about
Clustering cancer gene expression data: a comparative studyFast Bayesian Inference of Copy Number Variants using Hidden Markov Models with Wavelet CompressionpGQL: A probabilistic graphical query language for gene expression time coursesPartially-supervised protein subclass discovery with simultaneous annotation of functional residues.Constrained mixture estimation for analysis and robust classification of clinical time series.PyMix--the python mixture package--a tool for clustering of heterogeneous biological data.Using hidden Markov models to analyze gene expression time course data.Identifying protein complexes directly from high-throughput TAP data with Markov random fields.Semi-supervised learning for the identification of syn-expressed genes from fused microarray and in situ image data.Decoding non-unique oligonucleotide hybridization experiments of targets related by a phylogenetic tree.Gene expression trees in lymphoid developmentThe discriminant power of RNA features for pre-miRNA recognitionExploiting prior knowledge and gene distances in the analysis of tumor expression profiles with extended Hidden Markov Models.Fast MCMC sampling for hidden Markov Models to determine copy number variations.Turtle: identifying frequent k-mers with cache-efficient algorithms.Single cell genome analysis of an uncultured heterotrophic stramenopile.Automatic learning of pre-miRNAs from different species.Indel-tolerant read mapping with trinucleotide frequencies using cache-oblivious kd-trees.Selecting oligonucleotide probes for whole-genome tiling arrays with a cross-hybridization potential.Efficient algorithms for the computational design of optimal tiling arrays.Classifying short gene expression time-courses with Bayesian estimation of piecewise constant functions.Inferring differentiation pathways from gene expression.CLEVER: clique-enumerating variant finder.ProClust: improved clustering of protein sequences with an extended graph-based approach.SLIQ: simple linear inequalities for efficient contig scaffolding.The Graphical Query Language: a tool for analysis of gene expression time-courses.Context-specific independence mixture modeling for positional weight matrices.Selecting signature oligonucleotides to identify organisms using DNA arrays.Robust inference of groups in gene expression time-courses using mixtures of HMMs.Optimal robust non-unique probe selection using Integer Linear Programming.New, improved, and practical k-stem sequence similarity measures for probe design.Analyzing gene expression time-courses.Strongly Connected Components can Predict Protein StructureSpeeding Up Bayesian HMM by the Four Russians MethodSemi-supervised Clustering of Yeast Gene Expression DataComparative study on normalization procedures for cluster analysis of gene expression datasetsRanking and selecting clustering algorithms using a meta-learning approachInteger linear programming approaches for non-unique probe selectionJoint Analysis of In-situ Hybridization and Gene Expression DataAn Indicator for the Number of Clusters: Using a Linear Map to Simplex Structure
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description
hulumtues
@sq
researcher
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ricercatore
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wetenschapper
@nl
հետազոտող
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name
Alexander Schliep
@ast
Alexander Schliep
@en
Alexander Schliep
@es
Alexander Schliep
@nl
Alexander Schliep
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type
label
Alexander Schliep
@ast
Alexander Schliep
@en
Alexander Schliep
@es
Alexander Schliep
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Alexander Schliep
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prefLabel
Alexander Schliep
@ast
Alexander Schliep
@en
Alexander Schliep
@es
Alexander Schliep
@nl
Alexander Schliep
@sl
P108
P214
P106
P1153
6506369556
P1960
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P21
P214
P2456
P31
P496
0000-0002-3555-3188
P735
P7859
lccn-no2010056169