Cloud observations in Switzerland using hemispherical sky cameras

We present observations of total cloud cover and cloud type classification results from a sky camera network comprising four stations in Switzerland. In a comprehensive intercomparison study, records of total cloud cover from the sky camera, long-wave radiation observations, Meteosat, ceilometer, and visual observations were compared. Total cloud cover from the sky camera was in 65–85% of cases within ±1 okta with respect to the other methods. The sky camera overestimates cloudiness with respect to the other automatic techniques on average by up to 1.1 ± 2.8 oktas but underestimates it by 0.8 ± 1.9 oktas compared to the human observer. However, the bias depends on the cloudiness and therefore needs to be considered when records from various observational techniques are being homogenized. Cloud type classification was conducted using the k-Nearest Neighbor classifier in combination with a set of color and textural features. In addition, a radiative feature was introduced which improved the discrimination by up to 10%. The performance of the algorithm mainly depends on the atmospheric conditions, site-specific characteristics, the randomness of the selected images, and possible visual misclassifications: The mean success rate was 80–90% when the image only contained a single cloud class but dropped to 50–70% if the test images were completely randomly selected and multiple cloud classes occurred in the images.

An improved single-plaquette gauge action

We describe and test a nonperturbatively improved single-plaquette lattice action for 4-d SU(2) and SU(3) pure gauge theory, which suppresses large fluctuations of the plaquette, without requiring the naive continuum limit for smooth fields. We tune the action parameters based on torelon masses in moderate cubic physical volumes, and investigate the size of cut-off effects in other physical quantities, including torelon masses in asymmetric spatial volumes, the static quark potential, and gradient flow observables. In 2-d O(N) models similarly constructed nearest-neighbor actions have led to a drastic reduction of cut-off effects, down to the permille level, in a wide variety of physical quantities. In the gauge theories, we find significant reduction of lattice artifacts, and for some observables, the coarsest lattice result is very close to the continuum value. We estimate an improvement factor of 40 compared to using the Wilson gauge action to achieve the same statistical accuracy and suppression of cut-off effects.

Integrating sequence information in microarray data analysis by free energy modeling

Microarray technology is a high-throughput method for genotyping and gene expression profiling. Limited sensitivity and specificity are one of the essential problems for this technology. Most of existing methods of microarray data analysis have an apparent limitation for they merely deal with the numerical part of microarray data and have made little use of gene sequence information. Because it's the gene sequences that precisely define the physical objects being measured by a microarray, it is natural to make the gene sequences an essential part of the data analysis. This dissertation focused on the development of free energy models to integrate sequence information in microarray data analysis. The models were used to characterize the mechanism of hybridization on microarrays and enhance sensitivity and specificity of microarray measurements. ^ Cross-hybridization is a major obstacle factor for the sensitivity and specificity of microarray measurements. In this dissertation, we evaluated the scope of cross-hybridization problem on short-oligo microarrays. The results showed that cross hybridization on arrays is mostly caused by oligo fragments with a run of 10 to 16 nucleotides complementary to the probes. Furthermore, a free-energy based model was proposed to quantify the amount of cross-hybridization signal on each probe. This model treats cross-hybridization as an integral effect of the interactions between a probe and various off-target oligo fragments. Using public spike-in datasets, the model showed high accuracy in predicting the cross-hybridization signals on those probes whose intended targets are absent in the sample. ^ Several prospective models were proposed to improve Positional Dependent Nearest-Neighbor (PDNN) model for better quantification of gene expression and cross-hybridization. ^ The problem addressed in this dissertation is fundamental to the microarray technology. We expect that this study will help us to understand the detailed mechanism that determines sensitivity and specificity on the microarrays. Consequently, this research will have a wide impact on how microarrays are designed and how the data are interpreted. ^

Performance tiers: Implementing comparative effectiveness analysis in the health care setting through operations research and spatial methods

This dissertation develops and tests a comparative effectiveness methodology utilizing a novel approach to the application of Data Envelopment Analysis (DEA) in health studies. The concept of performance tiers (PerT) is introduced as terminology to express a relative risk class for individuals within a peer group and the PerT calculation is implemented with operations research (DEA) and spatial algorithms. The analysis results in the discrimination of the individual data observations into a relative risk classification by the DEA-PerT methodology. The performance of two distance measures, kNN (k-nearest neighbor) and Mahalanobis, was subsequently tested to classify new entrants into the appropriate tier. The methods were applied to subject data for the 14 year old cohort in the Project HeartBeat! study.^ The concepts presented herein represent a paradigm shift in the potential for public health applications to identify and respond to individual health status. The resultant classification scheme provides descriptive, and potentially prescriptive, guidance to assess and implement treatments and strategies to improve the delivery and performance of health systems. ^

Targeting TRAF6 for Cancer Therapeutical Development

Tumor necrosis factor (TNF)-Receptor Associated Factors (TRAFs) are a family of signal transducer proteins. TRAF6 is a unique member of this family in that it is involved in not only the TNF superfamily, but the toll-like receptor (TLR)/IL-1R (TIR) superfamily. The formation of the complex consisting of Receptor Activator of Nuclear Factor κ B (RANK), with its ligand (RANKL) results in the recruitment of TRAF6, which activates NF-κB, JNK and MAP kinase pathways. TRAF6 is critical in signaling with leading to release of various growth factors in bone, and promotes osteoclastogenesis. TRAF6 has also been implicated as an oncogene in lung cancer and as a target in multiple myeloma. In the hopes of developing small molecule inhibitors of the TRAF6-RANK interaction, multiple steps were carried out. Computational prediction of hot spot residues on the protein-protein interaction of TRAF6 and RANK were examined. Three methods were used: Robetta, KFC2, and HotPoint, each of which uses a different methodology to determine if a residue is a hot spot. These hot spot predictions were considered the basis for resolving the binding site for in silico high-throughput screening using GOLD and the MyriaScreen database of drug/lead-like compounds. Computationally intensive molecular dynamics simulations highlighted the binding mechanism and TRAF6 structural changes upon hit binding. Compounds identified as hits were verified using a GST-pull down assay, comparing inhibition to a RANK decoy peptide. Since many drugs fail due to lack of efficacy and toxicity, predictive models for the evaluation of the LD50 and bioavailability of our TRAF6 hits, and these models can be used towards other drugs and small molecule therapeutics as well. Datasets of compounds and their corresponding bioavailability and LD50 values were curated based, and QSAR models were built using molecular descriptors of these compounds using the k-nearest neighbor (k-NN) method, and quality of these models were cross-validated.

Hybrid Approach Combining Machine Learning and a Rule-Based Expert System for Text Categorization

This paper discusses a novel hybrid approach for text categorization that combines a machine learning algorithm, which provides a base model trained with a labeled corpus, with a rule-based expert system, which is used to improve the results provided by the previous classifier, by filtering false positives and dealing with false negatives. The main advantage is that the system can be easily fine-tuned by adding specific rules for those noisy or conflicting categories that have not been successfully trained. We also describe an implementation based on k-Nearest Neighbor and a simple rule language to express lists of positive, negative and relevant (multiword) terms appearing in the input text. The system is evaluated in several scenarios, including the popular Reuters-21578 news corpus for comparison to other approaches, and categorization using IPTC metadata, EUROVOC thesaurus and others. Results show that this approach achieves a precision that is comparable to top ranked methods, with the added value that it does not require a demanding human expert workload to train

Towards hand biometrics in mobile devices

The increasing demand of security oriented to mobile applications has raised the attention to biometrics, as a proper and suitable solution for providing secure environment to mobile devices. With this aim, this document presents a biometric system based on hand geometry oriented to mobile devices, involving a high degree of freedom in terms of illumination, hand rotation and distance to camera. The user takes a picture of their own hand in the free space, without requiring any flat surface to locate the hand, and without removals of rings, bracelets or watches. The proposed biometric system relies on an accurate segmentation procedure, able to isolate hands from any background; a feature extraction, invariant to orientation, illumination, distance to camera and background; and a user classification, based on k-Nearest Neighbor approach, able to provide an accurate results on individual identification. The proposed method has been evaluated with two own databases collected with a HTC mobile. First database contains 120 individuals, with 20 acquisitions of both hands. Second database is a synthetic database, containing 408000 images of hand samples in different backgrounds: tiles, grass, water, sand, soil and the like. The system is able to identify individuals properly with False Reject Rate of 5.78% and False Acceptance Rate of 0.089%, using 60 features (15 features per finger)

Markov blanket-based approach for learning multi-dimensional Bayesian network classifiers: An application to predict the European Quality of Life-5 Dimensions (EQ-5D) from the 39-item Parkinson's Disease Questionnaire (PDQ-39)

Multi-dimensional Bayesian network classifiers (MBCs) are probabilistic graphical models recently proposed to deal with multi-dimensional classification problems, where each instance in the data set has to be assigned to more than one class variable. In this paper, we propose a Markov blanket-based approach for learning MBCs from data. Basically, it consists of determining the Markov blanket around each class variable using the HITON algorithm, then specifying the directionality over the MBC subgraphs. Our approach is applied to the prediction problem of the European Quality of Life-5 Dimensions (EQ-5D) from the 39-item Parkinson’s Disease Questionnaire (PDQ-39) in order to estimate the health-related quality of life of Parkinson’s patients. Fivefold cross-validation experiments were carried out on randomly generated synthetic data sets, Yeast data set, as well as on a real-world Parkinson’s disease data set containing 488 patients. The experimental study, including comparison with additional Bayesian network-based approaches, back propagation for multi-label learning, multi-label k-nearest neighbor, multinomial logistic regression, ordinary least squares, and censored least absolute deviations, shows encouraging results in terms of predictive accuracy as well as the identification of dependence relationships among class and feature variables.

Investigating verbal intelligence using the TF-IDF approach

In this paper we investigated differences in language use of speakers yielding different verbal intelligence when they describe the same event. The work is based on a corpus containing descriptions of a short film and verbal intelligence scores of the speakers. For analyzing the monologues and the film transcript, the number of reused words, lemmas, n-grams, cosine similarity and other features were calculated and compared to each other for different verbal intelligence groups. The results showed that the similarity of monologues of higher verbal intelligence speakers was greater than of lower and average verbal intelligence participants. A possible explanation of this phenomenon is that candidates yielding higher verbal intelligence have a better short-term memory. In this paper we also checked a hypothesis that differences in vocabulary of speakers yielding different verbal intelligence are sufficient enough for good classification results. For proving this hypothesis, the Nearest Neighbor classifier was trained using TF-IDF vocabulary measures. The maximum achieved accuracy was 92.86%.

Codificador de voz MIDI

El presente proyecto tiene el objetivo de facilitar la composición de canciones mediante la creación de las distintas pistas MIDI que la forman. Se implementan dos controladores. El primero, con objeto de transcribir la parte melódica, convierte la voz cantada o tarareada a eventos MIDI. Para ello, y tras el estudio de las distintas técnicas del cálculo del tono (pitch), se implementará una técnica con ciertas variaciones basada en la autocorrelación. También se profundiza en el segmentado de eventos, en particular, una técnica basada en el análisis de la derivada de la envolvente. El segundo, dedicado a la base rítmica de la canción, permite la creación de la percusión mediante el golpe rítmico de objetos que disponga el usuario, que serán asignados a los distintos elementos de percusión elegidos. Los resultados de la grabación de estos impactos serán señales de corta duración, no lineales y no armónicas, dificultando su discriminación. La herramienta elegida para la clasificación de los distintos patrones serán las redes neuronales artificiales (RNA). Se realizara un estudio de la metodología de diseño de redes neuronales especifico para este tipo de señales, evaluando la importancia de las variables de diseño como son el número de capas ocultas y neuronas en cada una de ellas, algoritmo de entrenamiento y funciones de activación. El estudio concluirá con la implementación de dos redes de diferente naturaleza. Una red de Elman, cuyas propiedades de memoria permiten la clasificación de patrones temporales, procesará las cualidades temporales analizando el ataque de su forma de onda. Una red de propagación hacia adelante feed-forward, que necesitará de robustas características espectrales y temporales para su clasificación. Se proponen 26 descriptores como los derivados de los momentos del espectro: centroide, curtosis y simetría, los coeficientes cepstrales de la escala de Mel (MFCCs), y algunos temporales como son la tasa de cruces por cero y el centroide de la envolvente temporal. Las capacidades de discriminación inter e intra clase de estas características serán evaluadas mediante un algoritmo de selección, habiéndose elegido RELIEF, un método basado en el algoritmo de los k vecinos mas próximos (KNN). Ambos controladores tendrán función de trabajar en tiempo real y offline, permitiendo tanto la composición de canciones, como su utilización como un instrumento más junto con mas músicos. ABSTRACT. The aim of this project is to make song composition easier by creating each MIDI track that builds it. Two controllers are implemented. In order to transcribe the melody, the first controler converts singing voice or humming into MIDI files. To do this a technique based on autocorrelation is implemented after having studied different pitch detection methods. Event segmentation has also been dealt with, to be more precise a technique based on the analysis of the signal's envelope and it's derivative have been used. The second one, can be used to make the song's rhythm . It allows the user, to create percussive patterns by hitting different objects of his environment. These recordings results in short duration, non-linear and non-harmonic signals. Which makes the classification process more complicated in the traditional way. The tools to used are the artificial neural networks (ANN). We will study the neural network design to deal with this kind of signals. The goal is to get a design methodology, paying attention to the variables involved, as the number of hidden layers and neurons in each, transfer functions and training algorithm. The study will end implementing two neural networks with different nature. Elman network, which has memory properties, is capable to recognize sequences of data and analyse the impact's waveform, precisely, the attack portion. A feed-forward network, needs strong spectral and temporal features extracted from the hit. Some descriptors are proposed as the derivates from the spectrum moment as centroid, kurtosis and skewness, the Mel-frequency cepstral coefficients, and some temporal features as the zero crossing rate (zcr) and the temporal envelope's centroid. Intra and inter class discrimination abilities of those descriptors will be weighted using the selection algorithm RELIEF, a Knn (K-nearest neighbor) based algorithm. Both MIDI controllers can be used to compose, or play with other musicians as it works on real-time and offline.

Maintaining distances with the engineer: patterns of coexistence in plant communities beyond the patch-bare dichotomy

Two-phase plant communities with an engineer conforming conspicuous patches and affecting the performance and patterns of coexisting species are the norm under stressful conditions. To unveil the mechanisms governing coexistence in these communities at multiple spatial scales, we have developed a new point-raster approach of spatial pattern analysis, which was applied to a Mediterranean high mountain grassland to show how Festuca curvifolia patches affect the local distribution of coexisting species. We recorded 22 111 individuals of 17 plant perennial species. Most coexisting species were negatively associated with F. curvifolia clumps. Nevertheless, bivariate nearest-neighbor analyses revealed that the majority of coexisting species were confined at relatively short distances from F. curvifolia borders (between 0-2 cm and up to 8 cm in some cases). Our study suggests the existence of a fine-scale effect of F. curvifolia for most species promoting coexistence through a mechanism we call 'facilitation in the halo'. Most coexisting species are displaced to an interphase area between patches, where two opposite forces reach equilibrium: attenuated severe conditions by proximity to the F. curvifolia canopy (nutrient-rich islands) and competitive exclusion mitigated by avoiding direct contact with F. curvifolia.

Estudio de los factores que condicionan, a escala local, la presencia de Epidendrum rhopalostele (Orchidaceae): Implicaciones para su conservación

El análisis de los factores que determinan el establecimiento y supervivencia de orquídeas epífitas, incluyen: a) las condiciones microambientales de los bosques que las mantienen, b) preferencias por las características de los hospederos donde crecen, c) limitación en la dispersión de semillas, d) interacciones planta-planta, y e) asociaciones micorrízicas para la germinación y resultan esenciales para el desarrollo de estrategias para la conservación y manejo de este grupo de plantas. Este trabajo ha evaluado la importancia de estos factores en Epidendrum rhopalostele, orquídea epífita del bosque de niebla montano, a través de los análisis de los patrones espaciales de los árboles que la portan y de la propia orquídea, a escala de población, estudios de asociación y métodos moleculares. Estos últimos han consistido en el uso de marcadores AFLP para el análisis de la estructura genética de la orquídea y en la secuenciación-clonación de la región ITS para la identificación de los hongos micorrízicos asociados. El objetivo de esta tesis es, por tanto, una mejor comprensión de los factores que condicionan la presencia de orquídeas epífitas en los remanentes de bosque de niebla montano y una evaluación de las implicaciones para la conservación y mantenimiento de sus hábitats y la permanencia de sus poblaciones. El estudio fue realizado en un fragmento de bosque de niebla montano de sucesión secundaria situado al este de la Cordillera Real, en los Andes del sur de Ecuador, a 2250 m.s.n.m y caracterizado por una pendiente marcada, temperatura media anual de 20.8°C y precipitación anual de 2193 mm. En este fragmento se mapearon, identificaron y caracterizaron todos los árboles presentes con DBH > 1 cm y todos los individuos de Epidendrum rhopalostele. Así mismo se tomaron muestras de hoja para obtener ADN de todas las orquídeas registradas y muestras de raíces de individuos con flor de E. rhopalostele, uno por cada forófito, para el análisis filogenético de micorrizas. Análisis espaciales de patrones de puntos basados en la K de Ripley y la distancia al vecino más cercano fueron usados para los árboles, forófitos y la población de E. rhopalostele. Se observó que la distribución espacial de árboles y forófitos de E. rhopalostele no es aleatoria, ya que se ajusta a un proceso agregado de Poisson. De ahí se infiere una limitación en la dispersión de las semillas en el fragmento estudiado y en el establecimiento de la orquídea. El patrón de distribución de la población de E. rhopalostele en el fragmento muestra un agrupamiento a pequeña escala sugiriendo una preferencia por micro-sitios para el establecimiento de la orquídea con un kernel de dispersión de las semillas estimado de 0.4 m. Las características preferentes del micro-sitio como tipos de árboles (Clusia alata y árboles muertos), tolerancia a la sombra, corteza rugosa, distribución en los dos primeros metros sugieren una tendencia a distribuirse en el sotobosque. La existencia de una segregación espacial entre adultos y juveniles sugiere una competencia por recursos limitados condicionada por la preferencia de micro-sitio. La estructura genética de la población de E. rhopalostele analizada a través de Structure y PCoA evidencia la presencia de dos grupos genéticos coexistiendo en el fragmento y en los mismos forófitos, posiblemente por eventos de hibridización entre especies de Epidendrum simpátricas. Los resultados del análisis de autocorrelación espacial efectuados en GenAlex confirman una estructura genético-espacial a pequeña escala que es compatible con un mecanismo de dispersión de semillas a corta distancia ocasionada por gravedad o pequeñas escorrentías, frente a la dispersión a larga distancia promovida por el viento generalmente atribuida a las orquídeas. Para la identificación de los micobiontes se amplificó la región ITS1-5.8S-ITS2, y 47 secuencias fueron usadas para el análisis filogenético basado en neighborjoining, análisis bayesiano y máximum-likelihood que determinó que Epidendrum rhopalostele establece asociaciones micorrízicas con al menos dos especies diferentes de Tulasnella. Se registraron plantas que estaban asociadas con los dos clados de hongos encontrados, sugiriendo ausencia de limitación en la distribución del hongo. Con relación a las implicaciones para la conservación in situ resultado de este trabajo se recomienda la preservación de todo el fragmento de bosque así como de las interacciones existentes (polinizadores, micorrizas) a fin de conservar la diversidad genética de esta orquídea epífita. Si fuere necesaria una reintroducción se deben contemplar distancias entre los individuos en cada forófito dentro de un rango de 0.4 m. Para promover el reclutamiento y regeneración de E. rhopalostele, se recomienda que los forófitos correspondan preferentemente a árboles muertos o caídos y a especies, como Clusia alata, que posean además corteza rugosa, sean tolerantes a la sombra, y en el área del sotobosque con menor luminosidad. Además es conveniente que las orquídeas en su distribución vertical estén ubicadas en los primeros metros. En conclusión, la limitación en la dispersión, las características del micro-sitio, las interacciones intraespecíficas y con especies congenéricas simpátricas y las preferencias micorrízicas condicionan la presencia de esta orquídea epífita en este tipo de bosque. ABSTRACT The analysis of factors that determine the establishment and survival of epiphytic depends on factors such as a) microenvironmental conditions of forest, b) preference for host characteristics where orchids grow, c) seed dispersal limitation, d) plant-plant interaction, e) priority mycorrhizal associations for germination, are essential for the development of strategies for management and conservation. This work evaluated the importance of these factors in Epidendrum rhopalostele, an epiphytic orchid of montane cloud forest through the analysis of spatial patterns of host trees and the orchid, in a more specific scale, with association studies and molecular methods, including AFLPs for orchid population genetic structure and the sequencing of the ITS region for associated mycorrhizal fungi. The aim of this thesis is to understand the factors that condition the presence of epiphytic orchids in the remnants of montane cloud forest and to assess the implications for the conservation and preservation of their habitats and the persistence of the orchid populations. The study was carried out in a fragment of montane cloud forest of secondary succession on the eastern slope of Cordillera Real in the Andes of southern Ecuador, located at 2250 m a.s.l. characterized by a steep slope, mean annual temperature of 20.8°C and annual precipitation of 2193 mm. All trees with DBH > 1 cm were mapped, characterized and identified. All E. rhopalostele individuals present were counted, marked, characterized and mapped. Leaf samples of all orchid individuals were collected for DNA analysis. Root samples of flowering E. rhopalostele individuals were collected for phylogenetic analysis of mycorrhizae, one per phorophyte. Spatial point pattern analysis based on Ripley`s K function and nearest neighbor function was used for trees, phorophytes and orchid population. We observed that spatial distribution of trees and phorophytes is not random, as it adjusts to a Poisson cluster process. This suggests a limitation for seed dispersal in the study fragment that is affecting orchid establishment. Furthermore, the small-scale spatial pattern of E. rhopalostele evidences a clustering that suggests a microsite preference for orchid establishment with a dispersal kernel of 0.4 m. Microsite features such as types of trees (dead trees or Clusia alata), shade tolerance trees, rough bark, distribution in the first meters suggest a tendency to prefer the understory for their establishment. Regarding plant-plant interaction a spatial segregation between adults and juveniles was present suggesting competition for limited resources conditioned for a microsite preference. Analysis of genetic structure of E. rhopalostele population through Structure and PCoA shows two genetic groups coexisting in this fragment and in the same phorophyte, possibly as a result of hybridization between sympatric species of Epidendrum. Our results of spatial autocorrelation analysis develop in GenAlex confirm a small-scale spatial-genetic structure within the genetic groups that is compatible with a short-distance dispersal mechanism caused by gravity or water run-off, instead of the long-distance seed dispersal promoted by wind generally attributed to orchids. For mycobionts identification ITS1-5.8S-ITS2 rDNA region was amplified. Phylogenetic analysis was performed with neighborjoining, Bayesian likelihood and maximum-likelihood for 47 sequences yielded two Tulasnella clades. This orchid establishes mycorrhizal associations with at least two different Tulasnella species. In some cases both fungi clades were present in same root, suggesting no limitation in fungal distribution. Concerning the implications for in situ conservation resulting from this work, the preservation of all forest fragment and their interactions (pollinators, mycorrhiza) is recommended to conserve the genetic diversity of this species. If a reintroduction were necessary, distances between individuals in each phorophyte within a range of 0.4 m, are recommended. To promote recruitment and regeneration of E. rhopalostele it is recommended that phorophytes correspond to dead or fallen trees or species, such as Clusia alata. Trees that have rough bark and are shade tolerant are also recommended. Furthermore, regarding vertical distribution, it is also convenient that orchids are located in the first meter (in understory, area with less light). In conclusion, limitation on seed dispersal, microsite characteristics, plant-plant interactions or interaction with cogeneric sympatric species and mycorrhizal preferences conditioned the presence of this epiphytic orchid in this fragment forest.

Nup93, a Vertebrate Homologue of Yeast Nic96p, Forms a Complex with a Novel 205-kDa Protein and Is Required for Correct Nuclear Pore Assembly

Yeast and vertebrate nuclear pores display significant morphological similarity by electron microscopy, but sequence similarity between the respective proteins has been more difficult to observe. Herein we have identified a vertebrate nucleoporin, Nup93, in both human and Xenopus that has proved to be an evolutionarily related homologue of the yeast nucleoporin Nic96p. Polyclonal antiserum to human Nup93 detects corresponding proteins in human, rat, and Xenopus cells. Immunofluorescence and immunoelectron microscopy localize vertebrate Nup93 at the nuclear basket and at or near the nuclear entry to the gated channel of the pore. Immunoprecipitation from both mammalian and Xenopus cell extracts indicates that a small fraction of Nup93 physically interacts with the nucleoporin p62, just as yeast Nic96p interacts with the yeast p62 homologue. However, a large fraction of vertebrate Nup93 is extracted from pores and is also present in Xenopus egg extracts in complex with a newly discovered 205-kDa protein. Mass spectrometric sequencing of the human 205-kDa protein reveals that this protein is encoded by an open reading frame, KIAAO225, present in the human database. The putative human nucleoporin of 205 kDa has related sequence homologues in Caenorhabditis elegans and Saccharomyces cerevisiae. To analyze the role of the Nup93 complex in the pore, nuclei were assembled that lack the Nup93 complex after immunodepletion of a Xenopus nuclear reconstitution extract. The Nup93-complex–depleted nuclei are clearly defective for correct nuclear pore assembly. From these experiments, we conclude that the vertebrate and yeast pore have significant homology in their functionally important cores and that, with the identification of Nup93 and the 205-kDa protein, we have extended the knowledge of the nearest-neighbor interactions of this core in both yeast and vertebrates.

Non-CpG methylation is prevalent in embryonic stem cells and may be mediated by DNA methyltransferase 3a

Current evidence indicates that methylation of cytosine in mammalian DNA is restricted to both strands of the symmetrical sequence CpG, although there have been sporadic reports that sequences other than CpG may also be methylated. We have used a dual-labeling nearest neighbor technique and bisulphite genomic sequencing methods to investigate the nearest neighbors of 5-methylcytosine residues in mammalian DNA. We find that embryonic stem cells, but not somatic tissues, have significant cytosine-5 methylation at CpA and, to a lesser extent, at CpT. As the expression of the de novo methyltransferase Dnmt3a correlates well with the presence of non-CpG methylation, we asked whether Dnmt3a might be responsible for this modification. Analysis of genomic methylation in transgenic Drosophila expressing Dnmt3a reveals that Dnmt3a is predominantly a CpG methylase but also is able to induce methylation at CpA and at CpT.

Prediction of the stability of DNA triplexes.

We present rules that allow one to predict the stability of DNA pyrimidine.purine.pyrimidine (Y.R.Y) triple helices on the basis of the sequence. The rules were derived from van't Hoff analysis of 23 oligonucleotide triplexes tested at a variety of pH values. To predict the enthalpy of triplex formation (delta H degrees), a simple nearest-neighbor model was found to be sufficient. However, to accurately predict the free energy of the triplex (delta G degrees), a combination model consisting of five parameters was needed. These parameters were (i) the delta G degrees for helix initiation, (ii) the delta G degrees for adding a T-A.T triple, (iii) the delta G degrees for adding a C(+)-G.C triple, (iv) the penalty for adjacent C bases, and (v) the pH dependence of the C(+)-G.C triple's stability. The fitted parameters are highly consistent with thermodynamic data from the basis set, generally predicting both delta H degrees and delta G degrees to within the experimental error. Examination of the parameters points out several interesting features. The combination model predicts that C(+) -G.C. triples are much more stabilizing than T-A.T triples below pH 7.0 and that the stability of the former increases approximately equal to 1 kcal/mol per pH unit as the pH is decreased. Surprisingly though, the most stable sequence is predicted to be a CT repeat, as adjacent C bases partially cancel the stability of one another. The parameters successfully predict tm values from other laboratories, with some interesting exceptions.