Effects of the silicon core structures on the hole mobility of star-shaped oligothiophenes.

Star-shaped compounds with three or four oligothiophene units linked by an organosilicon core were prepared and their hole-transport capabilities were studied. A top-contact type thin film transistor (TFT) with a vapour-deposited film of tris[(ethylterthiophenyl)dimethylsilyl]methylsilane (3T(3)Si(4)) showed field-effect mobility (µ(FET)) of 4.4 × 10(-5) cm(2) V(-1) s(-1), while the device with the carbon centred analogue tris[(ethylterthiophenyl)dimethylsilyl]methane (3T(3)Si(3)C) showed no TFT activity. Intrinsic intramolecular hole mobility of 3T(3)Si(4) and 3T(3)Si(3)C was determined by time-resolved microwave conductivity measurements to be 8 × 10(-2) and 2 × 10(-2) cm(2) V(-1) s(-1), respectively, arising from higher degree of σ-π interaction in 3T(3)Si(4). To know more about the effects of the organosilicon core structures on the intermolecular hole mobility, we calculated internal reorganization energies for hole transfer at the (U)B3LYP/6-311+G(d,p)//(U)B3LYP/6-31G(d) level, which suggested smoother intermolecular charge transfer in the silicon derivative than the carbon and germanium analogues. Star-shaped compounds with quarterthiophene units behave in a different manner from the terthiophene derivatives and tris[(ethylquarterthiophenyl)dimethylsilyl]methane (4T(3)Si(3)C) showed higher TFT mobility of µ(FET) = 1.2 × 10(-3) cm(2) V(-1) s(-1) than its silicon analogue (4T(3)Si(4): µ(FET) = 5.4 × 10(-4) cm(2) V(-1) s(-1)). This is probably due to the more condensed packing of 4T(3)Si(3)C in the film, arising from the shorter Si-C bonding. Compounds with four terthiophene units were also prepared and tetrakis[(ethylterthiophenyl)-dimethylsilyl]silane (3T(4)Si(5)) showed the mobility of µ(FET) = 2.0 × 10(-4) cm(2) V(-1) s(-1), higher than that of 3T(3)Si(4), indicating the potential of tetrakis(oligothiophenyl) compounds as the TFT materials. Tetrakis[(ethylterthiophenyl)dimethylsilyl]germane (3T(4)Si(4)Ge) was less thermally stable and could not be processed to a film by vapour-deposition, but was found to be TFT active in the spin-coated film, although the mobility was rather low (µ(FET) = 7.7 × 10(-7) cm(2) V(-1) s(-1)).

A novel strategy to search conserved transcription factor binding sites among coexpressing genes in human.

We report various transcription factor binding sites (TFBSs) conserved among co-expressed genes in human promoter region using expression and genomic data. Assuming similar promoter structure induces similar transcriptional regulation, hence induces similar expression profile, we compared the promoter structure similarities between co-expressed genes. Comprehensive TF binding site predictions for all human genes were conducted for 19,777 promoter regions around the transcription start site (TSS) given from DBTSS and promoter similarity search were conducted among coexpressing genes data provided from newly developed COXPRESdb. Combination of Position Weight Matrix (PWM) motif prediction and bootstrap method, 7,313 genes have at least one statistically significant conserved TFBS. We also applied basket method analysis for seeking combinatorial activities of those conserved TFBSs.

Predicting differences in gene regulatory systems by state space models.

We propose a statistical strategy to predict differentially regulated genes of case and control samples from time-course gene expression data by leveraging unpredictability of the expression patterns from the underlying regulatory system inferred by a state space model. The proposed method can screen out genes that show different patterns but generated by the same regulations in both samples, since these patterns can be predicted by the same model. Our strategy consists of three steps. Firstly, a gene regulatory system is inferred from the control data by a state space model. Then the obtained model for the underlying regulatory system of the control sample is used to predict the case data. Finally, by assessing the significance of the difference between case and predicted-case time-course data of each gene, we are able to detect the unpredictable genes that are the candidate as the key differences between the regulatory systems of case and control cells. We illustrate the whole process of the strategy by an actual example, where human small airway epithelial cell gene regulatory systems were generated from novel time courses of gene expressions following treatment with(case)/without(control) the drug gefitinib, an inhibitor for the epidermal growth factor receptor tyrosine kinase. Finally, in gefitinib response data we succeeded in finding unpredictable genes that are candidates of the specific targets of gefitinib. We also discussed differences in regulatory systems for the unpredictable genes. The proposed method would be a promising tool for identifying biomarkers and drug target genes.