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检索条件"任意字段=6th International Conference on Bioinformatics Models, Methods and Algorithms, BIOINFORMATICS 2015"
237 条 记 录,以下是11-20 订阅
排序:
Does the Inclusion of Data Sampling Improve the Performance of Boosting algorithms on Imbalanced bioinformatics Data?  14
Does the Inclusion of Data Sampling Improve the Performance ...
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IEEE 14th international conference on Machine Learning and Applications ICMLA
作者: Fazelpour, Alireza Khoshgoftaar, Taghi M. Dittman, David J. Napolitano, Amri Florida Atlantic Univ Boca Raton FL 33431 USA
bioinformatics datasets contain many challenging characteristics, such as class imbalance, which adversely impacts the performance of supervised classification models built on these datasets. Techniques such as ensemb... 详细信息
来源: 评论
Backward Pattern Matching on Elastic Degenerate Strings  12
Backward Pattern Matching on Elastic Degenerate Strings
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14th international Joint conference on Biomedical Engineering Systems and Technologies (BIOSTEC) / 12th international conference on bioinformatics models, methods and algorithms (bioinformatics)
作者: Prochazka, Petr Cvacho, Ondrej Krcal, Lubos Holub, Jan Czech Tech Univ Fac Informat Technol Dep Theoret Comp Sci Thakurova 2700-9 Prague 6 Czech Republic
Recently, the concept of Elastic Degenerate Strings (EDS) was introduced as a way of representing a sequenced population of the same species. Several on-line Elastic Degenerate String Matching (EDSM) algorithms were p... 详细信息
来源: 评论
Choosing an Appropriate Ensemble Classifier for Balanced bioinformatics Data  16
Choosing an Appropriate Ensemble Classifier for Balanced Bio...
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IEEE 16th international conference on Information Reuse and Integration
作者: Fazelpour, Alireza Khsohgoftaar, Taghi M. Dittman, David J. Napolitano, Amri Florida Atlantic Univ Boca Raton FL 33431 USA
bioinformatics datasets contain a number of characteristics, such as noisy data and difficult to learn class boundaries, which make it challenge to build effective predictive models. One option for improving results i... 详细信息
来源: 评论
Functional site prediction selects correct protein models
Functional site prediction selects correct protein models
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6th international conference on bioinformatics, InCoB 2007
作者: Chelliah, Vijayalakshmi Taylor, William R. Division of Mathematical Biology National Institute for Medical Research The Ridgeway Mill Hill London NW7 1AA United Kingdom
Background: the prediction of protein structure can be facilitated by the use of constraints based on a knowledge of functional sites. Without this information it is still possible to predict which residues are likely... 详细信息
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Cancer Prediction using Clinical and Genomic Data Fusion: A Systematic Review  6
Cancer Prediction using Clinical and Genomic Data Fusion: A ...
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6th international conference on Cybernetics and Intelligent System, ICORIS 2024
作者: Julian, Kelvin Nugroho, Kuncahyo Setyo Nirwantono, Rudi Pardamean, Bens Computer Science Department BINUS Graduate Program Bina Nusantara University Jakarta Indonesia Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta Indonesia Biotechnology Department Faculty of Engineering Bina Nusantara University Jakarta Indonesia
this systematic review provides a comprehensive overview of the methods used to integrate genomic and clinical data in cancer prediction. the review includes 19 studies across various cancers, including breast, colore... 详细信息
来源: 评论
Finite difference methods, theory and applications: 6th international conference, FDM 2014 Lozenetz, Bulgaria, June 18-23, 2014 revised selected papers  6th
Finite difference methods, theory and applications: 6th inte...
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6th international conference on Finite Difference methods, FDM 2014
作者: Dimov, Ivan Faragó, István Vulkov, Lubin Institute of Information and Communication Technologies Bulgarian Academy of Sciences Sofia Bulgaria Institute of Mathematics and MTA-ELTE Numerical Analysis and Large Networks Research Group Eötvös Loránd University Budapest Hungary University of Rousse Rousse Bulgaria
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Selecting the appropriate ensemble learning approach for balanced bioinformatics data  28
Selecting the appropriate ensemble learning approach for bal...
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28th international Florida Artificial Intelligence Research Society conference, FLAIRS 2015
作者: Dittman, David J. Khoshgoftaar, Taghi M. Napolitano, Amri Florida Atlantic University United States
Ensemble learning (process of combining multiple models into a single decision) is an effective tool for improving the classification performance of inductive models. While ideal for domains like bioinformatics with m... 详细信息
来源: 评论
Aggregating Statistically Correlated Metabolic Pathways Into Groups to Improve Prediction Performance
Aggregating Statistically Correlated Metabolic Pathways Into...
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13th international conference on bioinformatics models, methods and algorithms (bioinformatics) held as part of 15th international Joint conference on Biomedical Engineering Systems and Technologies (BIOSTEC)
作者: Basher, Abdur Rahman M. A. Hallam, Steven J. Univ British Columbia Grad Program Bioinformat Vancouver BC V5Z 4S6 Canada Univ British Columbia Dept Microbiol & Immunol Vancouver BC V6T 1Z3 Canada
Metabolic pathway prediction from genomic sequence information is an essential step in determining the capacity of living things to transform matter and energy at different levels of biological organization. A detaile... 详细信息
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An Approximate Execution of Rule-Based Multi-level models
An Approximate Execution of Rule-Based Multi-level Models
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11th international conference on Computational methods in Systems Biology (CMSB)
作者: Helms, Tobias Luboschik, Martin Schumann, Heidrun Uhrmacher, Adelinde M. Univ Rostock Inst Comp Sci D-18059 Rostock Germany
In cell biology, models increasingly capture dynamics at different organizational levels. therefore, new modeling languages are developed, e. g., like ML-Rules, that allow a compact and concise description of these mo... 详细信息
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Sequential parallel LASSO models for eQTL analysis  15
Sequential parallel LASSO models for eQTL analysis
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6th ACM conference on bioinformatics, Computational Biology, and Health Informatics, BCB 2015
作者: He, Anhong Hall, Benika Wen, Jia Liang, Yingbin Shi, Xinghua Syracuse University 900 South Crouse Ave. SyracuseNY13244 United States University of North Carolina at Charlotte 9201 University City Blvd. CharlotteNC28223 United States
the availability of large-scale genomic and transcriptomic data on populations makes it necessary to perform computationally intensive expression quantitative trait locus (eQTL) analysis. Modeling in a sparse learning... 详细信息
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