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

An integrated encyclopedia of DNA elements in the human genome.

The human genome encodes the blueprint of life, but the function of the vast majority of its nearly three billion bases is unknown. The Encyclopedia of DNA Elements (ENCODE) project has systematically mapped regions of transcription, transcription factor association, chromatin structure and histone modification. These data enabled us to assign biochemical functions for 80% of the genome, in particular outside of the well-studied protein-coding regions. Many discovered candidate regulatory elements are physically associated with one another and with expressed genes, providing new insights into the mechanisms of gene regulation. The newly identified elements also show a statistical correspondence to sequence variants linked to human disease, and can thereby guide interpretation of this variation. Overall, the project provides new insights into the organization and regulation of our genes and genome, and is an expansive resource of functional annotations for biomedical research