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Bioinformatics of Health and Disease

Bioinformatics of Health and Disease
Virtual Screening on HIV-1 Reverse Transcriptase Inhibitors
Jyotika Singh, Sudhir Kumar
Indian Agricultural Research Institute, India

Acquired Immunodeficiency Syndrome (AIDS) epidemic has affected human lives in both developed and developing countries equally. The causative agent for this dreaded disease is a virus called HIV (Human Immunodeficiency Virus). The enzyme reverse transcriptase (RT) plays an important role in its activity. High-throughput screening (HTS) has been advantageous over traditional methods of screening in

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Bioinformatics of Health and Disease
T2DM-GeneMiner a web resource for meta-analysis and marker identification for type 2 diabetes mellitus
Axel Rasche, Ralf Herwig
MPI Molecular Genetics, Germany

Multiple functional genomics data for type 2 diabetes mellitus we joined in a meta-analysis approach for scoring genes. We derived a set of 213 disease relevant genes, whereon functional information on cellular networks is extrapolated. A web interface allows screening of a gene in the underlying data.

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Bioinformatics of Health and Disease
PIDexpert , decision support system for immunodeficiencies
Crina Samarghitean, Kirsi Varpa, Kati Iltanen, Merja Helminen, Mauno Vihinen
Institute of Medical Technology, University of Tampere, Finland

PIDexpert is a medical expert system, which help physicians in the diagnosis and treatment of primary immunodeficiencies. It gives the diagnostic picture based on clinical history, physical findings and laboratory tests. PIDexpert includes a knowledge base, a query base, a knowledge acquisition system, an inference engine and a user interface.

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Bioinformatics of Health and Disease
Large­scale design of primers for genes from atypical plants
Imen Riani
Institut Pasteur de Tunis, Tunisia

Salinity is one of the principal barriers in the intensification of the cultivation of cereals. Currently several genes involved in the tolerance with salinity were characterized Arabidopsis,whereas little is known about these genes in cereals and others monocotyledones because of the lack of sequence data. We propose here the protocol for systematic bioinformatic analysis of the orthologs of Arabidopsis thaliana, Oryza sativa (abundantly studied) and Populus trichocarpa genes in plants (maize, tomato, citrus, olives, and dates), and to store the results in a database freely available via the Web.

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Bioinformatics of Health and Disease
A procedure to decompose high resolution mass spectra
Nicola Barbarini, Paolo Magni, Riccardo Bellazzi
University of Pavia, Italy

In the present work, we will propose a novel strategy to decompose high resolution SELDI/MALDI-TOF mass spectra obtained from a mixture of pepitdes/proteins by grouping together the mass/charge ratios corresponding to the same protein, exploiting the available knowledge on MS technique, chemistry of proteins and statistical considerations.

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Bioinformatics of Health and Disease
Computational Cancer Genomics from a Systems-Biologic Perspective: From Sequence and Function to Pathways and Networks
Jimmy Lin, Bert Vogelstein, Ken Kinzler, Laura Wood, Nickolas Papadopoulos , Will Parsons, Sian Jones, Susan Zhang, Tobias Sjoblom, Victor Velculescu, Giovanni Parmigiani , Christine Gan
Johns Hopkins Medical Institutions, United States

We present a comprehensive systems-biologic analysis of the breast and colorectal cancer genomes (Sjöblom et al. 2006). We identified top candidate sequence similarity clusters, protein domains, functional groups, protein-protein networks, interactome hubs, and pathways, that are likely to play a role in carcinogenesis and malignant progression.

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Bioinformatics of Health and Disease
A network of protein domains that are present in chimeric tyrosine-kinase proteins in cancer
Ińigo Ortiz de Mendibil Ayuso, José Luis Vizmanos , Francisco Novo
University of Navarra (UNAV), Spain

Because of the presence of fusion proteins, with TK activity, implicated in different types of tumors, a collection of gene-mapped translocation breakpoints was created, called TICdb. Using TICdb, a network of genes translocated in cancer was also created focused on the part of this network that includes genes coding for TKs.

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Bioinformatics of Health and Disease
A method for estimating the number of peaks in liquid chromatography-mass spectrometry data sets
Teresa Szczepinska, Sander Piersma, Marius Codrea, Jaap Heringa, Elena Marchiori
VU University Amsterdam, Netherlands

We propose a method for estimating the number of peaks in LC-MS data, to be used in algorithms for simultaneous peak detection and alignment based on clustering. The method can be embedded as a part of a computational tool for disease biomarker detection.

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Bioinformatics of Health and Disease
In silico knock out screening of the metabolic network of plasmodium falciparum to yield Potential Drug Targets
Segun Fatumo, Ezekiel Adebiyi
Covenant University, Nigeria

Plasmodium falciparum is responsible for nearly all malaria-related deaths. We constructed the metabolic network and developed a tool which analyzes metabolic pathways of plasmodium falciparum and then identify essential reactions/enzymes that may be considered as drug targets. Some reactions were identified as essential for survival or growth of the organism.

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Bioinformatics of Health and Disease
A Systematic Strategy for Large-Scale Analysis of Genotype-Phenotype Correlations
Paul Fisher,Cornelia Hedeler, Katherine Wolstencroft, Helen Hulme, Harry Noyes, Stephen Kemp, Robert Stevens, Andrew Brass
Univeristy of Manchester, United Kingdom

It is increasingly common to combine Quantitative Trait Loci and Microarray data to aid in the search for candidate genes responsible for phenotypic variation. Workflows provide a means for systematically processing these large datasets and represent a framework for the re-use and the explicit declaration of experimental methods.

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Bioinformatics of Health and Disease
Semi- supervised class discovery using quantitative phenotypes – CVD as a case study
Roy Navon, Israel Steinfeld, Zohar Yakhini, Diego Ardigo, Ivana Zavaroni
Agilent Tecnologies / Tel Aviv University, Israel

Genomic studies typically focus on comparing disease to healthy population. In our work, various parameters were stratified solely from healthy subjects including expression profiling of their PBM cells.
We present a semi-supervised class discovery, constraining the search space to patterns that respect an order induced by the rich quantitative annotations.


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