Dan Tulpan

InnateDB: facilitating systems‐level analyses of the mammalian innate immune response

Although considerable progress has been made in dissecting the signaling pathways involved in the innate immune response, it is now apparent that this response can no longer be productively thought of in terms of simple linear pathways. InnateDB (www.innatedb.ca) has been developed to facilitate systems‐level analyses that will provide better insight into the complex networks of pathways and interactions that govern the innate immune response. InnateDB is a publicly available, manually curated, integrative biology database of the human and mouse molecules, experimentally verified interactions and pathways involved in innate immunity, along with centralized annotation on the broader human and mouse interactomes. To date, more than 3500 innate immunity‐relevant interactions have been contextually annotated through the review of 1000 plus publications. Integrated into InnateDB are novel bioinformatics resources, including network visualization software, pathway analysis, orthologous interaction network construction and the ability to overlay user‐supplied gene expression data in an intuitively displayed molecular interaction network and pathway context, which will enable biologists without a computational background to explore their data in a more systems‐oriented manner.

MetaboHunter: an automatic approach for identification of metabolites from 1H-NMR spectra of complex mixtures

BackgroundOne-dimensional 1H-NMR spectroscopy is widely used for high-throughput characterization of metabolites in complex biological mixtures. However, the accurate identification of individual compounds is still a challenging task, particularly in spectral regions with higher peak densities. The need for automatic tools to facilitate and further improve the accuracy of such tasks, while using increasingly larger reference spectral libraries becomes a priority of current metabolomics research.ResultsWe introduce a web server application, called MetaboHunter, which can be used for automatic assignment of 1H-NMR spectra of metabolites. MetaboHunter provides methods for automatic metabolite identification based on spectra or peak lists with three different search methods and with possibility for peak drift in a user defined spectral range. The assignment is performed using as reference libraries manually curated data from two major publicly available databases of NMR metabolite standard measurements (HMDB and MMCD). Tests using a variety of synthetic and experimental spectra of single and multi metabolite mixtures show that MetaboHunter is able to identify, in average, more than 80% of detectable metabolites from spectra of synthetic mixtures and more than 50% from spectra corresponding to experimental mixtures. This work also suggests that better scoring functions improve by more than 30% the performance of MetaboHunters metabolite identification methods.ConclusionsMetaboHunter is a freely accessible, easy to use and user friendly 1H-NMR-based web server application that provides efficient data input and pre-processing, flexible parameter settings, fast and automatic metabolite fingerprinting and results visualization via intuitive plotting and compound peak hit maps. Compared to other published and freely accessible metabolomics tools, MetaboHunter implements three efficient methods to search for metabolites in manually curated data from two reference libraries.Availabilityhttp://www.nrcbioinformatics.ca/metabohunter/

Stochastic Local Search Algorithms for DNA Word Design

We present results on the performance of a stochastic local search algorithm for the design of DNA codes, namely sets of equallength words over the nucleotides alphabet {A,C,G, T} that satisfy certain combinatorial constraints. Using empirical analysis of the algorithm, we gain insight on goodd esign principles. We report several cases in which our algorithm finds word sets that match or exceed the best previously known constructions.

Thermodynamically based DNA strand design

We describe a new algorithm for design of strand sets, for use in DNA computations or universal microarrays. Our algorithm can design sets that satisfy any of several thermodynamic and combinatorial constraints, which aim to maximize desired hybridizations between strands and their complements, while minimizing undesired cross-hybridizations. To heuristically search for good strand sets, our algorithm uses a conflict-driven stochastic local search approach, which is known to be effective in solving comparable search problems. The PairFold program of Andronescu et al. [M. Andronescu, Z. C. Zhang and A. Condon (2005) J. Mol. Biol., 345, 987–1001; M. Andronescu, R. Aguirre-Hernandez, A. Condon, and H. Hoos (2003) Nucleic Acids Res., 31, 3416–3422.] is used to calculate the minimum free energy of hybridization between two mismatched strands. We describe new thermodynamic measures of the quality of strand sets. With respect to these measures of quality, our algorithm consistently finds, within reasonable time, sets that are significantly better than previously published sets in the literature.

Hybrid randomised neighbourhoods improve stochastic local search for DNA code design

Sets of DNA strands that satisfy combinatorial constraints play an important role in various approaches to biomolecular computation, nanostructure design, and molecular tagging. The problem of designing such sets of DNA strands, also known as the DNA code design problem, appears to be computationally hard. In this paper, we show how a recently proposed stochastic local search algorithm for DNA code design can be improved by using hybrid, randomised neighbourhoods. This new type of neighbourhoods tructure equally supports small changes to a given candidate set of strands as well as much larger modifications, which correspondt o random, long range connections in the search space induced by the standard (1-mutation) neighbourhood. We report several cases in which our algorithm finds word sets that match or exceed the best previously known constructions.

Non-intrusive Patient Monitoring of Alzheimer's Disease Subjects Using Wireless Sensor Networks

On aging there is a decrease in the cognitive functions of the brain which can result in behavioral anomalies such as wandering and susceptibility to fall, typical of patients with Alzheimers disease. In order to learn how to manage patients with cognitive impairment it is necessary to non-intrusively monitor brain activity in conjunction with body movements. To facilitate the translation of insights derived through wireless monitoring into robust strategies for crisis prevention and management, we provide a preliminary assessment of a patient monitoring infrastructure, and we discuss related issues and challenges.

HyDEn: a hybrid steganocryptographic approach for data encryption using randomized error-correcting DNA codes.

This paper presents a novel hybrid DNA encryption (HyDEn) approach that uses randomized assignments of unique error-correcting DNA Hamming code words for single characters in the extended ASCII set. HyDEn relies on custom-built quaternary codes and a private key used in the randomized assignment of code words and the cyclic permutations applied on the encoded message. Along with its ability to detect and correct errors, HyDEn equals or outperforms existing cryptographic methods and represents a promising in silico DNA steganographic approach.

1H NMR metabolomics combined with gene expression analysis for the determination of major metabolic differences between subtypes of breast cell lines

1H NMR analysis was performed on metabolic extracts from a selection of six breast cell lines, including normal-immortalized, invasive ductal carcinomas and adenocarcinomas. Metabolites with significant concentration differences between normal and cancerous cells as well as ER+ and ER− (estrogen receptor) cells were determined and their relation to the differentially expressed genes was explored. Major differences have been shown for many amino acids and this was linked to expression level changes of related genes. Observed changes in choline concentration were connected to expression level changes of the SCL44A1 transporter gene.

Experimental evaluation of four feature detection methods for close range and distant airborne targets for Unmanned Aircraft Systems applications

Feature detection for Unmanned Aircraft Systems (UAS) sense and avoid scenarios is a crucial preliminary step for target detection. Its importance culminates when distant (pixel size) targets representing incoming aircraft are considered. This paper presents an experimental evaluation of four popular feature detection methods using flight test data and based on evaluation criteria such as first detection distance and percentage of frames with detected target features. Our results show that for close range targets all four methods have similar performance, while for distant (pixel-size) targets, the Shi and Tomasi method outperforms the other three methods (Harris-Stephens-Plessey, SUSAN and FAST).

Free energy estimation of short DNA duplex hybridizations.

BackgroundEstimation of DNA duplex hybridization free energy is widely used for predicting cross-hybridizations in DNA computing and microarray experiments. A number of software programs based on different methods and parametrizations are available for the theoretical estimation of duplex free energies. However, significant differences in free energy values are sometimes observed among estimations obtained with various methods, thus being difficult to decide what value is the accurate one.ResultsWe present in this study a quantitative comparison of the similarities and differences among four published DNA/DNA duplex free energy calculation methods and an extended Nearest-Neighbour Model for perfect matches based on triplet interactions. The comparison was performed on a benchmark data set with 695 pairs of short oligos that we collected and manually curated from 29 publications. Sequence lengths range from 4 to 30 nucleotides and span a large GC-content percentage range. For perfect matches, we propose an extension of the Nearest-Neighbour Model that matches or exceeds the performance of the existing ones, both in terms of correlations and root mean squared errors. The proposed model was trained on experimental data with temperature, sodium and sequence concentration characteristics that span a wide range of values, thus conferring the model a higher power of generalization when used for free energy estimations of DNA duplexes under non-standard experimental conditions.ConclusionsBased on our preliminary results, we conclude that no statistically significant differences exist among free energy approximations obtained with 4 publicly available and widely used programs, when benchmarked against a collection of 695 pairs of short oligos collected and curated by the authors of this work based on 29 publications. The extended Nearest-Neighbour Model based on triplet interactions presented in this work is capable of performing accurate estimations of free energies for perfect match duplexes under both standard and non-standard experimental conditions and may serve as a baseline for further developments in this area of research.