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Bioinformática : Aplicaciones a la proteómica y genómica Colegio de Postgraduados
Riaño Pachón, Diego Mauricio; González Estrada, Elizabeth; Alexa, Adrian; Ramírez, Fidel; Vischi Winck, Flavia; Gómez Merino, Fernando, Coord.; Silva Rojas, Hilda Victoria, Coord.; Pérez Rodríguez, Paulino, Coord..
En esta publicación intitulada “Bioinformática: aplicaciones a la genómica y proteómica” se detallan algunos de los avances más sobresalientes de los temas de genómica y proteómica, derivados de un curso internacional sobre el tema, organizado por el Colegio de Postgraduados. Estos avances incluyen aspectos de las dos ciencias ómicas, incluyendo genómica y biología estructural, código R, análisis comparativo y evolución, agrupamiento y minería de datos en R, redes de interacciones entre proteínas y proteómica bioinformática. BIOINFORMATICS : APPLICATIONS TO GENOMICS AND PROTEOMICS. ABSTRACT : In this publication entitled "Bioinformatics: applications to genomics and proteomics" are some of the most salient issues of genomics and proteomics, derived from an...
Tipo: Libro Palavras-chave: Bioinformática; Proteómica; Genómica; ADN; Proteínas; Modelación; Simulación; Análisis de genómas; Biología estructural; Código R; Análisis comparativo; Minería de datos; Computación aplicada; Bioinformatics; Proteomics; DNA; Proteins; Models; Genomics; Simulation; R Code; Data mining; Computing; Genome analysis.
Ano: 2010 URL: http://hdl.handle.net/10521/313
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Data mining and influential analysis of gene expression data for plant resistance gene identification in tomato (Solanum lycopersicum) Electron. J. Biotechnol.
Torres-Avilés,Francisco; Romeo,José S; López-Kleine,Liliana.
Background Molecular mechanisms of plant-pathogen interactions have been studied thoroughly but much about them is still unknown. A better understanding of these mechanisms and the detection of new resistance genes can improve crop production and food supply. Extracting this knowledge from available genomic data is a challenging task. Results Here, we evaluate the usefulness of clustering, data-mining and regression to identify potential new resistance genes. Three types of analyses were conducted separately over two conditions, tomatoes inoculated with Phytophthora infestans and not inoculated tomatoes. Predictions for 10 new resistance genes obtained by all applied methods were selected as being the most reliable and are therefore reported as potential...
Tipo: Journal article Palavras-chave: Classification; Data mining; Functional gene prediction; GEE models; Gene expression data; Plant immunity genes.
Ano: 2014 URL: http://www.scielo.cl/scielo.php?script=sci_arttext&pid=S0717-34582014000200004
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A legume genomics resource: The Chickpea Root Expressed Sequence Tag Database Electron. J. Biotechnol.
Jayashree,B; Buhariwalla,Hutokshi K; Shinde,Sanjeev; Crouch,Jonathan H.
Chickpea, a lesser-studied grain legume, is being investigated due to its taxonomic proximity with the model legume genome Medicago truncatula and its ability to endure and grow in relatively low soil water contents making it a model legume crop for the study of agronomic response to drought stress. Public databases currently contain very few sequences from chickpea associated with expression in root tissues. However, root traits are likely to be one of the most important components of drought tolerance in chickpea. Thus, we have generated a set of over 2800 chickpea expressed sequence tags (ESTs) from a library constructed after subtractive suppressive hybridization (SSH) of root tissue from two closely related chickpea genotypes possessing different...
Tipo: Journal article Palavras-chave: Cloning; Data mining; Drought avoidance; Drought tolerance; EST database; Root traits; Stress.
Ano: 2005 URL: http://www.scielo.cl/scielo.php?script=sci_arttext&pid=S0717-34582005000200002
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IDENTIFICATION OF HOMOGENEOUS RAINFALL ZONES DURING GRAIN CROPS IN PARANÁ, BRAZIL REA
Lopes,Allan R.; Marcolin,Jonatas; Johann,Jerry A.; Boas,Márcio A. Vilas; Schuelter,Adilson R..
ABSTRACT The aim of this study is to identify homogeneous rainfall zones in the winter and summer 1st and 2nd crops, in the state of Paraná, Brazil. The zones were defined by clustering using the expectation-maximization (EM) algorithm to transform seasonal rainfall series. Monthly average rainfall data collected from 157 weather stations for 20 years (1996 to 2015) were employed. The results show that the number of homogeneous zones varied among growing seasons. The summer crop presented two clusters, with rainfall averages of 1489 and 1925 mm; the second crop presented four clusters, with averages of 1849, 1004, 1454, and 1182 mm; and the winter crop had three clusters, with averages of 969, 1498, and 1171 mm. Clustering was a useful instrument to...
Tipo: Info:eu-repo/semantics/article Palavras-chave: Data mining; Clusters; Expectation-maximization; Weka; Soybean; Maize; Wheat.
Ano: 2019 URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0100-69162019000600707
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COMPARATIVE ASSESSMENT BETWEEN PER-PIXEL AND OBJECT-ORIENTED FOR MAPPING LAND COVER AND USE REA
Prudente,Victor H. R.; Silva,Bruno B. da; Johann,Jerry A.; Mercante,Erivelto; Oldoni,Lucas V..
ABSTRACT: The traditional per-pixel classification methods consider only spectral information, and may be limited. Object-based classifiers, however, also consider shape and texture, firstly segmenting the image, and then classifying individual objects. Thus, a Geographic Object-Based Image Analysis (GEOBIA) was compared in conjunction with data mining techniques and a traditional per-pixel method. A cut of Landsat-8, bands 2 to 7, orbit/point 223/77, located between the municipalities of Cascavel, Corbélia, Cafelândia and Tupãssi, in the west part of the state of Paraná, from 12/18/2013 was used. In the GEOBIA approach was realized image segmentation, spatial and spectral attribute extraction, and classification using the decision tree supervised...
Tipo: Info:eu-repo/semantics/article Palavras-chave: GeoDMA; Data mining; Decision tree.
Ano: 2017 URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0100-69162017000501015
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Large-scale analysis of NBS domain-encoding resistance gene analogs in Triticeae Genet. Mol. Biol.
Bouktila,Dhia; Khalfallah,Yosra; Habachi-Houimli,Yosra; Mezghani-Khemakhem,Maha; Makni,Mohamed; Makni,Hanem.
Proteins containing nucleotide binding sites (NBS) encoded by plant resistance genes play an important role in the response of plants to a wide array of pathogens. In this paper, an in silico search was conducted in order to identify and characterize members of NBS-encoding gene family in the tribe of Triticeae. A final dataset of 199 sequences was obtained by four search methods. Motif analysis confirmed the general structural organization of the NBS domain in cereals, characterized by the presence of the six commonly conserved motifs: P-loop, RNBS-A, Kinase-2, Kinase-3a, RNBS-C and GLPL. We revealed the existence of 11 distinct distribution patterns of these motifs along the NBS domain. Four additional conserved motifs were shown to be significantly...
Tipo: Info:eu-repo/semantics/article Palavras-chave: NBS domain; Data mining; Phylogeny; Plant resistance genes; Triticeae.
Ano: 2014 URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1415-47572014000400017
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Looking for exceptions on knowledge rules induced from HIV cleavage data set Genet. Mol. Biol.
Prati,Ronaldo Cristiano; Monard,Maria Carolina; Carvalho,André C. P. L. F. de.
The aim of data mining is to find useful knowledge inout of databases. In order to extract such knowledge, several methods can be used, among them machine learning (ML) algorithms. In this work we focus on ML algorithms that express the extracted knowledge in a symbolic form, such as rules. This representation may allow us to ''explain'' the data. Rule learning algorithms are mainly designed to induce classification rules that can predict new cases with high accuracy. However, these sorts of rules generally express common sense knowledge, resulting in many interesting and useful rules not being discovered. Furthermore, the domain independent biases, especially those related to the language used to express the induced knowledge, could induce rules that are...
Tipo: Info:eu-repo/semantics/article Palavras-chave: Data mining; Exceptions; HIV; Protease.
Ano: 2004 URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1415-47572004000400027
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Identifying water stress-response mechanisms in citrus by in silico transcriptome analysis Genet. Mol. Biol.
Torres,Gisele A.M.; Gimenes,Marcos A.; Rosa Jr.,Vicente E. de; Quecini,Vera.
Water deficit is one of the most critical environmental stresses to which plants are submitted during their life cycle. The evolutionary and economic performance of the plant is affected directly by reducing its survival in the natural environment and its productivity in agriculture. Plants respond to water stress with biochemical and physiological modifications that may be involved in tolerance or adaptation mechanisms. A great number of genes have been identified as transcriptionally regulated for water deficit. EST sequencing projects provide a significant contribution to the discovery of expressed genes. The identification and determination of gene expression patterns is important not only to understand the molecular bases of plant responses but also...
Tipo: Info:eu-repo/semantics/article Palavras-chave: Environmental stress; CitEST; Data mining; Tolerance mechanisms; Water deficit.
Ano: 2007 URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1415-47572007000500018
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In silico identification of coffee genome expressed sequences potentially associated with resistance to diseases Genet. Mol. Biol.
Alvarenga,Samuel Mazzinghy; Caixeta,Eveline Teixeira; Hufnagel,Bárbara; Thiebaut,Flávia; Maciel-Zambolim,Eunize; Zambolimand,Laércio; Sakiyama,Ney Sussumu.
Sequences potentially associated with coffee resistance to diseases were identified by in silico analyses using the database of the Brazilian Coffee Genome Project (BCGP). Keywords corresponding to plant resistance mechanisms to pathogens identified in the literature were used as baits for data mining. Expressed sequence tags (ESTs) related to each of these keywords were identified with tools available in the BCGP bioinformatics platform. A total of 11,300 ESTs were mined. These ESTs were clustered and formed 979 EST-contigs with similarities to chitinases, kinases, cytochrome P450 and nucleotide binding site-leucine rich repeat (NBS-LRR) proteins, as well as with proteins related to disease resistance, pathogenesis, hypersensitivity response (HR) and...
Tipo: Info:eu-repo/semantics/article Palavras-chave: Coffea; Data mining; ESTs; Genomics; In silico; Bioinformatics.
Ano: 2010 URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1415-47572010000400031
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In silico analysis of the endogenous time-keeping mechanism in citrus Genet. Mol. Biol.
Quecini,Vera.
The endogenous time-keeping mechanism is responsible for organizing plant physiology and metabolism according to periodic environmental changes, such as diurnal cycles of light and dark and seasonal progression throughout the year. In plants, circadian rhythms control gene expression, stomatal opening, and the timing component of the photoperiodic responses, leading to enhanced fitness due to increased photosynthetic rates and biomass production. We have investigated the citrus genome databases of expressed sequence tags (EST) in order to identify genes coding for functionally characterized proteins involved in the endogenous time-keeping mechanism in Arabidopsis thaliana. Approximately 180,000 EST sequences from 53 libraries were investigated and 81...
Tipo: Info:eu-repo/semantics/article Palavras-chave: Central oscillator; Circadian clock; Data mining; Photoperiodic responses; Regulatory feedback loop.
Ano: 2007 URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1415-47572007000500008
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Identification of photoperception and light signal transduction pathways in citrus Genet. Mol. Biol.
Quecini,Vera.
Studies employing model species have elucidated several aspects of photoperception and light signal transduction that control plant development. However, the information available for economically important crops is scarce. Citrus genome databases of expressed sequence tags (EST) were investigated in order to identify genes coding for functionally characterized proteins responsible for light-regulated developmental control in model plants. Approximately 176,200 EST sequences from 53 libraries were queried and all bona fide and putative photoreceptor gene families were found in citrus species. We have identified 53 orthologs for several families of transcriptional regulators and cytoplasmic proteins mediating photoreceptor-induced responses although some...
Tipo: Info:eu-repo/semantics/article Palavras-chave: Cryptochrome; Data mining; Light signaling; Phototropin; Phytochrome.
Ano: 2007 URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1415-47572007000500007
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C4.5: um recurso para geração de árvores de decisão. Infoteca-e
BERNARDES, R. M..
O Sistema de Indução C4.5. Requerimentos-chave para a utilização do software. Um exemplo ilustrativo. Algumas dicas de uso.
Tipo: Séries anteriores (INFOTECA-E) Palavras-chave: Árvores de decisão; Mineração de dados; Data mining; KDD; Knowledge Discovery in Databases; Sistema de indução C4; 5.
Ano: 2001 URL: http://www.infoteca.cnptia.embrapa.br/infoteca/handle/doc/8304
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Identification of the autophagy pathway in a mollusk bivalve, Crassostrea gigas ArchiMer
Picot, Sandy; Faury, Nicole; Arzul, Isabelle; Chollet, Bruno; Renault, Tristan; Morga, Benjamin.
The Pacific oyster, Crassostrea gigas, is a mollusk bivalve commercially important as a food source. Pacific oysters are subjected to stress and diseases during culture. The autophagy pathway is involved in numerous cellular processes, including responses to starvation, cell death, and microorganism elimination. Autophagy also exists in C. gigas, and plays a role in the immune response against infections. Although this process is well-documented and conserved in most animals, it is still poorly understood in mollusks. To date, no study has provided a complete overview of the molecular mechanism of autophagy in mollusk bivalves. In this study, human and yeast ATG protein sequences and public databases (Uniprot and NCBI) were used to identify protein members...
Tipo: Text Palavras-chave: Autophagy; Autophagy related; Crassostrea gigas; Data mining; Immunohistochemistry; Real-time PCR; Western blot.
Ano: 2020 URL: https://archimer.ifremer.fr/doc/00606/71785/70270.pdf
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A regionally scalable habitat typology for assessing benthic habitats and fish communities: Application to New Caledonia reefs and lagoons ArchiMer
Pelletier, Dominique; Selmaoui‐folcher, Nazha; Bockel, Thomas; Schohn, Thomas.
Scalable assessments of biodiversity are required to successfully and adaptively manage coastal ecosystems. Assessments must account for habitat variations at multiple spatial scales, including the small scales (<100 m) at which biotic and abiotic habitat components structure the distribution of fauna, including fishes. Associated challenges include achieving consistent habitat descriptions and upscaling from in situ‐monitored stations to larger scales. We developed a methodology for (a) determining habitat types consistent across scales within large management units, (b) characterizing heterogeneities within each habitat, and (c) predicting habitat from new survey data. It relies on clustering techniques and supervised classification rules and was...
Tipo: Text Palavras-chave: Coral Sea Marine Park; Data mining; Habitat prediction; Habitat typology; In situ monitoring; Marine protected areas; Scaling up; Supervised classification rules; Underwater video.
Ano: 2020 URL: https://archimer.ifremer.fr/doc/00632/74433/74153.pdf
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Which parameters determine farm development in Germany? AgEcon
Roder, Norbert; Kilian, Stefan.
In 2005, Germany implemented the Single Payment Scheme which lead to the conversion of direct payments into tradable, production decoupled, single farm payments. The transition from coupled to decoupled support instruments may impact the rate of structural change. The rate of structural change may accelerate since farms with a high share of income derived from CAP payments will abandon farming and lease their land. However, there are also good reasons why the rate of structural change might decrease especially if farmers do not behave as profit maximizers. In Germany agricultural land use is very heterogeneous with respect to management orientation and productivity even at local level. Most of the concerns related to structural change and development of...
Tipo: Conference Paper or Presentation Palavras-chave: Structural change; Data mining; Fischler Reform; Agricultural and Food Policy; Q16; Q15; R14.
Ano: 2008 URL: http://purl.umn.edu/44788
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DATA MINING BASED MODEL AGGREGATION AgEcon
Szucs, Imre.
Applying modelling techniques for getting acquainted with customer behaviour, predicting the customers’ next step is neccessary to keep in competition, by decreasing the capital requirement (Basel II - IRB) or making the portfolio more profitable. According to the easily implementable modelling techniques, data mining solutions widespread in practice. Using these models with no conditions can lead into inconsistent future on portfolio change. Consequence of this situation, contradictory predictions and conclusions come into existence. Recognizing and conscious handling of inconsistent predictions is an important task for experts working on different scene of the knowledge based economy and society. By realizing and solving the problem of inconsistency in...
Tipo: Journal Article Palavras-chave: Model aggregation; Consistent future; Data mining; CRM; Basel II; Research and Development/Tech Change/Emerging Technologies.
Ano: 2007 URL: http://purl.umn.edu/58928
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MODEL TREE: AN APPLICATION IN REAL ESTATE APPRAISAL AgEcon
Acciani, Claudio; Fucilli, Vincenzo; Sardaro, Ruggiero.
In the last twenty years in real estate appraisal there has been a growing interest for new and reliable assessment techniques essentially through the introduction of pluriparametric estimate, in particular of linear regression. However, also these techniques seem having not a great deal of adherence to very complex markets, for which the detection of best suited techniques to investigate market segments is necessary. The aim of the research is to test the applicative possibilities of model tree to land market, in order to highlight possible market segments in the original data set not detectable a priori.
Tipo: Conference Paper or Presentation Palavras-chave: Data mining; Model tree; Multiple regression analysis; Land market appraisal; Research Methods/ Statistical Methods; C01.
Ano: 2008 URL: http://purl.umn.edu/44853
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Regional differences in the determinants for structural change in German agriculture AgEcon
Roeder, Norbert; Kilian, Stefan.
In Germany agricultural land use is very heterogeneous with respect to management orientation and productivity even at local level. Also the rate of structural change shows a wide variation. While for a limited number of factors (e.g. farm size) a stable relation to structural change could be widely confirmed for different parts of Germany, the results for other indicators are contradictory. This holds especially for indicators describing to the marginality of a site. Many concerns related to structural change and development of land use intensity, e.g. abandonment of high nature value farmland, are only relevant in a very specific local context. Therefore, it is necessary to establish indicators for farm development on a disaggregated level. This paper...
Tipo: Conference Paper or Presentation Palavras-chave: Structural change; Data mining; Regionalization; Agricultural and Food Policy; Land Economics/Use; Q10; Q15.
Ano: 2009 URL: http://purl.umn.edu/51463
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Boosted regression (boosting): An introductory tutorial and a Stata plugin AgEcon
Schonlau, Matthias.
Boosting, or boosted regression, is a recent data-mining technique that has shown considerable success in predictive accuracy. This article gives an overview of boosting and introduces a new Stata command, boost, that implements the boosting algorithm described in Hastie, Tibshirani, and Friedman (2001, 322). The plugin is illustrated with a Gaussian and a logistic regression example. In the Gaussian regression example, the R2 value computed on a test dataset is R2 = 21.3% for linear regression and R2 = 93.8% for boosting. In the logistic regression example, stepwise logistic regression correctly classifies 54.1% of the observations in a test dataset versus 76.0% for boosted logistic regression. Currently, boost accommodates Gaussian (normal), logistic,...
Tipo: Journal Article Palavras-chave: Boost; Boosted regression; Boosting; Data mining; Research Methods/ Statistical Methods.
Ano: 2005 URL: http://purl.umn.edu/117524
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Multiple-test procedures and smile plots AgEcon
Newson, Roger; The ALSPAC Study Team.
multproc carries out multiple-test procedures, taking as input a list of p-values and an uncorrected critical p-value, and calculating a corrected overall critical p-value for rejection of null hypotheses. These procedures define a confidence region for a set-valued parameter, namely the set of null hypotheses that are true. They aim to control either the family-wise error rate (FWER) or the false discovery rate (FDR) at a level no greater than the uncorrected critical p-value. smileplot calls multproc and then creates a smile plot, with data points corresponding to estimated parameters, the p-values (on a reverse log scale) on the y-axis, and the parameter estimates (or another variable) on the x-axis. There are y-axis reference lines at the uncorrected...
Tipo: Journal Article Palavras-chave: Smile plot; Multiple-test procedure; Closed testing procedure; Data mining; Family-wise error rate; False discovery rate; Bonferroni; Sidák; Holm; Holland; Copenhaver; Hochberg; Rom; Simes; Benjamini; Yekutieli; Krieger; Liu; Research Methods/ Statistical Methods.
Ano: 2003 URL: http://purl.umn.edu/116061
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