XTractor- PubMed mined everyday manually

The XTractor Knowledgebase Advantage

XTractor — Thu, 09 Dec 2010 10:32:31 +0000

Now speed up your research, not at the cost of your convenience of storage!
Modify content as per your research needs
No longer – subscription based database charges, a one time investment that can provide you with the required content at your fingertips
No dependencies on rigid user interface but integrate content with your most favorite interface & visualization or legacy platforms
Harness the power of public identifiers such as UniProt, DrugBank, Gene Ontology and MeSH used annotation of Literature in turn to enable easy content integration
View your experimental content in combination with XTractor content
24 rule based categories for classification of facts from PubMed; based on Marker studies, Mutations, Pathways etc.
All content available as XML format
Above all, content stays secure within your firewalls
Avail a quarterly update on latest published PubMed content

Wire to us for information XTsales@molecularconnections.com

Semantically enriched PubMed content with 24 rule based Categories/Classification

XTractor — Wed, 17 Nov 2010 07:25:09 +0000

With large volumes of literature knowledge available on PubMed. It’s highly time consuming to keep track of the literature updates and integrate the literature findings with one’s own experimental data.

If you are looking at semantically enriched PubMed content from 1927 onwards with appropriate content classification then, Molecular Connections brings you the opportunity to own a fully annotated and classified XTractor Knowledgebase.

Unlike most of the knowledgebase providers, where the content is tied with their own user interfaces, thus limit the ability to perform the most intricate queries or prevent inhouse integrations of content. This model enables storage of the annotated content at the user’s end and also integrate with one’s proprietary/public knowledge and content in-house.

24 Rule Based Categories to classify the Information:

24 Rule Based Categories

XTractor – Knowledgebase

XTractor — Thu, 28 Oct 2010 07:02:31 +0000

Now, get access to the entire XTractor Knowledgebase content of more than 13 million categorized facts from PubMed!!

Some of the questions you can answer with the XTractor Knowledgebase content

Content spread across 24 rule based categories of XTractor Knowledgebase

Content Spread across 24 rule based categories of XTractor Knowledgebase content

Webinar on “Understanding multiple target preferences for Drug Re-purposing & Therapeutic Switching in Cancer therapies”

XTractor — Thu, 01 Apr 2010 09:41:03 +0000

Join us as we share some Re-purposing insights on some key cancer drugs through Semantic Knowledge discovery

Cancer can be biomedically interpreted as abnormal cell proliferation – A cascade of events characterized by changes in several biomedical entities like proteins, processes & drugs. Several Drugs influence cancer therapy and many of them may have applications in treatment of different cancer types or they may find uses in other disease areas as well. Drug repurposing has been gaining importance in the last few years as an increasing number of drug development and pharmaceutical companies see their drug pipelines drying up and realize that many previously promising NCEs have failed to deliver.

In this presentation we will demonstrate how XTractor Premium platform can be used to reveal the relationships of various drugs / genes / proteins targets and receptor types from manually annotated facts from published sources, semantically find links and facilitate forming hypotheses for potential Re-purposing & Therapeutic Switching. We will present a case study to showcase how evidences from literature can suggest or bring about a potential Drug Re-purposing.

We will also demonstrate & help discover distinctive features influenced by common biomedical entities between several drugs, with the help of advanced semantic search and concept linking capabilities of our Semantic Knowledge discovery Platform with Expert curated Knowledgebase. These searches can be applied to annotated facts within XTractor Platform or could be customized to work on any in-house, proprietary data sources of your organization.

To register please follow the link below

http://www.xtractor.in/premium?webinar=true

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

XTractor — Fri, 11 Dec 2009 07:07:50 +0000

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 SemanticKnowledge 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.

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.

XTractor knowledgebase crosses 300000+ facts

XTractor — Thu, 22 Oct 2009 12:52:20 +0000

XTractor is one of its kind biomedical literature knowledgebase which updates refined facts from PubMed every single day.

The XTractor Premium Knowledgebase now has more than 300000 facts with more coverage of manually annotated drug and disease related facts published in PubMed…

The product is currently being widely used by more than 2000 researchers across the globe.

http://www.xtractor.in/premium

For a 1-month FREE Trial access: http://www.xtractor.in/trial.do

For trial access contact: http://www.xtractor.in/trial.do

XTractor outlink Integration with Entrez Gene

XTractor — Thu, 15 Oct 2009 06:09:06 +0000

Entrez gene is the most widely used data resource for Gene based information worldwide. To enable researchers to obtain high quality manually annotated information from XTractor when they search for a Gene on Entrez Gene, we are now providing direct links from Entrez Gene records to corresponding Gene Reports in XTractor.

To use this outlinked option- when in Entrez Gene, for any human gene select the “Link Out” option from the Display menu in Entrez Gene and click on the XTractor link. You will be taken directly to the XTractor graphical report for the Gene of interest and also manually annotated facts on the associated Diseases, Drugs and the Biological Processes for the Gene.

http://www.xtractor.in/ncbiSearch.do?xid=XT_15377&symbol=BRCA1

About XTractor Premium:

XTractor Premium – a platform for discovery, analysis and modelling of published biomedical facts. The application also comes with -XTractor Premium Knowledgebase – the only knowledgebase, which provides “manually” annotated facts from PubMed on a weekly basis. XTractor- (basic version) has been widely adopted by the life sciences research community and has more than 2000 users from 300 organizations across the globe.

http://www.xtractor.in/premium

For trial access write to us at: http://www.xtractor.in/trial.do

XTractor Premium – Semantic Search over manually indexed data

XTractor — Wed, 23 Sep 2009 05:52:04 +0000

Searching through the vast repositories of biomedical literature, has been a long standing problem. XTractor Premium comes with a highly advanced semantic search feature which enables you to mine the most relevant information in matter of seconds. In comparison to similar application which guarantee results – XTractor Premium is far more effective in addressing scientific problems. We have multiple ontologies integrated into our semantic search panel, so that your search time is reduced.

EG: You could ask questions like:
Which are the GPCR class I receptors that are involved in colon cancer
OR which of the anti asthmatic drugs are also used for treatment diabetes type 2.

The search retrieves you the most significant results- due to the fact that XTractor relies on manual annotation of data. Manual annotation enables us to reduce the false positive mapping and also enables the correct alias/synonym mapping to a large extent. So inturn better results and faster discovery.

Many biomedical search engines talk about searching through the entire Medline but results are highly erroneous as they do not handle cases such as isoform specificity of a proteins and also since they are limited to keyword based or single entity based searching it gives the end user a limited chance to view all the published findings. Many of these search engines just run their query on the top 100 or 200 abstracts for refining purposes- but XTractor Premium with its inbuilt semantic search indexes is able to quickly compute multiple relationships across entities and enables faster generation of scientific hypothesis from the evergrowing XTractor knowledgebase of more than 250000 facts.

To use Semantic search feature- get a free access at:

http://www.xtractor.in/trial.do

Can Antidiabetic Drugs be reused in Alzheimer Disease?

XTractor — Fri, 04 Sep 2009 05:57:35 +0000

We recently did some interesting analysis on common regulatory pathway points across two different diseases using XTractor Premium ( http://www.xtractor.in/premium).

A case study on antidiabetic drugs and can they be reused in Alzheimer’s disease – a hypothetical view purely drawn from the fact that common functional proteins and pathways mediators that are involved in both Diabetes type 2 and Alzheimers Disease.

We analyzed the antidiabetic drugs which regulate PPAR gamma and inturn induce IDE ( insulin degrading enzyme) which acts as key mechanism in Alzhemiers disease regulation as well.

So using the high end analytical features – such as semantic search over the semantically enriched content in XTractor, with in minutes- we were able to derive hypothetical relationships between antidiabetic agents such as: Rosiglitazone, Telmisartan and Losartan act through PPAR gamma cascades and could probably be used in treatment of Alzhemiers disease as well.

The Case study 11: can be viewed at : http://www.xtractor.in/case_study.do

Case Study 11 – To explore the possibilty of using Anti-diabetic drugs in treatment of Alzheimer’s disease Using XTractor

XTractor is the only knowledgebase which enables the researcher to quickly link concepts semantically and is 100% manually annotated.

Free trail contact: http://www.xtractor.in/trial.do
mail us at: xtractorpremium@molecularconnections.com

The changing landscape of text mining

XTractor — Tue, 28 Jul 2009 10:48:45 +0000

A number of factors have impelled sustained text analytics market growth. The technology; text mining and related visualization and analytical software deliver unmatched capabilities in domains such as intelligence and life science. Text analysis is seen as a subspecies of business intelligence, and capabilities will be an essential component of the eventual creation of the Semantic web. By automating the reading process, text analytics allows analysts and researchers to tap material that had not previously been systematically mined in at least a semi automated manner. It allows to work far faster than before and to analyze far greater volumes of information than ever before. Importantly, text analytics can make a huge difference in text analysis and processing costs and enable the creation of new information products and services.

Applications of text mining in the life sciences includes pharmaceutical lead generation – mining scientific literature to accelerate expensive, time consuming drug-discovery processes, the huge and growing volume of on-line content, advances in search and information retrieval, cheap computing power, and better software have created a market for application of these same text technologies to a much broader variety of business, scientific, and research problems.

In spite of the progress in text mining, there is still a lot of scope for improvement. Not all lingual nuances are picked up; also, incorrect usage due to human error may lead to altered/incorrect results. At the present moment in time, maybe a backup plan; like quick manual checks of the processed materials may be the way. Manual checks are necessary especially in life sciences where synonyms are a norm and replacing one name with another, incorrect one is a high possibility.

One such example of this type application is XTractor Premium –a platform for discovery, analysis and modelling of published biomedical facts. The application also comes with -XTractor Premium Knowledgebase – the only knowledgebase, which provides “manually” annotated facts from PubMed on a daily basis.

http://www.xtractor.in/premium

For a 1-month FREE Trial access: http://www.xtractor.in/trial.do