Bioinformatics

Dysregulation of TFDP1 and of the cell cycle pathway in high-grade glioblastoma multiforme: a bioinformatic analysis

X. Lu, Lv, X. D., Ren, Y. H., Yang, W. D., Li, Z. B., Zhang, L., Bai, X. F., Lu, X., Lv, X. D., Ren, Y. H., Yang, W. D., Li, Z. B., Zhang, L., and Bai, X. F., Dysregulation of TFDP1 and of the cell cycle pathway in high-grade glioblastoma multiforme: a bioinformatic analysis, vol. 15, p. -, 2016.

Despite extensive research, the prognosis of high-grade glioblastoma multiforme (GBM) has improved only slightly because of the limited response to standard treatments. Recent advances (discoveries of molecular biomarkers) provide new opportunities for the treatment of GBM. The aim of the present study was to identify diagnostic biomarkers of high-grade GBM. First, we combined 3 microarray expression datasets to screen them for genes differentially expressed in patients with high-grade GBM relative to healthy subjects.

A discrete artificial bee colony algorithm for detecting transcription factor binding sites in DNA sequences

D. Karaboga, Aslan, S., Karaboga, D., Aslan, S., Karaboga, D., and Aslan, S., A discrete artificial bee colony algorithm for detecting transcription factor binding sites in DNA sequences, vol. 15, p. -, 2016.

The great majority of biological sequences share significant similarity with other sequences as a result of evolutionary processes, and identifying these sequence similarities is one of the most challenging problems in bioinformatics. In this paper, we present a discrete artificial bee colony (ABC) algorithm, which is inspired by the intelligent foraging behavior of real honey bees, for the detection of highly conserved residue patterns or motifs within sequences.

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