A robust high-sensitivity algorithm for automated detection of proteins in two-dimensional electrophoresis gels

The automated interpretation of two-dimensional gel electrophoresis images used in protein separation and analysis presents a formidable problem in the detection and characterization of ill-defined spatial objects. We describe in this paper a hierarchical algorithm that provides a robust, high-sensitivity solution to this problem, which can be easily adapted to a variety of experimental situations. The software implementation of this algorithm functions as part of a complete package designed for general protein gel analysis applications

Serum biomarkers of Hepatitis B Virus infected liver and methods for detection thereof

The invention provides a method for detecting the presence of altered serum proteins in an Hepatitis B Virus (HBV)-infected patient with liver inflammation, comprising: obtaining a sample of serum from the patient; subjecting the sample to protein gel electrophoresis to separate proteins contained therein; staining proteins separated on the electrophoresis gel with silver nitrate solution; scanning the images of stained proteins into an image analysis scanner to obtain gel images; comparing the gel images to control samples of electrophoresis gels prepared from serum of normal patient and serum of HBV-infected patient with liver inflammation to determine whether the sample of serum from the patient contains specific serum proteins. This invention also provides serum protein biomarkers for the diagnosis of patients with HBV infection and liver inflammation.published_or_final_versio

Serum biomarkers of hepatitis b virus infected liver and methods for detection thereof

The invention provides a method for detecting the presence of altered serum proteins in an Hepatitis B Virus (HBV)-infected patient with liver inflammation, comprising: obtaining a sample of serum from the patient; subjecting the sample to protein gel electrophoresis to separate proteins contained therein; staining proteins separated on the electrophoresis gel with silver nitrate solution; scanning the images of stained proteins into an image analysis scanner to obtain gel images; comparing the gel images to control samples of electrophoresis gels prepared from serum of normal patient and serum of HBV-infected patient with liver inflammation to determine whether the sample of serum from the patient contains specific serum proteins. This invention also provides serum protein biomarkers for the diagnosis of patients with HBV infection and liver inflammation.published_or_final_versio

Serum Biomarkers Of Hepatitis B Virus Infected Liver And Methods For Detection Thereof

The Invention Provides A Method For Detecting The Presence Of Altered Serum Proteins In An Hepatitis B Virus (Hbv)-Infected Patient With Liver Inflammation, Comprising: Obtaining A Sample Of Serum From The Patient; Subjecting The Sample To Protein Gel Electrophoresis To Separate Proteins Contained Therein; Staining Proteins Separated On The Electrophoresis Gel With Silver Nitrate Solution; Scanning The Images Of Stained Proteins Into An Image Analysis Scanner To Obtain Gel Images; Comparing The Gel Images To Control Samples Of Electrophoresis Gels Prepared From Serum Of Normal Patient And Serum Of Hbv-Infected Patient With Liver Inflammation To Determine Whether The Sample Of Serum From The Patient Contains Specific Serum Proteins. This Invention Also Provides Serum Protein Biomarkers For The Diagnosis Of Patients With Hbv Infection And Liver Inflammation.published_or_final_versio

SERUM BIOMARKERS OF HEPATITIS B VIRUS INFECTED LIVER AND METHODS FOR DETECTION THEREOF

The invention provides a method for detecting the presence of altered serum proteins in an Hepatitis B Virus (HBV)-infected patient with liver inflammation, comprising: obtaining a sample of serum from the patient; subjecting the sample to protein gel electrophoresis to separate proteins contained therein; staining proteins separated on the electrophoresis gel with silver nitrate solution; scanning the images of stained proteins into an image analysis scanner to obtain gel images; comparing the gel images to control samples of electrophoresis gels prepared from serum of normal patient and serum of HBV-infected patient with liver inflammation to determine whether the sample of serum from the patient contains specific serum proteins. This invention also provides serum protein biomarkers for the diagnosis of patients with HBV infection and liver inflammation.published_or_final_versio

A Novel Gaussian Extrapolation Approach for 2D Gel Electrophoresis Saturated Protein Spots

Analysis of images obtained from two-dimensional gel electrophoresis (2D-GE) is a topic of utmost importance in bioinformatics research, since commercial and academic software available currently has proven to be neither completely effective nor fully automatic, often requiring manual revision and refinement of computer generated matches. In this work, we present an effective technique for the detection and the reconstruction of over-saturated protein spots. Firstly, the algorithm reveals overexposed areas, where spots may be truncated, and plateau regions caused by smeared and overlapping spots. Next, it reconstructs the correct distribution of pixel values in these overexposed areas and plateau regions, using a two-dimensional least-squares fitting based on a generalized Gaussian distribution. Pixel correction in saturated and smeared spots allows more accurate quantification, providing more reliable image analysis results. The method is validated for processing highly exposed 2D-GE images, comparing reconstructed spots with the corresponding non-saturated image, demonstrating that the algorithm enables correct spot quantificatio

Application of multivariate data analysis for the classification of two dimensional gel images in Neuroproteomics

Two-dimensional gel electrophoresis (2DE) still plays a key role in proteomics for exploring the protein content of complex biological mixtures. However, the development of fully automatic strategies in extracting interpretable information from gel images is still a challenging task. In this work, we present a computational strategy aiming at an automatic classification of the discriminant patterns emerging from separation images intended as fingerprints of the correspondent biological conditions. The method was applied to gel images acquired in a study on motor neuron diseases: 33 2DE maps generated from samples of cerebrospinal fluid were processed (26 pathologic and 7 control subjects). Quantitative image descriptors were extracted and fitted to a partial least squares-discriminant analysis (PLSDA) assessing the chance to classify the samples. Moreover, the model was able to identify gel areas that most differ through the clinical categories. Combining multivariate statistical techniques with 2DEs may represent a valid tool to extract informative protein patterns. This kind of approach can contribute to the development of a system of screening to discriminate different clinical conditions on the basis of the overall patterns emerging from the maps, representing a useful complementary analysis in the routine of a proteomic laboratory. © 2011 Mazzara S, et al