Manos A. Papadakis

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Our current understanding of how natural genetic variation affects gene expression beyond well-annotated coding genes is still limited. The use of deep sequencing technologies for the study of expression quantitative trait loci (eQTLs) has the potential to close this gap. Here, we generated the first recombinant strain library for fission yeast and(More)
We propose and analyze acceleration schemes for hard thresholding methods with applications to sparse approximation in linear inverse systems. Our acceleration schemes fuse combinatorial, sparse projection algorithms with convex optimization algebra to provide computationally efficient and robust sparse recovery methods. We compare and contrast the(More)
We analyze localized textural consistencies in high-resolution X-ray CT scans of coronary arteries to identify the appearance of diagnostically relevant changes in tissue. For the efficient and accurate processing of CT volume data, we use fast wavelet algorithms associated with three-dimensional isotropic multiresolution wavelets that implement a(More)
We construct examples of non-separable Isotropic Multiresolution Analyses (IMRA) for L 2 (R d). We develop a wave equation based poststack depth migration scheme using the frames arising from IMRA. If we discretise the signal at only one resolution level, then the method reduces to a so-called explicit scheme (see for example [8, 10]). The multiscale(More)
The main goal of this paper is to introduce formally the concept of texture segmentation/identification in three dimensional images. A major problem in texture texture segmentation/identification is the lack of robustness to both translations and rotations. This problem is more difficult to overcome in 3D-images, such as those generated by modalities such(More)
Recent advances in high-resolution fluorescence microscopy have enabled the systematic study of morphological changes in large populations of cells induced by chemical and genetic perturbations, facilitating the discovery of signaling pathways underlying diseases and the development of new pharmacological treatments. In these studies, though, due to the(More)
The two-parameter family of Hermite Distributed Approximating Func-tionals (HDAFs) is shown to possess all properties that are essential requirements in filter design. When properly scaled, HDAFs provide an arbitrarily sharp high-frequency cutoff while retaining their smoothness. More precisely , bounds on the Fourier transform of the HDAF integral kernel(More)
Accurate segmentation of 3D vessel-like structures is a major challenge in medical imaging. In this paper, we introduce a novel approach for the detection of 3D tubular structures that is particularly suited to capture the geometry of vessel-like networks, such as dendritic trees and vascular systems. Even though our approach relies on a system of isotropic(More)
Automated identification of the primary components of a neuron and extraction of its sub-cellular features are essential steps in many quantitative studies of neuronal networks. The focus of this paper is the development of an algorithm for the automated detection of the location and morphology of somas in confocal images of neuronal network cultures. This(More)