Biomarker discovery and redundancy reduction towards classification using a multi-factorial MALDI-TOF MS T2DM mouse model dataset

Diabetes like many diseases and biological processes is not mono-causal. On the one hand multifactorial studies with complex experimental design are required for its comprehensive analysis. On the other hand, the data from these studies often include a substantial amount of redundancy such as proteins that are typically represented by a multitude of peptides. Coping simultaneously with both complexities (experimental and technological) makes data analysis a challenge for Bioinformatics.

Towards more precise sugar beet management based on geostatistical analysis of spatial variability within fields

Within-field variation in sugar beet yield and quality was investigated in three commercial sugar beet fields in the east of England to identify the main associated variables and to examine the possibility of predicting yield early in the season with a view to spatially variable management of sugar beet crops. Irregular grid sampling with some purposively-located nested samples was applied. It revealed the spatial variability in each sugar beet field efficiently. In geostatistical analyses, most variograms were isotropic with moderate to strong spatial dependency indicating a significant spatial variation in sugar beet yield and associated growth and environmental variables in all directions within each field. The Kriged maps showed spatial patterns of yield variability within each field and visual association with the maps of other variables. This was confirmed by redundancy analyses and Pearson correlation coefficients. The main variables associated with yield variability were soil type, organic matter, soil moisture, weed density and canopy temperature. Kriged maps of final yield variability were strongly related to that in crop canopy cover, LAI and intercepted solar radiation early in the growing season, and the yield maps of previous crops. Therefore, yield maps of previous crops together with early assessment of sugar beet growth may make an early prediction of within-field variability in sugar beet yield possible. The Broom’s Barn sugar beet model failed to account for the spatial variability in sugar yield, but the simulation was greatly improved when corrected for early canopy development cover and when the simulated yield was adjusted for weeds and plant population. Further research to optimize inputs to maximise sugar yield should target the irrigation and fertilizing of areas within fields with low canopy cover early in the season.

High homologous gene conservation despite extreme autopolyploid redundancy in sugarcane

P>Modern sugarcane (Saccharum spp.) is the leading sugar crop and a primary energy crop. It has the highest level of `vertical` redundancy (2n = 12x = 120) of all polyploid plants studied to date. It was produced about a century ago through hybridization between two autopolyploid species, namely S. officinarum and S. spontaneum. In order to investigate the genome dynamics in this highly polyploid context, we sequenced and compared seven hom(oe)ologous haplotypes (bacterial artificial chromosome clones). Our analysis revealed a high level of gene retention and colinearity, as well as high gene structure and sequence conservation, with an average sequence divergence of 4% for exons. Remarkably, all of the hom(oe)ologous genes were predicted as being functional (except for one gene fragment) and showed signs of evolving under purifying selection, with the exception of genes within segmental duplications. By contrast, transposable elements displayed a general absence of colinearity among hom(oe)ologous haplotypes and appeared to have undergone dynamic expansion in Saccharum, compared with sorghum, its close relative in the Andropogonea tribe. These results reinforce the general trend emerging from recent studies indicating the diverse and nuanced effect of polyploidy on genome dynamics.

Multiple Pathways Analysis of Brain Functional Networks from EEG Signals: An Application to Real Data

In the present study, we propose a theoretical graph procedure to investigate multiple pathways in brain functional networks. By taking into account all the possible paths consisting of h links between the nodes pairs of the network, we measured the global network redundancy R (h) as the number of parallel paths and the global network permeability P (h) as the probability to get connected. We used this procedure to investigate the structural and dynamical changes in the cortical networks estimated from a dataset of high-resolution EEG signals in a group of spinal cord injured (SCI) patients during the attempt of foot movement. In the light of a statistical contrast with a healthy population, the permeability index P (h) of the SCI networks increased significantly (P < 0.01) in the Theta frequency band (3-6 Hz) for distances h ranging from 2 to 4. On the contrary, no significant differences were found between the two populations for the redundancy index R (h) . The most significant changes in the brain functional network of SCI patients occurred mainly in the lower spectral contents. These changes were related to an improved propagation of communication between the closest cortical areas rather than to a different level of redundancy. This evidence strengthens the hypothesis of the need for a higher functional interaction among the closest ROIs as a mechanism to compensate the lack of feedback from the peripheral nerves to the sensomotor areas.

Etikettdesign och prisklass för röda viner

Denna studie syftar till att undersöka om det finns ett samband mellan designfaktorer och prisklass på rödvinsetiketter. För att kartlägga förekommande designfaktorer har en visuell innehållsanalys gjorts inom tre olika prisklasser hämtad från Systembolagets hemsida. Utifrån den visuella innehållsanalysens resultat designades tre vinetiketter för varje prisklass. För att ta reda på om dessa designfaktorer hade ett samband med den tänkta prisklassen testades vinetiketterna mot konsumenter genom en webbenkät. Slutsatsen var att det fanns vissa generella drag som skiljer prisklasserna åt även om många designfaktorer var vanligt förekommande för alla prisklasser. Utifrån respondenternas svar visade sig vissa av designfaktorerna vara mer eller mindre tydliga för den tilltänkta prisklassen.

Uso da análise discriminante regularizada (RDA) no reconhecimento de padrões em imagens digitais hiperespectral de sensoriamento remoto

Em cenas naturais, ocorrem com certa freqüência classes espectralmente muito similares, isto é, os vetores média são muito próximos. Em situações como esta, dados de baixa dimensionalidade (LandSat-TM, Spot) não permitem uma classificação acurada da cena. Por outro lado, sabe-se que dados em alta dimensionalidade [FUK 90] tornam possível a separação destas classes, desde que as matrizes covariância sejam suficientemente distintas. Neste caso, o problema de natureza prática que surge é o da estimação dos parâmetros que caracterizam a distribuição de cada classe. Na medida em que a dimensionalidade dos dados cresce, aumenta o número de parâmetros a serem estimados, especialmente na matriz covariância. Contudo, é sabido que, no mundo real, a quantidade de amostras de treinamento disponíveis, é freqüentemente muito limitada, ocasionando problemas na estimação dos parâmetros necessários ao classificador, degradando portanto a acurácia do processo de classificação, na medida em que a dimensionalidade dos dados aumenta. O Efeito de Hughes, como é chamado este fenômeno, já é bem conhecido no meio científico, e estudos vêm sendo realizados com o objetivo de mitigar este efeito. Entre as alternativas propostas com a finalidade de mitigar o Efeito de Hughes, encontram-se as técnicas de regularização da matriz covariância. Deste modo, técnicas de regularização para a estimação da matriz covariância das classes, tornam-se um tópico interessante de estudo, bem como o comportamento destas técnicas em ambientes de dados de imagens digitais de alta dimensionalidade em sensoriamento remoto, como por exemplo, os dados fornecidos pelo sensor AVIRIS. Neste estudo, é feita uma contextualização em sensoriamento remoto, descrito o sistema sensor AVIRIS, os princípios da análise discriminante linear (LDA), quadrática (QDA) e regularizada (RDA) são apresentados, bem como os experimentos práticos dos métodos, usando dados reais do sensor. Os resultados mostram que, com um número limitado de amostras de treinamento, as técnicas de regularização da matriz covariância foram eficientes em reduzir o Efeito de Hughes. Quanto à acurácia, em alguns casos o modelo quadrático continua sendo o melhor, apesar do Efeito de Hughes, e em outros casos o método de regularização é superior, além de suavizar este efeito. Esta dissertação está organizada da seguinte maneira: No primeiro capítulo é feita uma introdução aos temas: sensoriamento remoto (radiação eletromagnética, espectro eletromagnético, bandas espectrais, assinatura espectral), são também descritos os conceitos, funcionamento do sensor hiperespectral AVIRIS, e os conceitos básicos de reconhecimento de padrões e da abordagem estatística. No segundo capítulo, é feita uma revisão bibliográfica sobre os problemas associados à dimensionalidade dos dados, à descrição das técnicas paramétricas citadas anteriormente, aos métodos de QDA, LDA e RDA, e testes realizados com outros tipos de dados e seus resultados.O terceiro capítulo versa sobre a metodologia que será utilizada nos dados hiperespectrais disponíveis. O quarto capítulo apresenta os testes e experimentos da Análise Discriminante Regularizada (RDA) em imagens hiperespectrais obtidos pelo sensor AVIRIS. No quinto capítulo são apresentados as conclusões e análise final. A contribuição científica deste estudo, relaciona-se à utilização de métodos de regularização da matriz covariância, originalmente propostos por Friedman [FRI 89] para classificação de dados em alta dimensionalidade (dados sintéticos, dados de enologia), para o caso especifico de dados de sensoriamento remoto em alta dimensionalidade (imagens hiperespectrais). A conclusão principal desta dissertação é que o método RDA é útil no processo de classificação de imagens com dados em alta dimensionalidade e classes com características espectrais muito próximas.

Bacterial functional redundancy along a soil reclamation gradient

A strategy to measure bacterial functional redundancy was developed and tested with soils collected along a soil reclamation gradient by determining the richness and diversity of bacterial groups capable of in situ growth on selected carbon substrates. Soil cores were collected from four sites along a transect from the Jamari tin mine site in the Jamari National Forest, Rondonia, RO, Brazil: denuded mine spoil, soil from below the canopy of invading pioneer trees, revegetated soil under new growth on the forest edge, and the forest floor of an adjacent preserved forest. Bacterial population responses were analyzed by amending these soil samples with individual carbon substrates in the presence of bromodeoxyuridine (BrdU), BrdU-labeled DNA was then subjected to a 16S-23S rRNA intergenic analysis to depict the actively growing bacteria from each site, the number and diversity of bacterial groups responding to four carbon substrates (L-serine, L-threonine, sodium citrate, and or-lactose hydrate) increased along the reclamation-vegetation gradient such that the preserved forest soil samples contained the highest functional redundancy for each substrate. These data suggest that bacterial functional redundancy increases in relation to the regrowth of plant communities and may therefore represent an important aspect of the restoration of soil biological functionality to reclaimed mine spoils. They also suggest that bacterial functional redundancy may be a useful indicator of soil quality and ecosystem functioning.

Analysis and functional annotation of an expressed sequence tag collection for tropical crop sugarcane

To contribute to our understanding of the genome complexity of sugarcane, we undertook a large-scale expressed sequence tag (EST),program. More than 260,000 cDNA clones were partially sequenced from 26 standard cDNA libraries generated from different sugarcane tissues. After the processing of the sequences, 237,954 high-quality ESTs were identified. These ESTs were assembled into 43,141 putative transcripts. of the assembled sequences, 35.6% presented no matches with existing sequences in public databases. A global analysis of the whole SUCEST data set indicated that 14,409 assembled sequences (33% of the total) contained at least one cDNA clone with a full-length insert. Annotation of the 43,141 assembled sequences associated almost 50% of the putative identified sugarcane genes with protein metabolism, cellular communication/signal transduction, bioenergetics, and stress responses. Inspection of the translated assembled sequences for conserved protein domains revealed 40,821 amino acid sequences with 1415 Pfam domains. Reassembling the consensus sequences of the 43,141 transcripts revealed a 22% redundancy in the first assembling. This indicated that possibly 33,620 unique genes had been identified and indicated that >90% of the sugarcane expressed genes were tagged.