Computing and Information Systems - Research Publications
Permanent URI for this collection
Search Results
1 - 10 of 78
-
ItemPhenDisco: phenotype discovery system for the database of genotypes and phenotypes.(Oxford University Press (OUP), 2014)The database of genotypes and phenotypes (dbGaP) developed by the National Center for Biotechnology Information (NCBI) is a resource that contains information on various genome-wide association studies (GWAS) and is currently available via NCBI's dbGaP Entrez interface. The database is an important resource, providing GWAS data that can be used for new exploratory research or cross-study validation by authorized users. However, finding studies relevant to a particular phenotype of interest is challenging, as phenotype information is presented in a non-standardized way. To address this issue, we developed PhenDisco (phenotype discoverer), a new information retrieval system for dbGaP. PhenDisco consists of two main components: (1) text processing tools that standardize phenotype variables and study metadata, and (2) information retrieval tools that support queries from users and return ranked results. In a preliminary comparison involving 18 search scenarios, PhenDisco showed promising performance for both unranked and ranked search comparisons with dbGaP's search engine Entrez. The system can be accessed at http://pfindr.net.
-
Item
-
Item
-
ItemCryptographic protocols with everyday objects(SPRINGER, 2014-01-01)Abstract Most security protocols appearing in the literature make use of cryptographic primitives that assume that the participants have access to some sort of computational device. However, there are times when there is need for a security mechanism to evaluate some result without leaking sensitive information, but computational devices are unavailable. We discuss here various protocols for solving cryptographic problems using everyday objects: coins, dice, cards, and envelopes.
-
ItemEvaluating influence of microRNA in reconstructing gene regulatory networks(SPRINGER, 2014-06-01)Gene regulatory network (GRN) consists of interactions between transcription factors (TFs) and target genes (TGs). Recently, it has been observed that micro RNAs (miRNAs) play a significant part in genetic interactions. However, current microarray technologies do not capture miRNA expression levels. To overcome this, we propose a new technique to reverse engineer GRN from the available partial microarray data which contains expression levels of TFs and TGs only. Using S-System model, the approach is adapted to cope with the unavailability of information about the expression levels of miRNAs. The versatile Differential Evolutionary algorithm is used for optimization and parameter estimation. Experimental studies on four in silico networks, and a real network of Saccharomyces cerevisiae called IRMA network, show significant improvement compared to traditional S-System approach.
-
ItemExplaining circuit propagation(SPRINGER, 2014-01-01)
-
ItemGeneralised blockmodelling of social and relational networks using evolutionary computing(SPRINGER WIEN, 2014-12-01)
-
ItemGenerating multiple alternative clusterings via globally optimal subspaces(SPRINGER, 2014-05-01)
-
ItemInformation security strategies: towards an organizational multi-strategy perspective(SPRINGER, 2014-04-01)
-
ItemLooking into the crystal-ball: a bright future for CP(SPRINGER, 2014-04-01)