922 resultados para GALAXIES: DISTANCES AND REDSHIFTS


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A recent all-object spectroscopic survey centred on the Fornax cluster of galaxies has discovered a population of subluminous and extremely compact members, called 'ultra-compact dwarf' (UCD) galaxies. In order to clarify the origin of these objects, we have used self-consistent numerical simulations to study the dynamical evolution a nucleated dwarf galaxy would undergo if orbiting the centre of the Fornax cluster and suffering from its strong tidal gravitational field. We find that the outer stellar components of a nucleated dwarf are removed by the strong tidal field of the cluster, whereas the nucleus manages to survive as a result of its initially compact nature. The developed naked nucleus is found to have physical properties (e. g. size and mass) similar to those observed for UCDs. We also find that although this formation process does not have a strong dependence on the initial total luminosity of the nucleated dwarf, it does depend on the radial density profile of the dark halo in the sense that UCDs are less likely to be formed from dwarfs embedded in dark matter haloes with central 'cuspy' density profiles. Our simulations also suggest that very massive and compact stellar systems can be rapidly and efficiently formed in the central regions of dwarfs through the merging of smaller star clusters. We provide some theoretical predictions on the total number and radial number density profile of UCDs in a cluster and their dependencies on cluster masses.

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We present new measurements of the luminosity function (LF) of luminous red galaxies (LRGs) from the Sloan Digital Sky Survey (SDSS) and the 2dF SDSS LRG and Quasar (2SLAQ) survey. We have carefully quantified, and corrected for, uncertainties in the K and evolutionary corrections, differences in the colour selection methods, and the effects of photometric errors, thus ensuring we are studying the same galaxy population in both surveys. Using a limited subset of 6326 SDSS LRGs (with 0.17 < z < 0.24) and 1725 2SLAQ LRGs (with 0.5 < z < 0.6), for which the matching colour selection is most reliable, we find no evidence for any additional evolution in the LRG LF, over this redshift range, beyond that expected from a simple passive evolution model. This lack of additional evolution is quantified using the comoving luminosity density of SDSS and 2SLAQ LRGs, brighter than M-0.2r - 5 log h(0.7) = - 22.5, which are 2.51 +/- 0.03 x 10(-7) L circle dot Mpc(-3) and 2.44 +/- 0.15 x 10(-7) L circle dot Mpc(-3), respectively (< 10 per cent uncertainty). We compare our LFs to the COMBO-17 data and find excellent agreement over the same redshift range. Together, these surveys show no evidence for additional evolution (beyond passive) in the LF of LRGs brighter than M-0.2r - 5 log h(0.7) = - 21 ( or brighter than similar to L-*).. We test our SDSS and 2SLAQ LFs against a simple 'dry merger' model for the evolution of massive red galaxies and find that at least half of the LRGs at z similar or equal to 0.2 must already have been well assembled (with more than half their stellar mass) by z similar or equal to 0.6. This limit is barely consistent with recent results from semi-analytical models of galaxy evolution.

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Ultraviolet (UV) nonionizing continuum and mid-infrared (IR) emission constitute the basis of two widely used star formation (SF) indicators at intermediate and high redshifts. We study 2430 galaxies with z < 1.4 in the Extended Groth Strip with deep MIPS 24 μm observations from FIDEL, spectroscopy from DEEP2, and UV, optical, and near-IR photometry from the AEGIS. The data are coupled with dust-reddened stellar population models and Bayesian spectral energy distribution (SED) fitting to estimate dust-corrected star formation rates (SFRs). In order to probe the dust heating from stellar populations of various ages, the derived SFRs were averaged over various timescales—from 100 Myr for "current" SFR (corresponding to young stars) to 1-3 Gyr for long-timescale SFRs (corresponding to the light-weighted age of the dominant stellar populations). These SED-based UV/optical SFRs are compared to total IR luminosities extrapolated from 24 μm observations, corresponding to 10-18 μm rest frame. The total IR luminosities are in the range of normal star-forming galaxies and luminous IR galaxies (10^10-10^12 L_☉). We show that the IR luminosity can be estimated from the UV and optical photometry to within a factor of 2, implying that most z < 1.4 galaxies are not optically thick. We find that for the blue, actively star-forming galaxies the correlation between the IR luminosity and the UV/optical SFR shows a decrease in scatter when going from shorter to longer SFR-averaging timescales. We interpret this as the greater role of intermediate age stellar populations in heating the dust than what is typically assumed. Equivalently, we observe that the IR luminosity is better correlated with dust-corrected optical luminosity than with dust-corrected UV light. We find that this holds over the entire redshift range. Many so-called green valley galaxies are simply dust-obscured actively star-forming galaxies. However, there exist 24 μm detected galaxies, some with L_IR>10^11 L_☉, yet with little current SF. For them a reasonable amount of dust absorption of stellar light (but presumably higher than in nearby early-type galaxies) is sufficient to produce the observed levels of IR, which includes a large contribution from intermediate and old stellar populations. In our sample, which contains very few ultraluminous IR galaxies, optical and X-ray active galactic nuclei do not contribute on average more than ~50% to the mid-IR luminosity, and we see no evidence for a large population of "IR excess" galaxies.

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By virtue of its proximity and richness, the Virgo galaxy cluster is a perfect testing ground to expand our understanding of structure formation in the Universe. Here, we present a comprehensive dynamical catalogue based on 190 Virgo cluster galaxies (VCGs) in the "Spectroscopy and H-band Imaging of the Virgo cluster" (SHIVir) survey, including kinematics and dynamical masses. Spectroscopy collected over a multi-year campaign on 4-8m telescopes was joined with optical and near-infrared imaging to create a cosmologically-representative overview of parameter distributions and scaling relations describing galaxy evolution in a rich cluster environment. The use of long-slit spectroscopy has allowed the extraction and systematic analysis of resolved kinematic profiles: Halpha rotation curves for late-type galaxies (LTGs), and velocity dispersion profiles for early-type galaxies (ETGs). The latter are shown to span a wide range of profile shapes which correlate with structural, morphological, and photometric parameters. A study of the distributions of surface brightnesses and circular velocities for ETGs and LTGs considered separately show them all to be strongly bimodal, hinting at the existence of dynamically unstable modes where the baryon and dark matter fractions may be comparable within the inner regions of galaxies. Both our Tully-Fisher relation for LTGs and Fundamental Plane analysis for ETGs exhibit the smallest scatter when a velocity metric probing the galaxy at larger radii (where the baryonic fraction becomes sub-dominant) is used: rotational velocity measured in the outer disc at the 23.5 i-mag arcsec^{-2} level, and velocity dispersion measured within an aperture of 2 effective radii, respectively. Dynamical estimates for gas-poor and gas-rich VCGs are merged into a joint analysis of the stellar-to-total mass relation (STMR), stellar TFR, and Mass-Size relation. These relations are all found to contain strong bimodalities or dichotomies between the ETG and LTG samples, alluding to a "mixed scenario'' evolutionary sequence between morphological/dynamical classes that involves both quenching and dry mergers. The unmistakable differentiation between these two galaxy classes appears robust against different classification schemes, and supports the notion that they are driven by different evolutionary histories. Future observations using integral field spectroscopy and including lower-mass galaxies should solidify this hypothesis.

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Aims. We present a dynamical analysis of the galaxy cluster Abell 1942 based on a set of 128 velocities obtained at the European Southern Observatory. Methods. Data on individual galaxies are presented and the accuracy of the determined velocities as some properties of the cluster are discussed. We have also made use of publicly available Chandra X-ray data. Results. We obtained an improved mean redshift value z = 0.22513 +/- 0.0008 and velocity dispersion sigma = 908(139)(+147) km s(-1). Our analysis indicates that inside a radius of similar to 1.5 h(70)(-1) Mpc (similar to 7 arcmin) the cluster is well relaxed, without any remarkable features and the X-ray emission traces the galaxy distribution fairly well. Two possible optical substructures are seen at similar to 5 arcmin from the centre in the northwest and the southwest directions, but are not confirmed by the velocity field. These clumps are, however, kinematically bound to the main structure of Abell 1942. X-ray spectroscopic analysis of Chandra data resulted in a temperature kT = 5.5+/-0.5 keV and metal abundance Z = 0.33 +/- 0.15 Z(circle dot). The velocity dispersion corresponding to this temperature using the T(X-sigma) scaling relation is in good agreement with the measured galaxy velocities. Our photometric redshift analysis suggests that the weak lensing signal observed to the south of the cluster and previously attributed to a ""dark clump"" is produced by background sources, possibly distributed as a filamentary structure.

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Three-dimensional spectroscopy techniques are becoming more and more popular, producing an increasing number of large data cubes. The challenge of extracting information from these cubes requires the development of new techniques for data processing and analysis. We apply the recently developed technique of principal component analysis (PCA) tomography to a data cube from the center of the elliptical galaxy NGC 7097 and show that this technique is effective in decomposing the data into physically interpretable information. We find that the first five principal components of our data are associated with distinct physical characteristics. In particular, we detect a low-ionization nuclear-emitting region (LINER) with a weak broad component in the Balmer lines. Two images of the LINER are present in our data, one seen through a disk of gas and dust, and the other after scattering by free electrons and/or dust particles in the ionization cone. Furthermore, we extract the spectrum of the LINER, decontaminated from stellar and extended nebular emission, using only the technique of PCA tomography. We anticipate that the scattered image has polarized light due to its scattered nature.

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This study presents the mass distribution for a sample of 18 late-type galaxies in nine Hickson compact groups. We used Ha rotation curves (RCs) from high-resolution two-dimensional velocity fields of Fabry-Perot observations and the J-band photometry from the Two Micron All Sky Survey, in order to determine the dark halo and the visible matter distributions. The study compares two halo density profiles, an isothermal core-like distribution, and a cuspy one. We also compare their visible and dark matter distributions with those of galaxies belonging to cluster and field galaxies coming from two samples: 40 cluster galaxies of Barnes et al. and 35 field galaxies of Spano et al. The central halo surface density is found to be constant with respect to the total absolute magnitude similar to what is found for the isolated galaxies. This suggests that the halo density is independent of galaxy type and environment. We have found that core-like density profiles better fit the RCs than cuspy-like ones. No major differences have been found between field, cluster, and compact group galaxies with respect to their dark halo density profiles.

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We present a new set of deep H I observations of member galaxies of the Fornax cluster. We detected 35 cluster galaxies in H I. The resulting sample, the most comprehensive to date, is used to investigate the distribution of neutral hydrogen in the cluster galaxies. We compare the H I content of the detected cluster galaxies with that of field galaxies by measuring H I mass-to-light ratios and the H I deficiency parameter of Solanes et al. (1996). The mean H I mass-to-light ratio of the cluster galaxies is 0.68 +/- 0.15, significantly lower than for a sample of H I-selected field galaxies (1.15 +/- 0.10), although not as low as in the Virgo cluster (0.45 +/- 0.03). In addition, the H I content of two cluster galaxies (NGC1316C and NGC1326B) appears to have been affected by interactions. The mean H I deficiency for the cluster is 0.38 +/- 0.09 (for galaxy types T = 1-6), significantly greater than for the field sample (0.05 +/- 0.03). Both these tests show that Fornax cluster galaxies are H I-deficient compared to field galaxies. The kinematics of the cluster galaxies suggests that the H I deficiency may be caused by ram-pressure stripping of galaxies on orbits that pass close to the cluster core. We also derive the most complete B-band Tully-Fisher relation of inclined spiral galaxies in Fornax. A subcluster in the South-West of the main cluster contributes considerably to the scatter. The scatter for galaxies in the main cluster alone is 0.50 mag, which is slightly larger than the intrinsic scatter of 0.4 mag. We use the Tully-Fisher relation to derive a distance modulus of Fornax relative to the Virgo cluster of -0.38 +/- 0.14 mag. The galaxies in the subcluster are (1.0 +/- 0.5) mag brighter than the galaxies of the main cluster, indicating that they are situated in the foreground. With their mean velocity 95 km s(-1) higher than that of the main cluster we conclude that the subcluster is falling into the main Fornax cluster.

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Axial X-ray Computed tomography (CT) scanning provides a convenient means of recording the three-dimensional form of soil structure. The technique has been used for nearly two decades, but initial development has concentrated on qualitative description of images. More recently, increasing effort has been put into quantifying the geometry and topology of macropores likely to contribute to preferential now in soils. Here we describe a novel technique for tracing connected macropores in the CT scans. After object extraction, three-dimensional mathematical morphological filters are applied to quantify the reconstructed structure. These filters consist of sequences of so-called erosions and/or dilations of a 32-face structuring element to describe object distances and volumes of influence. The tracing and quantification methodologies were tested on a set of undisturbed soil cores collected in a Swiss pre-alpine meadow, where a new earthworm species (Aporrectodea nocturna) was accidentally introduced. Given the reduced number of samples analysed in this study, the results presented only illustrate the potential of the method to reconstruct and quantify macropores. Our results suggest that the introduction of the new species induced very limited chance to the soil structured for example, no difference in total macropore length or mean diameter was observed. However. in the zone colonised by, the new species. individual macropores tended to have a longer average length. be more vertical and be further apart at some depth. Overall, the approach proved well suited to the analysis of the three-dimensional architecture of macropores. It provides a framework for the analysis of complex structures, which are less satisfactorily observed and described using 2D imaging. (C) 2002 Elsevier Science B.V. All rights reserved.

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We numerically investigate the dynamical evolution of non-nucleated dwarf elliptical/spiral galaxies (dE) and nucleated ones (dE,Ns) in clusters of galaxies in order to understand the origin of intracluster stellar objects, such as intracluster stars (ICSs), GCs (ICGCs), and ultracompact dwarfs (UCDs) recently discovered by all-object spectroscopic survey centred on the Fornax cluster of galaxies. We find that the outer stellar components of a nucleated dwarf are removed by the strong tidal field of the cluster, whereas the nucleus manages to survive as a result of its initially compact nature. The developed naked nucleus is found to have physical properties (e.g., size and mass) similar to those observed for UCDs. We also find that the UCD formation process, does depend on the radial density profile of the dark halo in the sense that UCDs are less likely to be formed from dwarfs embedded in dark matter halos with central 'cuspy' density profiles. Our simulations also suggest that very massive and compact stellar systems can be rapidly and efficiently formed in the central regions of dwarfs through the merging of smaller GCs. GCs initially in the outer part of dE and dE,Ns are found to be stripped to form ICGCs.

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This Thesis describes the application of automatic learning methods for a) the classification of organic and metabolic reactions, and b) the mapping of Potential Energy Surfaces(PES). The classification of reactions was approached with two distinct methodologies: a representation of chemical reactions based on NMR data, and a representation of chemical reactions from the reaction equation based on the physico-chemical and topological features of chemical bonds. NMR-based classification of photochemical and enzymatic reactions. Photochemical and metabolic reactions were classified by Kohonen Self-Organizing Maps (Kohonen SOMs) and Random Forests (RFs) taking as input the difference between the 1H NMR spectra of the products and the reactants. The development of such a representation can be applied in automatic analysis of changes in the 1H NMR spectrum of a mixture and their interpretation in terms of the chemical reactions taking place. Examples of possible applications are the monitoring of reaction processes, evaluation of the stability of chemicals, or even the interpretation of metabonomic data. A Kohonen SOM trained with a data set of metabolic reactions catalysed by transferases was able to correctly classify 75% of an independent test set in terms of the EC number subclass. Random Forests improved the correct predictions to 79%. With photochemical reactions classified into 7 groups, an independent test set was classified with 86-93% accuracy. The data set of photochemical reactions was also used to simulate mixtures with two reactions occurring simultaneously. Kohonen SOMs and Feed-Forward Neural Networks (FFNNs) were trained to classify the reactions occurring in a mixture based on the 1H NMR spectra of the products and reactants. Kohonen SOMs allowed the correct assignment of 53-63% of the mixtures (in a test set). Counter-Propagation Neural Networks (CPNNs) gave origin to similar results. The use of supervised learning techniques allowed an improvement in the results. They were improved to 77% of correct assignments when an ensemble of ten FFNNs were used and to 80% when Random Forests were used. This study was performed with NMR data simulated from the molecular structure by the SPINUS program. In the design of one test set, simulated data was combined with experimental data. The results support the proposal of linking databases of chemical reactions to experimental or simulated NMR data for automatic classification of reactions and mixtures of reactions. Genome-scale classification of enzymatic reactions from their reaction equation. The MOLMAP descriptor relies on a Kohonen SOM that defines types of bonds on the basis of their physico-chemical and topological properties. The MOLMAP descriptor of a molecule represents the types of bonds available in that molecule. The MOLMAP descriptor of a reaction is defined as the difference between the MOLMAPs of the products and the reactants, and numerically encodes the pattern of bonds that are broken, changed, and made during a chemical reaction. The automatic perception of chemical similarities between metabolic reactions is required for a variety of applications ranging from the computer validation of classification systems, genome-scale reconstruction (or comparison) of metabolic pathways, to the classification of enzymatic mechanisms. Catalytic functions of proteins are generally described by the EC numbers that are simultaneously employed as identifiers of reactions, enzymes, and enzyme genes, thus linking metabolic and genomic information. Different methods should be available to automatically compare metabolic reactions and for the automatic assignment of EC numbers to reactions still not officially classified. In this study, the genome-scale data set of enzymatic reactions available in the KEGG database was encoded by the MOLMAP descriptors, and was submitted to Kohonen SOMs to compare the resulting map with the official EC number classification, to explore the possibility of predicting EC numbers from the reaction equation, and to assess the internal consistency of the EC classification at the class level. A general agreement with the EC classification was observed, i.e. a relationship between the similarity of MOLMAPs and the similarity of EC numbers. At the same time, MOLMAPs were able to discriminate between EC sub-subclasses. EC numbers could be assigned at the class, subclass, and sub-subclass levels with accuracies up to 92%, 80%, and 70% for independent test sets. The correspondence between chemical similarity of metabolic reactions and their MOLMAP descriptors was applied to the identification of a number of reactions mapped into the same neuron but belonging to different EC classes, which demonstrated the ability of the MOLMAP/SOM approach to verify the internal consistency of classifications in databases of metabolic reactions. RFs were also used to assign the four levels of the EC hierarchy from the reaction equation. EC numbers were correctly assigned in 95%, 90%, 85% and 86% of the cases (for independent test sets) at the class, subclass, sub-subclass and full EC number level,respectively. Experiments for the classification of reactions from the main reactants and products were performed with RFs - EC numbers were assigned at the class, subclass and sub-subclass level with accuracies of 78%, 74% and 63%, respectively. In the course of the experiments with metabolic reactions we suggested that the MOLMAP / SOM concept could be extended to the representation of other levels of metabolic information such as metabolic pathways. Following the MOLMAP idea, the pattern of neurons activated by the reactions of a metabolic pathway is a representation of the reactions involved in that pathway - a descriptor of the metabolic pathway. This reasoning enabled the comparison of different pathways, the automatic classification of pathways, and a classification of organisms based on their biochemical machinery. The three levels of classification (from bonds to metabolic pathways) allowed to map and perceive chemical similarities between metabolic pathways even for pathways of different types of metabolism and pathways that do not share similarities in terms of EC numbers. Mapping of PES by neural networks (NNs). In a first series of experiments, ensembles of Feed-Forward NNs (EnsFFNNs) and Associative Neural Networks (ASNNs) were trained to reproduce PES represented by the Lennard-Jones (LJ) analytical potential function. The accuracy of the method was assessed by comparing the results of molecular dynamics simulations (thermal, structural, and dynamic properties) obtained from the NNs-PES and from the LJ function. The results indicated that for LJ-type potentials, NNs can be trained to generate accurate PES to be used in molecular simulations. EnsFFNNs and ASNNs gave better results than single FFNNs. A remarkable ability of the NNs models to interpolate between distant curves and accurately reproduce potentials to be used in molecular simulations is shown. The purpose of the first study was to systematically analyse the accuracy of different NNs. Our main motivation, however, is reflected in the next study: the mapping of multidimensional PES by NNs to simulate, by Molecular Dynamics or Monte Carlo, the adsorption and self-assembly of solvated organic molecules on noble-metal electrodes. Indeed, for such complex and heterogeneous systems the development of suitable analytical functions that fit quantum mechanical interaction energies is a non-trivial or even impossible task. The data consisted of energy values, from Density Functional Theory (DFT) calculations, at different distances, for several molecular orientations and three electrode adsorption sites. The results indicate that NNs require a data set large enough to cover well the diversity of possible interaction sites, distances, and orientations. NNs trained with such data sets can perform equally well or even better than analytical functions. Therefore, they can be used in molecular simulations, particularly for the ethanol/Au (111) interface which is the case studied in the present Thesis. Once properly trained, the networks are able to produce, as output, any required number of energy points for accurate interpolations.

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The disturbing emergence of multidrug-resistant strains of Mycobacterium tuberculosis (Mtb) has been driving the scientific community to urgently search for new and efficient antitubercular drugs. Despite the various drugs currently under evaluation, isoniazid is still the key and most effective component in all multi-therapeutic regimens recommended by the WHO. This paper describes the QSAR-oriented design, synthesis and in vitro antitubercular activity of several potent isoniazid derivatives (isonicotinoyl hydrazones and isonicotinoyl hydrazides) against H37Rv and two resistant Mtb strains. QSAR studies entailed RFs and ASNNs classification models, as well as MLR models. Strict validation procedures were used to guarantee the models' robustness and predictive ability. Lipophilicity was shown not to be relevant to explain the activity of these derivatives, whereas shorter N-N distances and lengthy substituents lead to more active compounds. Compounds I, 2, 4, 5 and 6, showed measured activities against H37Rv higher than INH (i.e., MIC <= 0.28 mu M), while compound 9 exhibited a six fold decrease in MIC against the katG (S315T) mutated strain, by comparison with INH (Le., 6.9 vs. 43.8 mu M). All compounds were ineffective against H37Rv(INH) (Delta katG), a strain with a full deletion of the katG gene, thus corroborating the importance of KatG in the activation of INH-based compounds. The most potent compounds were also shown not to be cytotoxic up to a concentration 500 times higher than MIC. (C) 2014 Elsevier Masson SAS. All rights reserved.

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The genetic variation and population structure of three populations of Anopheles darlingi from Colombia were studied using random amplified polymorphic markers (RAPDs) and amplified fragment length polymorphism markers (AFLPs). Six RAPD primers produced 46 polymorphic fragments, while two AFLP primer combinations produced 197 polymorphic fragments from 71 DNA samples. Both of the evaluated genetic markers showed the presence of gene flow, suggesting that Colombian An. darlingi populations are in panmixia. Average genetic diversity, estimated from observed heterozygosity, was 0.374 (RAPD) and 0.309 (AFLP). RAPD and AFLP markers showed little evidence of geographic separation between eastern and western populations; however, the F ST values showed high gene flow between the two western populations (RAPD: F ST = 0.029; Nm: 8.5; AFLP: F ST = 0.051; Nm: 4.7). According to molecular variance analysis (AMOVA), the genetic distance between populations was significant (RAPD:phiST = 0.084; AFLP:phiST = 0.229, P < 0.001). The F ST distances and AMOVAs using AFLP loci support the differentiation of the Guyana biogeographic province population from those of the Chocó-Magdalena. In this last region, Chocó and Córdoba populations showed the highest genetic flow.

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Rhizoctonia-like fungi are the main mycorrhizal fungi in orchid roots. Morphological characterization and analysis of conserved sequences of genomic DNA are frequently employed in the identification and study of fungi diversity. However, phytopathogenic Rhizoctonia-like fungi have been reliably and accurately characterized and identified through the examination of the fatty acid composition. To evaluate the efficacy of fatty acid composition in characterizing and identifying Rhizoctonia-like mycorrhizal fungi in orchids, three Epulorhiza spp. mycorrhizal fungi from Epidendrum secundum, two unidentified fungi isolated from Epidendrum denticulatum, and a phytopathogenic fungus, Ceratorhiza sp. AGC, were grouped based on the profile of their fatty acids, which was assessed by the Euclidian and Mahalanobis distances and the UPGMA method. Dendrograms distinguished the phytopathogenical isolate of Ceratorhiza sp. AGC from the mycorrhizal fungi studied. The symbionts of E. secundum were grouped into two clades, one containing Epulorhiza sp.1 isolates and the other the Epulorhiza sp.2 isolate. The similarity between the symbionts of E. denticulatum and Epulorhiza spp. fungi suggests that symbionts found in E. denticulatum may be identified as Epulorhiza. These results were corroborated by the analysis of the rDNA ITS region. The dendrogram constructed based on the Mahalanobis distance differentiated the clades most clearly. Fatty acid composition analysis proved to be a useful tool for characterizing and identifying Rhizoctonia-like mycorrhizal fungi.