Discovery of protein-protein interactions using a combination of linguistic, statistical and graphical information

BACKGROUND: The rapid publication of important research in the biomedical literature makes it increasingly difficult for researchers to keep current with significant work in their area of interest. RESULTS: This paper reports a scalable method for the discovery of protein-protein interactions in Medline abstracts, using a combination of text analytics, statistical and graphical analysis, and a set of easily implemented rules. Applying these techniques to 12,300 abstracts, a precision of 0.61 and a recall of 0.97 were obtained, (f = 0.74) and when allowing for two-hop and three-hop relations discovered by graphical analysis, the precision was 0.74 (f = 0.83). CONCLUSION: This combination of linguistic and statistical approaches appears to provide the highest precision and recall thus far reported in detecting protein-protein relations using text analytic approaches

Research Enterprise Office Search Portal

All the employees in University Technology Petronas need to access information instantaneously in order to enhance their functionality and efficacy. Is it easy to collaborate and gather the right information at the right time? Is all the research within a company documented? Is it easily available to all employees? And what happens when an employee leaves the company? This project is an analysis of current practices and outcomes of the search portal and the nature of it as they are evolving in most of the organizations. The findings suggest that interest in search engines across a variety of industries is very high, the technological foundations are varied, and the major concerns revolve around achieving the correct amount and type of accurate research and garnering support for contributing to the search portal. Implications for practice and suggestions for future research are drawn from the study findings. This project focused on the search function. The research is on how to make this search portal useful to the University Technology Petronas (UTP) community that is the UTP staff and lecturers. These search portal solutions are ideal for operations and maintenance manuals that once were reserved for 3-inch thick binders sitting on the shelves of many treatment plants. Moving the manual standard procedures, troubleshooting, theory, alarms, and equipment descriptions to an electronic, web-based solution offers many benefits. For one, the information can be updated and kept current much more effectively because it can be changed in one place and instantly updated at all access points. By developing this search portal, the staff and lecturers will be able to get information fast and efficiently

A Survey on Important Aspects of Information Retrieval

Information retrieval has become an important field of study and research under computer science due to the explosive growth of information available in the form of full text, hypertext, administrative text, directory, numeric or bibliographic text. The research work is going on various aspects of information retrieval systems so as to improve its efficiency and reliability. This paper presents a comprehensive survey discussing not only the emergence and evolution of information retrieval but also include different information retrieval models and some important aspects such as document representation, similarity measure and query expansion

Abstract OBIWAN- A Visual Interface for Prompted Query Refinement

Typically, users submit very simple search queries to digital document data collections. Often these queries can result in extremely broad answers or answers in which document relevance is hard to assess. Our group has developed a suite of tools which build sophisticated indexes to document collections. These tools can be used to provide cues to help users formulate more effective queries. In order to present these cues and manage the process of query refinement, we have developed a Javabased client server system which uses these indexes and tools. One of the most powerful parts of our system is its ability to recognize domain-specific multi-word names and terms, using heuristic methods, and to index these vocabulary items in such a way that we can look up vocabulary items that commonly are related to the original query terms. This system responds to an initial query by suggesting additional items that the user can use to focus the query. 1