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Table 1 Data-collection statistics and Matthews coefficients for (30D-34Q) and A31P.
"... In PAGE 3: ... Application of a crystal- lization procedure based on ionic strength reducers resulted in crystals suitable for X- ray analysis unlike conventional methods. Statistics from the data collection are presented in Table1 . (30D-34Q) crystal- lizes in the monoclinic space group C2, with Figure 2 Crystallization of (30D-34Q).... ..."
Table 1 Material constants for a-titanium (Matthew, 2000) and Al2024-T3
"... In PAGE 21: ...11) We apply the preceding model to two materials: rate-dependent a-titanium and rate- independent Al2024-T3. The material parameters used in the calculations are collected in Table1 .... ..."
Table 1. Oligonucleotide primer sequences
2006
"... In PAGE 3: ... 18S ribosomal RNA (18S rRNA, GenBank accession AY779625) was used as the reference gene following demonstration that its expression was constant in all samples. Primer pairs are listed in Table1 . Database searches, alignments, and se- Fig.... ..."
Table 2: Comparison of uniform and adaptive clustering. Due to the input size limitations of the error tool, error information is un- available for St. Matthew and Lucy models.
"... In PAGE 6: ... The average of all these distances is then taken to be the average error. Table2 summarizes the results of our experiments, which were run on a standard Linux PC with an 800 MHz P3 processor, 256 MB of memory, and a SCSI disk. In general, the adaptive algorithm produced better quality ap- proximations.... ..."
Table 2: Average triangle and point numbers of the octree cells in different LOD levels for the appearance preserving St. Matthew model compared to the triangle count of the purely geometrically simplified version.
"... In PAGE 5: ... This way the number of points used per HLOD is opti- mally adapted to the features of the simplified object. As shown in Table2 it might even happen that it decreases with the coarser level, which of course would not be possible by simple clustering. The main advantage of our technique is that due to the maximum size of a node on screen we can calculate the max- imum number of pixels a triangle can cover.... In PAGE 7: ...1. HLOD Generation Table2 shows the average number of triangles and points in an octree cell for each level of the HLOD hierarchy. While the number of triangles per octree node of the purely ge- ometrically simplified model is roughly constant, it varies strongly in the appearance preserving model due to varia- tions in model features.... In PAGE 8: ... Matthew 53 fps 93 fps lt;1 fps Table 3: Average frame rates for different rendering algo- rithms. Table2 ) becomes smaller and thus the maximum number of primitives per node is not significantly higher than for the geometric simplification. Additionally due to the coarser sampling these models are smoother and have less details to preserve.... ..."
Table 4.2: Numeric order of target documents by query and Gospel. Query Number Matthew Mark Luke John 6 7 14 10 22 16 19
Table 1: Average sensitivity (SEN), specificity (SPC), two-state accuracy (Q2) and Matthews correlation coefficient (MCC) for 10 different data sets in each experiment with different databases.
2007
"... In PAGE 3: ... Each set of 30,000 or 70,000 unlabeled samples was chosen randomly, and we used 10 datasets from each database in order to avoid sampling bias. The results are listed in Table1 . Swiss-Prot outper- formed UniProt and TrEMBL, which indicates the quality of unlabeled data is an important factor for prediction accuracy.... ..."
Table4. Accuracyofdifferentmethodsasmeasuredbyper-residueaccuracy and Matthews correlation coefficients (second line in each row) on a set of fivehelicalmembraneproteinsnotincludedinthetrainingset(includingtwo, 1u7c and 1xfh, that are not homologous to proteins included in the training)
"... In PAGE 6: ... Finally, in order to illustrate the performance of several top rank- ing methods on individual proteins we used a set of five recently solved membrane proteins. The results are shown in Table4 . Three out of these five proteins (including a bacteriorhodopsin structure, 1tn0, and a photosynthetic reaction center protein, 1umx) exhibit homology to those included in the training and are merely used to show the variation in accuracy observed for all the methods on different proteins.... In PAGE 6: ..., 2004), and it is, thus, laden with additional uncertainty. Nevertheless, we believe that the limited accuracy of the top ranking methods included in Table4 further underscores the need for continued development of improved methods for membrane domain prediction. 4 CONCLUSION We proposed a novel representation of an amino acid residue and its environment for membrane protein prediction.... ..."
Table 4 Accuracy of different methods as measured by per-residue accu- racy and Matthews correlation coefficients (second line in each row) on a set of five helical membrane proteins not included in the training set (in- cluding two, 1u7c and 1xfh, that are not homologous to proteins included in the training).
"... In PAGE 7: ...Finally, in order to illustrate the performance of several top ranking methods on individual proteins we used a set of five recently solved membrane proteins. The results are shown in Table4 . Three out of these five proteins (including a bacte- riorhodopsin structure, 1tn0, and a photosynthetic reaction center protein, 1umx) exhibit homology to those included in the training and are merely used to show the variation in accuracy observed for all the methods on different proteins.... In PAGE 7: ..., 2004), and it is, thus, laden with additional uncertainty. Nevertheless, we believe that the limited accu- racy of the top ranking methods included in Table4 further underscores the need for continued development of im- proved methods for membrane domain prediction. 4 CONCLUSION We proposed a novel representation of an amino acid resi- due and its environment for membrane protein prediction.... ..."
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Table 2: Overdraw Factors. Overdraw factors of the sub- divided shadow maps with and without subdivisions (SSM and SSM*) are shown. Overdraw factors of the power plant model are much higher than those of St. Matthew since size and irregularity of objects of the power plant is much higher.
2005
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