Summary: Chemical-genomic approaches that map interactions between small molecules and genetic perturbations offer a promising strategy for functional annotation of uncharacterized bioactive compounds. We recently developed a new high-throughput platform for mapping chemical-genetic (CG) interactions in yeast that can be scaled to screen large compound collections, and we applied this system to generate CG interaction profiles for more than 13 000 compounds. When integrated with the existing global yeast genetic interaction network, CG interaction profiles can enable mode-of-action prediction for previously uncharacterized compounds as well as discover unexpected secondary effects for known drugs. To facilitate future analysis of these valuable data, we developed a public database and web interface named MOSAIC. The website provides a convenient interface for querying compounds, bioprocesses (Gene Ontology terms) and genes for CG information including direct CG interactions, bioprocesses and gene-level target predictions. MOSAIC also provides access to chemical structure information of screened molecules, chemical-genomic profiles and the ability to search for compounds sharing structural and functional similarity. This resource will be of interest to chemical biologists for discovering new small molecule probes with specific modes-of-action as well as computational biologists interested in analysing CG interaction networks. Availability and implementation: MOSAIC is available at http://mosaic.cs.umn.edu. Contact: [email protected], [email protected], [email protected] or [email protected]. Supplementary information: Supplementary data are available at Bioinformatics online.

Chemical-genetic interactions-observed when the treatment of mutant cells with chemical compounds reveals unexpected phenotypes-contain rich functional information linking compounds to their cellular modes of action. To systematically identify these interactions, an array of mutants is challenged with a compound and monitored for fitness defects, generating a chemical-genetic interaction profile that provides a quantitative, unbiased description of the cellular function(s) perturbed by the compound. Genetic interactions, obtained from genome-wide double-mutant screens, provide a key for interpreting the functional information contained in chemical-genetic interaction profiles. Despite the utility of this approach, integrative analyses of genetic and chemical-genetic interaction networks have not been systematically evaluated. We developed a method, called CG-TARGET (Chemical Genetic Translation via A Reference Genetic nETwork), that integrates large-scale chemical-genetic interaction screening data with a genetic interaction network to predict the biological processes perturbed by compounds. In a recent publication, we applied CG-TARGET to a screen of nearly 14,000 chemical compounds in Saccharomyces cerevisiae, integrating this dataset with the global S. cerevisiae genetic interaction network to prioritize over 1500 compounds with high-confidence biological process predictions for further study. We present here a formal description and rigorous benchmarking of the CG-TARGET method, showing that, compared to alternative enrichment-based approaches, it achieves similar or better accuracy while substantially improving the ability to control the false discovery rate of biological process predictions. Additional investigation of the compatibility of chemical-genetic and genetic interaction profiles revealed that one-third of observed chemical-genetic interactions contributed to the highest-confidence biological process predictions and that negative chemical-genetic interactions overwhelmingly formed the basis of these predictions. We also present experimental validations of CG-TARGET-predicted tubulin polymerization and cell cycle progression inhibitors. Our approach successfully demonstrates the use of genetic interaction networks in the high-throughput functional annotation of compounds to biological processes.

A diversity scheme with Fractional Sampling (FS) in OFDM receivers has been investigated recently. FS path diversity makes use of imaging components of a desired signal transmitted on an adjacent channel. In the previous literature, a non-orthogonal access scheme over multiple channels with iterative interference cancellation (IIC) and FS was proposed. The conventional scheme has shown that the imaging component is transmitted non-orthogonally and path diversity is realized with FS and IIC. However, the conventional scheme does not take into account a spatial multiplexing transmission scheme such as multiple-input multiple-output (MIMO). Therefore, this paper proposes a MIMO-FS scheme with IIC and evaluates its performance through computer simulation. It is shown that in the MIMO situation with channel coding the proposed system improves the performance by 1.5dB at the BER of 10-5compared to a system without imaging components.

A diversity scheme with Fractional Sampling (FS) in OFDM receivers has been investigated recently. FS path diversity makes use of the imaging components of the desired signal transmitted on the adjacent channel. In this paper nonorthogonal access over multiple channels with iterative interference cancellation (IIC) and FS is proposed. The proposed scheme transmits the imaging component non- orthogonally on the adjacent channel. In order to accommodate the imaging component, it is underlaid on the other desired signal. Through diversity with FS and IIC, non-orthogonal access on multiple channels is realized. Our propose scheme can accommodate nonorthogonal signals with limited diversity gains.

A diversity scheme with Fractional Sampling (FS) in OFDM receivers has been investigated recently. In the previous literature it has been shown that performance improvement with path diversity through FS depends on the bandwidth of the total channel response including transmit and receive baseband filters. However, if the signal on the adjacent channel exists, that signal causes interference to the desired signal with FS. In this paper, an adjacent channel interference cancellation scheme has been proposed for the FS OFDM receiver. The proposed scheme demodulates the signal on the adjacent channel and regenerates it to be subtracted from the received signal. Numerical results through computer simulation show that the proposed scheme achieves BER improvement under low signal-to-interference-ratio (SIR) conditions.

We identified 5 975 567 mono- and 6 995 122 di-nucleosome positions of the fungus Aspergillus fumigatus, which was detected at high resolution based on the DNA sequence data obtained from both mono- and di-nucleosomal DNA fragments. We show that the distribution of lengths of the mono-nucleosomal DNA fragments has two peaks at 135 and 150 nt, whereas the distribution of di-nucleosomal DNA fragment lengths has a single peak at 285 nt. Although the gene bodies of the active and inactive genes and the inactive gene promoters had the two peaks of the mono-nucleosomal DNA fragment lengths, the active gene promoter lost the longer peak at 150 nt. Our findings strongly suggest that the nucleosomes protecting longer DNA fragments against MNase at the promoters, thereby inhibiting high gene expression.