A biophysical approach to large-scale protein-DNA binding data

About this book * Cutting-edge genome analysis methods from leading bioinformaticians An accurate description of current scientific developments in the field of bioinformatics and computational implementation is presented by research of the BioSapiens Network of Excellence. Bioinformatics is essential for annotating the structure and function of genes, proteins and the analysis of complete genomes and to molecular biology and biochemistry. Included is an overview of bioinformatics, the full spectrum of genome annotation approaches including; genome analysis and gene prediction, gene regulation analysis and expression, genome variation and QTL analysis, large scale protein annotation of function and structure, annotation and prediction of protein interactions, and the organization and annotation of molecular networks and biochemical pathways. Also covered is a technical framework to organize and represent genome data using the DAS technology and work in the annotation of two large genomic sets: HIV/HCV viral genomes and splicing alternatives potentially encoded in 1% of the human genome

PQ TREES, CONSECUTIVE ONES PROBLEM AND APPLICATIONS

A PQ tree is an advanced tree–based data structure, which represents a family of permutations on a set of elements. In this research article, we considered the significance of PQ trees and the Consecutive ones Problem to Computer Science and bioinformatics and their various applications. We also went further to demonstrate the operations of the characteristics of the Consecutive ones property by simulation, using high level programming languages. Attempt was also made at developing a PQ tree–Consecutive Ones analyzer, which could be instrumental not only as an educative tool to inquisitive students, but also serve as an important tool in developing clustering software in the field of bioinformatics and other application domains, with respect to solving real life problems

A multi-view approach to cDNA micro-array analysis

The official published version can be obtained from the link below.Microarray has emerged as a powerful technology that enables biologists to study thousands of genes simultaneously, therefore, to obtain a better understanding of the gene interaction and regulation mechanisms. This paper is concerned with improving the processes involved in the analysis of microarray image data. The main focus is to clarify an image's feature space in an unsupervised manner. In this paper, the Image Transformation Engine (ITE), combined with different filters, is investigated. The proposed methods are applied to a set of real-world cDNA images. The MatCNN toolbox is used during the segmentation process. Quantitative comparisons between different filters are carried out. It is shown that the CLD filter is the best one to be applied with the ITE.This work was supported in part by the Engineering and Physical Sciences Research Council (EPSRC) of the UK under Grant GR/S27658/01, the National Science Foundation of China under Innovative Grant 70621001, Chinese Academy of Sciences under Innovative Group Overseas Partnership Grant, the BHP Billiton Cooperation of Australia Grant, the International Science and Technology Cooperation Project of China under Grant 2009DFA32050 and the Alexander von Humboldt Foundation of Germany

Development of position tracking of BLDC motor using adaptive fuzzy logic controller

The brushless DC (BLDC) motor has many advantages including simple to construct, high torque capability, small inertia, low noise and long life operation. Unfortunately, it is a non-linear system whose internal parameter values will change slightly with different input commands and environments. In this proposed controller, Takagi-Sugeno-Kang method is developed. In this project, a FLC for position tracking and BLDC motor are modeled and simulated in MATLAB/SIMULINK. In order to verify the performance of the proposed controller, various position tracking reference are tested. The simulation results show that the proposed FLC has better performance compare the conventional PID controller

Analysis of Microarray Data to Confirm Novel Subtype of Breast Cancer

Microarray data of 1,056 breast tumors from NCBI\u27s GEO database were collected and analyzed. The goal was to discover microarrays most similar to a potentially novel subtype of breast cancer characterized by low claudin expression. Claudins form tight junctions, which regulate cell-cell movement of solutes and ions; faulty tight junctions have been correlated with cancer metastasis. Results showed little support for a Claudin-Low cluster. Nine clusters were found, when 5-6 were expected. These additional clusters may reveal novel subtypes