{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,5,19]],"date-time":"2025-05-19T18:22:05Z","timestamp":1747678925584},"reference-count":7,"publisher":"Oxford University Press (OUP)","issue":"8","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2015,4,15]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>Motivation: In bioinformatic applications, computationally demanding algorithms are often parallelized to speed up computation. Nevertheless, setting up computational environments for distributed computation is often tedious. Aim of this project were the lightweight ad hoc set up and fault-tolerant computation requiring only a Java runtime, no administrator rights, while utilizing all CPU cores most effectively.<\/jats:p>\n               <jats:p>Results: The Sputnik framework provides ad hoc distributed computation on the Java Virtual Machine which uses all supplied CPU cores fully. It provides a graphical user interface for deployment setup and a web user interface displaying the current status of current computation jobs. Neither a permanent setup nor administrator privileges are required. We demonstrate the utility of our approach on feature selection of microarray data.<\/jats:p>\n               <jats:p>Availability and implementation: The Sputnik framework is available on Github http:\/\/github.com\/sysbio-bioinf\/sputnik under the Eclipse Public License.<\/jats:p>\n               <jats:p>Contact: hkestler@fli-leibniz.de or hans.kestler@uni-ulm.de<\/jats:p>\n               <jats:p>Supplementary information: \u00a0Supplementary data are available at Bioinformatics online.<\/jats:p>","DOI":"10.1093\/bioinformatics\/btu818","type":"journal-article","created":{"date-parts":[[2014,12,14]],"date-time":"2014-12-14T01:33:54Z","timestamp":1418520834000},"page":"1298-1301","source":"Crossref","is-referenced-by-count":8,"title":["Sputnik: <i>ad hoc<\/i> distributed computation"],"prefix":"10.1093","volume":"31","author":[{"given":"Gunnar","family":"V\u00f6lkel","sequence":"first","affiliation":[{"name":"1 Core Unit Medical Systems Biology, 2Theoretical Computer Science, Ulm University, D-89069 Ulm, Germany and 3Leibniz Institute for Age Research-Fritz Lipmann Institute and FSU Jena, D-07745 Jena"},{"name":"1 Core Unit Medical Systems Biology, 2Theoretical Computer Science, Ulm University, D-89069 Ulm, Germany and 3Leibniz Institute for Age Research-Fritz Lipmann Institute and FSU Jena, D-07745 Jena"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ludwig","family":"Lausser","sequence":"additional","affiliation":[{"name":"1 Core Unit Medical Systems Biology, 2Theoretical Computer Science, Ulm University, D-89069 Ulm, Germany and 3Leibniz Institute for Age Research-Fritz Lipmann Institute and FSU Jena, D-07745 Jena"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Florian","family":"Schmid","sequence":"additional","affiliation":[{"name":"1 Core Unit Medical Systems Biology, 2Theoretical Computer Science, Ulm University, D-89069 Ulm, Germany and 3Leibniz Institute for Age Research-Fritz Lipmann Institute and FSU Jena, D-07745 Jena"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Johann M.","family":"Kraus","sequence":"additional","affiliation":[{"name":"1 Core Unit Medical Systems Biology, 2Theoretical Computer Science, Ulm University, D-89069 Ulm, Germany and 3Leibniz Institute for Age Research-Fritz Lipmann Institute and FSU Jena, D-07745 Jena"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hans A.","family":"Kestler","sequence":"additional","affiliation":[{"name":"1 Core Unit Medical Systems Biology, 2Theoretical Computer Science, Ulm University, D-89069 Ulm, Germany and 3Leibniz Institute for Age Research-Fritz Lipmann Institute and FSU Jena, D-07745 Jena"},{"name":"1 Core Unit Medical Systems Biology, 2Theoretical Computer Science, Ulm University, D-89069 Ulm, Germany and 3Leibniz Institute for Age Research-Fritz Lipmann Institute and FSU Jena, D-07745 Jena"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"286","published-online":{"date-parts":[[2014,12,12]]},"reference":[{"key":"2023051309020341900_btu818-B1","doi-asserted-by":"crossref","first-page":"41","DOI":"10.1038\/ng765","article-title":"MLL translocations specify a distinct gene expression profile that distinguishes a unique leukemia","volume":"30","author":"Armstrong","year":"2002","journal-title":"Nat. Genet."},{"key":"2023051309020341900_btu818-B2","doi-asserted-by":"crossref","first-page":"531","DOI":"10.1126\/science.286.5439.531","article-title":"Molecular classification of cancer: class discovery and class prediction by gene expression monitoring","volume":"286","author":"Golub","year":"1999","journal-title":"Science"},{"key":"2023051309020341900_btu818-B3","first-page":"359","article-title":"Correlation-based feature selection for discrete and numeric class machine learning","volume-title":"Proceedings ICML","author":"Hall","year":"2000"},{"key":"2023051309020341900_btu818-B4","doi-asserted-by":"crossref","first-page":"148","DOI":"10.1186\/1471-2105-6-148","article-title":"Feature selection and classification for microarray data analysis: Evolutionary methods for identifying predictive genes","volume":"6","author":"Jirapech-Umpai","year":"2005","journal-title":"BMC Bioinformatics"},{"key":"2023051309020341900_btu818-B5","doi-asserted-by":"crossref","first-page":"81","DOI":"10.1007\/s00180-012-0379-0","article-title":"Identifying predictive hubs to condense the training set of k-nearest neighbour classifiers","volume":"29","author":"Lausser","year":"2014","journal-title":"Comput. Stat."},{"key":"2023051309020341900_btu818-B6","doi-asserted-by":"crossref","first-page":"68","DOI":"10.1038\/nm0102-68","article-title":"Diffuse large B-cell lymphoma outcome prediction by gene-expression profiling and supervised machine learning","volume":"8","author":"Shipp","year":"2002","journal-title":"Nat. Med."},{"key":"2023051309020341900_btu818-B7","doi-asserted-by":"crossref","first-page":"11462","DOI":"10.1073\/pnas.201162998","article-title":"Predicting the clinical status of human breast cancer by using gene expression profiles","volume":"98","author":"West","year":"2001","journal-title":"PNAS"}],"container-title":["Bioinformatics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article-pdf\/31\/8\/1298\/50306054\/bioinformatics_31_8_1298.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article-pdf\/31\/8\/1298\/50306054\/bioinformatics_31_8_1298.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,5,13]],"date-time":"2023-05-13T09:02:23Z","timestamp":1683968543000},"score":1,"resource":{"primary":{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article\/31\/8\/1298\/213056"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2014,12,12]]},"references-count":7,"journal-issue":{"issue":"8","published-print":{"date-parts":[[2015,4,15]]}},"URL":"https:\/\/doi.org\/10.1093\/bioinformatics\/btu818","relation":{},"ISSN":["1367-4811","1367-4803"],"issn-type":[{"value":"1367-4811","type":"electronic"},{"value":"1367-4803","type":"print"}],"subject":[],"published-other":{"date-parts":[[2015,4,15]]},"published":{"date-parts":[[2014,12,12]]}}}