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Graded Lie algebras of maximal class, III

Journal of algebra, 2005-02, Vol.284 (2), p.435-461

Jurman, G.

2005

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An accelerated procedure for recursive feature ranking on microarray data

Neural networks, 2003-06, Vol.16 (5), p.641-648

2003

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Combining feature selection and DTW for time-varying functional genomics

IEEE transactions on signal processing, 2006-06, Vol.54 (6), p.2436-2443

2006

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A family of simple Lie algebras in characteristic two

Journal of algebra, 2004-01, Vol.271 (2), p.454-481

Jurman, G.

2004

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Functional analysis of multiple genomic signatures demonstrates that classification algorithms choose phenotype-related genes

The pharmacogenomics journal, 2010-08, Vol.10 (4), p.310-323

2010

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Targeted proteomics and the presence of carotid plaques in subjects at low cardiovascular disease risk

Atherosclerosis, 2023-08, Vol.379, p.S2-S3

2023

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Differential diagnosis of systemic lupus erythematosus and Sjögren's syndrome using machine learning and multi-omics data

Computers in biology and medicine, 2023-01, Vol.152, p.106373, Article 106373

2023

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Semisupervised learning for molecular profiling

IEEE/ACM transactions on computational biology and bioinformatics, 2005-04, Vol.2 (2), p.110-118

2005

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Promoter-level expression clustering identifies time development of transcriptional regulatory cascades initiated by ErbB receptors in breast cancer cells

Scientific reports, 2015-07, Vol.5 (1), p.11999-11999, Article 11999

2015

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Entropy-based gene ranking without selection bias for the predictive classification of microarray data

BMC bioinformatics, 2003-11, Vol.4 (1), p.54-54, Article 54

2003

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Quotients of maximal class of thin lie algebras. the case of characteristic two

Communications in algebra, 1999-01, Vol.27 (12), p.5749-5789

Jurman, G.

1999

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Supervised classification of combined copy number and gene expression data

Journal of integrative bioinformatics, 2007-12, Vol.4 (3), p.168-185

2007

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Machine learning methods for predictive proteomics

Briefings in bioinformatics, 2008-03, Vol.9 (2), p.119-128

2008

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Quotients of maximal class of thin lie algebras. the odd characteristic case

Communications in algebra, 1999-01, Vol.27 (12), p.5741-5748

1999

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Gene expression profiling identifies potential relevant genes in alveolar rhabdomyosarcoma pathogenesis and discriminates PAX3‐FKHR positive and negative tumors

International journal of cancer, 2006-06, Vol.118 (11), p.2772-2781

2006

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Graph metrics as summary statistics for Approximate Bayesian Computation with application to network model parameter estimation

Journal of complex networks, 2015-03, Vol.3 (1), p.52-83

2015

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Integrating gene expression profiling and clinical data

International journal of approximate reasoning, 2008, Vol.47 (1), p.58-69

2008

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Exact Bagging with k-Nearest Neighbour Classifiers

Lecture notes in computer science, 2004, p.72-81

2004

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Semisupervised Profiling of Gene Expressions and Clinical Data

Fuzzy Logic and Applications, 2006, p.284-289

2006

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Functional analysis of multiple genomic signatures demonstrates that classification algorithms choose phenotype-related genes: The MicroArray Quality Control II

Nature biotechnology, 2010, Vol.28 (OCT)

2010

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Machine Learning on Historic Air Photographs for Mapping Risk of Unexploded Bombs

Image Analysis and Processing – ICIAP 2005, 2005, p.735-742

2005

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Supervised classification of combined copy number and gene expression data

Journal of integrative bioinformatics, 2007-12, Vol.4 (3), p.168-185

2007

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Gene selection and classification by entropy-based recursive feature elimination

Proceedings of the International Joint Conference on Neural Networks, 2003, 2003, Vol.4, p.3077-3082 vol.4

2003

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Proteome Profiling without Selection Bias

19th IEEE Symposium on Computer-Based Medical Systems (CBMS'06), 2006, p.941-946

2006

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A Grid Environment for High-Throughput Proteomics

IEEE transactions on nanobioscience, 2007-06, Vol.6 (2), p.117-123

2007

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Graded Lie algebras of maximal class, III

An accelerated procedure for recursive feature ranking on microarray data

Combining feature selection and DTW for time-varying functional genomics

A family of simple Lie algebras in characteristic two

Functional analysis of multiple genomic signatures demonstrates that classification algorithms choose phenotype-related genes

Targeted proteomics and the presence of carotid plaques in subjects at low cardiovascular disease risk

Differential diagnosis of systemic lupus erythematosus and Sjögren's syndrome using machine learning and multi-omics data

Semisupervised learning for molecular profiling

Promoter-level expression clustering identifies time development of transcriptional regulatory cascades initiated by ErbB receptors in breast cancer cells

Entropy-based gene ranking without selection bias for the predictive classification of microarray data

Quotients of maximal class of thin lie algebras. the case of characteristic two

Supervised classification of combined copy number and gene expression data

Machine learning methods for predictive proteomics

Quotients of maximal class of thin lie algebras. the odd characteristic case

Gene expression profiling identifies potential relevant genes in alveolar rhabdomyosarcoma pathogenesis and discriminates PAX3‐FKHR positive and negative tumors

Graph metrics as summary statistics for Approximate Bayesian Computation with application to network model parameter estimation

Integrating gene expression profiling and clinical data

Exact Bagging with k-Nearest Neighbour Classifiers

Semisupervised Profiling of Gene Expressions and Clinical Data

Functional analysis of multiple genomic signatures demonstrates that classification algorithms choose phenotype-related genes: The MicroArray Quality Control II

Machine Learning on Historic Air Photographs for Mapping Risk of Unexploded Bombs

Supervised classification of combined copy number and gene expression data

Gene selection and classification by entropy-based recursive feature elimination

Proteome Profiling without Selection Bias

A Grid Environment for High-Throughput Proteomics

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