|Prediction of Protein-to-Protein Interactions|
C.Gilissen, P.Groot, P.Lucas, J.Veltman, A.GeurtsvanKessel and M.Egmont-Petersen
We use local extrema in microarray time series data as the basis for discretisation. By comparing discretised gene expressions using similarity functions, we discover putative protein-to-protein interactions. We validate the results by use of public true positive and true negative databases for protein-to-protein interactions and demonstrate the high predictiveness of these local extrema as a time series feature.
|Constructing Directed Metabolic Networks from Microarray Data|
J. M. Easton, T. N. Arvanitis, A. Peet and M. Viant
Although it has been several years since metabolic networks became a commonly used analysis technique in bioinformatics, the question of how best to construct them from experimental data is still not satisfactorily resolved. Here we present a method for the construction of directed metabolic networks from microarray datasets using an enhanced version of the KEGG LIGAND database.
|Biosensors using Surface Plasmon Resonance Dynamic Imaging|
J. Hottin, J. Spadavecchia, M. Canva, E. Maillart, M. Anger-Leroy and P. Kerourédan
We study the optical response of a SPRi detection system, characterizing temperature, stringency and time dependence of molecular interactions for the development of a DNA biochip. We are adapting this system and improve its robustness developing applications, as a 900 spots microarray identifying 65 mutations of the cystic fibrosis, for medical uses and industrial commercialization.
|A Novel Array-Based Assay for the Detection of IgG-Mediated Food Intolerance |
Andrew Macdonald, Michael J. Walker, Michael S. Walker and Julie G. Reeve
The Genarrayt 200+ Foods IgG test comprises of glass slides onto which 16 microarrays of over 200 different foods have been printed. Each microarray includes standards for quantitation and positive and negative controls for quality control. Food IgGs are detected by a novel fluorescent dye labelled anti-human IgG conjugate and results are measured using a laser scanner. Fluorescence intensity is directly proportional to antibody activity in the sample.
|Clinical Validation of a Protein Microarry Assay for Diagnostics of Autoimmune Disease|
S. Judice, D. Pawlak, H Appelhans, A. Frisse, M. Harvey and B. Stillman
We have developed an autoantigen microarray that will allow laboratories to measure the presence of autoantibobies associated with different collagenois and vasculitis-related autoimmune diseases for a single serum sample.
|Simplifying the Flow of Drug Discovery Data|
Dr. Jonathan M.R. Davies
Regardless of research disciplines, scientists need to easily reach the information pertinent to their research. Ideally this data access is easy. Researchers also need the ability to ‘move the data around’ to gain a better view or different perspective. This data manipulation needs to be straightforward. Incorporating the varying views and information required by different scientific disciplines is a considerable challenge.
|DNA Microarrays for Microbiological Diagnosis in Stem Cell Cultures|
F. Cobo, A. Nieto, P. Catalina, JL. Cortés, A. Barroso, C. Cabrera, R. Montes, A. Barnie and A. Concha
In stem cell cultures there is the possibility of infectious disease transmission to the recipients. Any microbial contamination of the donor`s biological products or introduced during the manufacturing process can potentially present a serious hazard to the recipients. The majority of potential contaminants are mycoplasma and other bacterias, yeasts and fungi. Moreover, viral and prion contamination of cell cultures and “feeder” cells is also a common risk.
|New Methods for Rapid Isothermal Amplification and Detection of Short DNA Sequences |
Goal: • Rapid, sensitive, specific, low tech, portable DNA diagnostic device
• Detection of clinical pathogens: SARS pathogen, Streptococcus pneumoniae, HSV I & II and biothreat agents: Bacillus anthracis, Brucella species
• Detection of single nucleotide polymorphisms (SNPs)
• Multiplexed detection format
|Biomathematical Information Compression and Signal Extraction for Gene Expression Microarray Data Analysis|
Sofiane Lariani, Elena Comelli, Patrick Descombes and Martin Grigorov
Gene expression Microarray data covers both signal (active key genes) and noise. A tentative to recognize any genes expression pattern without clearing the data is like recognizing faces and details on a jammed TV screen. Noise in this context can be related to fluctuation due to the experimental condition, to outliers, and also genes presenting no modulation between groups. In this work we present a biostatisticalmethod for noise filtering and statistical significance assessment.