Posts Tagged ‘life sciences’

Interest Grows In Riding The Semantic Wave

Image Courtesy: Flickr/ Peter Kaminski

Image Courtesy: Flickr/ Peter Kaminski

Industry leaders in sectors including banking and financial services look to have high hopes for semantic technology. They’re thinking about FIBO (Financial Industry Business Ontology) and leveraging semantic technology for more traditional types of data integration and analytics projects. At Cognizant, Thomas Kelly, a director in its Enterprise Information Management practice – and the author of this white paper on How Semantic Technology Drives Agile Business – sees the positive development that clients in the Fortune 500 space like these “are maturing in their use of semantic technology, from a project focus to more enterprise initiatives.”

The interest in FIBO, he says, is representative of an overall interest across in industries in leveraging industry ontologies as mechanisms to help companies better standardize, align and learn from the output of industry-wide efforts. The attention that industry analysts, including Gartner, have put on the semantic web in the last year – not to mention regulators beginning to consider its use in sharing information on a regulatory basis – have helped increase interest by commercial organizations, Kelly notes. That’s also evident in the life sciences sector, as another example, with the efforts of the FDA/PhUSE  Semantic Technology Working Group Project to include a draft set of existing CDISC standards in RDF.

The pickup in attention to many things semantic ties to the different perspectives that organizations need to manage about their data, which include “how they currently think of their data, how it is currently perceived in managing business operations; and where they are looking to go in the future that makes it more inclusive of what’s going on in the world outside their walls – that is, how the rest of the industry looks at this data and uses it to support their business processes,” he says.

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In Search Of Apps To Leverage Public BioMolecular Data In RDF Platform

rsz_rdfpfThe European Molecular Biology Laboratory (EMBL) and the European Bioinformatics Institute (EBI) that is part of Europe’s leading life sciences laboratory this fall launched a new RDF platform hosting data from six of the public database archives it maintains. That includes peer-reviewed and published data, submitted through large-scale experiments, from databases covering genes and gene expression, proteins (with SIB), pathways, samples, biomodels and molecules with drug-like properties. And next week, during a competition at SWAT4LS in Edinburgh, it’s hoping to draw developers with innovative use case ideas for life-sciences apps that can leverage that data to the benefit of bioinformaticians or bench biologists.

“We need developers to build apps on top of the platform, to build apps to pull in data from these and other sources,” explains Andy Jenkinson, Technical Project Manager at EMBL-EBI. “There is the potential using semantic technology to build those apps more rapidly,” he says, as it streamlines integrating biological data, which is a huge challenge given the data’s complexity and variety. And such apps will be a great help for lab scientists who don’t know anything about working directly with RDF data and SPARQL queries.

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YarcData Software Update Points Out That The Sphere Of Semantic Influence Is Growing

YarcDataRecent updates to YarcData’s software for its Urika analytics appliance reflect the fact that the enterprise is starting to understand the impact that semantic technology has on turning Big Data into actual insights.

The latest update includes integration with more enterprise data discovery tools, including the visualization and business intelligence tools Centrifuge Visual Network Analytics and TIBCO Spotfire, as well as those based on SPARQL and RDF, JDBC, JSON, and Apache Jena. The goal is to streamline the process of getting data in and then being able to provide connectivity to the tools analysts use every day.

As customers see the value of using the appliance to gain business insight, they want to be able to more tightly integrate this technology into wider enterprise workflows and infrastructures, says Ramesh Menon, YarcData vice president, solutions. “Not only do you want data from all different enterprise sources to flow into the appliance easily, but the value of results is enhanced tremendously if the insights and the ability to use those insights are more broadly distributed inside the enterprise,” he says. “Instead of having one analyst write queries on the appliance, 200 analysts can use the appliance without necessarily knowing a lot about the underlying, or semantic, technology. They are able to use the front end or discovery tools they use on daily basis, not have to leave that interface, and still get the benefit of the Ureka appliance.”

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Clinical Studies And The Road To Linked Data

Clinical studies aren’t what they used to be. In the past, the process was one-off: You conducted a study, gathered a lot of data, analyzed it, wrote a report, and submitted it to the authorities. But, says long-time Linked Data advocate Kerstin Forsberg, an information architect at AstraZeneca, that’s all changed in the last few years.

“A study is not a study on its own,” says Forsberg. Today, the goal is  to do meta-analysis across many studies, so parties ranging from  pharmaceuticals companies to contract research organizations to government authorities all are ‘customers’ of clinical data, so to speak. Data from various studies must be shared among all these parties. “It puts a new context around clinical trial data, that it must be easy to link data together, to link across several different studies,” she says.

The case is there to use modern information standards, like semantic web standards and Linked Data principles, to address this need. It’s why Forsberg is one of the individuals spearheading a volunteer effort to create RDF and OWL representations of the standards published by the Clinical Data Interchange Standards Consortium (CDISC) an international, non-profit organization that develops and supports global data standards for medical research.

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Connect Those Big Data Dots

It shouldn’t be surprising that Entagen, which makes the semantically-enabled Big Data analytics and collaboration engine TripleMap, has had its sights set on the life sciences space. CEO Christopher Bouton has his Ph.D in molecular neurobiology and has worked at a number of bio tech firms, as well as been the head of integrative data mining at Pfizer – a company that’s using TripleMap for visualized knowledge maps of associations between domain-specific entities (see our story here).

“We see some really compelling and exciting applications of this type of technology in the life sciences space,” says Bouton. But TripleMap can be applied to any scenario where Big Data dots must be connected so that users can collaborate around the understanding of the associations between entities – health care, legal, retail and finance all come to mind.

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Big Data Startup Ayasdi Launches; Machine Learning Platform Combines Computer Science And Topological Data Analysis

This week a new Big Data startup company launched, Ayasdi, co-founded by Stanford mathematics professor Gunner Carlsson and based on his DARPA-funded research in the area of applied topology, with $10+million in Series A funding led by Khosla Ventures and Floodgate.
The technology, dubbed the Insight Discovery platform, is explained to be the “first machine learning platform that combines computer science and a branch of mathematics known as Topological Data Analysis (TDA) that visualizes the entire dataset.” Hundreds of machine learning algorithms, it says, go to work exploring datasets to in minutes automatically discover insights that can’t be determined through query-based or ad hoc approaches.

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Semantic Tech: It’s Moving Mainstream, Playing To The Data-Is-An-Asset Crowd, And Living Life Out Loud

At the recent SemTech conference in NYC, The Semantic Web Blog had an opportunity to ask some leaders in the field about where semantic technology has been, and where it’s going.

David Wood, CTO, 3RoundStones:

The short take: Hiring has been on in a big way at semantic tech players as enterprises are moving in greater numbers to buy semantic software, recognizing their traditional vendors won’t solve their interoperability issues. Sem tech vendors should have a happy 2013 as semantics continues going mainstream.

The full take:

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Metaome Helps Bench Biologists Get More Value From Linked Data

How to help the bench biologist get value out of the wealth of life sciences Linked Data sets? Startup Metaome Science Informatics proposes to offer some help with its DistilBio semantic search and data integration technology, by streamlining the approach to posing user queries. The Distil in DistilBio stands for Data Integration using Semantic Technologies in the Life Sciences.

Metaome, which was founded by CEO Kalpana Krishnaswami and CTO Ramkumar Nandakumar as a bioinformatics services provider before transitioning to a product vendor, contains a few more than a dozen life sciences public data sets so far. Infomaticians in the life sciences space have the expertise to query such data across sets via SPARQL, but the front-line biologist isn’t necessarily an infomatician. So, DistilBio has created a query interface that makes it easier for them to ask large and complex questions in a simplified way across data sets while building a graph in the process.

“How does a user say what are the drugs used for Alzheimer’s disease and do have they have certain protein targets and are those protein targets implicated in other diseases?” says Krishnaswami. “To ask that in one shot right now is hard without working through a SPARQL endpoint using all the SPARQL syntax.”

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SWJ Call for Papers on Health Care Linked Data

The Semantic Web Journal has issued a call for papers on the topic of linked data for health care and the life sciences. According to the post, “Due to their descriptive nature and ongoing need to integrate large amounts of heterogeneous data, the areas of health care and the life sciences have long been used as a test-bed for the feasibility of Semantic Web technologies. Large scale integration projects like Bio2RDF, Chem2Bio2RDF, and the W3C HCLS’s (Health Care and Life Sciences) Linked Open Drug Data (LODD) have not only significantly contributed to the development of the Semantic Web’s Linked Data effort, but have also made social and technical contributions towards data integration, knowledge management, and knowledge discovery.” Read more

New Paper on Semantics and Drug Discovery Research

A new paper has been published entitled “Systems Chemical Biology and the Semantic Web: What They Mean for the Future of Drug Discovery Research.” The paper was written by David Wild, Ying Ding, Amit Sheth, Lee Harland, Eric Gifford, and Michael Lajiness. It can be downloaded for a fee of $27.95. According to the abstract, “Systems chemical biology, the integration of chemistry, biology and computation to generate understanding about the way small molecules affect biological systems as a whole, as well as related fields such as chemogenomics, are central to emerging new paradigms of drug discovery such as drug repurposing and personalized medicine.” Read more

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