Bioinformatics Commons^™

Impact Of Noise On Molecular Network Inference, Radhakrishnan Nagarajan, Marco Scutari

Biostatistics Faculty Publications

Molecular entities work in concert as a system and mediate phenotypic outcomes and disease states. There has been recent interest in modelling the associations between molecular entities from their observed expression profiles as networks using a battery of algorithms. These networks have proven to be useful abstractions of the underlying pathways and signalling mechanisms. Noise is ubiquitous in molecular data and can have a pronounced effect on the inferred network. Noise can be an outcome of several factors including: inherent stochastic mechanisms at the molecular level, variation in the abundance of molecules, heterogeneity, sensitivity of the biological assay or measurement …

A Semantic-Based Method For Extracting Concept Definitions From Scientific Publications: Evaluation In The Autism Phenotype Domain, Saeed Hassanpour, Martin J. O’Connor, Amar K. Das

Dartmouth Scholarship

Background: A variety of informatics approaches have been developed that use information retrieval, NLP and text-mining techniques to identify biomedical concepts and relations within scientific publications or their sentences. These approaches have not typically addressed the challenge of extracting more complex knowledge such as biomedical definitions. In our efforts to facilitate knowledge acquisition of rule-based definitions of autism phenotypes, we have developed a novel semantic-based text-mining approach that can automatically identify such definitions within text.

Results: Using an existing knowledge base of 156 autism phenotype definitions and an annotated corpus of 26 source articles containing such definitions, we evaluated and …

Pseudomonas Aeruginosa Ampr Transcriptional Regulatory Network, Deepak Balasubramanian

FIU Electronic Theses and Dissertations

In Enterobacteriaceae, the transcriptional regulator AmpR, a member of the LysR family, regulates the expression of a chromosomal β-lactamase AmpC. The regulatory repertoire of AmpR is broader in Pseudomonas aeruginosa, an opportunistic pathogen responsible for numerous acute and chronic infections including cystic fibrosis. Previous studies showed that in addition to regulating ampC, P. aeruginosa AmpR regulates the sigma factor AlgT/U and production of some quorum sensing (QS)-regulated virulence factors. In order to better understand the ampR regulon, the transcriptional profiles generated using DNA microarrays and RNA-Seq of the prototypic P. aeruginosa PAO1 strain with its isogenic ampR deletion …

Biomedical Informatics For Computer-Aided Decision Support Systems: A Survey, Ashwin Belle, Mark A. Kon, Kayvan Najarian

Computer Science Publications

The volumes of current patient data as well as their complexity make clinical decision making more challenging than ever for physicians and other care givers. This situation calls for the use of biomedical informatics methods to process data and form recommendations and/or predictions to assist such decision makers. The design, implementation, and use of biomedical informatics systems in the form of computer-aided decision support have become essential and widely used over the last two decades. This paper provides a brief review of such systems, their application protocols and methodologies, and the future challenges and directions they suggest.

A Structure-Preserving Hybrid-Chordal Filter For Sampling In Correlation Networksa Structure-Preserving Hybrid-Chordal Filter For Sampling In Correlation Networks, Kathryn Dempsey Cooper, Tzu-Yi Chen, Sriram Srinivasan, Sanjukta Bhowmick, Hesham Ali

Interdisciplinary Informatics Faculty Proceedings & Presentations

Biological networks are fast becoming a popular tool for modeling high-throughput data, especially due to the ability of the network model to readily identify structures with biological function. However, many networks are fraught with noise or coincidental edges, resulting in signal corruption. Previous work has found that the implementation of network filters can reduce network noise and size while revealing significant network structures, even enhancing the ability to identify these structures by exaggerating their inherent qualities. In this study, we implement a hybrid network filter that combines features from a spanning tree and near-chordal subgraph identification to show how a …

Hydraphiles: A Rigorously Studied Class Of Synthetic Channel Compounds With In Vivo Activity, Saeedeh Negin, Bryan Smith, Alexandra Unger, W. Leevy, George Gokel

Chemistry & Biochemistry Faculty Works

No abstract provided.