Semantic Laboratories
Solutions for Drug Discovery Research Intelligence

"SLabsResearch™ - A Drug Discovery Informatics reSearch Tool for Performing Conceptual Searches Across the Research Enterprise", Carlos S. Zamudio, 2006

Semantic Laboratories has developed a novel search platform, SLabsResearch™, which incorporates semantic technologies and search engine indexing of research enterprise data to facilitate the discovery and reuse of research data and knowledge.  Scientific ontologies are integrated with Wizard-style query interfaces to help users construct and perform conceptual queries across research data stored on file servers, relational databases, web portals and Internet resources such as PubMed and the U.S. Patent Office.

"Tailoring Content Management Systems for Drug Discovery Research", Carlos S. Zamudio, 2006

Content Management Systems have been developed to aid the organization with managing documents and other electronic media.  There are a large number of attractive commercial and open-source products exist to choose from. The whitepaper review of the principles of content management systems and discusses the ways to tailor their operations to the drug discovery research environment.

"The Semantic Laboratory^TM: Experiment Semantics, Ontologies and Workflows for Meta-Analysis and Creating Re-usable Drug Discovery Knowledge", Carlos S. Zamudio, 2005

A description and justification for the Semantic Laboratory^TM technologies as a semantic middleware platform to increase the re-use of drug discovery data and for performing meta-analysis across distributed data sets.

"Why IT Matters in Drug Discovery", Carlos S. Zamudio, 2005

A review of the role that Information Technologies plays in the continued evolution of drug discovery research and development. Recent improvements in corporate messaging, internet access, Web portals, database systems and computing platforms are key components in supporting the breadth of research's information requirements.

"Ontologies and Data Semantics in Drug Discovery", Carlos S. Zamudio, 2005

A description of the role that ontologies and other data semantic technologies will have in the challenge of integrating drug discovery research data.  We are already seeing a number of collaborative efforts in the bioinformatics and cheminformatics arenas towards constructing shareable ontologies to annotate biological and chemistry data sets.

"Object Role Modeling for Drug Discovery Data Modeling", Carlos S. Zamudio, 2005

A description of the Object Role Modeling (ORM) design methodology for data modeling and its application for drug discovery database design. ORM is a complementary tool to ER and UML design methodologies, which can be used to capture the description of data objects and their relationships using the vocabulary of scientific domains specified through natural language sentences.  Using ORM, scientists and data modelers can more easily collaborate on the specification of data solutions to be developed.  The ORM tools can then be used to generate both relational and XML database schemas for population using standard import methods.

"Really Simple Syndication (RSS), Atom and Research Process Management", Carlos S. Zamudio, 2005

Really Simple Syndication (also known as Rich Site Summary) and Atom are XML-based communication technology that has emerged as a standard for syndicating web content.  The RSS standard has been adopted by a wide range of information content providers and the RSS development community have created innovative user-based tools for aggregating this syndicated content. Atom is emerging is a potential replacement to RSS, solving problems encountered with the RSS 2.0 Specification.  This paper discusses the role that RSS and Atom may have in a research environment, where it can be used to aggregate syndicate research-related information such as the status of data processes occurring across the organization. 

"Web Services for Scientific Computing", Carlos S. Zamudio, 2005

The technology of Web Services is changing the landscape for delivery of computing services. In the area of scientific computing, it promises to provide a standards-based and flexible architecture for accessing and integrating distributed computing resources such as bioinformatics and cheminformatics algorithms.  Both scientific software vendors and custom application developers have embraced Web Services as a way to make their tools more easily accessed and integrated into drug discovery analysis.

"Scientific Workflows for Drug Discovery Data Analysis", Carlos S. Zamudio, 2005

Developing robust analysis pipelines for performing analysis of drug discovery research data is typically provided by informatics scientists developing software using scripting languages such as Perl, Python and vendor-supplied proprietary languages.  A new framework for analysis pipeline development has emerged, called Scientific Workflows, using visual programming methods and standards-based access to distributed computing resources to allow research scientists to more easily develop and share customized analysis drug discovery data.