Search Results - "Vlassis, Nikos"

Fast reconstruction of compact context-specific metabolic network models by Vlassis, Nikos, Pacheco, Maria Pires, Sauter, Thomas

“…Systemic approaches to the study of a biological cell or tissue rely increasingly on the use of context-specific metabolic network models. The reconstruction…”
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VizBin - an application for reference-independent visualization and human-augmented binning of metagenomic data by Laczny, Cedric C, Sternal, Tomasz, Plugaru, Valentin, Gawron, Piotr, Atashpendar, Arash, Margossian, Houry Hera, Coronado, Sergio, der Maaten, Laurens van, Vlassis, Nikos, Wilmes, Paul

“…Metagenomics is limited in its ability to link distinct microbial populations to genetic potential due to a current lack of representative isolate genome…”
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The Role of Metabolomics in the Study of Cancer Biomarkers and in the Development of Diagnostic Tools by Trezzi, Jean-Pierre, Vlassis, Nikos, Hiller, Karsten

“…This chapter introduces the emerging field of metabolomics and its application in the context of cancer biomarker research. Taking advantage of modern…”
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Community-integrated omics links dominance of a microbial generalist to fine-tuned resource usage by Muller, Emilie E. L., Pinel, Nicolás, Laczny, Cédric C., Hoopmann, Michael R., Narayanasamy, Shaman, Lebrun, Laura A., Roume, Hugo, Lin, Jake, May, Patrick, Hicks, Nathan D., Heintz-Buschart, Anna, Wampach, Linda, Liu, Cindy M., Price, Lance B., Gillece, John D., Guignard, Cédric, Schupp, James M., Vlassis, Nikos, Baliga, Nitin S., Moritz, Robert L., Keim, Paul S., Wilmes, Paul

“…Microbial communities are complex and dynamic systems that are primarily structured according to their members’ ecological niches. To investigate how niche…”
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Accelerated EM-based clustering of large data sets by Verbeek, Jakob J., Nunnink, Jan R. J., Vlassis, Nikos

“…Motivated by the poor performance (linear complexity) of the EM algorithm in clustering large data sets, and inspired by the successful accelerated versions of…”
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fastGapFill: efficient gap filling in metabolic networks by Thiele, Ines, Vlassis, Nikos, Fleming, Ronan M T

“…Genome-scale metabolic reconstructions summarize current knowledge about a target organism in a structured manner and as such highlight missing information…”
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FastMotif: spectral sequence motif discovery by Colombo, Nicoló, Vlassis, Nikos

“…Sequence discovery tools play a central role in several fields of computational biology. In the framework of Transcription Factor binding studies, most of the…”
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GenePEN: analysis of network activity alterations in complex diseases via the pairwise elastic net by Vlassis, Nikos, Glaab, Enrico

“…Complex diseases are often characterized by coordinated expression alterations of genes and proteins which are grouped together in a molecular network…”
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The global k-means clustering algorithm by Likas, Aristidis, Vlassis, Nikos, J. Verbeek, Jakob

“…We present the global k-means algorithm which is an incremental approach to clustering that dynamically adds one cluster center at a time through a…”
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Perseus: Randomized Point-based Value Iteration for POMDPs by Spaan, M. T.J., Vlassis, N.

“…Partially observable Markov decision processes (POMDPs) form an attractive and principled framework for agent planning under uncertainty. Point-based…”
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Optimal and Approximate Q-value Functions for Decentralized POMDPs by Oliehoek, F. A., Spaan, M. T. J., Vlassis, N.

“…Decision-theoretic planning is a popular approach to sequential decision making problems, because it treats uncertainty in sensing and acting in a principled…”
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Alignment-free Visualization of Metagenomic Data by Nonlinear Dimension Reduction by Laczny, Cedric C., Pinel, Nicolás, Vlassis, Nikos, Wilmes, Paul

“…The visualization of metagenomic data, especially without prior taxonomic identification of reconstructed genomic fragments, is a challenging problem in…”
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Polytopic uncertainty for linear systems: New and old complexity results by Vlassis, Nikos, Jungers, Raphaël

“…We survey the problem of deciding the stability or stabilizability of uncertain linear systems whose region of uncertainty is a polytope. This natural setting…”
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FAST$\mathrm{G}$AP$\mathrm{F}$ILL: efficient gap filling in metabolic networks by Thiele, Ines, Vlassis, Nikos, Fleming, Ronan T.

“…Genome-scale metabolic reconstructions summarize current knowledge about a target organism in a structured manner and as such highlight missing information…”
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Condensing the omics fog of microbial communities by Muller, Emilie E.L, Glaab, Enrico, May, Patrick, Vlassis, Nikos, Wilmes, Paul

“…Highlights • Systematic omic measurements will allow the inference of causal relationships. • A discovery-driven planning approach is required for their…”
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Learning model-free robot control by a Monte Carlo EM algorithm by Vlassis, Nikos, Toussaint, Marc, Kontes, Georgios, Piperidis, Savas

“…We address the problem of learning robot control by model-free reinforcement learning (RL). We adopt the probabilistic model for model-free RL of Vlassis and…”
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Fast Reconstruction of Compact Context-Specific Metabolic Network Models: e1003424 by Vlassis, Nikos, Pacheco, Maria Pires, Sauter, Thomas

“…Systemic approaches to the study of a biological cell or tissue rely increasingly on the use of context-specific metabolic network models. The reconstruction…”
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Conditions for duality between fluxes and concentrations in biochemical networks by Fleming, Ronan M.T., Vlassis, Nikos, Thiele, Ines, Saunders, Michael A.

“…Mathematical and computational modelling of biochemical networks is often done in terms of either the concentrations of molecular species or the fluxes of…”
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fast G ap F ill : efficient gap filling in metabolic networks by Thiele, Ines, Vlassis, Nikos, Fleming, Ronan M. T.

“…Motivation: Genome-scale metabolic reconstructions summarize current knowledge about a target organism in a structured manner and as such highlight missing…”
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A Spatially Constrained Generative Model and an EM Algorithm for Image Segmentation by Diplaros, A., Vlassis, N., Gevers, T.

“…In this paper, we present a novel spatially constrained generative model and an expectation-maximization (EM) algorithm for model-based image segmentation. The…”
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