28 research outputs found
Identification of two distinct Sp1- and RBF-1-like nuclear factors that bind to the upstream region of the human angiotensinogen promoter
Multiple DNA-protein interactions at the CpG island of the human pseudoautosomal geneMIC2
Effects of 8-oxo-7,8-dihydro-2′-deoxyguanosine on the binding of the transcription factor Sp1 to its cognate target DNA sequence (GC box)
Cleavage of transcription factor SP1 by caspases during anti-IgM-induced B-cell apoptosis
Super Paramagnetic Clustering of DNA Sequences
An unsupervised clustering of 4541 DNA sequences containing active promoter regions from vertebrate and arthropod classes (including their viral genes) was performed. All necessary information was solely gathered a priori from the DNA sequences by measuring frequencies of tri-nucleotides and tetra-nucleotides. We employed Super Paramagnetic Clustering, a novel clustering algorithm based on physical properties of an inhomogeneous granular ferromagnet. This method utilizes Swendsen-Wang cluster Monte Carlo simulations to distinguish clusters by measuring pairs of correlation functions from different resolutions. We identified two strongly separated clusters of human viral genes corresponding to the Epstein-Barr virus and the Herpes Simplex virus type 1. In addition, vertebrate and arthropod sequences were successfully separated into two different classes with merely 9.25% of arthropod sequences being misclassified. From a functional perspective, these sequences have high gene function correlations with sequences from the vertebrate cluster. By tuning a clustering parameter, Super Paramagnetic Clustering was able to classify vertebrate class further into two major clusters, from where a large number of housekeeping genes and tissue-specific genes were found respectively. The indications came from observation of gene expression function and consensus transcription factors which were found grouped together in specific positions of the DNA sequences