Gene expression trees in lymphoid development

<p>Abstract</p> <p>Background</p> <p>The regulatory processes that govern cell proliferation and differentiation are central to developmental biology. Particularly well studied in this respect is the lymphoid system due to its importance for basic biology and for clinical applications. Gene expression measured in lymphoid cells in several distinguishable developmental stages helps in the elucidation of underlying molecular processes, which change gradually over time and lock cells in either the B cell, T cell or Natural Killer cell lineages. Large-scale analysis of these <it>gene expression trees </it>requires computational support for tasks ranging from visualization, querying, and finding clusters of similar genes, to answering detailed questions about the functional roles of individual genes.</p> <p>Results</p> <p>We present the first statistical framework designed to analyze gene expression data as it is collected in the course of lymphoid development through clusters of co-expressed genes and additional heterogeneous data. We introduce dependence trees for continuous variates, which model the inherent dependencies during the differentiation process naturally as gene expression trees. Several trees are combined in a mixture model to allow inference of potentially overlapping clusters of co-expressed genes. Additionally, we predict microRNA targets.</p> <p>Conclusion</p> <p>Computational results for several data sets from the lymphoid system demonstrate the relevance of our framework. We recover well-known biological facts and identify promising novel regulatory elements of genes and their functional assignments. The implementation of our method (licensed under the GPL) is available at <url>http://algorithmics.molgen.mpg.de/Supplements/ExpLym/</url>.</p

Optimal transport distances for directed, weighted graphs: a case study with cell-cell communication networks

Comparing graphs by means of optimal transport has recently gained significant attention, as the distances induced by optimal transport provide both a principled metric between graphs as well as an interpretable description of the associated changes between graphs in terms of a transport plan. As the lack of symmetry introduces challenges in the typically considered formulations, optimal transport distances for graphs have mostly been developed for undirected graphs. Here, we propose two distance measures to compare directed graphs based on variants of optimal transport: (i) an earth movers distance (Wasserstein) and (ii) a Gromov-Wasserstein (GW) distance. We evaluate these two distances and discuss their relative performance for both simulated graph data and real-world directed cell-cell communication graphs, inferred from single-cell RNA-seq data.Comment: 5 pages, 1 figur

Inferring epigenetic and transcriptional regulation during blood cell development with a mixture of sparse linear models

Motivation: Blood cell development is thought to be controlled by a circuit of transcription factors (TFs) and chromatin modifications that determine the cell fate through activating cell type-specific expression programs. To shed light on the interplay between histone marks and TFs during blood cell development, we model gene expression from regulatory signals by means of combinations of sparse linear regression models. Results: The mixture of sparse linear regression models was able to improve the gene expression prediction in relation to the use of a single linear model. Moreover, it performed an efficient selection of regulatory signals even when analyzing all TFs with known motifs (>600). The method identified interesting roles for histone modifications and a selection of TFs related to blood development and chromatin remodelling. Availability: The method and datasets are available from http://www.cin.ufpe.br/~igcf/SparseMix. Contact: [email protected] Supplementary information:Supplementary data are available at Bioinformatics online

Clustering cancer gene expression data: a comparative study

Background The use of clustering methods for the discovery of cancer subtypes has drawn a great deal of attention in the scientific community. While bioinformaticians have proposed new clustering methods that take advantage of characteristics of the gene expression data, the medical community has a preference for using "classic" clustering methods. There have been no studies thus far performing a large-scale evaluation of different clustering methods in this context. Results/Conclusion We present the first large-scale analysis of seven different clustering methods and four proximity measures for the analysis of 35 cancer gene expression data sets. Our results reveal that the finite mixture of Gaussians, followed closely by k-means, exhibited the best performance in terms of recovering the true structure of the data sets. These methods also exhibited, on average, the smallest difference between the actual number of classes in the data sets and the best number of clusters as indicated by our validation criteria. Furthermore, hierarchical methods, which have been widely used by the medical community, exhibited a poorer recovery performance than that of the other methods evaluated. Moreover, as a stable basis for the assessment and comparison of different clustering methods for cancer gene expression data, this study provides a common group of data sets (benchmark data sets) to be shared among researchers and used for comparisons with new methods. The data sets analyzed in this study are available at http://algorithmics.molgen.mpg.de/Supplements/CompCancer/ webcite

Efeitos do sotalol sobre o eletrocardiograma de alta resolução avaliados por ensaio duplo-cego cruzado randomizado

A presente investigação teve por objetivo avaliar os efeitos do Sotalol sobre o eletrocardiograma de alta resolução (ECGAR), em uma população com arritmia ventricular idiopática. Foi estudado um grupo de 12 pacientes submetidos a um ensaio clínico do tipo duplo-cego cruzado e randomizado, para avaliaçao da eficácia da droga. Foram obtidos ECGAR em condiçoes de controle (C), uso de placebo (P) e de droga (O), confrontando os resultados entre as três situações e a eficácia medicamentosa. No vetor-magnitude foram analisados os seguintes parâmetros: voltagem média dos 40 ms terminais do complexo QRS filtrado (VM - normal > 20 µV), duração dos sinais de baixa amplitude < 40 µV no final da ativação (SBA - normal < 38 ms) e duração total do complexo QRS filtrado (OQRS - normal < 114.0 ms). Em função da resposta terapêutica, os pacientes foram divididos em responsivos (G1) e não-responsivos (G2). Não foram observadas diferenças estatisticamente significativas entre C e P. No Grupo I, composto por 5 pacientes (42% de eficácia), não foram observadas diferenças significativas nas 3 variáveis avaliadas entre as condições de P e O. No Grupo 11, composto por 7 pacientes, ocorreram modificaçoes nos SBA, cujos valores no P estavam em 24.80 ± 7.60 ms e passando com a O para 29.10 ± 14.76 ms (p < 0,01). Em 5 dos 7 pacientes deste grupo (71%), prolongaram-se no pós-droga os SBA, numa média de 11.20 ± 4.80 ms, com significância estatística em relaçao ao placebo (p < 0.04). Frente aos resultados observados com os SBA, foram obtidos sensibilidade de 71 %, especificidade de 86%, valor preditivo positivo de 83% e negativo de 75% para definir a populaçao responsiva à droga. Concluiu-se que na população estudada, o Sotalol, quando efetivo, não produziu modificações significativas nos parâmetros do ECGAR. Um incremento médio dos SBA de 11.2 ± 4.8 ms, por influência da droga, associou-se a uma ausência de resposta terapêutica

pGQL: A probabilistic graphical query language for gene expression time courses

<p>Abstract</p> <p>Background</p> <p>Timeboxes are graphical user interface widgets that were proposed to specify queries on time course data. As queries can be very easily defined, an exploratory analysis of time course data is greatly facilitated. While timeboxes are effective, they have no provisions for dealing with noisy data or data with fluctuations along the time axis, which is very common in many applications. In particular, this is true for the analysis of gene expression time courses, which are mostly derived from noisy microarray measurements at few unevenly sampled time points. From a data mining point of view the robust handling of data through a sound statistical model is of great importance.</p> <p>Results</p> <p>We propose probabilistic timeboxes, which correspond to a specific class of Hidden Markov Models, that constitutes an established method in data mining. Since HMMs are a particular class of probabilistic graphical models we call our method Probabilistic Graphical Query Language. Its implementation was realized in the free software package pGQL. We evaluate its effectiveness in exploratory analysis on a yeast sporulation data set.</p> <p>Conclusions</p> <p>We introduce a new approach to define dynamic, statistical queries on time course data. It supports an interactive exploration of reasonably large amounts of data and enables users without expert knowledge to specify fairly complex statistical models with ease. The expressivity of our approach is by its statistical nature greater and more robust with respect to amplitude and frequency fluctuation than the prior, deterministic timeboxes.</p

Demographic expansion and contraction in a neotropical fish during the Late Pleistocene-Holocene

Demographic changes during the late Pleistocene-Holocene left signatures in the DNA of contemporary populations. These signatures reveal demographic phenomena like the increase or decrease in effective population size. In this paper we searched for signatures of demographic change in the DNA of the Neotropical freshwater fish Poecilia vivipara . Also, we investigated whether demographic changes are correlated with palaeoclimatic events of the late Pleistocene-Holocene, in particular, if changes in effective population size are correlated with expansion and contraction of available habitats, induced by global ice-volume changes and sea-level fluctuations. We used Bayesian Skyline Plot (BSP) analysis with sequences from the mitochondrial gene cytochrome b to estimate the ancestral demography of the Neotropical freshwater fish P. vivipara . To test the assumptions of neutrality and absence of population structure we used Tajima?s D and Spatial Analysis of Molecular Variance (SAMOVA), respectively. Effective population size of P. vivipara remained stable until 75,000 years ago, increased by 10-fold reaching a maximum at approximately 25,000 years ago, then suddenly declined at the Pleistocene-Holocene boundary. Variation in effective population size in P. vivipara correlates with expansion and contraction of habitats induced by sea-level fluctuations, caused by the advance and retreat of ice sheets during the Last Glacial Maximum (LGM).Fil: Costa, Carolina L. N.. Universidade Estadual de Campinas; BrasilFil: Perez, Sergio Ivan. Universidad Nacional de La Plata. Facultad de Ciencias Naturales y Museo. Departamento Científico de Antropología; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata; ArgentinaFil: Louvise, José. Faculdade Do Vale Do Jaguaribe; BrasilFil: Tonhatti, Carlos H.. Universidade Estadual de Campinas; BrasilFil: Clemente Carvalho, Rute B. G.. Queens University. Department Of Biology; CanadáFil: Petryna, Ana Mabel. Universidade Federal do Rio de Janeiro; BrasilFil: dos Reis, S. F.. Universidade Estadual de Campinas; Brasi

Radiomarcaje y estudios de biodistribución de nanopartículas poliméricas como adyuvantes para la vacunación oftálmica frente a la brucelosis

Objetivos: Optimizar el radiomarcaje con 99mTc de nanopartículas de Gantrez® manosiladas y cargadas con el antígeno de Brucella Ovis (Man-NP-HS) y llevar a cabo estudios de biodistribución en ratón tras la administración de las nanopartículas por vía ocular. Metodología: Las Man-NP-HS se obtuvieron por el método de desplazamiento de disolvente. Se purificaron, liofilizaron y caracterizaron. A continuación, se marcaron con 74 MBq de 99mTcO4 - previamente reducido con una disolución ácida de cloruro de estaño, trabajando en ausencia de oxígeno y con un pH final de 4. El rendimiento del marcaje se evaluó mediante TLC. Los estudios de biodistribución se llevaron a cabo en ratones tras la administración oftálmica de la formulación y de un control de 99mTcO4 - libre. Para ello, se sacrificaron los animales a las 2 y a las 24 horas tras la administración ocular y se contaron los órganos en un contador gamma. Resultados: Se obtuvo un rendimiento de marcaje superior al 90%. Los estudios de biodistribución de 99mTc-Man-NP-HS permitieron detectar la actividad concentrada en mucosa nasal y ocular y tracto gastrointestinal tanto a las 2 como a las 24 horas, frente a la biodistribución de 99mTcO4 - libre que permaneció concentrado en la piel alrededor del ojo y en tracto gastrointestinal. Conclusión: Los estudios de biodistribución de 99mTc-Man-NP-HS tras administración oftálmica han permitido demostrar su biodistribución en mucosas y tracto gastrointestinal, característica indispensable como sistema de liberación de antígenos a través de mucosa ocular. Esto, junto con su elevada respuesta inmune, efectiva protección y no virulencia, convierte a estas nanopartículas en una vacuna ideal anti Brucelosis