Barbara Di Camillo

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Predicting protein function has become increasingly demanding in the era of next generation sequencing technology. The task to assign a curator-reviewed function to every single sequence is impracticable. Bioinformatics tools, easy to use and able to provide automatic and reliable annotations at a genomic scale, are necessary and urgent. In this scenario,(More)
BACKGROUND Reconstructing regulatory networks from gene expression profiles is a challenging problem of functional genomics. In microarray studies the number of samples is often very limited compared to the number of genes, thus the use of discrete data may help reducing the probability of finding random associations between genes. RESULTS A quantization(More)
BACKGROUND Microarray time series studies are essential to understand the dynamics of molecular events. In order to limit the analysis to those genes that change expression over time, a first necessary step is to select differentially expressed transcripts. A variety of methods have been proposed to this purpose; however, these methods are seldom applicable(More)
MOTIVATION Recent developments in experimental methods facilitate increasingly larger signal transduction datasets. Two main approaches can be taken to derive a mathematical model from these data: training a network (obtained, e.g., from literature) to the data, or inferring the network from the data alone. Purely data-driven methods scale up poorly and(More)
We present a novel Reverse Engineering algorithm, CNET, to reconstruct Gene Regulatory Networks from microarray time series data. CNET can be considered an improvement of the Mutual Information approach, present in the REVEAL [5] algorithm, with an innovative scoring function, to cope with noise, quantization errors and gene characteristic transcription(More)
Multifactorial diseases arise from complex patterns of interaction between a set of genetic traits and the environment. To fully capture the genetic biomarkers that jointly explain the heritability component of a disease, thus, all SNPs from a genome-wide association study should be analyzed simultaneously. In this paper, we present Bag of Naïve Bayes(More)
Next-generation sequencing technologies have fostered an unprecedented proliferation of high-throughput sequencing projects and a concomitant development of novel algorithms for the assembly of short reads. In this context, an important issue is the need of a careful assessment of the accuracy of the assembly process. Here, we review the efficiency of a(More)
In the last decade, Next-Generation Sequencing technologies have been extensively applied to quantitative transcriptomics, making RNA sequencing a valuable alternative to microarrays for measuring and comparing gene transcription levels. Although several methods have been proposed to provide an unbiased estimate of transcript abundances through data(More)
Human T-cell leukemia virus type 1 is a human retrovirus endemic in many areas of the world. Although many studies indicated a key role of the viral protein Tax in the control of viral transcription, the mechanisms controlling HTLV-1 expression and its persistence in vivo are still poorly understood. To assess Tax effects on viral kinetics, we developed a(More)
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