Search results for "Mining"
showing 10 items of 1730 documents
iSEE: Interactive SummarizedExperiment Explorer
2018
Data exploration is critical to the comprehension of large biological data sets generated by high-throughput assays such as sequencing. However, most existing tools for interactive visualisation are limited to specific assays or analyses. Here, we present the iSEE (Interactive SummarizedExperiment Explorer) software package, which provides a general visual interface for exploring data in a SummarizedExperiment object. iSEE is directly compatible with many existing R/Bioconductor packages for analysing high-throughput biological data, and provides useful features such as simultaneous examination of (meta)data and analysis results, dynamic linking between plots and code tracking for reproduci…
EvalMSA: A Program to Evaluate Multiple Sequence Alignments and Detect Outliers
2016
8 páginas, 3 figuras, 2 tablas.
ER+ Breast Cancers Resistant to Prolonged Neoadjuvant Letrozole Exhibit an E2F4 Transcriptional Program Sensitive to CDK4/6 Inhibitors
2018
AbstractPurpose: This study aimed to identify biomarkers of resistance to endocrine therapy in estrogen receptor–positive (ER+) breast cancers treated with prolonged neoadjuvant letrozole.Experimental Design: We performed targeted DNA and RNA sequencing in 68 ER+ breast cancers from patients treated with preoperative letrozole (median, 7 months).Results: Twenty-four tumors (35%) exhibited a PEPI score ≥4 and/or recurred after a median of 58 months and were considered endocrine resistant. Integration of the 47 most upregulated genes (log FC > 1, FDR < 0.03) in letrozole-resistant tumors with transcription-binding data showed significant overlap with 20 E2F4-regulated genes (P =…
Molecular, Biological and Structural Features of VL CDR-1 Rb44 Peptide, Which Targets the Microtubule Network in Melanoma Cells
2019
Microtubules are important drug targets in tumor cells, owing to their role in supporting and determining the cell shape, organelle movement and cell division. The complementarity-determining regions (CDRs) of immunoglobulins have been reported to be a source of anti-tumor peptide sequences, independently of the original antibody specificity for a given antigen. We found that, the anti-Lewis B mAb light-chain CDR1 synthetic peptide Rb44, interacted with microtubules and induced depolymerization, with subsequent degradation of actin filaments, leading to depolarization of mitochondrial membrane-potential, increase of ROS, cell cycle arrest at G2/M, cleavage of caspase-9, caspase-3 and PARP, …
Frequency and prognostic impact of ALK amplifications and mutations in the European Neuroblastoma Study Group (SIOPEN) high-risk neuroblastoma trial …
2021
Purpose: In neuroblastoma (NB), the ALK receptor tyrosine kinase can be constitutively activated through activating point mutations or genomic amplification. We studied ALK genetic alterations in high-risk (HR) patients on the HR-NBL1/SIOPEN trial to determine their frequency, correlation with clinical parameters, and prognostic impact. Materials and methods: Diagnostic tumor samples were available from 1,092 HR-NBL1/SIOPEN patients to determine ALK amplification status (n = 330), ALK mutational profile (n = 191), or both (n = 571). Results: Genomic ALK amplification (ALKa) was detected in 4.5% of cases (41 out of 901), all except one with MYCN amplification (MNA). ALKa was associated with …
Quantum clustering in non-spherical data distributions: Finding a suitable number of clusters
2017
Quantum Clustering (QC) provides an alternative approach to clustering algorithms, several of which are based on geometric relationships between data points. Instead, QC makes use of quantum mechanics concepts to find structures (clusters) in data sets by finding the minima of a quantum potential. The starting point of QC is a Parzen estimator with a fixed length scale, which significantly affects the final cluster allocation. This dependence on an adjustable parameter is common to other methods. We propose a framework to find suitable values of the length parameter σ by optimising twin measures of cluster separation and consistency for a given cluster number. This is an extension of the Se…
Discriminating graph pattern mining from gene expression data
2016
We consider the problem of mining gene expression data in order to single out interesting features that characterize healthy/unhealthy samples of an input dataset. We present and approach based on a network model of the input gene expression data, where there is a labelled graph for each sample. To the best of our knowledge, this is the first attempt to build a different graph for each sample and, then, to have a database of graphs for representing a sample set. Out main goal is that of singling out interesting differences between healthy and unhealthy samples, through the extraction of "discriminating patterns" among graphs belonging to the two different sample sets. Differently from the …
Application of Graph Clustering and Visualisation Methods to Analysis of Biomolecular Data
2018
In this paper we present an approach based on integrated use of graph clustering and visualisation methods for semi-supervised discovery of biologically significant features in biomolecular data sets. We describe several clustering algorithms that have been custom designed for analysis of biomolecular data and feature an iterated two step approach involving initial computation of thresholds and other parameters used in clustering algorithms, which is followed by identification of connected graph components, and, if needed, by adjustment of clustering parameters for processing of individual subgraphs.
EFMviz
2020
Elementary Flux Modes (EFMs) are a tool for constraint-based modeling and metabolic network analysis. However, systematic and automated visualization of EFMs, capable of integrating various data types is still a challenge. In this study, we developed an extension for the widely adopted COBRA Toolbox, EFMviz, for analysis and graphical visualization of EFMs as networks of reactions, metabolites and genes. The analysis workflow offers a platform for EFM visualization to improve EFM interpretability by connecting COBRA toolbox with the network analysis and visualization software Cytoscape. The biological applicability of EFMviz is demonstrated in two use cases on medium (Escherichia coli, iAF1…
Data mining approaches to identify biomineralization related sequences.
2015
Proteomics is an efficient high throughput technique developed to identify proteins from a crude extract using sequence homology. Advances in Next Generation Sequencing (NGS) have led to increase knowledge of several non-model species. In the field of calcium carbonate biomineralization, the paucity of available sequences (such as the ones of mollusc shells) is still a bottleneck in most proteomic studies. Indeed, this technique needs proteins databases to find homology. The aim of this study was to perform different data mining approaches in order to identify novel shell proteins. To this end, we disposed of several publicly non-model molluscs databases. Previously identified molluscan she…