Bioinformatics seemed to be jinxed in the beginning of my career but I am glad gradually multinationals are recognizing the power of prediction and insilico analysis. The latest to follow the trend are proprietary software giants Micosoft.
Microsoft Biology Foundation, or MFB, is a bioinformatics toolkit built atop the .NET framework. This toolkit is based on the concept of open development, code sharing, and cross-platform support.
Keeping with the spirit of this tradition, MFB will be released under the Microsoft Public License.
As claimed, the toolkit should be a super time saver for the users and promises to offer range of algorithms for manipulating DNA, RNA, and protein sequences; and a set of connectors to biological Web services such as NCBI BLAST.
Futuristic Goals of MFB
Extensibility
Language neutrality
Supporting best practices
Cross-platform and interoperability
Building community
Access
The first beta version of MBF is now available!
For More
http://research.microsoft.com/en-us/collaboration/tools/mbf.aspx
Monday, November 23, 2009
Wednesday, October 28, 2009
Fragment Based Drug Discovery
The jest of finding new drug is often eclipsed by unpredictable and uncontrollable aspects of drug designing. Basically, there are two approaches that are regularly practiced :
- Focus on a small library representing scaffolds that are known to inhibit a class of targets.
- Focus on small, simple molecules – Fragments screened at high concentration to find molecules that can be developed into drugs
These approaches require combination of expertise from computational chemists, structural biologists, organic chemists, biologists and biophysicists.
FBDD utilizes biophysical techniques to screen about 1000 small fragments which lie in range of 150-250 MW. Despite of the strong theoretical aspects, the implementation is a twisted tale of rigorous quantifying fragments because more complex molecules have greater probability of mismatches.
There are two major challenges of FBDD are as stated below:
- Lack of specialized methods to detect fragment binding
- Need of efficient optimization of fragment hits.
But despite all kind of stigma and apprehensions attached to this approach, today almost a dozen FBDD leads targeting different protein families in different disease areas have progressed towards clinical trials. As more leads take their course to clinical trials it will be possible to access the contribution of this approach to modern medicine.
For further reading on the topic please refer to:
Monday, September 7, 2009
New Approach to conquer diseases :Intrinsically disordered proteins as potential drug targets
A new approach is being taken up by researchers where they are now focusing on intrinsically disordered proteins as potential drug targets. A couple of exciting work have sprung up in the recent past.
A whole proteome analysis has been carried out for Mycobacterium tuberculosis in our lab. The study revealed 13 potential drug targets which should be considered while prioritizing Anti-microbial drug targets.
One such suggested drug target - GlmU (Rv1018c) has been prioritized by Open Source Drug Discovery (OSDD) consortium (http://sysborgtb.osdd.net/bin/view/OpenProjectSpace/MycobacteriumTuberculosisGlmURv1018cDrugTarget). Glmu is a bifunctional protein comprising of an Uridyltransfer domain at the N-terminal and an acetyltransfer domain towards the C-terminal. The interesting aspect is that the C-terminal of this protein is intrinsically disordered i.e, in native form this region doesn't adopt a rigid secondary structure, but has the ability to attain such structure once interacts with a suitable biomolecule (protein,DNA or small molecule). Recently structure of this particular protein has been solved, with the limitation that the intrinsically disordered tail is missing out. Exploring and exploiting this region might add new dimensions to our understanding of both - intrinsically disordered region as well anti-microbial targets which tend to remain disordered.
For more information please visit : http://www.rsc.org/publishing/journals/MB/article.asp?doi=b905518p
or email me.
Opinions/criticism/comments are invited.
A whole proteome analysis has been carried out for Mycobacterium tuberculosis in our lab. The study revealed 13 potential drug targets which should be considered while prioritizing Anti-microbial drug targets.
One such suggested drug target - GlmU (Rv1018c) has been prioritized by Open Source Drug Discovery (OSDD) consortium (http://sysborgtb.osdd.net/bin/view/OpenProjectSpace/MycobacteriumTuberculosisGlmURv1018cDrugTarget). Glmu is a bifunctional protein comprising of an Uridyltransfer domain at the N-terminal and an acetyltransfer domain towards the C-terminal. The interesting aspect is that the C-terminal of this protein is intrinsically disordered i.e, in native form this region doesn't adopt a rigid secondary structure, but has the ability to attain such structure once interacts with a suitable biomolecule (protein,DNA or small molecule). Recently structure of this particular protein has been solved, with the limitation that the intrinsically disordered tail is missing out. Exploring and exploiting this region might add new dimensions to our understanding of both - intrinsically disordered region as well anti-microbial targets which tend to remain disordered.
For more information please visit : http://www.rsc.org/publishing/journals/MB/article.asp?doi=b905518p
or email me.
Opinions/criticism/comments are invited.
Wednesday, June 17, 2009
Swine Flu protein - Neuraminidase
The Developed nations have recently been under threat of Swine Flu which is caused by virus H1N1. Various sequencing projects were triggered as per sensitivity of the problem. NCBI provides a collated form of sequence data from various labs. An article which appeared in "Medical news today" highlights the fast paced breakthroughs that can be achieved using bioinformtics. Here is an excerpt from the article :
In the Biology Direct journal's May 20th issue, Sebastian Maurer-Stroh, Ph.D., and his team of scientists at the Bioinformatics Institute (BII), one of the research institutes at Singapore's Biopolis, also demonstrated the use of a computational 3-dimensional (3D) structural model of the protein, neuraminidase.
"Because we were working as a team, driven by the common goal to understand potential risks from this new virus, our group at BII was able to successfully complete this difficult analysis within such a short time," said Dr. Maurer-Stroh, BII principal investigator and first author of the paper.
BII's interactive 3D model is available at the following link: http://mendel.bii.a-star.edu.sg/SEQUENCES/H1N1/
With the 3D model, Dr. Maurer-Stroh and his team were able to map the regions of the protein that have mutated and determine whether drugs and vaccines that target specific areas of the protein were effective.
Among their findings:
* neuraminidase structure of the 2009 H1N1 influenza A virus has undergone extensive surface mutations compared to closely related strains such as the H5N1 avian flu virus or other H1N1 strains including the 1918 Spanish flu;
* neuraminidase of the 2009 H1N1 influenza A virus strain is more similar to the H5N1 avian flu than to the historic 1918 H1N1 strain (Spanish flu);
* current mutations of the virus have rendered previous flu vaccinations directed against neuraminidase less effective; and
* commercial drugs, namely Tamiflu® and Relenza®, are still effective in treating the current H1N1 virus.
With the Biology Direct journal paper, the Singapore scientists have become the first to demonstrate how bioinformatics and computational biology can contribute towards managing the H1N1 influenza A virus.
In the Biology Direct journal's May 20th issue, Sebastian Maurer-Stroh, Ph.D., and his team of scientists at the Bioinformatics Institute (BII), one of the research institutes at Singapore's Biopolis, also demonstrated the use of a computational 3-dimensional (3D) structural model of the protein, neuraminidase.
"Because we were working as a team, driven by the common goal to understand potential risks from this new virus, our group at BII was able to successfully complete this difficult analysis within such a short time," said Dr. Maurer-Stroh, BII principal investigator and first author of the paper.
BII's interactive 3D model is available at the following link: http://mendel.bii.a-star.edu.sg/SEQUENCES/H1N1/
With the 3D model, Dr. Maurer-Stroh and his team were able to map the regions of the protein that have mutated and determine whether drugs and vaccines that target specific areas of the protein were effective.
Among their findings:
* neuraminidase structure of the 2009 H1N1 influenza A virus has undergone extensive surface mutations compared to closely related strains such as the H5N1 avian flu virus or other H1N1 strains including the 1918 Spanish flu;
* neuraminidase of the 2009 H1N1 influenza A virus strain is more similar to the H5N1 avian flu than to the historic 1918 H1N1 strain (Spanish flu);
* current mutations of the virus have rendered previous flu vaccinations directed against neuraminidase less effective; and
* commercial drugs, namely Tamiflu® and Relenza®, are still effective in treating the current H1N1 virus.
With the Biology Direct journal paper, the Singapore scientists have become the first to demonstrate how bioinformatics and computational biology can contribute towards managing the H1N1 influenza A virus.
Wednesday, February 25, 2009
Russ Altman's View on whether Bioinformatics & Computational biology are same or not !
I spent the first 15 years of my professional life unwilling to recognize a difference between bioinformatics and computational biology. It was not because I didn’t think that there was or could be a difference, but because I thought the difference was not significant. I have changed my position on this. I now believe that they are quite different and worth distinguishing. For me,
Computational biology = the study of biology using computational techniques. The goal is to learn new biology, knowledge about living sytems. It is about science.
Bioinformatics = the creation of tools (algorithms, databases) that solve problems. The goal is to build useful tools that work on biological data. It is about engineering.
All this became important to me when I finally joined a bioengineering department, and I was forced to ask myself if I was a scientist or an engineer. I am both, and now am at peace.
When I build a method (usually as software, and with my staff, students, post-docs–I never unfortunately do it myself anymore), I am engaging in an engineering activity: I design it to have certain performance characteristics, I build it using best engineering practices, I validate that it performs as I intended, and I create it to solve not just a single problem, but a class of similar problems that all should be solvable with the software. I then write papers about the method, and these are engineering papers. This is bioinformatics.
When I use my method (or those of others) to answer a biological question, I am doing science. I am learning new biology. The criteria for success has little to do with the computational tools that I use, and is all about whether the new biology is true and has been validated appropriately and to the standards of evidence expected among the biological community. The papers that result report new biological knowledge and are science papers. This is computational biology.
As I look at my published work I have always tried to balance the publications in biological/medical journals and those in engineering/informatics journals. It is an aesthetic really, there is no reason why one should feel compelled to do this. However, it is useful to know when you are doing biology and when you are doing something else. I suppose someone can argue with the my use of the term “bioinformatics” as an engineering discipline. That’s fine–I’m open to a different term. But I would ask why bioinformatics isn’t good. I think computational biology is more solid–the ‘biology’ is clearly the noun and the ‘computational’ is clearly the adjective.
Russ Altman's blog : http://rbaltman.wordpress.com/
Computational biology = the study of biology using computational techniques. The goal is to learn new biology, knowledge about living sytems. It is about science.
Bioinformatics = the creation of tools (algorithms, databases) that solve problems. The goal is to build useful tools that work on biological data. It is about engineering.
All this became important to me when I finally joined a bioengineering department, and I was forced to ask myself if I was a scientist or an engineer. I am both, and now am at peace.
When I build a method (usually as software, and with my staff, students, post-docs–I never unfortunately do it myself anymore), I am engaging in an engineering activity: I design it to have certain performance characteristics, I build it using best engineering practices, I validate that it performs as I intended, and I create it to solve not just a single problem, but a class of similar problems that all should be solvable with the software. I then write papers about the method, and these are engineering papers. This is bioinformatics.
When I use my method (or those of others) to answer a biological question, I am doing science. I am learning new biology. The criteria for success has little to do with the computational tools that I use, and is all about whether the new biology is true and has been validated appropriately and to the standards of evidence expected among the biological community. The papers that result report new biological knowledge and are science papers. This is computational biology.
As I look at my published work I have always tried to balance the publications in biological/medical journals and those in engineering/informatics journals. It is an aesthetic really, there is no reason why one should feel compelled to do this. However, it is useful to know when you are doing biology and when you are doing something else. I suppose someone can argue with the my use of the term “bioinformatics” as an engineering discipline. That’s fine–I’m open to a different term. But I would ask why bioinformatics isn’t good. I think computational biology is more solid–the ‘biology’ is clearly the noun and the ‘computational’ is clearly the adjective.
Russ Altman's blog : http://rbaltman.wordpress.com/
Friday, January 16, 2009
Bio-Linux Released !
The NERC Environmental Bioinformatics Centre (NEBC), based at the UK Centre for Ecology & Hydrology, has released the latest version of NEBC Bio-Linux, a specialised computing system designed for the environmental genomics research community.
Bio-Linux is a freely available computing platform designed to provide a one-stop shop for accessing a wide range of standard and cutting-edge bioinformatics tools in a Linux context.
The growth of molecular data from the fields of genomics, metagenomics and related ‘omic disciplines calls for ever improving methods of data collection, storage and analysis. The field of bioinformatics is rich in software and fast, economical computing environments are becoming essential components of almost all research labs pursing scientific questions using these data-rich technologies.
Intended users of NEBC Bio-Linux 5.0 range from students entering the field of bioinformatics and new users of Linux to institutional teaching labs and expert computational biology groups well versed in Linux looking to use the existence of freely available customised distributions to build and maintain computational infrastructure quickly and effectively.
Previously NEBC Bio-Linux was only easily accessible to NERC funded researchers through an application process. With the release of version 5.0, this system is available online for easy download. The simplified access means researchers worldwide can also benefit from the opportunities offered by Bio-Linux. Researchers in North America, Europe, New Zealand, India, Iran, Africa and China have already taken advantage of Bio-Linux and many more users are anticipated as the field of bioinformatics continues to grow rapidly.
Dawn Field, Director of NEBC said,“ To apply information technology to the field of molecular biology researchers need access to multi-user, networked machines that are fast and contain a large suite of software. The NEBC Bio-Linux project has distributed the specialist skills and expertise needed to build this type of infrastructure within the UK. The result is a new generation of PhD students and postdocs in this community with more sophisticated computing skills. With the release of version 5.0 we aim to allow the rest of the world to take advantage of these developments.” The intention is that Bio-Linux will become the underpinning computational environment for all activities within the MGF-Oxford node.
Dawn Field, adds, “We need to foster a highly collaborative community that can make use of a network of computers throughout the UK. NEBC Bio-Linux provides a powerful framework for delivering support, minimizing duplication of effort and most importantly, empowering researchers to take on their own analyses using a large suite of tools”.
The more visionary role of NEBC Bio-Linux is to build electronic networks of researchers with shared interests, using a shared platform. This is already happening with a recent application of Bio-Linux in Africa. Peter Dawyndt, Professor of Computing at the University of Ghent found Bio-Linux on the web. He comments, “Bio-Linux is a terrific solution to our need to bring state-of-the-art bioinformatics computing platform to students in Africa. With just a set of DVDs in our luggage, we are able to install a top-notch computing environment in which to deliver our entire bioinformatics course. Most importantly, the entire infrastructure stays behind and remains available to interested students.”
Bio-Linux is a derivative of Ubuntu Linux [http://www.ubuntu.com] customised for bioinformatics analysis and development work. Approximately 60 bioinformatics packages (providing around 500 individual programs) are installed on Bio-Linux, including open-source packages developed at the NEBC. In addition, Bio-Linux comes with comprehensive, categorised documentation for the bioinformatics packages installed. Users can install a full NEBC Bio-Linux system or just add some or all packages to already installed Debian or Ubuntu Linux systems.
Lead Developer, Stewart Houten, says “Bio-Linux 5.0 retains the added-value features of Bio-Linux 4.0, but is now based on the highly popular and user-friendly Ubuntu distribution and the Gnome desktop. The system is available as an installable DVD or USB memory stick, making it readily accessible to a wide audience.”
The open source GNU/Linux computing system is progressively being seized upon as the preferred choice in addressing researcher computing needs. Despite Linux distributions becoming easier to use, the task of configuring the system for a specific purpose and collecting, compiling and setting up the academic software remains challenging. Bio-Linux provides a solution to this challenge.
Researchers and developers alike are welcome to join the NEBC Bio-Linux project and more information about the project can be found on the NEBC Bio-Linux homepage (http://nebc.nox.ac.uk/biolinux.html). Stewart Houten adds, “We make design choices in consultation with our community and continually adapt NEBC Bio-Linux to meet their needs. This release responds to the growing skills in our community in the use of Bio-Linux and the striking increase in the number of users downloading Bio-Linux or its packages from locations outside the UK.”
NEBC Lead Bioinformatician, Bela Tiwari says, “The NEBC Bio-Linux network accelerates research through improved electronic communication and support. I can log into a remote machine when requested, allowing me to directly troubleshoot or undertake collaborative analysis. Likewise, researchers can make use of a range of mechanisms for securely sharing data. Having many users able to access a single well-maintained machine also makes effective use of NERC funds and research time alike.”
Excerpts from http://www.innovations-report.de/html/berichte/informationstechnologie/bio_linux_global_125318.html
Bio-Linux is a freely available computing platform designed to provide a one-stop shop for accessing a wide range of standard and cutting-edge bioinformatics tools in a Linux context.
The growth of molecular data from the fields of genomics, metagenomics and related ‘omic disciplines calls for ever improving methods of data collection, storage and analysis. The field of bioinformatics is rich in software and fast, economical computing environments are becoming essential components of almost all research labs pursing scientific questions using these data-rich technologies.
Intended users of NEBC Bio-Linux 5.0 range from students entering the field of bioinformatics and new users of Linux to institutional teaching labs and expert computational biology groups well versed in Linux looking to use the existence of freely available customised distributions to build and maintain computational infrastructure quickly and effectively.
Previously NEBC Bio-Linux was only easily accessible to NERC funded researchers through an application process. With the release of version 5.0, this system is available online for easy download. The simplified access means researchers worldwide can also benefit from the opportunities offered by Bio-Linux. Researchers in North America, Europe, New Zealand, India, Iran, Africa and China have already taken advantage of Bio-Linux and many more users are anticipated as the field of bioinformatics continues to grow rapidly.
Dawn Field, Director of NEBC said,“ To apply information technology to the field of molecular biology researchers need access to multi-user, networked machines that are fast and contain a large suite of software. The NEBC Bio-Linux project has distributed the specialist skills and expertise needed to build this type of infrastructure within the UK. The result is a new generation of PhD students and postdocs in this community with more sophisticated computing skills. With the release of version 5.0 we aim to allow the rest of the world to take advantage of these developments.” The intention is that Bio-Linux will become the underpinning computational environment for all activities within the MGF-Oxford node.
Dawn Field, adds, “We need to foster a highly collaborative community that can make use of a network of computers throughout the UK. NEBC Bio-Linux provides a powerful framework for delivering support, minimizing duplication of effort and most importantly, empowering researchers to take on their own analyses using a large suite of tools”.
The more visionary role of NEBC Bio-Linux is to build electronic networks of researchers with shared interests, using a shared platform. This is already happening with a recent application of Bio-Linux in Africa. Peter Dawyndt, Professor of Computing at the University of Ghent found Bio-Linux on the web. He comments, “Bio-Linux is a terrific solution to our need to bring state-of-the-art bioinformatics computing platform to students in Africa. With just a set of DVDs in our luggage, we are able to install a top-notch computing environment in which to deliver our entire bioinformatics course. Most importantly, the entire infrastructure stays behind and remains available to interested students.”
Bio-Linux is a derivative of Ubuntu Linux [http://www.ubuntu.com] customised for bioinformatics analysis and development work. Approximately 60 bioinformatics packages (providing around 500 individual programs) are installed on Bio-Linux, including open-source packages developed at the NEBC. In addition, Bio-Linux comes with comprehensive, categorised documentation for the bioinformatics packages installed. Users can install a full NEBC Bio-Linux system or just add some or all packages to already installed Debian or Ubuntu Linux systems.
Lead Developer, Stewart Houten, says “Bio-Linux 5.0 retains the added-value features of Bio-Linux 4.0, but is now based on the highly popular and user-friendly Ubuntu distribution and the Gnome desktop. The system is available as an installable DVD or USB memory stick, making it readily accessible to a wide audience.”
The open source GNU/Linux computing system is progressively being seized upon as the preferred choice in addressing researcher computing needs. Despite Linux distributions becoming easier to use, the task of configuring the system for a specific purpose and collecting, compiling and setting up the academic software remains challenging. Bio-Linux provides a solution to this challenge.
Researchers and developers alike are welcome to join the NEBC Bio-Linux project and more information about the project can be found on the NEBC Bio-Linux homepage (http://nebc.nox.ac.uk/biolinux.html). Stewart Houten adds, “We make design choices in consultation with our community and continually adapt NEBC Bio-Linux to meet their needs. This release responds to the growing skills in our community in the use of Bio-Linux and the striking increase in the number of users downloading Bio-Linux or its packages from locations outside the UK.”
NEBC Lead Bioinformatician, Bela Tiwari says, “The NEBC Bio-Linux network accelerates research through improved electronic communication and support. I can log into a remote machine when requested, allowing me to directly troubleshoot or undertake collaborative analysis. Likewise, researchers can make use of a range of mechanisms for securely sharing data. Having many users able to access a single well-maintained machine also makes effective use of NERC funds and research time alike.”
Excerpts from http://www.innovations-report.de/html/berichte/informationstechnologie/bio_linux_global_125318.html
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