Clustering with shallow trees

We propose a new method for hierarchical clustering based on the optimisation of a cost function over trees of limited depth, and we derive a message--passing method that allows to solve it efficiently. The method and algorithm can be interpreted as a natural interpolation between two well-known approaches, namely single linkage and the recently presented Affinity Propagation. We analyze with this general scheme three biological/medical structured datasets (human population based on genetic information, proteins based on sequences and verbal autopsies) and show that the interpolation technique provides new insight.Comment: 11 pages, 7 figure

Algorithms for Maneuvering Spacecraft Around Small Bodies

A document describes mathematical derivations and applications of autonomous guidance algorithms for maneuvering spacecraft in the vicinities of small astronomical bodies like comets or asteroids. These algorithms compute fuel- or energy-optimal trajectories for typical maneuvers by solving the associated optimal-control problems with relevant control and state constraints. In the derivations, these problems are converted from their original continuous (infinite-dimensional) forms to finite-dimensional forms through (1) discretization of the time axis and (2) spectral discretization of control inputs via a finite number of Chebyshev basis functions. In these doubly discretized problems, the Chebyshev coefficients are the variables. These problems are, variously, either convex programming problems or programming problems that can be convexified. The resulting discrete problems are convex parameter-optimization problems; this is desirable because one can take advantage of very efficient and robust algorithms that have been developed previously and are well established for solving such problems. These algorithms are fast, do not require initial guesses, and always converge to global optima. Following the derivations, the algorithms are demonstrated by applying them to numerical examples of flyby, descent-to-hover, and ascent-from-hover maneuvers

Finding undetected protein associations in cell signaling by belief propagation

External information propagates in the cell mainly through signaling cascades and transcriptional activation, allowing it to react to a wide spectrum of environmental changes. High throughput experiments identify numerous molecular components of such cascades that may, however, interact through unknown partners. Some of them may be detected using data coming from the integration of a protein-protein interaction network and mRNA expression profiles. This inference problem can be mapped onto the problem of finding appropriate optimal connected subgraphs of a network defined by these datasets. The optimization procedure turns out to be computationally intractable in general. Here we present a new distributed algorithm for this task, inspired from statistical physics, and apply this scheme to alpha factor and drug perturbations data in yeast. We identify the role of the COS8 protein, a member of a gene family of previously unknown function, and validate the results by genetic experiments. The algorithm we present is specially suited for very large datasets, can run in parallel, and can be adapted to other problems in systems biology. On renowned benchmarks it outperforms other algorithms in the field.Comment: 6 pages, 3 figures, 1 table, Supporting Informatio

Results of the French Evalda-Media evaluation campaign for literal understanding

International audienceThe aim of the MEDIA-EVALDA project is to evaluate the understanding capabilities of dialog systems. This paper presents the MEDIA protocol for speech understanding evaluation and describes the results of the June 2005 literal evaluation campaign. Five systems, both symbolic or corpus-based participated to the evaluation which is based on a common semantic representation. Different scorings have been performed on the system results. The understanding error rate, for the Full scoring is, depending on the systems, from 29% to 41.3%. A diagnosis analysis of these results is proposed

Reverse Engineering Gene Networks with ANN: Variability in Network Inference Algorithms

Motivation :Reconstructing the topology of a gene regulatory network is one of the key tasks in systems biology. Despite of the wide variety of proposed methods, very little work has been dedicated to the assessment of their stability properties. Here we present a methodical comparison of the performance of a novel method (RegnANN) for gene network inference based on multilayer perceptrons with three reference algorithms (ARACNE, CLR, KELLER), focussing our analysis on the prediction variability induced by both the network intrinsic structure and the available data. Results: The extensive evaluation on both synthetic data and a selection of gene modules of "Escherichia coli" indicates that all the algorithms suffer of instability and variability issues with regards to the reconstruction of the topology of the network. This instability makes objectively very hard the task of establishing which method performs best. Nevertheless, RegnANN shows MCC scores that compare very favorably with all the other inference methods tested. Availability: The software for the RegnANN inference algorithm is distributed under GPL3 and it is available at the corresponding author home page (http://mpba.fbk.eu/grimaldi/regnann-supmat

Beyond inverse Ising model: structure of the analytical solution for a class of inverse problems

I consider the problem of deriving couplings of a statistical model from measured correlations, a task which generalizes the well-known inverse Ising problem. After reminding that such problem can be mapped on the one of expressing the entropy of a system as a function of its corresponding observables, I show the conditions under which this can be done without resorting to iterative algorithms. I find that inverse problems are local (the inverse Fisher information is sparse) whenever the corresponding models have a factorized form, and the entropy can be split in a sum of small cluster contributions. I illustrate these ideas through two examples (the Ising model on a tree and the one-dimensional periodic chain with arbitrary order interaction) and support the results with numerical simulations. The extension of these methods to more general scenarios is finally discussed.Comment: 15 pages, 6 figure

Inference algorithms for gene networks: a statistical mechanics analysis

The inference of gene regulatory networks from high throughput gene expression data is one of the major challenges in systems biology. This paper aims at analysing and comparing two different algorithmic approaches. The first approach uses pairwise correlations between regulated and regulating genes; the second one uses message-passing techniques for inferring activating and inhibiting regulatory interactions. The performance of these two algorithms can be analysed theoretically on well-defined test sets, using tools from the statistical physics of disordered systems like the replica method. We find that the second algorithm outperforms the first one since it takes into account collective effects of multiple regulators

First astronomical unit scale image of the GW Ori triple. Direct detection of a new stellar companion

Young and close multiple systems are unique laboratories to probe the initial dynamical interactions between forming stellar systems and their dust and gas environment. Their study is a key building block to understanding the high frequency of main-sequence multiple systems. However, the number of detected spectroscopic young multiple systems that allow dynamical studies is limited. GW Orionis is one such system. It is one of the brightest young T Tauri stars and is surrounded by a massive disk. Our goal is to probe the GW Orionis multiplicity at angular scales at which we can spatially resolve the orbit. We used the IOTA/IONIC3 interferometer to probe the environment of GW Orionis with an astronomical unit resolution in 2003, 2004, and 2005. By measuring squared visibilities and closure phases with a good UV coverage we carry out the first image reconstruction of GW Ori from infrared long-baseline interferometry. We obtain the first infrared image of a T Tauri multiple system with astronomical unit resolution. We show that GW Orionis is a triple system, resolve for the first time the previously known inner pair (separation $\rho\sim$1.4 AU) and reveal a new more distant component (GW Ori C) with a projected separation of $\sim$8 AU with direct evidence of motion. Furthermore, the nearly equal (2:1) H-band flux ratio of the inner components suggests that either GW Ori B is undergoing a preferential accretion event that increases its disk luminosity or that the estimate of the masses has to be revisited in favour of a more equal mass-ratio system that is seen at lower inclination. Accretion disk models of GW Ori will need to be completely reconsidered because of this outer companion C and the unexpected brightness of companion B.Comment: 5 pages, 9 figures, accepted Astronomy and Astrophysics Letters. 201

Cancer targeting with biomolecules: a comparative study of photodynamic therapy efficacy using antibody or lectin conjugated phthalocyanine-PEG gold nanoparticles

The functionalisation of therapeutic nanoparticle constructs with cancer-specific biomolecules can enable selective tumour accumulation and targeted treatment. Water soluble gold nanoparticles (ca. 4 nm) stabilised by a mixed monolayer of a hydrophobic zinc phthalocyanine photosensitiser (C11Pc) and hydrophilic polyethylene glycol (PEG) have been prepared. The C11Pc-PEG gold nanoparticle constructs were further functionalised with jacalin, a lectin specific for the cancer-associated Thomsen–Friedenreich (T) carbohydrate antigen, or with monoclonal antibodies specific for the human epidermal growth factor receptor-2 (HER-2). The two biofunctionalised nanoparticle conjugates produced similar levels of singlet oxygen upon irradiation at 633 nm. Importantly, both nanoparticle conjugates demonstrated extensive, yet comparable, phototoxicity in HT-29 colorectal adenocarcinoma cells (80–90%) and in SK-BR-3 breast adenocarcinoma cells (>99%). Non-conjugated C11Pc-PEG gold nanoparticles were only minimally phototoxic. Lysosomal colocalisation studies performed with the HT-29 colon cancer cells and the SK-BR-3 breast cancer cells revealed that both nanoparticle conjugates were partially localised within acidic organelles, which is typical of receptor-mediated endocytosis. The similarity of the targeted PDT efficacy of the two biofunctionalised C11Pc-PEG gold nanoparticles is discussed with respect to targeting ligand binding affinity and cell surface antigen density as key determinants of targeting efficiency. This study highlights how targeting small cell-surface molecules, such as the T antigen, can mediate a selective photodynamic treatment response which is similar to that achieved when targeting overexpressed protein receptors, such as HER-2. The high prevalence of the T antigen present on the cellular surface of primary tumours emphasises the broad potential applications for lectin-targeted therapies

Evaluation of a novel antibody to define histone 3.3 G34R mutant brain tumours

Missense somatic mutations affecting histone H3.1 and H3.3 proteins are now accepted as the hallmark of paediatric diffuse intrinsic pontine gliomas (DIPG), non-brain stem paediatric high grade gliomas (pHGG) as well as a subset of adult glioblastoma multiforme (GBM). Different mutations give rise to one of three amino acid substitutions at two critical positions within the histone tails, K27M, G34R/V. Several studies have highlighted gene expression and epigenetic changes associated with histone H3 mutations; however their precise roles in tumourigenesis remain incompletely understood. Determining how such amino acid substitutions in a protein affect its properties can be challenging because of difficulties in detecting and tracking mutant proteins within cells and tissues. Here we describe a strategy for the generation of antibodies to discriminate G34R and G34V mutant histone H3 proteins from their wild-type counterparts. Antibodies were validated by western blotting and immunocytochemistry, using recombinant H3.3 proteins and paediatric GBM cell lines. The H3-G34R antibody demonstrated a high degree of selectivity towards its target sequence. Accordingly, immunostaining on a cohort of 22 formalin-fixed paraffin embedded tumours with a previously known H3.3 G34R mutation status, detected successfully the corresponding mutant protein in 11/11 G34R cases. Since there was a high concordance between genotype and immunohistochemical analysis of G34R mutant tumour samples, we analysed a series of tissue microarrays (TMAs) to assess the specificity of the antibody in a range of paediatric brain tumours, and noted immunoreactivity in 2/634 cases. Importantly, we describe the generation and validation of highly specific antibodies for G34 mutations. Overall our work adds to an extremely valuable portfolio of antibodies, not only for histopathologic detection of tumour-associated mutant histone sequences, but also facilitating the study of spatial/anatomical aspects of tumour formation and the identification of downstream targets and pathways in malignant glioma progression