### Table 4. Experiment 2, Comparison

"... In PAGE 11: ... The slope estimates were compared with a slope of 1, indicating perfect correspondence between the data and model. Table4 contains the slope estimates and the corresponding p values (df ; 192, varying ac- cording to the exact number of data recorded per subject, data that Bonferroni corrected for number of subjects; sig- nificant deviations from the model predictions with p , 0.05 marked by an asterisk; please contact authors for details).... ..."

### Table 6 Computation of Predicted Values for Selected Values of X

### Table 3 gives the predicted and computed x for the benchmarks.

1992

Cited by 2

### Table 1: Transcription factors commonly referred to in computational CRM prediction studies.

"... In PAGE 2: ... Despite the success of the computational method, a limitation has been the breadth of coverage. To the best knowledge of the authors, all the existing computational prediction studies have concentrated upon gap and pair-rule genes in which the CRMs are composed of a handful of maternal and gap factors listed in Table1 . Although the computational prediction techniques are general in nature, i.... ..."

### Table 1: Transcription factors commonly referred to in computational CRM prediction studies.

"... In PAGE 2: ... Despite the success of the computational method, a limitation has been the breadth of coverage. To the best knowledge of the authors, all the existing computational prediction studies have concentrated upon gap and pair-rule genes in which the CRMs are composed of a handful of mater- nal and gap factors listed in Table1 . Although the computational prediction techniques are general in nature, i.... ..."

### Table 1. Computing weights for prediction, #230Cltering and smoothing

2003

"... In PAGE 2: ... Further, we have s t = Z t a t , s tjt = Z t a tjt and ^ #2312 t = Z t ^ #230B t . For prediction and #230Cltering we apply the KF upto time t and apply the backwards recursion w j #2328#2301#2329=B t;j K j ; B t;j,1 = B t;j T j , w j #2328#2301#2329Z j ; j = t , 1;t, 2;:::;1; #23284#2329 with the initialisation B t;t,1 reported in Table1 . For smoothing we apply the KF upto time T and the SF upto time t.... ..."

Cited by 6

### Table 2: Computational methods for the prediction of protein-protein interactions

"... In PAGE 8: ... These approaches can be classified into five general categories: methods based on genomic information, evolutionary relationships, three dimensional protein structure, protein domains, and primary protein structure. Specific approaches that fall within these categories are listed in Table2 and are discussed below. Figure 1 presents the idea behind the five categories of methods.... ..."

### Table 4. Fields in cPSORTdb, the database of proteins of computationally predicted SCL

2005

Cited by 1

### Table 4. Free energy of computer-predicted RNA secondary structure of the 3 quot; terminal region*

1988

### Table 2: Predictions Computed from Decision Field Theory

2003

"... In PAGE 24: ... We assumed an equal probability of attending to each of the three dimensions, and the remaining parameters were the same as used to generate Figure 5. The asymptotic choice probability results, predicted the theory, are summarized in Table2 , below. ... ..."