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Autor:
Giulia Paciello, Elisa Ficarra
Publikováno v:
BMC Bioinformatics
Background Latest Next Generation Sequencing technologies opened the way to a novel era of genomic studies, allowing to gain novel insights into multifactorial pathologies as cancer. In particular gene fusion detection and comprehension have been dee
Publikováno v:
BMC Bioinformatics
Background Numerous publications attempt to predict cancer survival outcome from gene expression data using machine-learning methods. A direct comparison of these works is challenging for the following reasons: (1) inconsistent measures used to evalu
Publikováno v:
BMC Bioinformatics
Background Gene expression connectivity mapping has gained much popularity recently with a number of successful applications in biomedical research testifying its utility and promise. Previously methodological research in connectivity mapping mainly
Autor:
Charles Coutant, Roberto Incitti, Benoît Charles, Kai Yan, Lajos Pusztai, Euler Guimarães Horta, Fabrice Andre, René Natowicz, Philippe Guinot, Roman Rouzier
Publikováno v:
BMC Bioinformatics
BMC Bioinformatics, Vol 9, Iss 1, p 149 (2008)
BMC Bioinformatics, Vol 9, Iss 1, p 149 (2008)
Background DNA microarray technology has emerged as a major tool for exploring cancer biology and solving clinical issues. Predicting a patient's response to chemotherapy is one such issue; successful prediction would make it possible to give patient
Autor:
Andrew D. Smith, Hiroyuki Aburatani, Atsushi Niida, Michael Q. Zhang, Seiya Imoto, Tetsu Akiyama
Publikováno v:
BMC Bioinformatics
BMC Bioinformatics, Vol 10, Iss 1, p 71 (2009)
BMC Bioinformatics, Vol 10, Iss 1, p 71 (2009)
Background Although microarray-based studies have revealed global view of gene expression in cancer cells, we still have little knowledge about regulatory mechanisms underlying the transcriptome. Several computational methods applied to yeast data ha
Autor:
Abdul Rawoof, Vinod Kumar Verma, Mohammed M. Idris, Rimpi Khurana, Lekha Dinesh Kumar, Rekha A Nair, Ganesh Mahidhara, Alan Richard Clarke, Shrish Tiwari
Publikováno v:
BMC Bioinformatics
Background Given the estimate that 30% of our genes are controlled by microRNAs, it is essential that we understand the precise relationship between microRNAs and their targets. OncomiRs are microRNAs (miRNAs) that have been frequently shown to be de
Publikováno v:
BMC Bioinformatics
Background Many calssifiers which are constructed with chosen gene markers have been proposed to forecast the prognosis of patients who suffer from breast cancer. However, few of them has been applied in clinical practice because of the bad generaliz
Autor:
Shuangge Ma, Michael R. Kosorok
Publikováno v:
BMC Bioinformatics
BMC Bioinformatics, Vol 11, Iss 1, p 1 (2010)
BMC Bioinformatics, Vol 11, Iss 1, p 1 (2010)
Background Prognosis is of critical interest in breast cancer research. Biomedical studies suggest that genomic measurements may have independent predictive power for prognosis. Gene profiling studies have been conducted to search for predictive geno