Copasetic analysis: a framework for the blind analysis of microarray imagery.

Syst Biol (Stevenage)

Department of Information Systems and Computing, Brunel University, Uxbridge, Middlesex, UK.

Published: June 2004

From its conception, bioinformatics has been a multidisciplinary field which blends domain expert knowledge with new and existing processing techniques, all of which are focused on a common goal. Typically, these techniques have focused on the direct analysis of raw microarray image data. Unfortunately, this fails to utilise the image's full potential and in practice, this results in the lab technician having to guide the analysis algorithms. This paper presents a dynamic framework that aims to automate the process of microarray image analysis using a variety of techniques. An overview of the entire framework process is presented, the robustness of which is challenged throughout with a selection of real examples containing varying degrees of noise. The results show the potential of the proposed framework in its ability to determine slide layout accurately and perform analysis without prior structural knowledge. The algorithm achieves approximately, a 1 to 3 dB improved peak signal-to-noise ratio compared to conventional processing techniques like those implemented in GenePix when used by a trained operator. As far as the authors are aware, this is the first time such a comprehensive framework concept has been directly applied to the area of microarray image analysis.

Download full-text PDF

Source
http://dx.doi.org/10.1049/sb:20045002DOI Listing

Publication Analysis

Top Keywords

microarray image
12
processing techniques
8
techniques focused
8
image analysis
8
analysis
6
framework
5
copasetic analysis
4
analysis framework
4
framework blind
4
blind analysis
4

Similar Publications

Small interfering RNAs (siRNAs) have been successfully used as therapeutics to silence disease-causing genes when conjugated to ligands or formulated in lipid nanoparticles to target relevant cell types for efficacy while sparing other cells for safety. To support the development of new methods for delivery of siRNA therapeutics, we developed and characterized a panel of antibodies generated against chemically modified nucleotides used in therapeutic siRNA molecules, identifying a monoclonal antibody that detects a broad range of siRNA representing distinct sequences and modification patterns. By integrating this anti-siRNA antibody with additional reagents, we created a multiplex siRNA immunoassay that simultaneously quantifies siRNA uptake, trafficking, and silencing activity.

View Article and Find Full Text PDF

Spatial profiling of endoplasmic reticulum stress markers in tumor associated cells predicts patient outcomes in pancreatic cancer.

Neoplasia

January 2025

Children's Cancer Institute, Lowy Cancer Research Centre, University of New South Wales, Sydney, NSW 2031, Australia; School of Clinical Medicine, Faculty of Medicine & Health, University of New South Wales, Kensington, New South Wales 2031, Australia; UNSW Centre for Childhood Cancer Research, Faculty of Medicine &Health, University of New South Wales, Kensington, New South Wales 2031, Australia; Australian Centre for NanoMedicine, University of New South Wales, Sydney, NSW 2031, Australia. Electronic address:

Introduction: The impact of endoplasmic reticulum (ER) stress in tumor-associated cells, such as cancer associated fibroblasts (CAFs), immune cells and endothelial cells, on patient outcomes in clinical specimens have not been examined. For the first time, we characterized the expression and spatial locations of ER stress markers, BiP and CHOP, in tumor-associated cells and assessed their prognostic significance in a panel of pancreatic ductal adenocarcinoma (PDAC) patient samples.

Methods: Multiplex immunofluorescence was performed on tumor microarrays and images were analyzed using HALO AI software.

View Article and Find Full Text PDF

Isocitrate dehydrogenase wild-type glioblastoma (GBM) is characterised by a heterogeneous genetic landscape resulting from dynamic competition between tumour subclones to survive selective pressures. Improvements in metabolite identification and metabolome coverage have led to increased interest in clinically relevant applications of metabolomics. Here, we use liquid chromatography-mass spectrometry and gene expression microarray to profile integrated intratumour metabolic heterogeneity, as a direct functional readout of adaptive responses of subclones to the tumour microenvironment.

View Article and Find Full Text PDF

Penile cancer (PeCa) is a rare disease with poor prognosis in the metastatic stage. Neither effective adjuvant nor palliative therapeutic options are available. Research efforts in this field have so far failed to establish robust predictors of survival.

View Article and Find Full Text PDF

Massively parallel homogeneous amplification of chip-scale DNA for DNA information storage (MPHAC-DIS).

Nat Commun

January 2025

School of Chemistry and Chemical Engineering, New Cornerstone Science Laboratory, Frontiers Science Center for Transformative Molecules, National Center for Translational Medicine, Shanghai Jiao Tong University, Shanghai, China.

Chip scale DNA synthesis offers a high-throughput and cost-effective method for large-scale DNA-based information storage. Nevertheless, unbiased information retrieval from low-copy-number sequences remains a barricade that largely arises from the indispensable DNA amplification. Here, we devise a simulation-guided quantitative primer-template hybridization strategy to realize massively parallel homogeneous amplification of chip-scale DNA for DNA information storage (MPHAC-DIS).

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!