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  

Microarrays in daily life

Accurate assessment of a calf’s future performance may soon be possible by using microarrays.

By 2010, less than three years away,
Australia’s largest integrated beef research program, the Beef Cooperative Research Centre (CRC) anticipates cattle breeders may be able to get an accurate assessment of a bull or a dam’s future performance within a few months of its birth

Professor John Gibson, Beef CRC Adaptation and Cattle Welfare Research Leader, says microarray technology has enabled the entire 23,000-odd separate genes of the bovine genome to be printed on one microarray plate the size of a microscope slide. 

“Research overseas indicates that how an animal expresses its genes in early life provides an accurate picture of its gene expression at breeding age.” 

This leads to the prospect of microarrays being printed that carry genes of commercial interest, which could be then used to predict the breeding performance of young animals well before they reach breeding age.

 Prof. Gibson observes that this would help breeders quickly eliminate genetically dud bulls and cows early in their life, without the costs of feeding and progeny testing now required to determine the duds. 

Online Data sharing for scientists

Brent Edwards director of the Starkey Hearing Research Center in Berkeley, California, who blogs on innovation in science is writing his blog about an article on Nature magazine on online data sharing. Brent comments about the potential of new online data sharing sites such as Swivel and IBM’s Many Eyes . Accoding to the Nature reprt some scientists are already using these new tools to share sequence and microarray data. The potential value from scientists openly sharing their data is huge, possibly akin to the value provided by open-source software development.

Once data are uploaded to these sites (which are still being tested), people can reanalyse the numbers, mix them with other data and visualize them in different ways. Swivel focuses on letting users combine data sets, with some basic ways to present the results such as scatter graphs and bar charts. Many Eyes allows users to generate more complicated graphs such as network diagrams, which depict nodes and connections within networks, and treemaps, which display data as groups of nested rectangles

Despite the availability of many software solutions at the dispoal of scientists many of them still write their own code for bioinformatics and statistical analysis, perhaps the next frontier that might help the comunity could be the development of Firefox like software, that offers some basic functions free of cost, additional function can be bought or acquired free of cost as add ons form researchers, such a move would benefit researchers and students alike,

There are sure many more data sharing website like,,, but these are more of a data storage sites, and these does not offer the level of document collaboration features required by a life science researcher

Then there is few other sites like microsofts foldershare and others that offer features such as remote PC access gotomyPC VNC and webex are a few exmaple of this stable. some of these also allows to by pass even a firewall such as foldershare and can pose serious security risks to data and pc if handled improperly

its not so much of junk DNA- University of Oxford Scientists discoveres Cancer cure with it

 Junk DNA is not junk after all

Recently, scientists at the University of Oxford have discovered that ‘junk’ genetic material can switch off cancer tumours, preventing them from growing.

By using RNA to switch off a gene involved in controlling cell division, Oxford University scientists may have found a role for RNA in developing new cancer therapies. RNA is the mirror image of DNA, and is used to pass on instructions to the cell to build the proteins that run every body function.

The Human Genome Project found that human DNA carries approximately 34,000 genes that produce proteins. The remaining majority of the genome constituted what was considered to be junk DNA as it had no obvious function. However, this is set to change.

‘‘There has been a quiet revolution taking place in biology in past few years,’’ said Dr Alexandre Akoulitchev, a Senior Research Fellow at Oxford. ‘‘Scientists have begun to see ‘junk’ DNA as having an important function. The variety of RNA types produced from this so called ‘junk’ is staggering and the functional implications are huge.”

Akoulitchev studied the RNA that regulates a gene called DHFR. This gene produces an enzyme that controls the production of molecules called tetrahydrofolate and thymine that cells need to divide rapidly.

“Switching off the DHFR gene could help prevent ordinary cells from developing into cancerous tumour cells, by slowing down their replication. In fact, one of the first anti-cancer drugs, Methotrexate, acts by binding and inhibiting the enzyme produced by this gene. Targeting the gene itself would cut the enzyme out of the picture altogether. Understanding how we can use RNA to switch off or inhibit DHFR and other genes may have important therapeutic implications for developing new anti-cancer treatments.”

This research was funded by The Wellcome Trust and the Medical Research Council.

Original paper: Repression of the human dihydrofolate reductase gene by a non-coding interfering transcript was published in Nature on 22nd January 2006.

Microarray based Bio Detection Technologies

DNA microarray detection of antimicrobial resistance genes in diverse bacteria

Study published at
High throughput genotyping is essential for studying the spread of multiple antimicrobial resistance. A test oligonucleotide microarray designed to detect 94 antimicrobial resistance genes was constructed and successfully used to identify antimicrobial resistance genes in control strains. The microarray was then used to assay 51 distantly related bacteria, including Gram-negative and Gram-positive isolates, resulting in the identification of 61 different antimicrobial resistance genes in these bacteria. These results were consistent with their known gene content and resistance phenotypes. Microarray results were confirmed by polymerase chain reaction and Southern blot analysis. These results demonstrate that this approach could be used to construct a microarray to detect all sequenced antimicrobial resistance genes in nearly all bacteria.

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

New non-parametric analyis algorithm for Detecting Differentially Expressed Genes with Replicated Microarray Data

Previous nonparametric statistical methods on constructing the test and null statistics require having at least 4 arrays under each condition. In this paper, we provide an improved method of constructing the test and null statistics which only requires 2 arrays under one condition if the number of arrays under the other condition is at least 3. The conventional testing method defines the rejection region by controlling the probability of Type I error. In this paper, we propose to determine the critical values (or the cut-off points) of the rejection region by directly controlling the false discovery rate. Simulations were carried out to compare the performance of our proposed method with several existing methods. Finally, our proposed method is applied to the rat data of Pan et al. (2003). It is seen from both simulations and the rat data that our method has lower false discovery rates than those from the significance analysis of microarray (SAM) method of Tusher et al. (2001) and the mixture model method (MMM)of Pan et al. (2003).

study published by

Shunpu Zhang (2006) “An Improved Nonparametric Approach for Detecting Differentially Expressed Genes with Replicated Microarray Data,” Statistical Applications in Genetics and Molecular Biology: Vol. 5 : Iss. 1, Article 30.
Available at:

Even the hopeful US president jumps on Web2.0 bandwagon

 Barack Obama looks to be diving into this whole “Web 2.0” thing head first, what with his own Facebook profile, Flickr account, and YouTube account. In addition to all this stuff, he also has, a social networking type site for his supporters to create profiles, network, and make blogs all about how great Barack Obama is. Meanwhile Former Senator John Edwards is also facing setback in his blogs when two of his former bloggers bloggers Amanda Marcotte and Melissa McEwan are asked to step down for posting blogs that upset the Christian community and Bush supporters

So whats preventing our young scientists from going web2.0 and using blogs, Business networking sites such as Linkedin has given much required value to the business commnity compared to stes like Orkut whch is for the liter side of networking althought even orkut also offers communities too , shouldnt it be time to start one for the scientific community , there are few small steps in this way such as   Community of Science (COS) is the leading global resource for hard-to-find information critical to scientific research and other projects across all disciplines.  Networking – the new makes it possible. It is where the global laboratory, analysis, biotech, chemistry and pharma industry meets. Based on the theory of “six degrees of separation”, the club allows members to maintain their personal networks, generate new contacts and actively participate in various forums to exchange information, experiences and opinions. an international life science forum  reach a key decision maker and find your colleague or someone working in your field

google video publish your expertise in tackling the problems facing while operating your protolcs or project work , tips and tricks what ever it is all you need is a webcam

James from Research Information Network UK has commented on a previous blog I had published about an article on how researchers fish for information ,

Early in 2006, the Research Information Network commissioned a study as part of its work to promote better arrangements for researchers to find out what information resources relevant to their work are available, where these are, and how they may have access to them. The work has now been concluded, and the report from the study is attached below. 

Surprisingly many people still do not know hoe to use the search features of google yet

Microaray and Genomcis consortiums have now started to use more collaborating tools such as wikipedia and wiki pages. few good examples are and  and

Online Microarray tools

Open source was always the favourite with scientists, Now with companies liek Google and IBM pushing the concept of software as a service educational institutions and non profit organisation alike can offer there efficiencies and expertise to scores of scientists cost effectively

for a start take a look at the online microarray analysis tool offered at European Bioinformatics Institute

Microarray for Catharanthus Roseus

In the recently concluded Bio-Asia 2007 meeting  Ocimum Biosolutions has entered into an accord with a scientist for developing microarray  on the medicinal plant Catheranthus Roseus. 


Catharanthus roseus is known as the common or Madagascar periwinkle, though its name and classification may be contradictory in some literature because this plant was formerly classified as the species Vinca rosea, Lochnera rosea and Ammocallis rosea. Furthermore, lesser periwinkle (Vinca minor) may also be called common periwinkle. Both species are also known as myrtle.

Western researchers finally noticed the plant in the 1950’s when they learned of a tea Jamaicans were drinking to treat diabetes. They discovered the plant contains a motherlode of useful alkaloids (70 in all at last count). Some, such as catharanthine, leurosine sulphate, lochnerine, tetrahydroalstonine, vindoline and vindolinine lower blood sugar levels (thus easing the symptoms of diabetes). Others lower blood pressure, others act as hemostatics (arrest bleeding) and two others, vincristine and vinblastine, have anticancer properties. Periwinkles also contain the alkaloids reserpine and serpentine, which are powerful tranquilizers.

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 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

The genetic detective – Pharmacogenomics and personalized medicine

 THe following interesting study was published at  article is from royal society of chemistry website

A selective way to detect genetic variations could help scientists develop personalised medicine.

“[This method] should allow several thousands of single nucleotide variations, at different positions within a person’s genome, to be analysed in parallel.”
– Andreas Marx

Variations in our genetic make-up are responsible for some diseases and are known to be major players in an individual’s predisposition to drug side effects. Convenient and rapid detection of these variations could help doctors to adapt therapies for each patient. This idea has prompted Andreas Marx and colleagues at the University of Konstanz, Germany, to devise a high-throughput technique to detect variations between single nucleotides in genetic sequences. 

Marx’s system uses a microarray of oligonucleotide probes to analyse the DNA. The probes are attached by their 5′ end to a glass surface and treated with an enzyme, a DNA polymerase. The enzyme can add further nucleotides to the unattached ends of the probes. If a probe’s terminal base complements the DNA under investigation, the oligonucleotide chain continues to form; if the base is a mismatch, the chain does not extend further.

A microarray of oligonucleotide probes

Oligonucleotide probes are used to analyse DNA to detect variations between single nucleotides

‘Conventional enzyme-based strategies for detecting single nucleotide variations often lack sufficient selectivity,’ said Marx. The oligonucleotide chain can continue to form even when there is a mismatch. The team was able to increase the selectivity by modifying the terminal nucleotide of the probe with a methoxymethylene group. 

In human DNA, approximately one single nucleotide variation occurs per 1000 bases. This method ‘should allow several thousands of single nucleotide variations, at different positions within a person’s genome, to be analysed in parallel,’ said Marx. ‘This is still a challenging task that none of the present systems is able to achieve reliably.’

Oliver Seitz, an expert in DNA diagnostics at Humboldt University in Berlin, Germany, believes that Marx’s work could have a significant impact in developing diagnostic probes for DNA. ‘The method brings high specificity to the high-throughput format,’ said Seitz. ‘The challenge now is to combine multiplex analysis with specificity and signal amplification in a miniaturised format, to enable point-of-care diagnostics.’

Alison Stoddart


Increased single nucleotide discrimination in arrayed primer elongation by 4′C-modified primer probes

J Gaster, G Rangam and A Marx, Chem. Commun., 2007

Indian scientists from CCMB find new genetic mutations- and wins award from UK

UK award for CCMB scientist

The Hindu Business Line:January 22, 2007

Hyderabad: Dr K. Thangaraj, a scientist at the Centre for Cellular and Molecular Biology (CCMB), Hyderabad has received the first Major UK-India Education and Research Initiative (UKIERI) Award.Launched by the UK Prime Minister, Mr Tony Blair, during his last visit to India, the UKIERI award is aimed to promote the innovative research and academic excellence between the two countries.

The award has been given to Dr Thangaraj and his collaborators Dr Mart Mirazon Lahr and Dr Toomas Kivisild of Cambridge University for a four-year collaborative project involving genetic analysis of the various populations in India.

It also involves mutual exchange visits of scientists between CCMB and Cambridge University.

Major Award

This is the first major award given to carry out the research in the field of genomics, out of the six major awards selected from 103 proposals from India and the UK.

The award was presented by Mr Gordon Brown, Chancellor of the Exchequer of Britain, at a function in New Delhi recently, according to a CCMB release.

It carries a research grant of Rs 2.5 crore. The project aims at probing the question: “Was the first `out of Africa’ settlement of Homo sapiens in India?”

Dr Lalji Singh, Director of CCMB, said that the initiative would bring many more international research collaborations in future to the centre.

Indian scientists from CCMB find new genetic mutations

Novel genetic mutations associated with certain neuro-generative disorders, cardio-myopathies and male infertility have been found in Indian population by scientists of the Centre for Cellular and Molecular Biology (CCMB) in studies conducted in collaboration with other medical institutions.

The mutations have been found in mitochondrial DNA which is inherited from the mother, unlike the chromosomal DNA, inherited from both the parents. Mitochondrion plays an important role in cellular energy metabolism. In the past decade, genetic variations in mitochondrial DNA have been linked with various disorders, particularly neurological.

Senior scientist of CCMB Kumaraswamy Thangaraj, who led the research teams, told  that they had begun studying the molecular basis of mitochondrial disorders in the population a couple of years ago. They focussed on neuro-muscular diseases, cardiomyopathy, male infertility and recurrent pregnancy loss and analysed hundreds of samples in each category.

The studies showed new genetic variations associated with neuro-generative disorders like MELAS (Mitochondrial encephalopathy lactic acidosis stroke-like episodes) and Leigh, cardiomyopathies and male infertility. Dr. Thangaraj said most of the mutations found in the Western were not found here. “Since Indians have a unique origin, the genetic variations will be different,” he added. CCMB scientists are analysing samples to identify specific sets of mutations associated with mitochondrial disorders for early diagnosis. Regarding genetic causes for male infertility, he said the problem of low sperm motility was looked into to understand the involvement of mitochondrial DNA. C11994T mutation in ND4 gene of mitochondria was found to be associated with low motility, he added



Scientists find Extraterrestrial genes in Human DNA

A group of researchers working at the Human Genome Project indicate that they made an astonishing scientific discovery: They believe so-called 97% non-coding sequences in human DNA is no less than genetic code of extraterrestrial life forms.

The non-coding sequences are common to all living organisms on Earth, from moulds to fish to humans. In human DNA, they constitute larger part of the total genome, says Prof. Sam Chang, the group leader. Non-coding sequences, originally known as “junk DNA”, were discovered years ago, and their function remained a mystery. The overwhelming majority of Human DNA is “Off-world” in origin. The apparent “extraterrestrial junk genes” merely “enjoy the ride” with hard working active genes, passed from generation to generation.

After comprehensive analysis with the assistance of other scientists, computer programmers, mathematicians, and other learned scholars, Professor Chang had wondered if the apparently “junk Human DNA” was created by some kind of “extraterrestrial programmer”. The alien chunks within Human DNA, Professor Chang further observes, “have its own veins, arteries, and its own immune system that vigorously resists all our anti-cancer drugs.”

Professor Chang further stipulates that “Our hypothesis is that a higher extraterrestrial life form was engaged in creating new life and planting it on various planets. Earth is just one of them. Perhaps, after programming, our creators grow us the same way we grow bacteria in Petri dishes. We can’t know their motives – whether it was a scientific experiment, or a way of preparing new planets for colonization, or is it long time ongoing business of seedling life in the universe.”

Professor Chang further indicates that “If we think about it in our human terms, the apparent “extraterrestrial programmers” were most probably working on “one big code” consisting of several projects, and the projects should have produced various life forms for various planets. They have been also trying various solutions. They wrote “the big code”, executed it, did not like some function, changed them or added new one, executed again, made more improvements, tried again and again.”

Professor Chang’s team of researchers furthermore concludes that, “The apparent “extraterrestrial programmers” may have been ordered to cut all their idealistic plans for the future when they concentrated on the “Earth project” to meet the pressing deadline. Very likely in an apparent rush, the “extraterrestrial programmers” may have cut down drastically on big code and delivered basic program intended for Earth.”

Professor Chang is only one of many scientists and other researchers who have discovered extraterrestrial origins to Humanity.


 read full article at


Rapid genotyping of methicillin-resistant Staphylococcus aureus (MRSA) using OLigonucleotide microarrays

Published by 

1Institute for Medical Microbiology and Hygiene, Faculty of Medicine ‘Carl Gustav Carus’, Technical University of Dresden, Dresden and 2Clondiag Chip Technologies GmbH, Jena, Germany
This study evaluated a DNA oligonucleotide array that recognised 38 different Staphylococcus aureus targets, including all relevant resistance determinants and some toxins and species-specific controls. A new method for labelling sample DNA, based on a linear multiplex amplification that incorporated biotin-labelled dUTP into the amplicon, was established, and allowed detection of hybridisation of the amplicons to the array with an enzymic precipitation reaction. The whole assay was validated by hybridisations with a panel of reference strains and cloned specific PCR products of all targets. To
evaluate performance under routine conditions, the assay was used to test 100 methicillin-resistant S. aureus (MRSA) isolates collected from a university hospital in Saxony, Germany. The results showed a high correlation with conventional susceptibility data. The ermA and ermC macrolide resistance genes were found in 40% and 32% of the isolates, respectively. The most prevalent aminoglycoside resistance gene was aphA3 (57% of the isolates), followed by aacA–aphD (29%) and aadD (29%); tet genes, mupR
and dfrA were rare. There were no isolates with van genes or genes involved in resistance to quinupristin–dalfopristin. Enterotoxins were detected in 27% of the isolates. Genes encoding Panton– Valentine leukocidin, toxic shock syndrome toxin and exfoliative toxins were not found. The DNA array facilitated rapid and reliable detection of resistance determinants and toxins under conditions used in a routine laboratory and has the potential to be used for array-based high-throughput screening.

complete article at

Similar studies are also published at

Microarrays for taxonomics studies

The develpment of barcode microarray may be a subject of debate , but it may hel in transgenomic studies, and would help in finding new avenues for use of microarrays

microarray data as Phenotype

Microarrays provide a method of quantifying the expression and order of genes in a particular genome — acting as a surrogate measure of cell physiology, said researchers at Baylor College of Medicine in a report that appears online today in the journal Nature Genetics.

“Microarray data are good phenotypes to determine the order of genes and are a good surrogate measure of cell status,” said Dr. Gad Shaulsky, associate professor of molecular and human genetics at BCM.

Microarrays are fairly new technology that can help scientists understand how genes interact as well as how they are regulated by networks within the cell. They are created by the placement of tiny droplets of functional DNA on glass slides. Then researchers attach fluorescent labels to nucleic acids (DNA or RNA) from the cells under study. These labeled nucleic acids are allowed to bind to the DNA on the slides. Researchers then use a microscope to measure how much of a specific nucleic acid is present.

Genotype is the genetic fingerprint of a particular cell. Phenotype is the outward manifestation of the genotype. For example, a person may have genes for eye color. That is that individual’s genotype. Blue eyes is the phenotype.

The microarray data Shaulsky and his collaborators used show that they can determine the order in which genes act in a cascade that results in a particular phenotype.

Shaulsky and his co-authors performed their work in Dictyostelium (Dictyostelium discoideum), a form of soil amoeba used in the laboratory because many of its 10,000 genes are homologues or equivalents of genes found in humans.

Using microarray data alone, they determined the orders in which genes function in a particular pathway in that organism. The protein kinase A (PKA) signaling pathway occurs when the organism encounters starvation. The pathway enables the single cells to combine into a multi-cell organism.

“We pretended we did not know the order of genes in the pathway,” said Shaulsky. “We were able to reconstruct the pathway from the microarray data. This means the microarray provides a good phenotype that is quantitative. We can prove that gene A comes before gene B and give mathematical support for these findings.”

“This is a proof of principle that we set out to do – assessing the function of unknown genes is feasible,” said Shaulsky. “It can be done with a microarray phenotype.”

Others who participated in the research included Drs. Nancy Van Driessche, Ezgi O. Booth, Paul Hill and Adam Kuspa, all of Baylor College of Medicine; and Janez Demsar, Peter Juvan and Blaz Zupan of the Faculty of Computer and Information Science, University of Ljubljana, Ljubljana, Slovenia.

Source : Baylor College of Medicine

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

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


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
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

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.

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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.

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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.

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• 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.

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• 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.

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• 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.

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• 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.

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• 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.

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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.

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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.

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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.

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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.

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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.

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