Biopeer

Shaping a Web That Better Serves Humanity

One hundred million nodes – that’s the number of servers now interconnected on the Internet, writes Catherine Varmazis. Citing the rapid growth of the World Wide Web over the last decade, a group of scientists from the Massachusetts Institute of Technology (MIT) and the U.K.’s University of Southampton believe the Web is now so large as to require its own field of study if it is to evolve systematically and serve humanity optimally.

At a briefing held at MIT in Cambridge, Mass., on Thursday 9 November, the scientists announced the formation of the Web Science Research Initiative (WSRI), the purpose of which is to produce the scientific advances necessary to guide the future design and use of the Web. Using a multidisciplinary approach, the WSRI will generate a research agenda for understanding the scientific, technical, and social challenges underlying the growth of the Web. WSRI researchers will address how Web-based information is accessed, and its reliability. Legal questions and social networks – how people use the Web to communicate – will be critical areas of study.

Full article: http://www.bio-itworld.com/newsitems/2006/nov/11-06-06-wsri

Tags: semantic web

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Computer program to assess diabetes risk with increased accuracy

An innovative computer program is on its way to becoming the first multidisciplinary diagnostic tool for diabetes. Designed to help health professionals identify the risk of developing Type 2 diabetes, the program is being prototyped at Trinity Western University (TWU).

While there is currently no cure for the disease, Type 2 diabetes—the more rampant of the two types—is preventable. TWU computing science professor, Alma Barranco-Mendoza, is developing a revolutionary intelligent system able to assess diabetes risk with increased accuracy. The sophisticated algorithm developed by Mendoza is capable of assessing numerous risk factors—including lifestyle, race, genetic information, family medical history and pancreas tissue images. Instead of providing a general reading of low, medium or high which is what patients now get, the new program will weigh the various factors and express risk as a specified percentage.

This unique, highly original algorithm not only represents an outstanding contribution to the field of computing sciences but also signifies progress in diabetes research data collection, representation and analysis. With the help of this program, diabetes research groups will be able to develop more comprehensive profiles of “at-risk” patients, thereby increasing the understanding and precision of diabetes risk-assessment in general.

Says Mendoza, “Once a certain amount of data is gathered, the intelligent system will start learning by itself. It would mine the data and identify trends not evident to us. It is believed that there may be DNA markers for the disease and if we can identify them we’re on our way to finding a very fast and effective early diagnostic test and even possibly making headways to eventually find a cure”.

Indo-Italian initiative on drug discovery

Global technology services major Tata Consultancy Services Ltd (TCS) has entered into an agreement with Congenia, a biotechnology start-up promoted by Italy’s Genextra SpA Group, to provide advanced fragment-based lead optimisation solutions for drug discovery.

Under the pact, TCS’ Life Sciences R&D Division would work on ‘P66’, a target protein identified by Congenia as a key protein involved in several age-related diseases, and develop optimised drug leads based on it. Using modules of its own indigenised software ‘Bio-Suite’ to work on the target protein, TCS would screen a ‘virtual fragment library’ of potential lead molecules to predict which of these might bind themselves to the target protein and thereby inhibit its function. TCS would also produce a first-cut analysis of the ADMET (Absorption, Distribution, Metabolism, Excretion, and Toxicity) profile of the lead molecules. Congenia will further develop the optimised lead molecules produced by TCS through animal trials and eventually human clinical trials.

Increasing costs of discovering new drugs and taking them to the market puts the average cost of discovering a new drug at about one billion dollars. A large portion of this cost results from the failure of drug candidates at various stages of testing. Presently, a great deal of drug discovery especially in bio-pharmaceuticals consists of simply trying out all possible combinations of proteins and drug candidates and putting them through high throughput screening. The use of IT solutions in the drug discovery process will allow pharmaceutical companies to eliminate many combinations at the simulation stage itself. This would not only mean a significant reduction in cost of drug discovery, but would also cut down on the time to market of much-awaited blockbuster drugs.

Whither the pharma blockbuster?

From Corante this week commenting on a NYT article—Pharmaceutical companies reconsider the future of blockbuster drugs.  Are the days of the mega blockbuster over?  The drug that everyone must have?  Is the future the custom compound?  With improvements in biotech I certainly think so.  Profit?  The profit is in reduced timelines and less distribution.

 

Perhaps this will a benefit of years genomics research.

 

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Tristram Hussey, M.S. was the webmaster for Glaxo Wellcome and GlaxoSmithKline.  Now he is a professional blogger and blog consultant, the Chief Blogging Officer for Qumana Software, and Managing Director of Qumana Services.  He can be reached at tris AT qumana DOT com or tris AT trishussey DOT com.

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To push forward, bioinformatics needs more powerful tools

A mini-review and abstract of the importance of improving and innovation in the field of Bioinformatics.  Like all data-based, and computationally heavy fields, bioinformatics needs continuous improvement of the tools.

Bioinformatics in microbial biotechnology - a mini review

Arvind K Bansal

Microbial Cell Factories 2005, 4:19 doi:10.1186/1475-2859-4-19

Published 28 June 2005

Microbial Cell Factories | Abstract |

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Bioinformatics leads to locating a new gene regulation system

Researchers at  Institute for Information Transmission Problems (IITP) in Moscow have used bioinformatics techniques to analyze several taxa of bacteria—Bioinformatics reveals new gene regulation system.

 

"By comparing 140 sequenced bacterial genomes, researchers have uncovered a system for regulating genes essential to bacterial replication – and they did it solely by computer keystrokes and mouse clicks."

While the researches say that this particular research isn't applicable to human health research the techniqueis:

 

"There are 100 enzymes functioning at the core of bacterial metabolism for which the genes are still unknown," ... "By comparing hundreds of genomes, you can see patterns that are not seen when looking at just a couple of them."

Technorati Tags : Bioinformatics

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Tristram Hussey, M.S. is a professional blogger and blog consultant, the Chief Blogging Officer for Qumana Software, and Managing Director of Qumana Services.  He can be reached at tris AT qumana DOT com or tris AT trishussey DOT com.

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In these complex research fazes SeqPad dramati...

 "SeqPad is a productivity & collaboration solution for Life Science researchers in the specialized domains of Genomics, Proteomics and Phylogenetics. It has in particular a clear added value in the early fazes of drug discovery: target identification and lead identification & selection. Genohm, the company developing SeqPad for the last three years, made a FREE trial version of seqpad available on their website. The software suite was well received at Bio2005, Philadelphia. "

 

"In these complex research fazes SeqPad dramatically increases the research productivity, because of it's DNA & Protein aware application logic that offers researchers an interpretative and integrated workspace for performing sequence analysis and annotation. In addition to SeqPad, Genohm offers BioLinux, BioTorrent & TreeIllustrator."

 

Via:BioinforMatrix - The SeqPad software suite Release

 

 Technorati Tags : Bioinformatics, SeqPad

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Tristram Hussey, M.S. is a professional blogger and blog consultant, the Chief Blogging Officer for Qumana Software, and Managing Director of Qumana Services.  He can be reached at tris AT qumana DOT com or tris AT trishussey DOT com.

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Which gene did you mean?

Via this post--Tagging your research | nodalpoint.org—I found an interesting revolution occurring in the areas of genetics and genomics.  Tagging—the setting of keywords on a post picture to help connect it with similar pieces of information—is coming to genomics and genetics.

Abstract (provisional)

Computational Biology needs computer-readable information records. Increasingly, meta-analysed and pre-digested information is being used in the follow up of high throughput experiments and other investigations that yield massive data sets. Semantic enrichment of plain text is crucial for computer aided analysis. In general people will think about semantic tagging as just another form or text mining, and that term has quite a negative connotation by now. Efforts so far have tried to develop tools and technologies that retrospectively extract the correct information from text, which is usually full of ambiguities. Although remarkable results have been obtained in experimental circumstances, the wide spread use of information mining tools is lagging behind earlier expectations. This commentary proposes to make semantic tagging an integral process to electronic publishing.

BioMed Central | Abstract | 1471-2105-6-142 | Which gene did you mean?

It make a tremendous amount of sense tag a sequence and then see how it connects to others in the same area.  Could be a huge boost in drug discovery and disease genetics.

 

Technorati Tags : genomics, tagging, tags, genetics

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Tris Hussey is a professional blogger and blog consultant, the Chief Blogging Officer for Qumana Software, and Managing Director of Qumana Services.  He can be reached at tris AT qumana DOT com or tris AT trishussey DOT com.

 

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Predicting genes in genomes

BioMed Central | Abstract | 1471-2105-6-131 | Gene finding in the chicken genome

PDF Version (401KB)

 

Abstract (provisional)

 

Background

 

Despite the continuous production of genome sequence for a number of organisms, reliable, comprehensive, and cost effective gene prediction remains problematic. This is particularly true for genomes for which there is not a large collection of known gene sequences, such as the recently published chicken genome. We used the chicken sequence to test comparative and homology-based gene-finding methods followed by experimental validation as an effective genome annotation method.

 

Results

 

We performed experimental evaluation by RT-PCR of three different computational gene finders, Ensembl, SGP2 and TWINSCAN, applied to the chicken genome. A Venn diagram was computed and each component of it was evaluated. The results showed that de novo comparative methods can identify up to about 700 chicken genes with no previous evidence of expression, and can correctly extend about 40% of homology-based predictions at the 5' end.

 

Conclusions

 

De novo comparative gene prediction followed by experimental verification is effective at enhancing the annotation of the newly sequenced genomes provided by standard homology-based methods.

Technorati Tags : Bioinformatics, genome, genes, chicken genome

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Tris Hussey is a professional blogger and blog consultant, the Chief Blogging Officer for Qumana Software, and Managing Director of Qumana Services.  He can be reached at tris AT qumana DOT com or tris AT trishussey DOT com.

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Object-oriented genomics?

Can the world of programming help genomics and bioinformatics?  Here's something interesting from Nodalpoint.org--Object-oriented Biology | nodalpoint.org :

I have just read an interesting article which discusses about the application of object-orientation paradigm, used in popular programming languages such as Ruby, Java or C#, in dynamical and statical description of different gene products and their derived forms. Object attributes and properties, which could refer to proteins and their ulterior complexes, come from vocabulary terms created in Gene Ontology initiative.

Sounds cool to me.  This could allow for easier descriptions and expansions of genomics.  Humans as a programming language. I, Robot.

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