Affymetrix and Illumina in war path again as fresh patent litigation on microarray patents

Illumina and Affymetrix have been in a patent battle since 2004. In its second wave of patent infringement litigation cas against illumina filed in UK, Germany and US, Affymetrix has targeted technology offered by Solexa, the company acquired by Illumina in January 2007, as well as all of Illumina’s BeadArray(TM) products.

The new case is for patents 5,902,723, 6,403,320, 6,420,169, 6,576,42, 7,056,666, 0834575, 0853679, 0799897

Affymetrix previously sued Illumina for patent infringement in 2004 in the United States District Court for the District of Delaware. In March 2007, the jury returned a verdict in favor of Affymetrix.

Affymetrix has developed one of the industry’s strongest patent portfolios, featuring more than 400 patents granted in the U.S. and more than 40 patents granted in Europe.

More details on the case is available at Affymetrix Investor Website

Things have improved for Affymetrix this year, The company has aposted Q3 profits with the company’s revenues for the quarter increasing 12 per cent to $94.9m compared with $84.7m during the same period last year.

The results of these lawsuits could dramatically change the face of the DNA microarray market that has seen such growth due to the application of genetic information to drug discovery and ‘personalised medicine’.

 

Affymetrix launches Affymetrix University an education effort

Affymetrix  launched Affymetrix University, a series of courses that will be held throughout Europe and North America.

from Affy website

Santa Clara-based Affymetrix  said the courses give biologists a better understanding of how to design their microarray experiments successfully with appropriate quality control, and how to apply statistical methods to interpret biological results more effectively.

for more details check the Affymetrix website  

Affymetrix expands into personalized medicine The next big thing

Affymetrix expands into personalized medicine! Why because The next big thing in health care? is You the individual

personalized medicine is the place step every one wants to be. Roche recently went after Nimblegen for a small foothold in this developing ssicne field, Now its the turn of Affymetrix the leader in microarray DNA chips.

The company is trying to get ahead of the market curve by partnering with drug companies that are making precisely targeted medicines, tailored for patients who have specific gene variations

the company opened the Affymetrix Clinical Services Laboratory to analyze the genes in blood and saliva samples for pharmaceutical companies, diagnostic laboratory businesses and hospitals

Genetically Guided Treatment For Cancer

Two critical characteristics of breast cancer that are important to treatment can be identified by measuring gene expression in the tumor, a research team led by scientists at The University of Texas M. D. Anderson Cancer Center reports in Lancet Oncology online.

Researchers developed and validated a new genomic microarray test that identifies whether a tumor’s growth is fueled by the female hormone estrogen and the role of a growth factor receptor known as HER-2 that makes a tumor vulnerable to a specific drug.

“This is one important step towards personalized diagnosis and treatment planning based on an integrated genomic test of an individual tumor,” said senior author W. Fraser Symmans, M.D., associate professor in the M. D. Anderson Department of Pathology.

The Lancet Oncology paper results are the latest in an effort by the research team to develop a single test to quickly and efficiently determine the characteristics and vulnerabilities of a patient’s breast cancer and ultimately to guide treatment.

About 70 percent of breast cancers are estrogen-receptor positive and another 15 to 25 percent are human epidermal growth factor receptor-2 (HER-2) positive. Each receptor status requires different types of treatment.

“This moves us closer to developing an integrated single genomic test that could estimate the risk of cancer relapse after surgery, determine the ER and HER2 receptor status, and also gauge the sensitivity of the tumor to hormone therapy and chemotherapy,” says Lajos Pusztai, M.D., Ph.D., associate professor in the M. D. Anderson Department of Breast Medical Oncology, and team leader with Symmans.

Last fall, the group published a study showing that a genomic microarray test can also predict a patient’s response to chemotherapy. They also presented a paper in December showing that another genomic index predicts how an ER-positive patient will respond to hormonal therapy.

The study was funded by the National Cancer Institute, the Breast Cancer Research Foundation and the Goodwin Foundation.

Co-authors with Symmans and Pusztai are: first author Yun Gong, M.D., and Nour Sneige, M.D., of the M. D. Anderson Department of Pathology; Kai Yan, Keith Anderson, and Kenneth Hess, of the M. D. Anderson Department of Biostatistics; Feng Lin, M.D., Vicente Valero, M.D., Daniel Booser, M.D., Jaime Mejia, M.D., and Gabriel Hortobagyi, M.D., of the M. D. Anderson Department of Breast Medical Oncology; Christos Sotiriou, M.D., Ph.D., Institut Jules Bordet, Brussels, Belgium; Fabrice Andre, M.D., of Institut Gustave Roussy, Villejuif, France; Frankie Holmes, M.D., John Pippen Jr., M.D., and Svetislava Vukelja, M.D., of U.S. Oncology-Texas Oncology; Henry Gomez, M.D., of the Instituto Nacional de Enfermedades Neoplasicas, Lima, Peru; and Luis Barajas, M.D., Departmento de Ginecologia Oncologica, Instituto Mexicano del Seguro Social, Guadalajara, Mexico.

Contact: Scott Merville
University of Texas M. D. Anderson Cancer Center

NYIT Professor Discovers Next Generation of DNA and RNA Microarrays brings hopes of personalized medicine

A novel invention developed by a scientist from New York Institute of Technology (NYIT) could revolutionize biological and clinical research and may lead to treatments for cancer, AIDS, Alzheimer’s, diabetes, and genetic and infectious diseases.

The invention allows the immobilisation of intact. double-stranded, multi-stranded or alternative DNA or RNA and has the potential to revolutionise biological and clinical research by allowing scientists to duplicate the cell environment and experiment with human, bacterial and viral genes.

Since the discovery of DNA, biologists have worked to unlock the secrets of the human cell.

Scientist Dr. Claude E. Gagna, Ph.D., an associate professor at NYIT’s School of Health Professions, Behavioral and Life Sciences, discovered how to immobilize intact double-stranded (ds-), multi-stranded or alternative DNA and RNA on one microarray. This immobilization allows scientists to duplicate the environment of a cell, and study, examine and experiment with human, bacterial and viral genes. This invention provides the methodology to analyze more than 150,000 non-denatured genes.

The “Gagna/NYIT Multi-Stranded and Alternative DNA, RNA and Plasmid Microarray,” has been patented (#6,936,461) in the United States and is pending in Europe and Asia. Gagna’s discovery will help scientists understand how transitions in DNA structure regulate gene expression (B-DNA to Z-DNA), and how DNA-protein, and DNA-drug interactions regulate genes. The breakthrough can aid in genetic screening, clinical diagnosis, forensics, DNA synthesis-sequencing and biodefense.

“This patent represents a leap forward from conventional DNA microarrays that use hybridisation,” said Dr Gagna, associate professor of the New York Institute of Technology.

This will help pharmaceutical companies produce new classes of drugs that target genes, with fewer side effects,” Dr Gagna continued.

“It will lower the cost and increase the speed of drug discovery, saving millions of dollars.”

Since the invention of the DNA microarray in 1991, the technology has become one of the most powerful research tools for drug discovery research allowing scientist to perform thousands of experiments with incredible accuracy and speed. According to MarketResearch.com sales of DNA microarrays are expected to be higher than $5.3bn (€ bn) by 2009.

The technology hinges around a novel surface that increases the adherence of DNA to the microarray so that any type of nucleic acid can be anchored, unlike conventional arrays that allow only single-stranded DNA to be immobilised.

Additionally, Gagna has developed a novel surface that increases the adherence of the DNA to the microarray so that any type of nucleic acid can be anchored. Unlike conventional microarrays, which immobilize single-stranded DNA, scientists will now be able to “secure intact, non-denatured, unaltered ds-DNA, triplex-, quadruplex-, or pentaplex DNA onto the microarray,” says Gagna. “With this technology, one day we will have tailor-made molecular medicine for patients.”

“With this technology, one day we will have tailor-made molecular medicine for patients,” said Dr Gagna.

and sure the news site are buzzing with the discovery

read more about the research and the original article details at

Dr Gagna, associate professor of the New York Institute of Technology. and also at www.nyit.edu/dnamicroarrays


Microarray test to anlyse the role of estrogen in breast cancer

Two critical characteristics of breast cancer that are important to treatment can be identified by measuring gene expression in the tumor, a research team led by scientists at The University of Texas M. D. Anderson Cancer Center reports in Lancet Oncology online.

Researchers developed and validated a new genomic microarray test that identifies whether a tumor’s growth is fueled by the female hormone estrogen and the role of a growth factor receptor known as HER-2 that makes a tumor vulnerable to a specific drug. The status of these factors is now determined by pathology tests.

About 70 percent of breast cancers are estrogen-receptor positive and another 15 to 25 percent are human epidermal growth factor receptor-2 (HER-2) positive. Each receptor status requires different types of treatment.

Read the complete article that talkes about the revolutionary test that promises to chage the way cancer is treated

http://www.huliq.com/11047/er-and-her-2-status-of-breast-tumors 

standardization in microarray analysis software industry

scouting for the right software for the microarray analysis software , kept me thinkng why despite these software being used by scores or scientists no one has come forward to create what can be called as a standard for such software, the confusion rains in this field as one company’s software data do not work with another one and vice versa, For an industry like biology and drug discovery  that is trying to benefit from the knowledge of mathematics statitics and chemistry physics inability to port data across platform is a serious roadblock. there are standards such as MIAMe and MAGE but these are just data standards, not for softwares, I believe ther should be  something similar to ISO standards, SEI CMI etc.

majority of the newsgroup and forums are used by graduate and at times senor researchers to find out which is the best software to be used, I thought of starting a wiki page where researchers can post their comments and rate the products and compare the features against each other,

can open source ideals begin to give a real answer to biotech’s future

would it be possible to adopt the ideals of the open source in microarray development, there has been many research works that can be hailed as open source ideals in the biotechnology space, human genome project can be the perfect example, But apart from the few attempts by academia and non profits institutions there havnt been many attempts to look at this as a way forward, Microarray development can be termed as a lucrative field where such a coalition would accrue great benefits, By releasing the research works for others for free of cost it is possible to bring down the cost of microarray, there is no doubt that it would benefit the new research frontiers such as pharmacogenomics and toxicogenomics, by reducing the cost per array closer to any to other screening test currently adopted in hospitals or used by forensic labs. Microarray can also be used for reducing the costly PCR technique by closing in on a more focused number of genes to amplify from But it would mean that there has to be enough researchers out there who will be buying theses product in the first stage itself so as the company involved i such an audacious attempt would recover its cost and make profits to continue further work, thats a major hurdle to overcome, as custom microarray or at times even the existing one may not be useful to every researcher even if they are working on the same genome for example one person may be in toxicology research and the other in ecology or pure genetics even if they work on same genome the controls required and number of gene of interest would vary vastly across the spectrum, it may take a long time for the open source ideals to bear any fruit in this arena but that may be the way forward to bring meaningful results with less cost, till outsourcing can be a start for all things to come

 Abin paul Xavier

http://www.ocimumbio.com

microarray software

Ocimum Biosolutions is a life sciences R&D enabling company with three focus areas, BioIT, Microarrays and Research services. The Microarray division of Ocimum has been recently acquired from MWG Biotech. These include Catalog “OciChip”, Custom “OciChip” and microarray services.

Ocimum biosolutions offers an           Affymetrix compatable smicroarray software            microarray analysis software called Genowiz, An evaluation copy of the software is avaialble at http://www.coimumbio.com

Genowiz™

Genowiz™ is a powerful gene expression analysis program that has been designed to store, process and visualize gene expression data efficiently. It includes a suite of advanced analysis methods and allows researchers to select analysis methods appropriate for their dataset. Genowiz™ allows researchers to organize experimental information (MIAME), import data files quickly and easily, work with multiple experiments at the same time, import gene annotation files, pre-process and normalize data, perform cluster analysis, classify and view gene information, perform functional classification and track down intricate correlations in data by performing pathway analysis. All analysis done is tracked, saved into a database and can be retrieved at any point of time.

 


What’s New
• Import Affymetrix Raw Data
• Merge Clusters
• One Sample t-Test
SVM
View and Update NetAffx™ Annotations
• Annotation Views
• URL Editor
• Search for Gene Ontology and Pathway terms
• Regulatory, Signal Transduction and Disease Pathways

Click to view bigger image


Data and Gene List Import
Genowiz™ supports a wide range of data formats pertaining to cDNA and Affymetrix data. Users can directly import .CEL and .CDF files into Genowiz™. Users also have an option to upload data in customized formats. Customized uploader allows users to add and save new data formats. One-Click Uploader can then identify these formats.

Gene List files for annotating genes can also be imported.

Click to view bigger image


MIAME
Minimum Information About a Microarray Experiment (MIAME) facilitates adoption of standards for microarray experiment annotation and data representation. Genowiz™ focuses on establishing standard microarray experimental data repositories and information sharing within the scientific community. Researchers can also exchange MIAME data by using MAGE ML document exchange format.

Click to view bigger image


Data Transformation, Normalization and Filtration

In any type of expression analysis, pre-processing of data to reduce undesirable variation among datasets and to bring data to a common platform is a vital step. Genowiz™ provides users with a wide range of data transformation, normalization and filtration tools. These include:

Data transformation options such as imputation of missing values, log transformations, mean/median, Z-transformation, subtract control, divide by control, scaling etc.
Normalization techniques such as normalization for dye swap replicates, cDNA raw data normalization options (cDNA Loess and Print tip Loess) and quantile normalization. Separate normalization techniques are provided for cDNA and Affymetrix arrays. Normalization can be done using all genes or control genes.
Filter data based on replicate genes, fold change, mean, standard deviation, calls and missing values. Replicate samples are handled using various parametric/non-parametric tests. Multiple testing correction can be applied to reduce false positives.

Click to view bigger image


Data Analysis and Visualization
Genowiz™ comes equipped with several data analysis tools. Complete with excellent graphics, it is an excellent tool for interpretation of biologically meaningful results. Some of these tools include partition clustering, hierarchical clustering, SOM, PCA, gene shaving and discriminant PCA and SVM. Option for merging, clusters of interest has also been provided.

Click to view bigger image


• Partition Clustering (K-means, Forgy’s)
This tool classifies genes or samples in user-defined groups using distance parameters. The obtained clusters can be re-clustered. Re-clustering utility helps scientists pick a set of genes of their interest. A 2D PCA view shows the distribution of genes in various clusters.

Click to view bigger image


• Hierarchical Clustering
One of the most important tools for studying relations between genes, this tool creates a dendrogram based on the relative distance between genes. The different optional parameters help the user in correctly determining the relationship between two genes. Models of analysis include single linkage, complete linkage and average linkage clustering. Genes, samples, or both together can be clustered.

Click to view bigger image


• Self Organizing Maps
A two-way classification of genes into clusters based on novel artificial neural networks is an integral feature of data clustering tools in Genowiz™. This gives a deeper insight into clusters, as neighboring clusters are very similar to each other.

Click to view bigger image


• Principal Component Analysis
This tool involves a mathematical procedure that transforms a number of (possibly) correlated variables into a (smaller) number of uncorrelated variables called principal components. These provide an insight into existent variability in the data.

Click to view bigger image


• Gene Shaving
This method identifies subsets of genes with coherent expression patterns and large variation across conditions. Gene shaving differs from hierarchical clustering and other methods of gene expression analysis in that genes may belong to more than one cluster.

Click to view bigger image


Classification

Classification algorithms are used to classify samples, based on information from similar samples with known classes that are available in training data. In Genowiz™, Support Vector Machines (SVM) and Discriminant PCA are used to predict classes for unclassified samples.

Click to view bigger image


Biological Analysis
Genowiz™ annotates genes and classifies them into functional categories (Gene Ontology). Option of importing annotation files is also provided. Integrated pathways module aids researchers in understanding metabolic pathways in relation to expression data. Pathway maps edited/created can be associated with author details too. Coupled with biological information and gene ontological classification, it forms an excellent tool in understanding biological systems. Search can be performed on the gene ontology and pathway tree to look for ontologies or pathways of interest.

Click to view bigger image


Utilities

Several utility options are present to add value to the analysis performed:

Gene List Comparison: Subtle relations among datasets can be probed using this feature.

Pattern Simulation: An expression pattern can be defined and Genowiz™ lists out all genes with a similar expression pattern. This gene list can be saved and exported.

Gene Tracking: Important genes or genes of interest can be tagged and tracked throughout the analysis.

Click to view bigger image


View and Update NetAffx™ annotations

Annotations for the uploaded data can be viewed by connecting to NetAffx™ database. Connecting to the NetAffx™ database and selecting a corresponding chip will retrieve annotations from that chip. Flexibility to update annotation information for existing chips and add annotation information for new chips is also present, thus enabling researchers to view updated annotations for chips.

Click to view bigger image


Technical Support
Ocimum’s technical support staff is available 24 hours, five days a week, to answer your questions about Genowiz™ over phone, e-mail and web chat. All questions previously answered by the support staff are available on the website for visitors.

Click to view bigger image


Sytem Requirements:

 

Request FREE trial

%d bloggers like this: