Research Article

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Flowering gene; Flowering locus T; Gene expression; Phalaenopsis; Spike induction

The influence of warm day and cool night conditions on induction of spikes in Phalaenopsis orchids has been studied with respect to photosynthetic efficiency, metabolic cycles and physiology. However, molecular events involved in spike emergence induced by warm day and cool night conditions are not clearly understood. We examined gene expression induced by warm day and cool night ... more

D.M. Li; F.B. Lǚ; G.F. Zhu; Y.B. Sun; Y.C. Xu; M.D. Jiang; J.W. Liu; Z. Wang
Chromobacterium violaceum; Gene expression; Gene regulation; RNA processing; Transcription; Translation

The repertoire of 4,431 open reading frames (ORFs), eight rRNA operons and 98 tRNA genes of Chromobacterium violaceum must be expressed in a regulated manner for successful adaptation to a wide variety of environmental conditions. To accomplish this feat, the organism relies on protein machineries involved in transcription, RNA processing and translation. Analysis of the C. violaceum ... more

R. Silva; J.R. Araripe; E. Rondinelli; T.P. Ürményi
Double-stranded RNA (dsRNA); Gene expression; RNA interference; Trypanosoma

Mechanisms controlling gene expression in trypanosomatids depend on several layers of regulation, with most regulatory pathways acting at a post-transcriptional level. Consequently, these parasites can follow the rapid changes associated with transitions between the insect vector and the mammalian host, with instant reprogramming of genetic expression. Using primarily Trypanosoma ... more

S.M.R. Teixeira; W.D. da Rocha
Clustering; Gene expression; Gene-gene interactions; Supervised learning

We show here an example of the application of a novel method, MUTIC (model utilization-based clustering), used for identifying complex interactions between genes or gene categories based on gene expression data. The method deals with binary categorical data which consist of a set of gene expression profiles divided into two biologically meaningful categories. It does not require data ... more

L.S. Coelho; M.A. Mudado; B. Goertzel; C. Pennachin
Bioinformatics tool; Comparative genomic hybridization; DNA microarray; Gene expression; Genomic shotgun libraries; Optimal clones

In DNA microarray experiments, the gene fragments that are spotted on the slides are usually obtained by the synthesis of specific oligonucleotides that are able to amplify genes through PCR. Shotgun library sequences are an alternative to synthesis of primers for the study of each gene in the genome. The possibility of putting thousands of gene sequences into a single slide allows the ... more

M.E. Cantão; J.E. Ferreira; E.G.M. Lemos
Co-regulation; Escherichia coli; Gene expression; Microarray analysis; Partial correlation; Transcriptional regulation

Transcriptional control is an essential regulatory mechanism employed by bacteria. Much about transcriptional regulation remains to be discovered, even for the most widely studied bacterium, Escherichia coli. In the present study, we made a genome-wide low-order partial correlation analysis of E. coli microarray data with the purpose of recovering regulatory ... more

D.F.T. Veiga; F.F.R. Vicente; M. Grivet; A. de la Fuente; A.T.R. Vasconcelos
Functional annotation; Gene expression; Tag classification; Web-based bioinformatics tool

Serial analysis of gene expression (SAGE) technology produces large sets of interesting genes that are difficult to analyze directly. Bioinformatics tools are needed to interpret the functional information in these gene sets. We present an interactive web-based tool, called Gene Class, which allows functional annotation of SAGE data using the Gene Ontology (GO) database. This tool ... more

G.S.P. Pereira; R.M. Brandão; S. Giuliatti; M.A. Zago; W.A. Silva
Bayesian bootstrap; Bioinformatics; Gene expression; Microarray; Statistics; Web tool

One of the goals of gene expression experiments is the identification of differentially expressed genes among populations that could be used as markers. For this purpose, we implemented a model-free Bayesian approach in a user-friendly and freely available web-based tool called BayBoots. In spite of a common misunderstanding that Bayesian and model-free approaches are incompatible, ... more

R.Z.N. Vêncio; D.F.C. Patrão; C.S. Baptista; C.A.B. Pereira; B. Zingales
Feature selection; Gene expression; Genetic algorithms; Microarrays; Multi-class SVM

Microarrays are a new technology that allows biologists to better understand the interactions between diverse pathologic state at the gene level. However, the amount of data generated by these tools becomes problematic, even though data are supposed to be automatically analyzed (e.g., for diagnostic purposes). The issue becomes more complex when the expression data involve multiple ... more

B.Feres de Souza; A.Ponce de L. de Carvalho
C4ST-1; Chondroitin sulfate; CHST11; cis-regulatory modules; Gene expression; TGFβ

Chondroitin-4-sulfotransferase-1(C4ST-1)/carbohydrate sul­fotransferase 11 (CHST11) is a Golgi-bound enzyme involved in the biosyn­thesis of the glycosaminoglycan chondroitin sulfate. The sulfation pattern of chondroitin is tightly regulated during development, injury and disease, with the temporal and spatial expression of chondroitin sulfotransferase genes be­lieved to be a crucial ... more

C.M. Willis; J.L. Wrana; M. Klüppel