PubMed Canada to Store Government-Funded Studies

Canada has started a national online archive that will house papers and data coming from government-funded research, and will be funded by the Canadian Institutes of Health Research.

Modeled on the National Institutes of Health's PubMed Central, the PubMed Central Canada resource was launched to provide Canadians with a free and open national digital repository of peer-reviewed health and life sciences literature, including research funded by CIHR.

PMC Canada was developed through a partnership between the National Research Council's Canada Institute for Scientific and Technical Information (NRC-CISTI), which will build the infrastructure and manage the repository, the US National Library of Medicine, and CIHR.

The resource supports the Policy on Access to Research Outputs, which requires that CIHR grant recipients make their peer-reviewed publications freely accessible online within six months after they are published.

"The global movement to provide barrier-free access to research is gaining strength and with good reason, said Ian Graham, CIHR's VP of Knowledge Translation, in a statement.

"Having desktop access to a searchable, permanent and freely accessible archive of Canadian health research will serve as a valuable resource for researchers, enabling them to translate that knowledge into solutions to important health issues," NRC-CISTI Director General Pam Bjornson added.

The first phase of PMC Canada includes development of a bilingual interface and help desk and a manuscript submission system. The planned second phase of the repository will incorporate a customized web front-end and enhanced reporting and alerting features for system funders and users.

PMC Canada's future development will be guided by an advisory committee that will include health researchers and other stakeholders.

World's fastest growing Semantic discovery & Expert Curated Knowledgebase platform crosses 500,000 biomedical facts now

Indian Life Sciences Informatics Company, Molecular Connections announced today, that their XTractor Premium platform now has more that 503,985 "Expert" annotated biomedical facts from literature and is the fastest growing knowledgebase currently.

XTractor Premium platform is Fast Becoming the definitive Semantic Knowledge discovery & Expert curated Knowledgebase for Life Science Researchers. The XTractor Premium Knowledgebase in addition to more than 503,985 relationships on proteins, drugs, biological process and diseases has advanced semantic search, concept linking analytics for effective knowledge discovery and modeling.

XTractor Premium provides Precision based mining of the most relevant facts. Compared to natural language processing engines, manual annotation approach reduces false positives rate by 12-35%.

XTractor premium serves as a platform to stay current with weekly updates from PubMed. Provides “Topic Tracking” with email alerts on specific biological entities of interest via the “Watch List” feature.

The Highlights

Semantic Search: The first of its kind highly advanced search feature, where in one could query the XTractor Premium Knowledgebase using multiple ontologies. This would enable you to narrow down on your targets at ease.

Concept Linking: Our advanced query feature would enable you to make assumptions from multiple abstracts, and discover facts, which are hitherto not published.

Bibliographic search: Search based on author, organization, affiliation or country.

Save Export and Visualize: Save and export the data in user-friendly formats, also XTractor Premium is made compatible with CytoScape - so one can visualize the networks rendered using a in-house CytoScape plug-in.

Web based and onsite installation available

To know more about the advantages of the XTractor Premium and to register for a free trial account and a webex demo please visit XTractor Premium portal www.xtractor.in/premium.

About XTractor Premium Knowledgebase
XTractor knowledgebase currently contains 503,985 relationships on biomarkers, clinical trials, pathways, knockout studies, mutations, drug interactions, toxicity, pharmacokinetics, disease mechanisms. It is the Only Knowledgebase that gets updated everyday with manually annotated relationships from the latest PubMed publications and contains more than more than 1,269 Unique Drugs, 3,602 Unique Diseases, 11,407 Unique Proteins, and 3,266 Unique Biological Processes. Hence in no time one gets to access one of the largest and the most current manually annotated datasets across the world.

About Molecular Connections
Molecular Connections is a pioneering In silico Discovery Services Company. It provides high quality, cost effective curation, literature informatics solutions and annotation services as well as products. Dr. Limsoon Wong is the Chairman of Molecular Connections. Customers of Molecular Connections include leading pharmaceutical and biotechnology, drug discovery, genomics, proteomics, medical technology, equipment companies and academic institutions spanning across the globe. In addition, Molecular Connections has powerful tool development, database integration, effective data visualization capabilities, specific expertise in building knowledge bases for rapidly growing needs in, ADME Tox, clinical, drugs, chemistry and patent industries. For more information write to us at xtractorpremium@molecularconnections.com

Recent Awards
Deloitte Technology Fast 50 India Winners |Deloitte Technology Fast 500 APAC Winners |CNBC - ICICI Emerging India Awards ‘Small Enterprise of the Year’

XTractor Premium - A Platform for discovery, knowledge sharing, analysis and modelling of published biomedical facts.

• The only Knowledgebase which provides "manually" annotated facts from PubMed on a weekly basis
  
• Innovative Features like Semantic Search, Concept Linking, Bibliographic search, Save, Export and Visualize
  
• Only Knowledgebase with daily updations from PubMed
  
• XTractor Premium now at an Special Introductory Offer. Subscribe now and save!
  
• Request for a Trial
  

Collective Intelligence in Action - XTractor Premium

There's a great deal of wisdom in a crowd, but how do you listen to a thousand people talking at once? Identifying the wants, needs, and knowledge of internet users can be like listening to a mob. In the Web 2.0 era, leveraging the collective power of user contributions, interactions, and feedback is the key to market dominance. A new category of powerful programs and web based technology lets you discover the patterns, inter-relationships, and individual profiles-the collective intelligence, locked in the data people leave behind as they surf websites, post blogs, and interact with other users.

XTractor Premium is one such initiative, epitome of Collective Intelligence in Action for bio medical data. Implemens collective intelligence concepts of vital data gathering and mining techniques like analyzing trends, discovering relationships, and making predictions. It provides a pragmatic approach to personalization by combining content-based analysis with collaborative approaches for effective literature mining in todays eonomy...

XTractor Premium - A Platform for discovery, knowledge sharing, analysis and modelling of published biomedical facts.

• The only Knowledgebase which provides "manually" annotated facts from PubMed on a weekly basis
  
• Innovative Features like Semantic Search, Concept Linking, Bibliographic search, Save, Export and Visualize
  
• Only Knowledgebase with daily updations from PubMed
  
• XTractor Premium now at an Special Introductory Offer. Subscribe now and save!
  
• Request for a Trial
  

The future of biocuration

Blogging about curation in the past several issues have been discussed but here is something very critical.

To thrive, the field that links biologists and their data urgently needs structure, recognition and support.

Biocuration, the activity of organizing, representing and making biological information accessible to both humans and computers, has become an essential part of biological discovery and biomedical research. But curation increasingly lags behind data generation in funding, development and recognition.

Three urgent actions to advance this key field. First, authors, journals and curators should immediately begin to work together to facilitate the exchange of data between journal publications and databases. Second, in the next five years, curators, researchers and university administrations should develop an accepted recognition structure to facilitate community-based curation efforts. Third, curators, researchers, academic institutions and funding agencies should, in the next ten years, increase the visibility and support of scientific curation as a professional career.

Failure to address these three issues will cause the available curated data to lag farther behind current biological knowledge. Researchers will observe an increasing occurrence of obvious gaps in knowledge. As these gaps expand, resources will become less effective for generating and testing hypotheses, and the usefulness of curated data will be seriously compromised. When all the data produced or published are curated to a high standard and made accessible as soon as they become available, biological research will be conducted in a manner that is quite unlike the way it is done now.

Researchers will be able to process massive amounts of complex data much more quickly. They will garner insight about the areas of their interest rapidly with the help of inference programs. Digesting information and generating hypotheses at the computer screen will be so much faster that researchers will get back to the bench quickly for more experiments. Experiments will be designed with more insight; this increased specificity will cause an exponential growth in knowledge, much as we are experiencing exponential growth in data today.

Also read this

Do you want to know more?

Be a part of the XTractor community. XTractor is the first of its kind - Literature alert service, that provides manually curated and annotated sentences for the Keywords of user preference. XTractor maps the extracted entities (genes, processes, drugs, diseases etc) to multiple ontologies and enables customized report generation. With XTractor the sentences are categorized into biological significant relationships and it also provides the user with the ability to create his own database for a set of Key terms. Also the user could change the Keywords of preference from time to time, with changing research needs. The categorized sentences could then be tagged and shared across multiple users. Thus XTractor proves to be a platform for getting real-time highly accurate data along with the ability to Share and collaborate.

Sign up it's free, and takes less than a minute. Just click here:www.xtractor.in.

Smart tools to track, analyze and visualize research II

Previously blogging about Smart tools to track, analyze and visualize research discussed about the latest trends in literature abstraction, alert services and analysis tools. This time as a sequel check out one of the finest alert service using the web 2.0 technology. It is absolutely FREE! It is very simple, just visit the site www.xtractor.in and register. Almost immediately you are provided with a user-name and pw to access the alert service.

Smart tools to track, analyze and visualize research II

Talking about the development in the field of literature and scientific publication search. Looking beyond NLP some of the advancements and service models based on NLP and other advanced methods. Today to the user's delight there are quite a few companies and organization that provide services that absolutely make a scientist life easy!

These services revolve around customized alert services for selected search terms, specific research area of interest even more so pertaining to a list of custom key-word and search terms that the service providers allow the scientist to choose form. The scientist can simply subscribe to such service, sit back and wait for daily updates. The updates are provided on a day to day basis at his desktop.

A scientist gets abstract summarization, full text summarization so that he need not actually go through the ordeal of reading through pages of scientific literature. Some once else does the job for him and just pick up the right things that he would look for in such papers. It is a very interactive service where on a daily basis the user can keep track of the quality of the service and set it right so that he can make sure that he just gets the right things he ever wants and nothing else other than that.

Over and above the service is provided using cutting edge technology, attractive web interface. Such interface come in all colour with floating dockable modules which is easy to use and some smart tools too. These smart tools enable the user to track, analyze, visualize and develop relationships among blocks of data that is being provided as "lego blocks".

Check out this product, XTRACTOR™ the first of its kind - SCIENTIFIC LITERATURE alert service which also provides manually annotated sentences for the keywords of YOUR preference

• Highly accurate, manually annotated sentences for given keywords.
• Daily scientific literature updates at your desktop along with the extracted facts – manually curated.
• Provision to change keywords with your changing research preferences
• Annotated sentences and abstracts get stored in your profile, as and when they get updated in LITERATURE.
• Classify and create your own datasets of annotated facts
• Enhanced experiences of reading & analyzing literature
• Access your profile/ datasets from anytime, anywhere
• Discover and Create newer relations from scientific facts classified by the XTractor™ Community.
• Tag your favorite abstracts/sentences and share them across other users
• Much more faster and an Absolutely Free Service

Be a part of the XTractor community. XTractor is the first of its kind - Literature alert service, that provides manually curated and annotated sentences for the Keywords of user preference. XTractor maps the extracted entities (genes, processes, drugs, diseases etc) to multiple ontologies and enables customized report generation. With XTractor the sentences are categorized into biological significant relationships and it also provides the user with the ability to create his own database for a set of Key terms. Also the user could change the Keywords of preference from time to time, with changing research needs. The categorized sentences could then be tagged and shared across multiple users. Thus XTractor proves to be a platform for getting real-time highly accurate data along with the ability to Share and collaborate.

Sign up it's free, and takes less than a minute. Just click here:www.xtractor.in.

18 Ways to Improve your PubMed searches

Be a part of the XTractor community. XTractor is the first of its kind - Literature alert service, that provides manually curated and annotated sentences for the Keywords of user preference. XTractor maps the extracted entities (genes, processes, drugs, diseases etc) to multiple ontologies and enables customized report generation. With XTractor the sentences are categorized into biological significant relationships and it also provides the user with the ability to create his own database for a set of Key terms. Also the user could change the Keywords of preference from time to time, with changing research needs. The categorized sentences could then be tagged and shared across multiple users. Thus XTractor proves to be a platform for getting real-time highly accurate data along with the ability to Share and collaborate.

Sign up it's free, and takes less than a minute. Just click here:www.xtractor.in.

Sigma-Aldrich continues to make the Acta more useful and accessible to scientists around the world

Sigma-Aldrich announced that its highly acclaimed chemistry review journal, Aldrichimica Acta, has again been ranked #1 by Impact Factor, out of 56 similar journals in the field of Organic Chemistry. In 2007, the latest year for which such rankings are available, the Acta achieved an Impact Factor of 11.929. The Acta was also ranked #1 in 2006 and 2005. These rankings appear annually in the Science Edition of Journal Citation Reports(R) (JCR), which is published by Thomson ISI(R). JCR, Science Edition, tracks close to 5,900 international science journals annually and offers quantifiable statistical data, which allows the systematic and objective ranking of journals by relative importance within their subject categories.

The Aldrichimica Acta publishes in-depth reviews on topics of current interest to chemists. It is published four times a year and distributed at no charge to about 130,000 subscribers worldwide who are members of the scientific community.

XTRACTOR™ Data Mining Simplified

The first of its kind - SCIENTIFIC LITERATURE alert service which also provides manually annotated sentences for the keywords of YOUR preference

• Highly accurate, manually annotated sentences for given keywords.
• Daily scientific literature updates at your desktop along with extracted facts - manually curated.
• Provision to change keywords with your changing research preferences.
• Annotated sentences and abstracts get stored in your profile, as and when they get updated in PubMed.
• Classify and create your own datasets of annotated facts.
• Enhanced experiences of reading & analyzing literature.
• Access your profile / datasets from anytime, anywhere.
• Discover and Create newer relations from scientific facts classified by the XTractor™ Community.
• Tag your favorite abstracts and share them across other users.
• Much more faster and an Absolutely Free Service

PRODUCT HIGHLIGHTS

Abstract Summarization
The XTractor™ system would provide extracted relations in addition to identifying the abstracts of subscriber's interest. Our experience suggests time required for summarization of an abstract is the greatest as the user needs to understand the context, analyze the content and make sense of the relation followed by extraction. So not only the abstracts would be prioritized and delivered to the subscriber but also sentences, which are extracted and processed manually.

Categorization
Categorization involves tagging the extracted sentences to most popular ontology(s) in biology and chemical spaces. XTractor™ would ensure highly accurate (manual curation) in all its annotation efforts be it genes, processes or drug names, all mapped to their relevant ontology(s). So you need not work again on reclassification of sentences or facts to accurate ontology(s).

Topic Tracking
XTractor™ provides updates to the subscribers on a daily basis based on topic tracking in PubMed. The service allows the user to Key in the Keywords of interest and notifies them via email when new articles get published in PubMed. Unlike the other free NLP utilities that are available, Molecular Connections would be using its skilled scientists to validate the data.

Do you want to know more?

Interactive WikiProteins Project Invites Researchers to Annotate Biological Concepts

Hoping to bring together “a million minds” to annotate proteins, a team of researchers has launched a large-scale, community-based project called WikiProteins that combines automated text, data, and concept mining, manual annotation, and a newly developed software component called the Knowlet.

The project, which aims to annotate proteins and protein-related biomedical concepts such as diseases or organisms, will be powered by a platform technology designed by a group of scientists and a Rockville, Md.-based startup and will be made available free of charge in perpetuity for the scientific community and the public.

Called WikiProfessional, the platform “in a technical sense powers the community-version that we have now put out there, but you could take exactly the same technology platform and install it locally at a pharmaceutical company for them to do drug-lead discovery,” said Albert Mons, a computational linguist and co-founder of the startup, Knewco.

“Philosophically we wanted to hand off the responsibility for the quality of the content of the system to the community and then provide generic technology that can be used to grow the knowledgebase on a daily basis,”

Given high-throughput data and the increasing number of papers describing them, “comprehensive and timely annotation of the literature for facts by any central team of experts [is] an unachievable goal. Computer assistance in the annotation process is, therefore urgently needed,” the scientists wrote in a paper published in the current issue of Genome Biology.

WikiProteins was created over the last two years and announced on May 28, by a team of scientists from the Swiss Institute of Bioinformatics, the GO consortium and the IntAct database at the European Molecular Biology Laboratory-European Bioinformatics Institute, Erasmus Medical Centre, Leiden University Medical Centre, both in the Netherlands, the Brazilian Stela Institute, the WikiMedia Foundation, and Knewco.

The project is an interactive and semantically supported workspace based on Wiki pages and contains a knowledgebase, a navigation tool, and a section on the people in its annotating community. Beneath that layer is a relational Wiki based on WikiData software, an indexer, and software that creates components called Knowlets, which stores the relationships between all the mined concepts.

Knowlets are at the core of this platform, a proprietary concept mining software component and ontology format that Knewco has developed over the last two years.

Writing in the Genome Biology paper, the team said information is mined from scientific publications and the Knowlet links two given concepts, but records that information only once.

“This approach results in a minimal growth of the ‘concept space’ as compared to the text space,” the authors wrote. New and unique facts in the scientific literature expand the corpus to a much lesser degree than the totality of the text generated by new academic journal articles.

Concept pairs are placed in what the WikiProteins creators call a “related concept cloud.” By applying a meta-analysis algorithm, the software calculates a semantic association to reflect the strength and type of relationship the concepts have.

The relationship is dynamic and recalculated based on newly mined information. Its calculated value is based on three factors: factual statements found in the scientific literature or databases, increasing co-occurrence of two concepts in a sentence or a paragraph, and predictive associations based on the overlap of the two concepts.

The WikiProteins terminology has been mapped to concept identifiers in the Wiki-based terminology system called OmegaWiki. WikiProteins and OmegaWiki are driven by a relational database that is linked to the Knowlets by on-the-fly indexing of all Wiki pages. An indexer called Peregrine is designed to recognize concepts by the Wiki, and the indexer is coupled to a terminology system derived from OmegaWiki.

Each biomedical concept has its own page that includes up-to-date annotations. Registered users can become annotators and edit records. WikiProteins shows the new record alongside the original one that was mined from the authoritative databases. Professional annotators at their respective databases can choose to incorporate some of new community-entered information into their database.

Do you want to know more?

Automatic content for the people

Anyone who has ever built a website knows that maintaining it is a lot of work. There’s just making sure it hasn’t gone offline because the httpd daemon died. Constant monitoring for script kiddies and their SQL injections. Not to mention continually feeding it with fresh content, lest your audience become bored and desert.

I’ve always thought it would be cool to build a site that could more or less look after itself. There’s a myriad of content management systems to choose from, most of which are somewhat hackable in whatever language they happen to be coded in. One of the more mature in this respect is Drupal - which is the engine behind Eureka! Science News. It’s a fully-automated science news portal, using a bunch of customised Drupal modules to aggregate, cluster, categorise and rank articles.

First impressions are excellent. Coders will enjoy this post at Drupal explaining how it all works.

Molecular Connections Pvt. Ltd. to Sponsor ICIC for the second time

The International Conference in Trends for Scientific Information Professionals

Habitual attendees say that "it is the meeting to which they go to spot the trends, as well as the meeting that provides unparalleled opportunities for networking" Trends and networking will be high on the Nice agenda in October 2008.

The ICIC meeting covers trends in the field of scientific and professional information with an impressive line-up of significant figures in the information world. Among the topics that will be covered and discussed by the 22+ speakers are:

• Tools for Competitive Intelligence (e.g., mining tools, visualisation tools, analysis tools, etc)
• Challenges for the information community over the next five years
• Changes in the information environment for patents, innovation and intellectual property
• Trends in Search Engines and Information Retrieval (also see)
• Case Studies in Data and Content Integration

Structured Digital Abstracts - Easier Literature Searching

Already blogging on similar lines and the subject of Bring in data from the published literature in my earlier blog Smart tools to track, analyze and visualize research , here is another interesting experiment on similar lines:

The experiment centres on Structured Digital Abstracts (SDA). SDA are extensions of the normal journal article abstracts that describe the relationship between two biological entities, mentioning the method used to study the relationship. Each sentence is preceded by one or more identifiers pointing to the corresponding database entries that contain the full details of the interaction e.g. protein A interacts with protein B, by method X.

The aim of SDA is to assist data entry, text mining and literature searching by extracting the salient data from the article into simple sentences using a defined structure and controlled vocabularies.

Gianni Cesareni, Editor of FEBS Letters explains:

Many articles in biological journals describe relationships between entities (genes, proteins, etc.) yet this information cannot be efficiently used because of difficulties in retrieving from text. Databases capture this valuable information and organize it in a structured format ready for automatic analysis. The experiment of using SDAs will facilitate database entry and improve disclosure, to the benefit of authors and readers.

Protein structure databases with new web services for structural biology and biomedical research

The Protein Data Bank Japan (PDBj) curates, edits and distributes protein structural data as a member of the worldwide Protein Data Bank (wwPDB) and currently processes 25–30% of all deposited data in the world. Structural information is enhanced by the addition of biological and biochemical functional data as well as experimental details extracted from the literature and other databases. Several applications have been developed at PDBj for structural biology and biomedical studies: (i) a Java-based molecular graphics viewer, jV; (ii) display of electron density maps for the evaluation of structure quality; (iii) an extensive database of molecular surfaces for functional sites, eF-site, as well as a search service for similar molecular surfaces, eF-seek; (iv) identification of sequence and structural neighbors; (v) a graphical user interface to all known protein folds with links to the above applications, Protein Globe. Recent examples are shown that highlight the utility of these tools in recognizing remote homologies between pairs of protein structures and in assigning putative biochemical functions to newly determined targets from structural genomics projects.

for more

Semi-automated workflows - Taverna Interaction Service

Have you been wondering about possibility of automating every scientific workflow? :

The Taverna Interaction Service: enabling manual interaction in workflows by Anders Lanzén and Tom Oinn

Taverna is an application that eases the integration of tools and databases for life science research by the construction of workflows. The Taverna Interaction Service extends the functionality of Taverna by defining human interaction within a workflow and acting as a mediation layer between the automated workflow engine and one or more users.

Try Taverna plugin is very likely an answer to automation of bioinformatics workflows...
(Bioinformatics Advance Access abstract)

Smart tools to track, analyze and visualize research

Yes i am talking about the development in the field of literature search and scientific publication search. Looking beyond NLP some of the advancements and service models based on NLP and other advanced methods. Today to the user's delight there are quite a few companies and organization that provide services that absolutely make an scientist life easy!

These services revolve around customized alert services for selected search terms, specific research area of interest even more so pertaining to a list of custom key-word and search terms that the service providers allow the user to choose form. The scientist can simply subscribe to such service, sit back and wait for daily updates. The updates are provided on a day to day basis at his desktop.

He gets abstract summarization, full text summarization so that he need not actually go through the ordeal of reading through pages of scientific literature. Some once else does the job for him and just pick up the right things that he would look for in such papers. It is a very interactive service where on a daily basis the user can keep track of the quality of the service and set it right so that he can make sure that he just gets the right things he ever wants and nothing else other than that.

Over and above the service is provided using cutting edge technology, attractive web interface. Such interface come in all colour with floating dockable modules which is easy to use and some smart tools too. These smart tools enable the user to track, analyze, visualize and develop relationships among blocks of data that is being provided as "lego blocks".

"Knowledge is power" but knowledge is money too big money these days!

As an estimate companies providing such services are looking at a market size of $770 million worldwide which spans across verticals like bio-cheminformatics, knowledge management and content database. While the estimated market size for computational chemistry and knowledge management for life science vertical is approximately $400 million.

Life Science and Informatics

What is this?
is this a new industry?
or a old wine in a new bottle?

may be the later is true, bioinformatics is more popularly known by this name in the industry circle these days!

Well Life Sciences and Informatics can be any thing form anything form computational biology, all omes and omics, core bioinformatics to curation and literature mining, database creation, in the area of biology, chemistry , bio-chem space.

Cheminformatics, insilico chemistry and insilico biology how best to describe the host of activities involved that companies do to serve their clients and earn revenues for their firms...

There are number of companies in India and bangalore is the forefront as a major bio-cluster with 20 to 30 companies operation in this sphere.

there are companies with the sole focus as informatics as business
to name a few :

• Molecular Connections Pvt. Ltd.
• Jubilant Biosys
  
• Strand Life Sciences
  
• Ocimumbio (hyderbad)
  

While IT companies which are also in to Life Sciences as one of their business verticals

• TCS
• HCL (not yet in Bangalore)
• Wipro etc.
  

now how good are these companies doing?
how good are they in terms of the international markets and how profitable is their business?
what do they do?
their clients?

These are some interesting things that could be discussed in this blog page...

Links:

• http://www.kameshwaran.fr.fm/
• http://jkamesh.googlepages.com/
• BioIT Alliance
• See what Wiki has to say about Informatics