How does it work?

• Click on “Upload terms” which is just below the search bar on the DistilBio homepage.
• This will take you to a login page where you can sign up if you are new to DistilBio or login if you already have a username and password.
• Once you login, the upload page comes up. Give your list a name and select the type of data. This could be a list of compounds, drugs, diseases, genes or proteins. The list should contain only items of the same data type.

• You can also upload database identifiers by selecting “I’ m using standard database identifiers” and selecting the appropriate database and adding the prefix if any.
• Paste the items in the box and you are ready to go.
• Hit the upload button and your query is saved and it takes you to “My saved searches” page. Here you can view, run or delete your query.
• In case DistilBio cannot find any of the terms that you have uploaded this will be flagged and will not be considered in the search.
• Run your query to find all connections available in DistilBio.

Want to take DistilBio for a spin? Copy and paste the following genes in DistilBio. I have added genes only for humans to narrow down the results.

akt1[homo sapiens]
abl1[homo sapiens]
brca1[homo sapiens]
brca2[homo sapiens]
cdk4[homo sapiens]
adam29[homo sapiens]
mapk1[homo sapiens]
map3k8[homo sapiens]
ctnnb1[homo sapiens]
egfr[homo sapiens]

You can explore the connections for these genes like pathway, disease, GO-terms, cell-lines, mutations. You can also select any genes and filter or extend the queries based on the genes.

We are working on pushing this feature forward to include more upload options and welcome your inputs. Stay tuned, there’s more to come.

The DistilBio bookmarklet detects the terms using relevant life-science ontologies and synonyms. Clicking on the terms takes the user to the DistilBio site that displays all the connections available for the term. The results are derived from many publicly available data sources such as Uniprot, Drugbank, PharmGKB, OMIM, CTD, Chembl, Chemspider, IntAct, MINT and Gene Ontology and presented as a set of connections.

To see how the bookmarklet works, let us look at an article related to biology on the net. I found a paper in plosone.org and clicked on the DistilBio Terms button. This displays a panel on the right of the page with a list of the terms detected in the paper and categorized into pathway, genes, proteins, drugs, diseases, compounds and organisms. Clicking on any of the terms takes the user to the DistilBio site and displays all the connections available for the term.

Try it on your data too

This app can also be used by users to find terms in their data which are not webpages. All the user has to do is go to http://terms.distilbio.com/tools and click on the “Try it” button. The user can now copy & paste their data in the box and hit submit. All biomedical concepts are detected and displayed as clickable links to the DisitlBio data.

The terms are displayed as below

A disclaimer is that the context of some of the results shown may differ from what is referred to in the article. The user will have to use their discretion while viewing the results.

Installing the bookmarklet is very simple.

1. Go to http://terms.distilbio.com/tools.
2. Display your Bookmarks bar by hitting Shift+Ctrl+B
3. Drag the “DistilBio Terms” button (displayed in the site) to your Bookmarks bar.
4. When you are browsing the web, push the “DistilBio terms” button to highlight all recognized terms in the page.

This app is best viewed in Firefox 3.4+ or Chrome 10.1+

We would love to hear from you. Do leave your feedback & suggestions as comments in this blog or drop us an email at info@metaome.com

]]> http://blog.metaome.com/distilbio/metaome-releases-the-distilbio-terms-bookmarklet/feed/ 0 http://blog.metaome.com/distilbio/distilbio-new-features-and-data/ http://blog.metaome.com/distilbio/distilbio-new-features-and-data/#comments Wed, 27 Feb 2013 16:43:46 +0000 preethi http://blog.metaome.com/?p=786 Continue reading →]]> Over the past few weeks we have been adding new features and data to enhance the user experience. Some of the new features are detailed below.

Features:

Instant display of results

The query interface has been revamped to display results instantaneously as the user starts typing a query. Earlier, as the user created a query, nodes were formed in the panel above the search box and the user had to hit “Search” to view results. In the new release, as the user starts typing a query, the various options are displayed in the auto-complete and the results are simultaneously displayed in the result interface below the search box. The results displayed below changes dynamically as the user continues typing. For example, as the user types “Aspirin”, results are displayed instantly. Results change as the user continues adding letters to the search term. Users can also view the query nodes by clicking on the arrow above the query box.

Facet modification

Earlier, the facets in the result browser were static and sometimes this presented a problem when there were multiple facets and user had to scroll down the page to find relevant data. Now, the facets can be maximizes, minimized and moved around to view only the data the user in interested in viewing.

Provenance

One of the first things a researcher asks when he/she finds a connection between 2 concepts is “what is the provenance for this connection?” In the latest release of DistilBio, users can click on the connecting link between 2 facets and view the source of the data (displayed to the top right of the page) and also the curated publications for the links. The curated publications are derived from the source databases from which the data has been integrated.

Numerical operators

Querying using numerical operators is another feature that has been enabled in DistilBio. Many a times users while working on small molecules/drugs/proteins need to find molecules of a particular molecular weight or logP value etc.  Users can now build queries in DistilBio using numerical operators like <, >, =. For example, if a user wants to find all compounds that target the protein cdk1 in human.

Query: cdk1_human ---> compound

The results show 3326 compounds targeting the protein cdk1_human. To narrow down the list, the user can now find compounds with a molecular weight of say < 300.

Query: cdk1_human ---> compound ---> molecular weight <300

This narrows down the list to about 494 compounds. Similarly the user can further narrow down the list using LogP, LogD, ALogP values etc.

Regular expressions

There are instances when the user will want to find a drug, protein etc but will not know the complete name of the molecule. DistilBio now allows the use of regular expressions to enable the user find the search term easily. For example, if a user wants to find all the “Gliptins” and is not sure of the names of the drugs, the query can now be built as follows:

Query: *gliptin

From the drop-down, select the type “Drug ending with” to indicate that the name of the drug ends with gliptin.

Results displayed below will show that there are 3 gliptins – Saxagliptin, Sitagliptin, Vildagliptin. All the links available for the drugs are also displayed in the facets.

Data

Updated Data

Data has been updated for most datasets to the latest version available. Swissprot has been updated to the Dec 2012 release version. For a complete list of databases integrated in DistilBio have a look at the help page.

Protein domains

Protein domain data from Interpro has been added in DistilBio. Users can now query for proteins and find domains present in the protein and also find all proteins that contain a particular domain.

Query: cdk1_human > proteindomain

Results show 3 domains for the protein. For instance, if a user wants to find all proteins that contain the domain “Protein kinase, catalytic domain”, the user can extend the query by selecting the domain and clicking on extend and add the concept “protein” to the query.

Query: Protein kinase, catalytic domain > protein

This displays all proteins that contain the protein domain “Protein kinase, catalytic domain”

Small molecule Activity and assay data

Data from ChEMBL database has been updated to include data on bio-activities and assay. Users can now query for small molecules and their associated activities and also find bio-assays in which these compounds and activities have been measured.

Query: Compound > activity > assay

New properties for data from DrugBank and Swiss-Prot

DistilBio now covers most of the data available in DrugBank and Swiss-Prot.

New properties that have been added to the drug data from DrugBank include

• Absorption
• Brand Mixtures
• Food Interactions
• LogP
• Manfacturer
• Molecular Formula
• Pharmacodynamics
• pKa
• Volume Of Distribution
• Water Solubility

New connections and properties have also been added to protein data from Swiss-Prot. Connections that have been added include protein sites and regions like active site, binding site, metal binding regions, motifs etc. Users can also query for catalytic activities, PTM, induction, biophysicochemical properties such as Km, Vmax. Cross-references to databases covered in Swiss-Prot have also been included. For a complete list of connections and properties have a look at the help page of DistilBio.

We would love to hear your inputs on the latest release of DistilBio. You could respond to this blog or write to us at distilbio@metaome.com.

]]> http://blog.metaome.com/distilbio/distilbio-new-features-and-data/feed/ 0 http://blog.metaome.com/distilbio/distilbio-terms-app-now-available-in-elseviers-sciencedirect/ http://blog.metaome.com/distilbio/distilbio-terms-app-now-available-in-elseviers-sciencedirect/#comments Wed, 22 Aug 2012 17:17:16 +0000 preethi http://blog.metaome.com/?p=729 Continue reading →]]> The DistilBio Terms application detects and lists biomedical concepts such as genes, proteins, drugs, compounds and pathway mentioned in the article. Once the user has installed the app, it is visible when viewing ScienceDirect articles and detects the terms using relevant life-science ontologies and synonyms.

Clicking on the terms takes the user to the DistilBio site that displays all the connections available for the term. The results are derived from many publicly available data sources such as Uniprot, Drugbank, PharmGKB, OMIM, CTD, Chembl, Chemspider, IntAct, MINT and Gene Ontology and presented as a set of connections.

Let us look at a paper and see how this app works. On opening the full text of a paper, the DistilBio terms is displayed in the side panel on the right of the article with a list of the terms detected in the paper and categorized into pathway, genes, proteins, drugs, diseases, compounds and organisms. The terms are also highlighted as clickable links in the text of the article.

Clicking on any of the terms displays the connections available for the particular term. Clicking on Breast Cancer in the above example displays the results as below.

Clicking on the name (as shown in red) takes the user to the DistilBio site where the user can explore further.

A disclaimer is that the context of some of the results shown may differ from what is refered to in the article. The user will have to use their discretion while viewing the results.

To install the app, follow the instructions below:

1. To get started you will need to have an account on Elsevier’s Science Direct.  If you already do, please login at ScienceDirect and move on to the next step. If you don’t have an account you can create an account for free at ScienceDirect (click on Register on the top right of the page).
2. Now open the “DistilBio Terms” app page and click on “Add Application”.
3. Open any article on Science Direct and you will see a widget titled “DistilBio Terms” appear on the right column of the page.
4. After the widget has loaded, click on any terms on the widget to view all connections for that specific term in DistilBio.

This app is best viewed in Firefox 3.4+ or Chrome 10.1+.

We would love to get your feedback on the app and if you found it useful.

As the user starts typing the search term a count for the number of entries available is displayed at the right of the search box. This allows the user to know the number of entries available and probably specify the search term to narrow it down what the user is looking for. The count appears for only the first search term and does not appear for subsequent search terms added.

The “type” of data eg: drug, disease, gene, connection, property etc now appears to the right of the drop-down box for easier readability.

Earlier the drop-down box displayed the first 5 entries for the search term. This has now been increased to 20 entries. The user can scroll down to find more relevant search terms. We are also looking at adding a “more” option in case more entries are available. This is a feature that will be added soon.

We are also working on displaying only actual connections available for a search term. Eg: Drug A has data available for 5 connections whereas Drug B has data available only for 3 connections. Currently all the possible connections for a drug are displayed for both A and B in the drop-down. We are looking at displaying only the entries that have data for the search term specified by the user. This ensures that the user is not faced with empty results, rather finds more relevant results that they are looking for.

Do try out the new features and we would love to hear your feedback!

As we add new features and data to DistilBio, we would like this process to be user driven. This means that we would like you to tell us what you want. Searches across public data will remain free.

Input that we are specifically looking for:

1. Are there specific databases you would like us to add?
2. Are there specific types of data you would like us to add? Fore.g. gene expression data, clinical data etc.?
3. Are there specific analysis tools that you would like us to add e.g. Blast, Clustalw etc.?
4. Would a chemistry structure search be useful?
5. How could we make the UI better to enhance the user experience?
6. Could you we enhance the tool so it would suit specific communities centered on a model organism, a target or a disease?
7. Would the tool be useful to search across private data?
8. Anything else you can think of?

Any inputs would be welcome. You can respond on this blog, or write to me at kalpana@metaome.com

Thanks,
Kalpana Krishnaswami,
CEO and Founder
Metaome Science Informatics

This has been enhanced in the new version to rank “connections” related to the query higher over “properties”. The suggestions are also ranked in terms of the number of connections available for the particular query. For instance, when you query for a drug, the autosuggest now prompts the connections <interacts with> and <targets> as terms 1 and 2. Similarly for a disease, highest numbers of connections are available for <reference> and <related>. This is for “reference publications” and “related drugs” for the disease. This feature should make querying easier for a user to build complex queries by showing the connections/properties available for each type.

Do give us your feedback!

I chose the compound “Letrozole” as an example to illustrate this. Letrozole is an approved drug used as an adjuvant treatment for hormonally-responsive breast cancer. Make sure the type “compound” is selected.  (Watch Demo Video)

Query:  letrozole (compound)                          Run query

The results are as below

The results show the compound’s protein targets, assays, cell lines, tissues and organisms in which the assays were conducted apart from patents and publications. Selecting each facet displays the details in the tab to the right. The chemical structure of the compound can be seen by selecting the structure tab. Further, selecting the “Card view” displays some basic properties of the compound like molecular weight, LogP, LogD, ALogP.

The query can be further extended at the protein level. Let us look at the protein CP19A_human (Aromatase) and all the compounds that target this protein and the assays associated with the compound. Select the protein CP19A_human and extend the query to find all the compounds and assay. This can be further extended to include the organism in which the assay was done. The query now reads as follows

Query: CP19A_Human > compound > assay > human         Run Query

The results are as below:

As seen, there is a huge list of compounds and assays associated with this protein. Selecting a compound displays the assays associated with it. Selecting the assay facet displays the details of the assay, like the assay name, type and also links to the ChEMBL database.

Apart from this, the query for the protein can be extended to view biological processes, protein interactions and approved drugs.

Here, I have looked at the chemistry side of drug discovery and illustrated a simple search for a compound and its properties. We are in the process of adding new data and features and would love to hear from you on what would be interesting to users from a chemistry perspective.  Do give us your feedback on distilbio@metaome.com or leave a comment to this post!

• Ability to filter, refine and analyse results
• “Ease of use of DistilBio”
• Missing results which were known and relevant
• Queries yielding no results

Let’s look at the issues a little closely and the measures taken by the DistilBio team to handle this. (Watch demo video)

Features

Filtering and Analysis

Filtering and analysis of results were areas that needed refinement from the previous version of DistilBio.  Earlier, all the facets were displayed linearly, while queries could be branched. This is led to some confusion about understanding the results. The revamped result interface of DistilBio shows the relationships on the canvas, thus retaining and displaying the connections accurately.

The results can also be selected and filtered to display only instances and their relationships that a user is interested in. For instance, if a query is created for a Aspirin – Protein – Disease. Generally multiple target proteins and associated diseases are shown. Clicking and highlighting the protein facet displays information regarding proteins. Selecting diseases (check boxes) narrows the results showing only proteins connected with the selected diseases.  The details tab to the right displays data of the facet that has been selected in this case: Protein. To view another facet’s detail, click the facet header and the description changes whilst retaining the filters.

Apart from this, if a user finds an instance(s) of interest, the query can now extended by selecting the facet and the instance(s) that the user is interested in and clicking on the “Extend” button (displayed at the top of the page). This creates a new query for that particular instance and more nodes could be added to this query.

Clicking on the name of the instance in the details tab provides a relationship profile of the instance which is very similar to doing a simple search such as Aspirin. The simple search has been further enhanced to encompass all relationships between the facets – direct and inverse relationships. For example, Uniprot links proteins to drugs while DrugBank links drugs to proteins. DistilBio captures both these relations and links them inversely too.

More Complete Results

In a simple search that yields the relationship profile, there is also a “More” link (displayed at the top in each facet) if more results are available.

In a regular search, if more results are available for the query, DistilBio now displays a “Get More results” button at the top in the result page. Clicking on the button allows the user to increase the limit. The user can iteratively  fetch more results ensuring that relevant results for each query are not missed out!

List Query (Multiple Instance Query)

Another interesting feature is the “List Query”. In an earlier post of mine, I had done a comparative study of the drugs aspirin, acetaminophen and ibuprofen. The query I had created gave me the common protein targets between these drugs. With the “List Query”, all 3 drugs can be starting nodes of the query and protein targets of the all three drugs can be found in a single query. This gives us an union of all the protein targets of these drugs. Clicking on the drug facet will display the numbers beside the protein indicating how many drugs target the protein. Proteins with the number 3 will be the common proteins targets between these drugs.

Let us see the query below:

Query: Aspirin, Acetaminophen, Ibuprofen > protein

The result is as below

As can be seen, PGH1_HUMAN and PGH2_HUMAN are common protein targets for these drugs.

I will also use the Rabeprazole example to highlight some of the features we have discussed. While working on my earlier post, I had to run multiple queries to get my results. Some of the new features added to DistilBio have made the searches much easier!

I first ran a query to find the protein targets of the drug Rabeprazole and the drugs that target these proteins.

Query: Rabeprazole > protein > drug

The results are as below

The “Get More Results” button is displayed. By clicking on it, you can increase the limit and all results available are displayed.

In the screenshot below, I have selected 2 proteins – 5HT1D_Human and DRD3_Human for further analysis. The drug list below now displays drugs targeting these 2 proteins. Clicking on the name 5HT1D_HUMAN in the right tab will create a simple search and display all relationships available for the protein.

You can also see the “Extend” button. You can extend your query for the selected proteins by clicking on this. You could also add further nodes to the query as shown below. I have selected the proteins 5HT1D_HUMAN and DRD3_HUMAN to extend my query. When a new query graph is created, I also added the node to find the diseases associated with these proteins.

The above query is an example for “List Query” and this displays all diseases associated with the 2 proteins.

Limit Enhancement

Previously, when a user ran a query, the default limit for the number of results to be displayed was 100. Sometimes, users did not find some of the known relevant results for their queries. Also, in case there were more results available for the query, the user would be unaware of it. Now, in the query interface, the limit for the results has been increased to 500 from 100. So a user gets more relevant results in each query. Some relationship searches, for instance like Protein-Disease, will have a huge number of results. The upper limit has been set to 10000.

Empty Result

One reason for unavailability of results was that if a user created a query for an instance and added other nodes, result would be available only if results were available for all nodes. Eg.: If a query is created for a drug, its target proteins and properties of the drug, previously only if proteins + properties were available then results were displayed. This problem has been handled in the latest release of DistilBio, where an user can add nodes to the instance and get results even if one relationship is available. ie., target proteins will be displayed even if drug properties are not available.

The other issue frequently encountered was that no results were available for some queries. Now, the user has the option of exploring each node of the query to find relationships available for that node.

New Datasets

Gene Ontology

Gene Ontology (GO) terms associated with gene products in terms of biological processes, cellular component and molecular function is now available in DistilBio. I had highlighted the use of this in my earlier post, you could check it to understand how the GO terms could used.

Cell Image Library

DistilBio now also has data from The Cell Image Library. You could run a query to find images and the GO Biological processes and publications associated with it. You could also include organism and the cell type that you are interested in. Alternatively, you could run a query for your protein of interest, the GO biological processes and image associated with it. Else, you could also find publications and images associated with your protein of interest.

We would love to hear your feedback on the new features and enhancements to DistilBio! Email us at: distilbio@metaome.com or leave your feedback on www.distilbio.com. Or you could always leave your comments to this post!

]]> http://blog.metaome.com/distilbio/whats-new-in-distilbio/feed/ 0 http://blog.metaome.com/distilbio/where-does-this-piece-of-data-come-from/ http://blog.metaome.com/distilbio/where-does-this-piece-of-data-come-from/#comments Thu, 12 Apr 2012 12:04:17 +0000 preethi http://blog.metaome.com/?p=575 Continue reading →]]> DistilBio integrates data sets from various sources like Entrez Gene, Uniprot, DrugBank, PharmGKB, CTD, CHEMBL, protein interaction databases like IntAct, MINT etc. Each connection is backed by a data source.

Let us look at an example to see how data sources can be viewed in DistilBio.

I ran a query for breast cancer, the drugs used in the treatment and the proteins targeted by these drugs.

Query: Breast cancer > drug > protein             Run Query

Sources for Relationships/Connections

As seen below, the results are displayed in 3 facets – One for the “Disease” (Breast Cancer), one for the “Drug” and other for the “Proteins” targeted by these drugs. Selecting the “Drug” facet displays the sources (seen in the box to the left, circled in red) of the data for all the relationships/connections for the drug facet i.e., Breast cancer-has drug-Drug and Drug-targets-Protein. In this case, the data sources are DrugBank and PharmGKB. Selecting either of this will display the results only from the particular source.

For instance, I selected the drug “Epirubicin”. Now, selecting the protein facet displays the data sources for the protein targets. Clicking on “drugbank” in the sources box will display the data from DrugBank. Generally, DrugBank provides the primary target of a drug while other databases will give primary as well as off-targets. Depending on the requirement,  the appropriate data source could be selected.

In the details tab to the right, data sources for each piece of data is mentioned, e.g. Synonyms. Apart from that, there is also an external link to the original data source.

Further, there are cross references to the data sources for relationships like PharmGKB, CTD, Chemspider etc. with clickable links to the relevant database as shown below.

At times there are differences in data between DistilBio and the cross referenced data. This is mostly due to difference in the version of data being used. While DistilBio runs periodic updates to make sure new information is updated, typically there is a lag.