3G Doctor

I am working on the topic (software as a service) SaaS applications in Medical and Healthcare field, so the next few months my focus there.

So this week I like to post about 3GDoctor.com a service that allows you to video consult with General Medical Council registered Doctors using a 3G Video Mobile. When you register as a patient with 3G Doctor you can also use it to create, store and manage your Personal Health Record which can be referred to by your Doctor during video consultations. Yummy now that feels like the next google acqusition target.

Mediserve is another company that is now planning to came up with SaaS model of their applications.

And of course have to talk about Microsoft , even though I work for Oracle andicrosoft is competition.

Digipede is developing on microsofts .net plafrom to help anyone providing SaaS on the Microsoft platform. And they claim to have a bioinformatics company testing their application to develop bioinformatics application in SaaS model And it lok like that customer is The Friedrich Miescher Institute (FMI) as a part of the Novartis Research Foundation, details of the case study on Digipede website

And yes I ahve written about  GeneBio earlier their claims to have PhenyxOnline as the first commercial platform in the proteomics field offered in a SaaS model    

Also came across this intersting post by Paweł Szczęsny.  Thinking about RaaS: Research-as-a-Service

Microsoft Research, Indian Institute of Science Collaborate

Microsoft Research announced a sponsored research and collaboration agreement with the Indian Institute of Science (IISc) in Bangalore, India, to accelerate the scientific discovery process by increasing computational power in scientific and engineering research. This is the first agreement Microsoft Research has signed in India as part of a global effort to collaborate with leading institutions around advanced computing for science and engineering. Under this agreement, Microsoft Research has committed to providing funding and research expertise to assist with major projects around life sciences research and advanced high-performance computing platforms based on Microsoft Windows Compute Cluster Server 2003 for scientific applications, such as modeling of the Indian Ocean in the coming two to three years.

Professor Nagasuma Chandra, on the faculty of the Bioinformatics Centre at IISc, will be the principal investigator collaborating with Microsoft Research India for the biological data mapping project. The goal of the project is to create research tools for integration of various biological data, leading to greater understanding of biological systems as well as facilitating ready applications in many stages of drug and vaccine discovery.

Prof. R. Govindarajan of Supercomputer Education and Research Centre at IISc will lead the second project on high-performance applications using commodity clusters.

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 http://www.gotomyfiles.com, http://www.xdrive.com, http://www.ibackup.com, 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

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

The Insider -Code inside Codes : Scientists Discover Parallel Codes in Genes

Researchers from The Weizmann Institute of Science report the discovery of two new properties of the genetic code. Their work, which appears online in Genome Research, shows that the genetic code—used by organisms as diverse as reef coral, termites, and humans—is nearly optimal for encoding signals of any length in parallel to sequences that code for proteins. In addition, they report that the genetic code is organized so efficiently that when the cellular machinery misses a beat during protein synthesis, the process is promptly halted before energy and resources are wasted.

DNA sequences that code for proteins need to convey, in addition to the protein-coding information, several different signals at the same time. These “parallel codes” include binding sequences for regulatory and structural proteins, signals for splicing, and RNA secondary structure. Here, we show that the universal genetic code can efficiently carry arbitrary parallel codes much better than the vast majority of other possible genetic codes. This property is related to the identity of the stop codons. We find that the ability to support parallel codes is strongly tied to another useful property of the genetic code—minimization of the effects of frame-shift translation errors. Whereas many of the known regulatory codes reside in nontranslated regions of the genome, the present findings suggest that protein-coding regions can readily carry abundant additional information.

“Our findings open the possibility that genes can carry additional, currently unknown codes,” explains Dr. Uri Alon, principal investigator on the project. “These findings point at possible selection forces that may have shaped the universal genetic code.”

The genetic code consists of 61 codons—tri-nucleotide sequences of DNA—that encode 20 amino acids, the building blocks of proteins. In addition, three codons signal the cellular machinery to stop protein synthesis after a full-length protein is built.

While the best-known function of genes is to code for proteins, the DNA sequences of genes also harbor signals for folding, organization, regulation, and splicing. These DNA sequences are typically a bit longer: from four to 150 or more nucleotides in length.


Store Digital data with live bacteria

A research team said this week it had developed a technology for storing digital data in the DNA of bacteria, which unlike most living organisms can survive for millennia in the right conditions.

Japanese researchers have successfully stored messages in the DNA of bacteria. The hardiness of the hay bacillus bacteria ensures the digital data encoded into them can last for millenia.

Generally found in soil or decaying matter, hay bacillus are exceptionally resistant to extreme weather conditions. Two megabits (data equivalent to 1.6 million Roman letters) can be stored in each bacterium of hay bacillus in the form of implants. These tiny implants can be extracted in a lab and read like ordinary text at a later date.

Each hay bacillus bacterium can store two megabits — the equivalent of 1.6 million Roman letters. The scientists can take out the microscopic implants in a laboratory and read them so they appear as ordinary text.

The team at Keio University’s Institute for Advanced Biosciences said the technology needs to be perfected but that it was optimistic about its future uses.

“If I wanted to store my personal diary in these live bacteria and take it with me to my grave, then my story can live for thousands and thousands of years,” head researcher Yoshiaki Ohashi said with a laugh.

In practical terms, the technology could eventually benefit companies such as pharmaceutical makers which want to “stamp” their brand.

“In doing so, the company can detect piracy and protect its patent. They can also store information at one specific area of the gene and retrieve it from there,” Ohashi said.

The researchers insert the data at four different places so even if one is disrupted, there would be backup.

But the team said they still needed to work before the technology could go on the market. In particular, the scientists need to ensure that the DNA will not be altered as live bacteria naturally evolve.

Hay bacillus bacteria are generally found in soil or decaying matter and are especially resistant to extreme weather.

One of the practical applications of this technology lies in the area of pharmaceuticals. Fraudulent drugs are a major problem but if pharmaceutical companies could “stamp” their signature into the drugs, it would prevent piracy and at the same time protect their patents. To prevent corruption of the message encoding, the data would be inserted into 4 different places as multiple backups.
The bacteria’s hardiness and ability to preserve data for future generations would also be extremely useful in storing vast amounts of data which would not be suspectible to the types of damage that wipe out computer hard drives. Information stored on DNA lasts for more than one hundred million years.

The researchers project being able to develop a type of living memory for a new breed of organic computers which would use strands of DNA to perform calculations and would have the ability to heal themselves if damaged.

Though the promise of this technology is very high, the scientists caution more work is needed before it can be marketed. One of the hurdles to overcome is ensuring very slow mutation rates in the DNA as the bacteria evolve, otherwise the messages encoded will be rendered unreadable.

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: http://www.bepress.com/sagmb/vol5/iss1/art30

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