"... In PAGE 10: ... For comparison, we looked at the mutant phenotypes and interactions for the two non- essential TRAPP I/II subunits, Trs33 and Trs85/Gsg1. These two subunits show ample genetic and physical interactions with protein trafficking regulators ( Table1 , S4, S5), more than those shown by Trs65. For cell-wall biogenesis, we show here that deletion of TRS33, but not TRS85, results in a cell wall defect similar to that of trs65 (Figure S1).... In PAGE 13: ... In such a case, we expect all intracellular trafficking regulators to have connections with the other two processes similar to those of Trs65. However, our survey of the two other non-essential TRAPP subunits suggests this is not the case ( Table1 ). An alternative possibility is that not all regulators of 13 1... In PAGE 29: ...Table1 : Summary of physical and genetic interactions as well as mutant phenotypes of the three non-essential TRAPP complex subunits A: Physical and genetic interactions TRAPP Number of interactions with proteins that function in the following processes a: Subunit (Type of Interactions b) Membrane Cell-Wall Stress Other Total Trafficking Biogenesis Response Trs65 13 7 6 6 44 (G+P) (G) (G+P) (G+P) Trs33 23 1 0 4 28 (G+P) (G) (G+P) Trs85 40 1 1 31 63 (G+P) (G) (P) (G+P) a Interactions are from BioGrid ((Stark et al., 2006) as of February 25, 2007) are detailed in Supplementary Tables: S2, S4, and S5.... ..."

"... In PAGE 10: ... For comparison, we looked at the mutant phenotypes and interactions for the two non- essential TRAPP I/II subunits, Trs33 and Trs85/Gsg1. These two subunits show ample genetic and physical interactions with protein trafficking regulators ( Table1 , S4, S5), more than those shown by Trs65. For cell-wall biogenesis, we show here that deletion of TRS33, but not TRS85, results in a cell wall defect similar to that of trs65 (Figure S1).... In PAGE 13: ... In such a case, we expect all intracellular trafficking regulators to have connections with the other two processes similar to those of Trs65. However, our survey of the two other non-essential TRAPP subunits suggests this is not the case ( Table1 ). An alternative possibility is that not all regulators of 13 1... In PAGE 15: ... Table1 : Summary of physical and genetic interactions as well as mutant phenotypes of the three non-essential TRAPP complex subunits A: Physical and genetic interactions TRAPP Number of interactions with proteins that function in the following processesa: Subunit (Type of Interactions b) Membrane Cell-Wall Stress Other Total Trafficking Biogenesis Response Trs65 13 7 6 6 44 (G+P) (G) (G+P) (G+P) Trs33 23 1 0 4 28 (G+P) (G) (G+P) Trs85 40 1 1 31 63 (G+P) (G) (P) (G+P) a Interactions are from BioGrid ((Stark et al., 2006) as of February 25, 2007) are detailed in Supplementary Tables: S2, S4, and S5.... ..."

"... In PAGE 12: ...3 Results Output from the interactive system were queries like those shown in table 9. Table10 shows the results of applying these searches predictively and retrospectively. The predictive result should not be compared with the routing results (Ta- ble 7) because the routing queries were derived using a very large amount of relevance information, whereas the interactive queries had the bene t only of those few rel- evant documents found by the searchers.... ..."

"... In PAGE 12: ...3 Results Output from the interactive system were queries in the form 120:294:125:guerilla 120:294:84:thailand 120:294:66:@0152 120:294:63:holidai 120:294:58:@0151 120:294:113:econom consequ op=adj 120:294:112:intern terror op=adj 120:294:110:trade restrict op=adj 120:294:51:travel 120:294:98:trade polici op=adj 120:294:98:econom e#0Bect op=adj 120:294:93:properti damag op=sames 120:294:45:@0278 120:294:41:@0091 120:294:70:econom impact op=adj 120:294:23:busi where the #0Celds are topic:threshold-weight:term-group #5Bop#5D, the terms beginning with `@ apos; usually represent- ing synonym classes, the term groups to be combined using a suitable weighting function. Table9 shows the results of applying these searches predictively and retrospectively. The predictive result should not be compared with the routing results #28Ta- ble 7#29 because the routing queries were derived using a very large amountofrelevance information, whereas the interactive queries had the bene#0Ct only of those few rel- evant documents found by the searchers.... ..."

"... In PAGE 7: ... Research was conducted through three methods: 1) observation of player interaction in the EverQuest world, 2) informational interviews with EverQuest players and 3) reading the leading web site forums devoted to out-of-game interaction between EverQuest players. The data collected through the selected research methods was analyzed by three researchers, with the goal of identifying interaction in the game that fit any of the identified patterns, shown in Table2 . If two or more researchers identified the existence of a pattern in the raw data, it was marked as present in the... ..."

"... In PAGE 25: ...1. Data Description Table8 reports the interaction terms used in the panel regressions. There are six industry characteristics, each measured relative to the manufacturing average.... ..."

"... In PAGE 9: ...8 which are based on the statistical results in Figure 1, and (2) the common transcriptional activators in Table 1. Furthermore, the detected interactive activities among these TFs are presented in Table2 . In this study, we focus on detecting the stress-specific TFs and the common transcriptional activators that are always activative in the gene transcription process even in the absence of any specific stress; these common TFs can also be easily found by the conventional statistical method.... In PAGE 9: ... For example, our proposed method can easily find the common TFs Abf1, Rap1, Cin5, Fhl1 and Reb1 [27-31] in osmotic shock, heat shock, hydrogen peroxide treatment and cell cycle in Table 1. The interactive activities of these TFs under different environmental conditions are ranked in interactive activities matrices in Table2 . In addition, our method also can order the relative roles of the TFs in stress-specific genes of the transcriptional regulatory system.... In PAGE 13: ... The interaction between Fkh2 and Ndd1 has the second strongest regulatory ability according to our results. Furthermore, we also find strong interactivities between Swi4 and Swi6, and between Mbp1 and Swi6 ( Table2 ). According to the conventional results in the yeast cell cycle, complexes of Swi4 and Swi6 (SBF) as well as Mbp1 and Swi6 (MBF), both of which are heterodimers, are active during the G1/S phase [47,51].... In PAGE 27: ...e., 10 m = (see Table2 in the cell cycle case). In this study, for the convenience of table listing, we choose s =15 and m =10 in Equation (11) and Equation (14), respectively.... ..."

"... In PAGE 1: ... Cyclosporine and tacrolimus are metabolized in the liver through the cytochrome P-450 system. There- fore, many drugs administered during anesthesia or perioperatively may affect cyclosporine or tacrolimus blood levels ( Table1 ). All immunosuppressive drugs now in use have significant side effects that may have a direct impact on anesthetic and perioperative manage- ment (8) (Table 2).... ..."