NETWORK TOPOLOGY IN HUMAN PROTEIN INTERACTION DATA PREDICTS FUNCTIONAL ASSOCIATION

High-throughput assays, such as yeast two-hybrid system, have generated a huge amount of protein-protein interaction (PPI) data in the past decade. This tremendously increases the need for developing reliable methods to systematically and automatically suggest protein functions and relationships between them. With the available PPI data, it is now possible to study the functions and relationships in the context of a large-scale network. To data, several network-based schemes have been provided to effectively annotate protein functions on a large scale. However, due to those inherent noises in high-throughput data generation, new methods and algorithms should be developed to increase the reliability of functional annotations. Previous work in a yeast PPI network (Samanta and Liang, 2003) has shown that the local connection topology, particularly for two proteins sharing an unusually large number of neighbors, can predict functional associations between proteins, and hence suggest their functions. One advantage of the work is that their algorithm is not sensitive to noises (false positives) in high-throughput PPI data. In this study, we improved their prediction scheme by developing a new algorithm and new methods which we applied on a human PPI network to make a genome-wide functional inference. We used the new algorithm to measure and reduce the influence of hub proteins on detecting functionally associated proteins. We used the annotations of the Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) as independent and unbiased benchmarks to evaluate our algorithms and methods within the human PPI network. We showed that, compared with the previous work from Samanta and Liang, our algorithm and methods developed in this study improved the overall quality of functional inferences for human proteins. By applying the algorithms to the human PPI network, we obtained 4,233 significant functional associations among 1,754 proteins. Further comparisons of their KEGG and GO annotations allowed us to assign 466 KEGG pathway annotations to 274 proteins and 123 GO annotations to 114 proteins with estimated false discovery rates of <21% for KEGG and <30% for GO. We clustered 1,729 proteins by their functional associations and made pathway analysis to identify several subclusters that are highly enriched in certain signaling pathways. Particularly, we performed a detailed analysis on a subcluster enriched in the transforming growth factor β signaling pathway (P<10-50) which is important in cell proliferation and tumorigenesis. Analysis of another four subclusters also suggested potential new players in six signaling pathways worthy of further experimental investigations. Our study gives clear insight into the common neighbor-based prediction scheme and provides a reliable method for large-scale functional annotations in this post-genomic era.

A dual resonance, image -guided, volume localization technique for magnetic resonance spectroscopy

An interleaved, dual resonance, volume localization technique for $\sp1$H/$\sp{31}$P magnetic resonance spectroscopy has been designed, implemented on a 2 T imager/spectrometer, and verified with phantom studies.^ Localization techniques, including several single voxel techniques and spectroscopic imaging, were implemented, and studies were performed to compare the efficiency of each sequence of $\sp1$H/$\sp{31}$P spectral acquisitions. The sequence chosen was a hybrid of the stimulated echo single voxel technique and the spectroscopic imaging technique.^ Water suppression during the $\sp1$H spectral acquisitions was accomplished by the use of three narrow bandwidth RF saturation pulses in combination with three spoiler gradients. The spoiler gradient amplitudes were selected on the basis of a numerical solution of the Bloch equations. A post-acquisition water suppression algorithm was used to minimize any residual water signal.^ For interleaved $\sp1$H/$\sp{31}$P acquisitions, a dual resonance RF coil was constructed and interfaced to the existing RF detection system via a custom-designed dual resonance transcoupler and switching system. Programmable attenuators were incorporated to allow for changes in receiver and transmitter attenuation "on the fly".^ To provide the rapidly switched gradient fields required for the $\sp1$H/$\sp{31}$P acquisitions, an actively screened gradient coil system was designed and implemented. With this system, gradient field rise times on the order of 100 $\mu$s were obtained. These rapid switching times were necessary for minimizing intrasequence delays and for improving localization quality and water suppression efficiency.^ The interleaved $\sp1$H/$\sp{31}$P volume localization technique was tested using a two-compartment phantom. Analysis of the data showed that the spectral contamination was less than three percent. One-to-one spatial correspondence of the $\sp1$H and $\sp{31}$P spectra was verified and allowed for direct correlation of the spectral data with a standard magnetic resonance image. ^