XTractor knowledgebase crosses 300000+ facts

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

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

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?

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

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

XTractor knowledgebase touches 200000 facts within just 1 year of its launch

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 200000 facts updated in just 1 year of its launch providing information on Disease mechanisms, Biomarkers, Drug effects and interactions, Clinical trials, Prognosis, Pathways, Knockouts, Mutations, RNAi studies, and much more…

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 Premium published in Nature Methods

This week we got our first application note on XTractor Premium published in Nature Methods– a science methodology journal publishing laboratory techniques and methods papers in the life sciences and areas of chemistry.

The article can be accessed at: http://www.nature.com/app_notes/nmeth/2009/090906/full/an7147.html#a1

Title: “XTractor Premium – a Knowledgebase of manually annotated biomedical relationships updated everyday from PubMed abstracts”

The article initially addresses the main drawbacks of data mining – the organization of the quantum of published biomedical literature in  PUBMED, time and cost consumed in analysing this data. It brings out the utilities of the XTractor Premium, which can accurately process this vast repertoire of scientific information with a quick turn around time. It also features the advanced analytical tools that come in handy with the XTractor Premium Knowledgebase such as Semantic Search, Concept linking, Bibliographic Search and comprehensive downloadable reports for faster analysis of the biomedical data.

The case study “Tracking common gene polymorphisms across multiple Diseases using XTractor” presented in the article provides the ability of XTractor Premium to help us discover newer facts in published literature within a quick 15-20 mins analysis time.

http://www.xtractor.in/premium

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

XTractor Premium – Increasing coverage of proteins, diseases, drugs and processes

With the growing number of relationships, XTractor Premium Knowledgebase now contains a more comprehensive list of proteins, diseases, drugs and processes allowing the analysis of published biomedical facts on a wider range than before. We estimated the number of each of these entities annotated till date and found that XTractor Premium Knowledgebase currently covers 44% of Swiss Prot Proteins, 50 % of MesH diseases, 62% of Drugs from Drugbank and 17% of biological Processes from Gene Ontology DBs within one year of content.

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

What do Lung Cancer, Ovarian Cancer, Breast Cancer and Colon Cancer have in common?

Common Proteins:

ABCB1, AKT1, AKT2, AKT3, ALDH1A1, AURKA, BCL2, BIRC5, CASP1, CASP3, CASP7, CASP8, CASP9, CCL2, CCND1, CCNE1, CD274, CD40, CD40LG, CD82, CD8A, CDH1, CDKN1A, CDKN1B, CDKN2A, CEACAM5, CTNNB1, CXCR4, DAG1, EGF, EGFR, EPHA2, ERBB2, ESR1, ESR2, FN1, FRAP1, GSTM1, HDAC1, HIF1A, HSPA5, IFNG, IGF1, IGF1R, IL1B, IL2, IL8, ITGB1, JUN, KRAS, KRT20, LEFTY2, LEP, MAP2K1, MAPK1, MAPK10, MAPK11, MAPK14, MAPK3, MAPK8, MAPK9, MKI67, MMP1, MMP13, MMP14, MMP2, MMP9, MUC1, MYC, NFKB1, NFKB2, PIK3C3, PIK3CA, PIK3CG, PIK3R1, PIK3R2, PLAU, PLAUR, PTEN, PTGS2, PTK2, PTK2B, RB1, REL, RELA, RELB, SCGB2A2, SRC, STAT3, STK11, TERT, TGFB1, TGFB2, TGFB3, TNF, TNFRSF10B, TNFSF10, TP53, TYMS, VEGFA, VEGFB, VEGFC, VIM

Common Processes:

angiogenesis, anti-apoptosis, apoptosis, autophagy, cell adhesion, cell cycle, cell cycle arrest, cell death, cell differentiation, cell growth, cell migration, cell proliferation, DNA Methylation, drug resistance, epithelial to mesenchymal transition, gene expression, gene silencing, growth, lymphangiogenesis, metabolism, methylation, negative regulation of cell growth, negative regulation of cell proliferation, response to hypoxia, response to oxidative stress, RNA interference, signal transduction

Common Drugs:

Cetuximab, Cisplatin, Doxorubicin, Etoposide, Fluorouracil, Gefitinib, Paclitaxel

Common Diseases:

Carcinoma, Hepatocellular; Carcinoma, Lewis Lung; Carcinoma, Renal Cell; Colorectal Neoplasms; Esophageal Neoplasms; Glioblastoma; Head and Neck Neoplasms; Inflammation; Kidney Neoplasms; Leukemia; Liver Neoplasms; Melanoma; Neoplasm Metastasis; Neuroectodermal Tumors; Osteosarcoma; Pancreatic Neoplasms; Prostatic Neoplasms; Skin Neoplasms; Stomach Neoplasms; Thyroid Neoplasms; Uterine Cervical Neoplasms; Uterine Neoplasms

Try XTractor Premium Semantic Search to know more, www.xtractor.in/premium

Mail us at xtractorpremium@molecularconnections.com

XTractor knowledgebase now touches 150000 relationships

Last week the XTractor knowledgebase has clocked 150,000 manually categorized biomedical facts.

The knowledgebase currently grows at a rate of more than 700 facts every single day from PubMed and covers information on Biomarkers, Disease mechanisms, Clinical Trials, mutations, knockouts and pathways.

Also we have recently crossed: >10000 + relationships on  knockout and mutation studies alone in XTractor.

• Knockout/Knockdown related facts: 10132
• Mutation related facts: 14331

So not only you get the most relavant scientific facts everyday but also individual up todate knowledgebases on Knockouts, mutations, biomarkers and so on….