvian Medeiros, et al. "Integrating ScientificWorkflows with Scientific Gateways: A Bioinformatics Experiment in the Brazilian National High-Performance Computing Network." In X Brazilian e-Science Workshop. Sociedade Brasileira de Computação - SBC, 2018. http://dx.doi.org/10.5753/bresci.2016.10010.

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Bioinformatics experiments are rapidly and constantly evolving due improvements in sequencing technologies. These experiments usually demand high performance computation and produce huge quantities of data. They also require different programs to be executed in a certain order, allowing the experiments to be modeled as workflows. However, users do not always have the infrastructure needed to perform these experiments. Our contribution is the integration of scientific workflow management systems and grid-enabled scientific gateways, providing the user with a transparent way to run these workflows in geographically distributed computing resources. The availability of the workflow through the gateway allows for a better usability of these experiments.&#x0D;
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Mondelli, Maria Luiza, Marcelo Monteiro Galheigo, Vivivan Medeiros, et al. "Integrating Scientific Workflows with Scientific Gateways: A Bioinformatics Experiment in the Brazilian National High-Performance Computing Network." In X Brazilian e-Science Workshop. Sociedade Brasileira de Computação - SBC, 2020. http://dx.doi.org/10.5753/bresci.2016.9124.

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Abstract:
Bioinformatics experiments are rapidly and constantly evolving due improvements in sequencing technologies. These experiments usually demand high performance computation and produce huge quantities of data. They also require different programs to be executed in a certain order, allowing the experiments to be modeled as workflows. However, users do not always have the infrastructure needed to perform these experiments. Our contribution is the integration of scientific workflow management systems and grid-enabled scientific gateways, providing the user with a transparent way to run these workflows in geographically distributed computing resources. The availability of the workflow through the gateway allows for a better usability of these experiments.
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Yeung, Ka Yee, Ling-Hong Hung, and Wes Lloyd. "Using BioDepot-workflow-Builder to Create and Execute Reproducible Bioinformatics Workflows." In BCB '18: 9th ACM International Conference on Bioinformatics, Computational Biology and Health Informatics. ACM, 2018. http://dx.doi.org/10.1145/3233547.3233665.

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Larsonneur, Elise, Jonathan Mercier, Nicolas Wiart, Edith Le Floch, Olivier Delhomme, and Vincent Meyer. "Evaluating Workflow Management Systems: A Bioinformatics Use Case." In 2018 IEEE International Conference on Bioinformatics and Biomedicine (BIBM). IEEE, 2018. http://dx.doi.org/10.1109/bibm.2018.8621141.

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Zhang, Lu, Yunsheng Wang, Pengfei Xuan, et al. "Sesame: A new bioinformatics semantic workflow design system." In 2013 IEEE International Conference on Bioinformatics and Biomedicine (BIBM). IEEE, 2013. http://dx.doi.org/10.1109/bibm.2013.6732546.

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Kanterakis, Alexandros, Galateia Iatraki, Konstantina Pityanou, et al. "Towards Reproducible Bioinformatics: The OpenBio-C Scientific Workflow Environment." In 2019 IEEE 19th International Conference on Bioinformatics and Bioengineering (BIBE). IEEE, 2019. http://dx.doi.org/10.1109/bibe.2019.00047.

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Han, Youngmahn. "Bioworks: A Workflow System for Automation of Bioinformatics Analysis Processes." In 2011 International Conference on Ubiquitious Computing and Multimedia Applications (UCMA). IEEE, 2011. http://dx.doi.org/10.1109/ucma.2011.25.

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Xu, Qing-Wei, and Yu Huang. "BiosFlow - A bioinformatics workflow platform based on semantic web technology." In 2009 International Conference on Future BioMedical Information Engineering (FBIE). IEEE, 2009. http://dx.doi.org/10.1109/fbie.2009.5405845.

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Xiao, X., M. Mahoui, Z. Miled, and B. Choudhury. "The Automation of SIBIOS Workflow Composition." In Sixth IEEE Symposium on BioInformatics and BioEngineering (BIBE'06). IEEE, 2006. http://dx.doi.org/10.1109/bibe.2006.253294.

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Welivita, Anuradha, Indika Perera, and Dulani Meedeniya. "An interactive workflow generator to support bioinformatics analysis through GPU acceleration." In 2017 IEEE International Conference on Bioinformatics and Biomedicine (BIBM). IEEE, 2017. http://dx.doi.org/10.1109/bibm.2017.8217691.

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