about
Entropy-based gene ranking without selection bias for the predictive classification of microarray dataRepeatability of published microarray gene expression analysesA comparison of MCC and CEN error measures in multi-class predictionFunctional analysis of multiple genomic signatures demonstrates that classification algorithms choose phenotype-related genes.The MicroArray Quality Control (MAQC)-II study of common practices for the development and validation of microarray-based predictive models.An accelerated procedure for recursive feature ranking on microarray data.The concordance between RNA-seq and microarray data depends on chemical treatment and transcript abundanceTerminated Ramp-Support vector machines: a nonparametric data dependent kernel.DTW-MIC Coexpression Networks from Time-Course Data.A machine learning pipeline for quantitative phenotype prediction from genotype data.RegnANN: Reverse Engineering Gene Networks using Artificial Neural Networks.Effect of size and heterogeneity of samples on biomarker discovery: synthetic and real data assessment.Algebraic comparison of partial lists in bioinformaticsA promoter-level mammalian expression atlasClinical value of prognosis gene expression signatures in colorectal cancer: a systematic review.Minerva and minepy: a C engine for the MINE suite and its R, Python and MATLAB wrappers.A combinatorial model of malware diffusion via bluetooth connections.Algebraic stability indicators for ranked lists in molecular profiling.Stability indicators in network reconstruction.A null model for Pearson coexpression networksPromoter-level expression clustering identifies time development of transcriptional regulatory cascades initiated by ErbB receptors in breast cancer cells.Machine learning methods for predictive proteomics.A grid environment for high-throughput proteomics.Metric projection for dynamic multiplex networks.Fast randomization of large genomic datasets while preserving alteration counts.Semisupervised learning for molecular profiling.Strategies for containing an influenza pandemic: the case of ItalyEvaluating reproducibility of AI algorithms in digital pathology with DAPPERA Machine Learning Pipeline for Discriminant Pathways IdentificationIntegrating gene expression profiling and clinical dataCombining feature selection and DTW for time-varying functional genomicsGene expression profiling identifies potential relevant genes in alveolar rhabdomyosarcoma pathogenesis and discriminatesPAX3-FKHR positive and negative tumorsProteome Profiling without Selection BiasSemisupervised Profiling of Gene Expressions and Clinical DataMachine Learning on Historic Air Photographs for Mapping Risk of Unexploded BombsEfficient randomization of biological networks while preserving functional characterization of individual nodesDifferential Network Analysis and Graph Classification: A Glocal ApproachCIDER: a pipeline for detecting waves of coordinated transcriptional regulation in gene expression time-course dataGraph metrics as summary statistics for Approximate Bayesian Computation with application to network model parameter estimationThe HIM glocal metric and kernel for network comparison and classification
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description
researcher
@en
wetenschapper
@nl
հետազոտող
@hy
name
Giuseppe Jurman
@ast
Giuseppe Jurman
@en
Giuseppe Jurman
@es
Giuseppe Jurman
@nl
Giuseppe Jurman
@sl
type
label
Giuseppe Jurman
@ast
Giuseppe Jurman
@en
Giuseppe Jurman
@es
Giuseppe Jurman
@nl
Giuseppe Jurman
@sl
prefLabel
Giuseppe Jurman
@ast
Giuseppe Jurman
@en
Giuseppe Jurman
@es
Giuseppe Jurman
@nl
Giuseppe Jurman
@sl
P106
P1153
6602367398
P21
P2456
P2798
P31
P496
0000-0002-2705-5728