Datasets:
vgainullin
/
xciting_data

Dataset card Data Studio Files
xet
 Community
1
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1
DISCUSSION
1
51
[ "B51" ]
17,626,050
pmid-11175784|pmid-15534222|pmid-12626739|pmid-12217908|pmid-15534222|pmid-16760900|pmid-16760900|pmid-11175784|pmid-15534222|pmid-12482955|pmid-16760900|pmid-12702209
It is also possible that there are weaker elements, which may only be revealed when combinatorial interactions among motifs are included in the regression models, or which may be required for spatially or temporally distinct subsets of muscle-enriched exons.
[ "51" ]
258
1,800
0
false
It is also possible that there are weaker elements, which may only be revealed when combinatorial interactions among motifs are included in the regression models, or which may be required for spatially or temporally distinct subsets of muscle-enriched exons.
[]
It is also possible that there are weaker elements, which may only be revealed when combinatorial interactions among motifs are included in the regression models, or which may be required for spatially or temporally distinct subsets of muscle-enriched exons.
true
true
true
true
true
310
1
DISCUSSION
1
51
[ "B51" ]
17,626,050
pmid-11175784|pmid-15534222|pmid-12626739|pmid-12217908|pmid-15534222|pmid-16760900|pmid-16760900|pmid-11175784|pmid-15534222|pmid-12482955|pmid-16760900|pmid-12702209
To obtain an initial estimate as to which of these factors may be most influential, we extended our study to include PWMs of width 5–7 nt.
[ "51" ]
138
1,801
0
false
To obtain an initial estimate as to which of these factors may be most influential, we extended our study to include PWMs of width 5–7 nt.
[]
To obtain an initial estimate as to which of these factors may be most influential, we extended our study to include PWMs of width 5–7 nt.
true
true
true
true
true
310
1
DISCUSSION
1
51
[ "B51" ]
17,626,050
pmid-11175784|pmid-15534222|pmid-12626739|pmid-12217908|pmid-15534222|pmid-16760900|pmid-16760900|pmid-11175784|pmid-15534222|pmid-12482955|pmid-16760900|pmid-12702209
The results are displayed on our website (http://vision.lbl.gov/People/ddas/NAR_SPLICE1/).
[ "51" ]
90
1,802
0
false
The results are displayed on our website (http://vision.lbl.gov/People/ddas/NAR_SPLICE1/).
[]
The results are displayed on our website.
true
true
true
true
true
310
1
DISCUSSION
1
51
[ "B51" ]
17,626,050
pmid-11175784|pmid-15534222|pmid-12626739|pmid-12217908|pmid-15534222|pmid-16760900|pmid-16760900|pmid-11175784|pmid-15534222|pmid-12482955|pmid-16760900|pmid-12702209
We observe that most motifs have similarities to the known motifs as identified above.
[ "51" ]
86
1,803
0
false
We observe that most motifs have similarities to the known motifs as identified above.
[]
We observe that most motifs have similarities to the known motifs as identified above.
true
true
true
true
true
310
1
DISCUSSION
1
51
[ "B51" ]
17,626,050
pmid-11175784|pmid-15534222|pmid-12626739|pmid-12217908|pmid-15534222|pmid-16760900|pmid-16760900|pmid-11175784|pmid-15534222|pmid-12482955|pmid-16760900|pmid-12702209
There is one motif in D200, GGSYVYW, which seems novel.
[ "51" ]
55
1,804
0
false
There is one motif in D200, GGSYVYW, which seems novel.
[]
There is one motif in D200, GGSYVYW, which seems novel.
true
true
true
true
true
310
1
DISCUSSION
1
51
[ "B51" ]
17,626,050
pmid-11175784|pmid-15534222|pmid-12626739|pmid-12217908|pmid-15534222|pmid-16760900|pmid-16760900|pmid-11175784|pmid-15534222|pmid-12482955|pmid-16760900|pmid-12702209
But since it has much higher P-value than others (P = 0.01), it is not readily clear if it is truly functional.
[ "51" ]
111
1,805
0
false
But since it has much higher P-value than others (P = 0.01), it is not readily clear if it is truly functional.
[]
But since it has much higher P-value than others, it is not readily clear if it is truly functional.
true
true
true
true
true
310
1
DISCUSSION
1
51
[ "B51" ]
17,626,050
pmid-11175784|pmid-15534222|pmid-12626739|pmid-12217908|pmid-15534222|pmid-16760900|pmid-16760900|pmid-11175784|pmid-15534222|pmid-12482955|pmid-16760900|pmid-12702209
Hence, we suspect that inclusion of combinatorial interactions among motifs may be most effective in revealing the novel motifs.
[ "51" ]
128
1,806
0
false
Hence, we suspect that inclusion of combinatorial interactions among motifs may be most effective in revealing the novel motifs.
[]
Hence, we suspect that inclusion of combinatorial interactions among motifs may be most effective in revealing the novel motifs.
true
true
true
true
true
310
1
DISCUSSION
1
51
[ "B51" ]
17,626,050
pmid-11175784|pmid-15534222|pmid-12626739|pmid-12217908|pmid-15534222|pmid-16760900|pmid-16760900|pmid-11175784|pmid-15534222|pmid-12482955|pmid-16760900|pmid-12702209
One question that needs to be addressed in future studies, as improved measures of binding specificity become available, is the importance of additional splicing factors such as the muscleblind proteins that are already known to influence the splicing of at least a few muscle-specific alternative exons (51).
[ "51" ]
309
1,807
1
false
One question that needs to be addressed in future studies, as improved measures of binding specificity become available, is the importance of additional splicing factors such as the muscleblind proteins that are already known to influence the splicing of at least a few muscle-specific alternative exons.
[ "51" ]
One question that needs to be addressed in future studies, as improved measures of binding specificity become available, is the importance of additional splicing factors such as the muscleblind proteins that are already known to influence the splicing of at least a few muscle-specific alternative exons.
true
true
true
true
true
310
2
DISCUSSION
1
58
[ "B58", "B35", "B59", "B60", "B27", "B61 B62 B63", "B64" ]
17,626,050
pmid-15691898|pmid-12840041|pmid-16839875|pmid-17456239|pmid-11175784|pmid-16760900|pmid-12574126|pmid-15824060|pmid-16260614|pmid-16449636|pmid-16537540|pmid-16839192|pmid-17101796|pmid-11158314|pmid-16403634|pmid-8663598|pmid-16403634|pmid-11313454|pmid-16109373|pmid-12574126|pmid-12150906|pmid-11528389|pmid-12022233|pmid-16314268
A working model that summarizes these findings is presented in Figure 5.
[ "58", "35", "59", "60", "27", "61–63", "64" ]
72
1,808
0
false
A working model that summarizes these findings is presented in Figure 5.
[]
A working model that summarizes these findings is presented in Figure 5.
true
true
true
true
true
311
2
DISCUSSION
1
58
[ "B58", "B35", "B59", "B60", "B27", "B61 B62 B63", "B64" ]
17,626,050
pmid-15691898|pmid-12840041|pmid-16839875|pmid-17456239|pmid-11175784|pmid-16760900|pmid-12574126|pmid-15824060|pmid-16260614|pmid-16449636|pmid-16537540|pmid-16839192|pmid-17101796|pmid-11158314|pmid-16403634|pmid-8663598|pmid-16403634|pmid-11313454|pmid-16109373|pmid-12574126|pmid-12150906|pmid-11528389|pmid-12022233|pmid-16314268
Fox, CELF and acuaac-binding factors are proposed as positive regulators of muscle-enriched exons via their binding to the downstream proximal intron.
[ "58", "35", "59", "60", "27", "61–63", "64" ]
150
1,809
0
false
Fox, CELF and acuaac-binding factors are proposed as positive regulators of muscle-enriched exons via their binding to the downstream proximal intron.
[]
Fox, CELF and acuaac-binding factors are proposed as positive regulators of muscle-enriched exons via their binding to the downstream proximal intron.
true
true
true
true
true
311
2
DISCUSSION
1
58
[ "B58", "B35", "B59", "B60", "B27", "B61 B62 B63", "B64" ]
17,626,050
pmid-15691898|pmid-12840041|pmid-16839875|pmid-17456239|pmid-11175784|pmid-16760900|pmid-12574126|pmid-15824060|pmid-16260614|pmid-16449636|pmid-16537540|pmid-16839192|pmid-17101796|pmid-11158314|pmid-16403634|pmid-8663598|pmid-16403634|pmid-11313454|pmid-16109373|pmid-12574126|pmid-12150906|pmid-11528389|pmid-12022233|pmid-16314268
The distribution of binding motifs among individual introns suggests that these factors function independently in some cases, and collaboratively in others, to specify muscle-enriched splicing.
[ "58", "35", "59", "60", "27", "61–63", "64" ]
193
1,810
0
false
The distribution of binding motifs among individual introns suggests that these factors function independently in some cases, and collaboratively in others, to specify muscle-enriched splicing.
[]
The distribution of binding motifs among individual introns suggests that these factors function independently in some cases, and collaboratively in others, to specify muscle-enriched splicing.
true
true
true
true
true
311
2
DISCUSSION
1
58
[ "B58", "B35", "B59", "B60", "B27", "B61 B62 B63", "B64" ]
17,626,050
pmid-15691898|pmid-12840041|pmid-16839875|pmid-17456239|pmid-11175784|pmid-16760900|pmid-12574126|pmid-15824060|pmid-16260614|pmid-16449636|pmid-16537540|pmid-16839192|pmid-17101796|pmid-11158314|pmid-16403634|pmid-8663598|pmid-16403634|pmid-11313454|pmid-16109373|pmid-12574126|pmid-12150906|pmid-11528389|pmid-12022233|pmid-16314268
For Fox proteins an especially widespread role is suggested by the high absolute abundance of ugcaug-binding motifs: almost half of the muscle-enriched exons in datasets of all four species possess at least one ugcaug motif in the D200 intronic region, and some of those lacking a proximal ugcaug have phylogenetically conserved distal ugcaug motif(s) (data not shown) analogous to the myosin II heavy chain-B neural specific exon (58).
[ "58", "35", "59", "60", "27", "61–63", "64" ]
436
1,811
1
false
For Fox proteins an especially widespread role is suggested by the high absolute abundance of ugcaug-binding motifs: almost half of the muscle-enriched exons in datasets of all four species possess at least one ugcaug motif in the D200 intronic region, and some of those lacking a proximal ugcaug have phylogenetically conserved distal ugcaug motif(s) (data not shown) analogous to the myosin II heavy chain-B neural specific exon.
[ "58" ]
For Fox proteins an especially widespread role is suggested by the high absolute abundance of ugcaug-binding motifs: almost half of the muscle-enriched exons in datasets of all four species possess at least one ugcaug motif in the D200 intronic region, and some of those lacking a proximal ugcaug have phylogenetically conserved distal ugcaug motif(s) (data not shown) analogous to the myosin II heavy chain-B neural specific exon.
true
true
true
true
true
311
2
DISCUSSION
1
58
[ "B58", "B35", "B59", "B60", "B27", "B61 B62 B63", "B64" ]
17,626,050
pmid-15691898|pmid-12840041|pmid-16839875|pmid-17456239|pmid-11175784|pmid-16760900|pmid-12574126|pmid-15824060|pmid-16260614|pmid-16449636|pmid-16537540|pmid-16839192|pmid-17101796|pmid-11158314|pmid-16403634|pmid-8663598|pmid-16403634|pmid-11313454|pmid-16109373|pmid-12574126|pmid-12150906|pmid-11528389|pmid-12022233|pmid-16314268
It will be interesting in the future to explore how coordination among these and other factors ultimately determines the spatial and temporal details of muscle-enriched splicing events.
[ "58", "35", "59", "60", "27", "61–63", "64" ]
185
1,812
0
false
It will be interesting in the future to explore how coordination among these and other factors ultimately determines the spatial and temporal details of muscle-enriched splicing events.
[]
It will be interesting in the future to explore how coordination among these and other factors ultimately determines the spatial and temporal details of muscle-enriched splicing events.
true
true
true
true
true
311
2
DISCUSSION
1
58
[ "B58", "B35", "B59", "B60", "B27", "B61 B62 B63", "B64" ]
17,626,050
pmid-15691898|pmid-12840041|pmid-16839875|pmid-17456239|pmid-11175784|pmid-16760900|pmid-12574126|pmid-15824060|pmid-16260614|pmid-16449636|pmid-16537540|pmid-16839192|pmid-17101796|pmid-11158314|pmid-16403634|pmid-8663598|pmid-16403634|pmid-11313454|pmid-16109373|pmid-12574126|pmid-12150906|pmid-11528389|pmid-12022233|pmid-16314268
Based on studies in other systems, PTB is predicted as a negative regulator of splicing, functioning primarily from upstream intronic sites to prevent inappropriate inclusion in non-muscle cell types (35,59,60).
[ "58", "35", "59", "60", "27", "61–63", "64" ]
211
1,813
0
false
Based on studies in other systems, PTB is predicted as a negative regulator of splicing, functioning primarily from upstream intronic sites to prevent inappropriate inclusion in non-muscle cell types.
[ "35,59,60" ]
Based on studies in other systems, PTB is predicted as a negative regulator of splicing, functioning primarily from upstream intronic sites to prevent inappropriate inclusion in non-muscle cell types.
true
true
true
true
true
311
2
DISCUSSION
1
58
[ "B58", "B35", "B59", "B60", "B27", "B61 B62 B63", "B64" ]
17,626,050
pmid-15691898|pmid-12840041|pmid-16839875|pmid-17456239|pmid-11175784|pmid-16760900|pmid-12574126|pmid-15824060|pmid-16260614|pmid-16449636|pmid-16537540|pmid-16839192|pmid-17101796|pmid-11158314|pmid-16403634|pmid-8663598|pmid-16403634|pmid-11313454|pmid-16109373|pmid-12574126|pmid-12150906|pmid-11528389|pmid-12022233|pmid-16314268
Finally, it is important to note that variations of this general model likely pertain to individual exons; in particular, Fox and CELF proteins can also have a negative role in the regulation of exons that are skipped in muscle (27,61–63).
[ "58", "35", "59", "60", "27", "61–63", "64" ]
239
1,814
0
false
Finally, it is important to note that variations of this general model likely pertain to individual exons; in particular, Fox and CELF proteins can also have a negative role in the regulation of exons that are skipped in muscle.
[ "27,61–63" ]
Finally, it is important to note that variations of this general model likely pertain to individual exons; in particular, Fox and CELF proteins can also have a negative role in the regulation of exons that are skipped in muscle.
true
true
true
true
true
311
2
DISCUSSION
1
64
[ "B58", "B35", "B59", "B60", "B27", "B61 B62 B63", "B64" ]
17,626,050
pmid-15691898|pmid-12840041|pmid-16839875|pmid-17456239|pmid-11175784|pmid-16760900|pmid-12574126|pmid-15824060|pmid-16260614|pmid-16449636|pmid-16537540|pmid-16839192|pmid-17101796|pmid-11158314|pmid-16403634|pmid-8663598|pmid-16403634|pmid-11313454|pmid-16109373|pmid-12574126|pmid-12150906|pmid-11528389|pmid-12022233|pmid-16314268
Future experimental analysis of these splicing factors, using functional splicing assays and targeted disruption of splicing factor activity in vivo (64), will be required to more fully test the predictions of this model.
[ "58", "35", "59", "60", "27", "61–63", "64" ]
221
1,815
1
false
Future experimental analysis of these splicing factors, using functional splicing assays and targeted disruption of splicing factor activity in vivo, will be required to more fully test the predictions of this model.
[ "64" ]
Future experimental analysis of these splicing factors, using functional splicing assays and targeted disruption of splicing factor activity in vivo, will be required to more fully test the predictions of this model.
true
true
true
true
true
311
2
DISCUSSION
1
58
[ "B58", "B35", "B59", "B60", "B27", "B61 B62 B63", "B64" ]
17,626,050
pmid-15691898|pmid-12840041|pmid-16839875|pmid-17456239|pmid-11175784|pmid-16760900|pmid-12574126|pmid-15824060|pmid-16260614|pmid-16449636|pmid-16537540|pmid-16839192|pmid-17101796|pmid-11158314|pmid-16403634|pmid-8663598|pmid-16403634|pmid-11313454|pmid-16109373|pmid-12574126|pmid-12150906|pmid-11528389|pmid-12022233|pmid-16314268
Figure 5.A candidate model showing splicing factors implicated in regulation of conserved muscle-enriched alternative exons.
[ "58", "35", "59", "60", "27", "61–63", "64" ]
124
1,816
0
false
Figure 5.A candidate model showing splicing factors implicated in regulation of conserved muscle-enriched alternative exons.
[]
Figure 5.A candidate model showing splicing factors implicated in regulation of conserved muscle-enriched alternative exons.
true
true
true
true
true
311
2
DISCUSSION
1
58
[ "B58", "B35", "B59", "B60", "B27", "B61 B62 B63", "B64" ]
17,626,050
pmid-15691898|pmid-12840041|pmid-16839875|pmid-17456239|pmid-11175784|pmid-16760900|pmid-12574126|pmid-15824060|pmid-16260614|pmid-16449636|pmid-16537540|pmid-16839192|pmid-17101796|pmid-11158314|pmid-16403634|pmid-8663598|pmid-16403634|pmid-11313454|pmid-16109373|pmid-12574126|pmid-12150906|pmid-11528389|pmid-12022233|pmid-16314268
Based on the conserved distribution of splicing factor binding sites across multiple vertebrate orders, the positive correlation with muscle-specific splicing and the high absolute abundance of ugcaug motifs, Fox proteins are proposed to play a major role in promoting inclusion of muscle-enriched exons.
[ "58", "35", "59", "60", "27", "61–63", "64" ]
304
1,817
0
false
Based on the conserved distribution of splicing factor binding sites across multiple vertebrate orders, the positive correlation with muscle-specific splicing and the high absolute abundance of ugcaug motifs, Fox proteins are proposed to play a major role in promoting inclusion of muscle-enriched exons.
[]
Based on the conserved distribution of splicing factor binding sites across multiple vertebrate orders, the positive correlation with muscle-specific splicing and the high absolute abundance of ugcaug motifs, Fox proteins are proposed to play a major role in promoting inclusion of muscle-enriched exons.
true
true
true
true
true
311
2
DISCUSSION
1
58
[ "B58", "B35", "B59", "B60", "B27", "B61 B62 B63", "B64" ]
17,626,050
pmid-15691898|pmid-12840041|pmid-16839875|pmid-17456239|pmid-11175784|pmid-16760900|pmid-12574126|pmid-15824060|pmid-16260614|pmid-16449636|pmid-16537540|pmid-16839192|pmid-17101796|pmid-11158314|pmid-16403634|pmid-8663598|pmid-16403634|pmid-11313454|pmid-16109373|pmid-12574126|pmid-12150906|pmid-11528389|pmid-12022233|pmid-16314268
The distribution of binding motifs among individual introns suggests that CELF proteins and by KH-type splicing factor(s) function independently in some cases, and together with Fox proteins in others, to specify muscle-enriched splicing.
[ "58", "35", "59", "60", "27", "61–63", "64" ]
238
1,818
0
false
The distribution of binding motifs among individual introns suggests that CELF proteins and by KH-type splicing factor(s) function independently in some cases, and together with Fox proteins in others, to specify muscle-enriched splicing.
[]
The distribution of binding motifs among individual introns suggests that CELF proteins and by KH-type splicing factor(s) function independently in some cases, and together with Fox proteins in others, to specify muscle-enriched splicing.
true
true
true
true
true
311
2
DISCUSSION
1
58
[ "B58", "B35", "B59", "B60", "B27", "B61 B62 B63", "B64" ]
17,626,050
pmid-15691898|pmid-12840041|pmid-16839875|pmid-17456239|pmid-11175784|pmid-16760900|pmid-12574126|pmid-15824060|pmid-16260614|pmid-16449636|pmid-16537540|pmid-16839192|pmid-17101796|pmid-11158314|pmid-16403634|pmid-8663598|pmid-16403634|pmid-11313454|pmid-16109373|pmid-12574126|pmid-12150906|pmid-11528389|pmid-12022233|pmid-16314268
In contrast, the enrichment of candidate PTB-binding sites in the proximal upstream intron suggests a role in preventing inappropriate inclusion of muscle-specific exons in other cell types.
[ "58", "35", "59", "60", "27", "61–63", "64" ]
190
1,819
0
false
In contrast, the enrichment of candidate PTB-binding sites in the proximal upstream intron suggests a role in preventing inappropriate inclusion of muscle-specific exons in other cell types.
[]
In contrast, the enrichment of candidate PTB-binding sites in the proximal upstream intron suggests a role in preventing inappropriate inclusion of muscle-specific exons in other cell types.
true
true
true
true
true
311
3
DISCUSSION
0
null
null
17,626,050
null
A candidate model showing splicing factors implicated in regulation of conserved muscle-enriched alternative exons.
null
115
1,820
0
false
null
null
A candidate model showing splicing factors implicated in regulation of conserved muscle-enriched alternative exons.
true
true
true
true
true
312
3
DISCUSSION
0
null
null
17,626,050
null
Based on the conserved distribution of splicing factor binding sites across multiple vertebrate orders, the positive correlation with muscle-specific splicing and the high absolute abundance of ugcaug motifs, Fox proteins are proposed to play a major role in promoting inclusion of muscle-enriched exons.
null
304
1,821
0
false
null
null
Based on the conserved distribution of splicing factor binding sites across multiple vertebrate orders, the positive correlation with muscle-specific splicing and the high absolute abundance of ugcaug motifs, Fox proteins are proposed to play a major role in promoting inclusion of muscle-enriched exons.
true
true
true
true
true
312
3
DISCUSSION
0
null
null
17,626,050
null
The distribution of binding motifs among individual introns suggests that CELF proteins and by KH-type splicing factor(s) function independently in some cases, and together with Fox proteins in others, to specify muscle-enriched splicing.
null
238
1,822
0
false
null
null
The distribution of binding motifs among individual introns suggests that CELF proteins and by KH-type splicing factor(s) function independently in some cases, and together with Fox proteins in others, to specify muscle-enriched splicing.
true
true
true
true
true
312
3
DISCUSSION
0
null
null
17,626,050
null
In contrast, the enrichment of candidate PTB-binding sites in the proximal upstream intron suggests a role in preventing inappropriate inclusion of muscle-specific exons in other cell types.
null
190
1,823
0
false
null
null
In contrast, the enrichment of candidate PTB-binding sites in the proximal upstream intron suggests a role in preventing inappropriate inclusion of muscle-specific exons in other cell types.
true
true
true
true
true
312
4
DISCUSSION
1
7
[ "B7", "B8", "B11", "B7", "B28" ]
17,626,050
pmid-11376152|pmid-15691898|pmid-16424921|pmid-11376152|pmid-15824060
Some of the cis-regulatory elements associated with muscle-enriched alternative exons have previously been observed flanking brain-enriched exons: ugcaug was the most over-represented motif in proximal downstream intron (7,8,11), and cucucu was the second most over-represented motif in the U100 region upstream of brain-enriched exons (7).
[ "7", "8", "11", "7", "28" ]
340
1,824
1
false
Some of the cis-regulatory elements associated with muscle-enriched alternative exons have previously been observed flanking brain-enriched exons: ugcaug was the most over-represented motif in proximal downstream intron, and cucucu was the second most over-represented motif in the U100 region upstream of brain-enriched exons.
[ "7,8,11", "7" ]
Some of the cis-regulatory elements associated with muscle-enriched alternative exons have previously been observed flanking brain-enriched exons: ugcaug was the most over-represented motif in proximal downstream intron, and cucucu was the second most over-represented motif in the U100 region upstream of brain-enriched exons.
true
true
true
true
true
313
4
DISCUSSION
1
7
[ "B7", "B8", "B11", "B7", "B28" ]
17,626,050
pmid-11376152|pmid-15691898|pmid-16424921|pmid-11376152|pmid-15824060
These observations suggest general roles for Fox- and PTB-related proteins in regulating tissue-specific splicing, at least for muscle and brain, but raise the question as to how tissue specificity is ultimately determined.
[ "7", "8", "11", "7", "28" ]
223
1,825
0
false
These observations suggest general roles for Fox- and PTB-related proteins in regulating tissue-specific splicing, at least for muscle and brain, but raise the question as to how tissue specificity is ultimately determined.
[]
These observations suggest general roles for Fox- and PTB-related proteins in regulating tissue-specific splicing, at least for muscle and brain, but raise the question as to how tissue specificity is ultimately determined.
true
true
true
true
true
313
4
DISCUSSION
1
28
[ "B7", "B8", "B11", "B7", "B28" ]
17,626,050
pmid-11376152|pmid-15691898|pmid-16424921|pmid-11376152|pmid-15824060
Several mechanisms may contribute to determination of temporal and spatial pattern of splicing switches, including tissue-specific differences in transcription and/or alternative splicing of Fox and PTB paralogs (28).
[ "7", "8", "11", "7", "28" ]
217
1,826
1
false
Several mechanisms may contribute to determination of temporal and spatial pattern of splicing switches, including tissue-specific differences in transcription and/or alternative splicing of Fox and PTB paralogs.
[ "28" ]
Several mechanisms may contribute to determination of temporal and spatial pattern of splicing switches, including tissue-specific differences in transcription and/or alternative splicing of Fox and PTB paralogs.
true
true
true
true
true
313
4
DISCUSSION
1
7
[ "B7", "B8", "B11", "B7", "B28" ]
17,626,050
pmid-11376152|pmid-15691898|pmid-16424921|pmid-11376152|pmid-15824060
Differential expression of additional RNA-binding proteins, such CELF proteins and KH-type acuaac-binding proteins in muscle, or NOVA1-related proteins in brain, likely also play a role, as may non-RNA-binding co-factors that preferentially interact with paralogs/isoforms of the primary RNA-binding proteins.
[ "7", "8", "11", "7", "28" ]
309
1,827
0
false
Differential expression of additional RNA-binding proteins, such CELF proteins and KH-type acuaac-binding proteins in muscle, or NOVA1-related proteins in brain, likely also play a role, as may non-RNA-binding co-factors that preferentially interact with paralogs/isoforms of the primary RNA-binding proteins.
[]
Differential expression of additional RNA-binding proteins, such CELF proteins and KH-type acuaac-binding proteins in muscle, or NOVA1-related proteins in brain, likely also play a role, as may non-RNA-binding co-factors that preferentially interact with paralogs/isoforms of the primary RNA-binding proteins.
true
true
true
true
true
313
5
DISCUSSION
0
null
null
17,626,050
null
In summary, normal metazoan development requires not only a transcriptional program, but also an alternative pre-mRNA splicing program to ensure that each gene encodes specific protein isoforms in the appropriate spatial and temporal patterns.
null
243
1,828
0
false
null
null
In summary, normal metazoan development requires not only a transcriptional program, but also an alternative pre-mRNA splicing program to ensure that each gene encodes specific protein isoforms in the appropriate spatial and temporal patterns.
true
true
true
true
true
314
5
DISCUSSION
0
null
null
17,626,050
null
Enrichment within the muscle dataset of genes with functions in cytoskeleton organization, microtubule stabilization and muscle development supports the notion that this splicing program is essential for proper expression of the unique muscle cytoskeleton.
null
256
1,829
0
false
null
null
Enrichment within the muscle dataset of genes with functions in cytoskeleton organization, microtubule stabilization and muscle development supports the notion that this splicing program is essential for proper expression of the unique muscle cytoskeleton.
true
true
true
true
true
314
5
DISCUSSION
0
null
null
17,626,050
null
The exon microarray employed in this study will enhance our ability to track the expression of individual exons during development and differentiation.
null
151
1,830
0
false
null
null
The exon microarray employed in this study will enhance our ability to track the expression of individual exons during development and differentiation.
true
true
true
true
true
314
5
DISCUSSION
0
null
null
17,626,050
null
As we have demonstrated here, this experimental approach is well complemented by the computational approach based on correlation with expression.
null
145
1,831
0
false
null
null
As we have demonstrated here, this experimental approach is well complemented by the computational approach based on correlation with expression.
true
true
true
true
true
314
5
DISCUSSION
0
null
null
17,626,050
null
We anticipate that correlation with exon expression will provide valuable insights into the cis-regulation of alternative splicing as additional datasets of tissue-specific exons become available for analysis.
null
209
1,832
0
false
null
null
We anticipate that correlation with exon expression will provide valuable insights into the cis-regulation of alternative splicing as additional datasets of tissue-specific exons become available for analysis.
true
true
true
true
true
314
0
INTRODUCTION
1
1
[ "b1", "b3", "b4", "b5", "b6", "b7", "b8", "b9", "b10", "b11", "b13" ]
17,135,207
pmid-15343339|pmid-16762047|pmid-16309778|pmid-12934013|pmid-15998455|pmid-14704708|pmid-12000970|pmid-14564010|pmid-15567862|pmid-16496022|pmid-15763560
At present, a great deal of biological information is represented as interactions between molecules.
[ "1", "3", "4", "5", "6", "7", "8", "9", "10", "11", "13" ]
100
1,833
0
false
At present, a great deal of biological information is represented as interactions between molecules.
[]
At present, a great deal of biological information is represented as interactions between molecules.
true
true
true
true
true
315
0
INTRODUCTION
1
4
[ "b1", "b3", "b4", "b5", "b6", "b7", "b8", "b9", "b10", "b11", "b13" ]
17,135,207
pmid-15343339|pmid-16762047|pmid-16309778|pmid-12934013|pmid-15998455|pmid-14704708|pmid-12000970|pmid-14564010|pmid-15567862|pmid-16496022|pmid-15763560
This information includes physical interactions that occur among proteins, DNA, RNA and small molecules (1–3); genetic interactions such as synthetic lethality, enhancement or suppression (4); and interactions due to co-expression (5) or co-citation (6).
[ "1", "3", "4", "5", "6", "7", "8", "9", "10", "11", "13" ]
254
1,834
1
false
This information includes physical interactions that occur among proteins, DNA, RNA and small molecules ; genetic interactions such as synthetic lethality, enhancement or suppression ; and interactions due to co-expression or co-citation.
[ "1–3", "4", "5", "6" ]
This information includes physical interactions that occur among proteins, DNA, RNA and small molecules ; genetic interactions such as synthetic lethality, enhancement or suppression ; and interactions due to co-expression or co-citation.
true
true
true
true
true
315
0
INTRODUCTION
1
1
[ "b1", "b3", "b4", "b5", "b6", "b7", "b8", "b9", "b10", "b11", "b13" ]
17,135,207
pmid-15343339|pmid-16762047|pmid-16309778|pmid-12934013|pmid-15998455|pmid-14704708|pmid-12000970|pmid-14564010|pmid-15567862|pmid-16496022|pmid-15763560
Modern analyses of interaction data typically accomplish two goals.
[ "1", "3", "4", "5", "6", "7", "8", "9", "10", "11", "13" ]
67
1,835
0
false
Modern analyses of interaction data typically accomplish two goals.
[]
Modern analyses of interaction data typically accomplish two goals.
true
true
true
true
true
315
0
INTRODUCTION
1
1
[ "b1", "b3", "b4", "b5", "b6", "b7", "b8", "b9", "b10", "b11", "b13" ]
17,135,207
pmid-15343339|pmid-16762047|pmid-16309778|pmid-12934013|pmid-15998455|pmid-14704708|pmid-12000970|pmid-14564010|pmid-15567862|pmid-16496022|pmid-15763560
The first goal is to clean the data, by filtering erroneous interactions that can be associated with high-throughput screens [false positives, e.g.
[ "1", "3", "4", "5", "6", "7", "8", "9", "10", "11", "13" ]
147
1,836
0
false
The first goal is to clean the data, by filtering erroneous interactions that can be associated with high-throughput screens [false positives, e.g.
[]
The first goal is to clean the data, by filtering erroneous interactions that can be associated with high-throughput screens [false positives, e.g.
true
true
true
true
true
315
0
INTRODUCTION
1
1
[ "b1", "b3", "b4", "b5", "b6", "b7", "b8", "b9", "b10", "b11", "b13" ]
17,135,207
pmid-15343339|pmid-16762047|pmid-16309778|pmid-12934013|pmid-15998455|pmid-14704708|pmid-12000970|pmid-14564010|pmid-15567862|pmid-16496022|pmid-15763560
(7,8)] or by predicting new interactions that may have been previously missed [false negatives, e.g.
[ "1", "3", "4", "5", "6", "7", "8", "9", "10", "11", "13" ]
100
1,837
0
false
] or by predicting new interactions that may have been previously missed [false negatives, e.g.
[ "7,8" ]
] or by predicting new interactions that may have been previously missed [false negatives, e.g.
false
false
true
true
false
315
0
INTRODUCTION
1
1
[ "b1", "b3", "b4", "b5", "b6", "b7", "b8", "b9", "b10", "b11", "b13" ]
17,135,207
pmid-15343339|pmid-16762047|pmid-16309778|pmid-12934013|pmid-15998455|pmid-14704708|pmid-12000970|pmid-14564010|pmid-15567862|pmid-16496022|pmid-15763560
The second goal is to organize the interactions into biological network models—i.e.
[ "1", "3", "4", "5", "6", "7", "8", "9", "10", "11", "13" ]
83
1,838
0
false
The second goal is to organize the interactions into biological network models—i.e.
[]
The second goal is to organize the interactions into biological network models—i.e.
true
true
true
true
true
315
0
INTRODUCTION
1
1
[ "b1", "b3", "b4", "b5", "b6", "b7", "b8", "b9", "b10", "b11", "b13" ]
17,135,207
pmid-15343339|pmid-16762047|pmid-16309778|pmid-12934013|pmid-15998455|pmid-14704708|pmid-12000970|pmid-14564010|pmid-15567862|pmid-16496022|pmid-15763560
collections of interactions hypothesized to work together towards a particular cellular function or within a common pathway (11–13).
[ "1", "3", "4", "5", "6", "7", "8", "9", "10", "11", "13" ]
132
1,839
0
false
collections of interactions hypothesized to work together towards a particular cellular function or within a common pathway.
[ "11–13" ]
collections of interactions hypothesized to work together towards a particular cellular function or within a common pathway.
false
true
true
true
false
315
1
INTRODUCTION
1
14
[ "b14", "b15", "b16", "b17", "b18", "b19", "b20", "b21", "b22", "b23", "b24" ]
17,135,207
pmid-11752321|pmid-16381839|pmid-12519993|pmid-16381927|pmid-14681455|pmid-15608231|pmid-16381923|pmid-16381885|pmid-12048284|pmid-15608230|pmid-16381929|NA|pmid-12611808|pmid-16381960
Interaction analysis is currently supported by two types of available databases (Figure 1).
[ "14", "15", "16", "17", "18", "19", "20", "21", "22", "23", "24" ]
91
1,840
0
false
Interaction analysis is currently supported by two types of available databases (Figure 1).
[]
Interaction analysis is currently supported by two types of available databases.
true
true
true
true
true
316
1
INTRODUCTION
1
14
[ "b14", "b15", "b16", "b17", "b18", "b19", "b20", "b21", "b22", "b23", "b24" ]
17,135,207
pmid-11752321|pmid-16381839|pmid-12519993|pmid-16381927|pmid-14681455|pmid-15608231|pmid-16381923|pmid-16381885|pmid-12048284|pmid-15608230|pmid-16381929|NA|pmid-12611808|pmid-16381960
First, the raw material for analysis is provided by databases of molecular interactions including the Database of Interacting Proteins (14), the Munich Center for Information on Protein Sequences (15), the Biomolecular Interaction Network Database (16), the BioGRID (17) and IntAct (18).
[ "14", "15", "16", "17", "18", "19", "20", "21", "22", "23", "24" ]
287
1,841
1
false
First, the raw material for analysis is provided by databases of molecular interactions including the Database of Interacting Proteins, the Munich Center for Information on Protein Sequences, the Biomolecular Interaction Network Database, the BioGRID and IntAct.
[ "14", "15", "16", "17", "18" ]
First, the raw material for analysis is provided by databases of molecular interactions including the Database of Interacting Proteins, the Munich Center for Information on Protein Sequences, the Biomolecular Interaction Network Database, the BioGRID and IntAct.
true
true
true
true
true
316
1
INTRODUCTION
1
14
[ "b14", "b15", "b16", "b17", "b18", "b19", "b20", "b21", "b22", "b23", "b24" ]
17,135,207
pmid-11752321|pmid-16381839|pmid-12519993|pmid-16381927|pmid-14681455|pmid-15608231|pmid-16381923|pmid-16381885|pmid-12048284|pmid-15608230|pmid-16381929|NA|pmid-12611808|pmid-16381960
Many of these databases provide confidence scores with each measured and predicted interaction.
[ "14", "15", "16", "17", "18", "19", "20", "21", "22", "23", "24" ]
95
1,842
0
false
Many of these databases provide confidence scores with each measured and predicted interaction.
[]
Many of these databases provide confidence scores with each measured and predicted interaction.
true
true
true
true
true
316
1
INTRODUCTION
1
14
[ "b14", "b15", "b16", "b17", "b18", "b19", "b20", "b21", "b22", "b23", "b24" ]
17,135,207
pmid-11752321|pmid-16381839|pmid-12519993|pmid-16381927|pmid-14681455|pmid-15608231|pmid-16381923|pmid-16381885|pmid-12048284|pmid-15608230|pmid-16381929|NA|pmid-12611808|pmid-16381960
Second, there are a growing number of so-called pathway databases, in which canonical diagrams of metabolic, signaling or regulatory pathways have been hand-curated from review articles and textbooks.
[ "14", "15", "16", "17", "18", "19", "20", "21", "22", "23", "24" ]
200
1,843
0
false
Second, there are a growing number of so-called pathway databases, in which canonical diagrams of metabolic, signaling or regulatory pathways have been hand-curated from review articles and textbooks.
[]
Second, there are a growing number of so-called pathway databases, in which canonical diagrams of metabolic, signaling or regulatory pathways have been hand-curated from review articles and textbooks.
true
true
true
true
true
316
1
INTRODUCTION
1
19
[ "b14", "b15", "b16", "b17", "b18", "b19", "b20", "b21", "b22", "b23", "b24" ]
17,135,207
pmid-11752321|pmid-16381839|pmid-12519993|pmid-16381927|pmid-14681455|pmid-15608231|pmid-16381923|pmid-16381885|pmid-12048284|pmid-15608230|pmid-16381929|NA|pmid-12611808|pmid-16381960
Metabolic pathways are the focus of Reactome (19), MetaCyc (20) and the Kyoto Encyclopedia of Genes and Genomes (21), while databases such as BioCarta (), CellMap (), the Signal Transduction Knowledge Environment (22), GeNet (23) and TransPATH (24) are primarily concerned with signaling and transcription.
[ "14", "15", "16", "17", "18", "19", "20", "21", "22", "23", "24" ]
306
1,844
1
false
Metabolic pathways are the focus of Reactome, MetaCyc and the Kyoto Encyclopedia of Genes and Genomes, while databases such as BioCarta (), CellMap (), the Signal Transduction Knowledge Environment, GeNet and TransPATH are primarily concerned with signaling and transcription.
[ "19", "20", "21", "22", "23", "24" ]
Metabolic pathways are the focus of Reactome, MetaCyc and the Kyoto Encyclopedia of Genes and Genomes, while databases such as BioCarta (), CellMap (), the Signal Transduction Knowledge Environment, GeNet and TransPATH are primarily concerned with signaling and transcription.
true
true
true
true
true
316
1
INTRODUCTION
1
14
[ "b14", "b15", "b16", "b17", "b18", "b19", "b20", "b21", "b22", "b23", "b24" ]
17,135,207
pmid-11752321|pmid-16381839|pmid-12519993|pmid-16381927|pmid-14681455|pmid-15608231|pmid-16381923|pmid-16381885|pmid-12048284|pmid-15608230|pmid-16381929|NA|pmid-12611808|pmid-16381960
All of these pathway databases are relevant to the second and perhaps ultimate goal of interaction analysis—models of well-defined and well-validated functional relationships among genes, proteins and/or metabolites.
[ "14", "15", "16", "17", "18", "19", "20", "21", "22", "23", "24" ]
216
1,845
0
false
All of these pathway databases are relevant to the second and perhaps ultimate goal of interaction analysis—models of well-defined and well-validated functional relationships among genes, proteins and/or metabolites.
[]
All of these pathway databases are relevant to the second and perhaps ultimate goal of interaction analysis—models of well-defined and well-validated functional relationships among genes, proteins and/or metabolites.
true
true
true
true
true
316
2
INTRODUCTION
1
14
[ "b14", "b17", "b48", "b18", "b15", "b16", "b19", "b22", "b23", "b21" ]
17,135,207
pmid-11752321|pmid-16381927|pmid-11911893|pmid-14681455|pmid-16381839|pmid-12519993|pmid-15608231|pmid-12048284|pmid-15608230|pmid-16381885
The need for a new type of database.
[ "14", "17", "48", "18", "15", "16", "19", "22", "23", "21" ]
36
1,846
0
false
The need for a new type of database.
[]
The need for a new type of database.
true
true
true
true
true
317
2
INTRODUCTION
1
14
[ "b14", "b17", "b48", "b18", "b15", "b16", "b19", "b22", "b23", "b21" ]
17,135,207
pmid-11752321|pmid-16381927|pmid-11911893|pmid-14681455|pmid-16381839|pmid-12519993|pmid-15608231|pmid-12048284|pmid-15608230|pmid-16381885
The CellCircuits database is positioned between raw molecular interaction databases (left) and databases of rigorously validated cellular pathways (right).
[ "14", "17", "48", "18", "15", "16", "19", "22", "23", "21" ]
155
1,847
0
false
The CellCircuits database is positioned between raw molecular interaction databases (left) and databases of rigorously validated cellular pathways (right).
[]
The CellCircuits database is positioned between raw molecular interaction databases (left) and databases of rigorously validated cellular pathways (right).
true
true
true
true
true
317
2
INTRODUCTION
1
14
[ "b14", "b17", "b48", "b18", "b15", "b16", "b19", "b22", "b23", "b21" ]
17,135,207
pmid-11752321|pmid-16381927|pmid-11911893|pmid-14681455|pmid-16381839|pmid-12519993|pmid-15608231|pmid-12048284|pmid-15608230|pmid-16381885
Interaction database icons represent (clockwise from top left) the Database of Interacting Proteins [DIP (14)]; the General Repository of Interaction Datasets
[ "14", "17", "48", "18", "15", "16", "19", "22", "23", "21" ]
158
1,848
0
false
Interaction database icons represent (clockwise from top left) the Database of Interacting Proteins ; the General Repository of Interaction Datasets
[ "DIP (14)" ]
Interaction database icons represent (clockwise from top left) the Database of Interacting Proteins ; the General Repository of Interaction Datasets
true
true
false
true
false
317
2
INTRODUCTION
1
14
[ "b14", "b17", "b48", "b18", "b15", "b16", "b19", "b22", "b23", "b21" ]
17,135,207
pmid-11752321|pmid-16381927|pmid-11911893|pmid-14681455|pmid-16381839|pmid-12519993|pmid-15608231|pmid-12048284|pmid-15608230|pmid-16381885
[GRID (17)]; Molecular INTeractions Database
[ "14", "17", "48", "18", "15", "16", "19", "22", "23", "21" ]
44
1,849
0
false
; Molecular INTeractions Database
[ "GRID (17)" ]
; Molecular INTeractions Database
false
false
false
true
false
317
2
INTRODUCTION
1
18
[ "b14", "b17", "b48", "b18", "b15", "b16", "b19", "b22", "b23", "b21" ]
17,135,207
pmid-11752321|pmid-16381927|pmid-11911893|pmid-14681455|pmid-16381839|pmid-12519993|pmid-15608231|pmid-12048284|pmid-15608230|pmid-16381885
[MINT (48)]; the IntAct molecular interactions database (18); the interaction database at the Munich Information Center for Protein Sequences [MIPS (15)]; and Biomolecular Interaction Network Database
[ "14", "17", "48", "18", "15", "16", "19", "22", "23", "21" ]
200
1,850
1
false
; the IntAct molecular interactions database ; the interaction database at the Munich Information Center for Protein Sequences ; and Biomolecular Interaction Network Database
[ "MINT (48)", "18", "MIPS (15)" ]
; the IntAct molecular interactions database ; the interaction database at the Munich Information Center for Protein Sequences ; and Biomolecular Interaction Network Database
false
false
false
true
false
317
2
INTRODUCTION
1
14
[ "b14", "b17", "b48", "b18", "b15", "b16", "b19", "b22", "b23", "b21" ]
17,135,207
pmid-11752321|pmid-16381927|pmid-11911893|pmid-14681455|pmid-16381839|pmid-12519993|pmid-15608231|pmid-12048284|pmid-15608230|pmid-16381885
[BIND (16)].
[ "14", "17", "48", "18", "15", "16", "19", "22", "23", "21" ]
12
1,851
0
false
.
[ "BIND (16)" ]
.
false
false
true
true
false
317
2
INTRODUCTION
1
19
[ "b14", "b17", "b48", "b18", "b15", "b16", "b19", "b22", "b23", "b21" ]
17,135,207
pmid-11752321|pmid-16381927|pmid-11911893|pmid-14681455|pmid-16381839|pmid-12519993|pmid-15608231|pmid-12048284|pmid-15608230|pmid-16381885
Pathway database icons represent Reactome (19); Signal Transduction Knowledge Environment
[ "14", "17", "48", "18", "15", "16", "19", "22", "23", "21" ]
89
1,852
1
false
Pathway database icons represent Reactome ; Signal Transduction Knowledge Environment
[ "19" ]
Pathway database icons represent Reactome ; Signal Transduction Knowledge Environment
true
true
false
true
false
317
2
INTRODUCTION
1
14
[ "b14", "b17", "b48", "b18", "b15", "b16", "b19", "b22", "b23", "b21" ]
17,135,207
pmid-11752321|pmid-16381927|pmid-11911893|pmid-14681455|pmid-16381839|pmid-12519993|pmid-15608231|pmid-12048284|pmid-15608230|pmid-16381885
[STKE (22)]; Gene Networks database [GeNet (23)]; BioCarta (); Kyoto Encyclopedia of Genes and Genomes [KEGG (21)]; and CellMap ().
[ "14", "17", "48", "18", "15", "16", "19", "22", "23", "21" ]
131
1,853
0
false
; Gene Networks database ; BioCarta (); Kyoto Encyclopedia of Genes and Genomes ; and CellMap ().
[ "STKE (22)", "GeNet (23)", "KEGG (21)" ]
; Gene Networks database ; BioCarta (); Kyoto Encyclopedia of Genes and Genomes ; and CellMap ().
false
false
true
true
false
317
3
INTRODUCTION
1
11
[ "b11", "b13" ]
17,135,207
pmid-16496022|pmid-15763560
Automatic inference of accurate and detailed molecular pathways, however, is well beyond the capability of current interaction analyses and integrative modeling approaches.
[ "11", "13" ]
172
1,854
0
false
Automatic inference of accurate and detailed molecular pathways, however, is well beyond the capability of current interaction analyses and integrative modeling approaches.
[]
Automatic inference of accurate and detailed molecular pathways, however, is well beyond the capability of current interaction analyses and integrative modeling approaches.
true
true
true
true
true
318
3
INTRODUCTION
1
11
[ "b11", "b13" ]
17,135,207
pmid-16496022|pmid-15763560
Although current approaches attempt to place interactions into subnetworks according to their putative function (11–13), such subnetworks are hypothetical in nature and thus inappropriate for entry into any of the existing databases of canonical pathways.
[ "11", "13" ]
255
1,855
0
false
Although current approaches attempt to place interactions into subnetworks according to their putative function, such subnetworks are hypothetical in nature and thus inappropriate for entry into any of the existing databases of canonical pathways.
[ "11–13" ]
Although current approaches attempt to place interactions into subnetworks according to their putative function, such subnetworks are hypothetical in nature and thus inappropriate for entry into any of the existing databases of canonical pathways.
true
true
true
true
true
318
3
INTRODUCTION
1
11
[ "b11", "b13" ]
17,135,207
pmid-16496022|pmid-15763560
Rather, the subnetwork models produced by automated approaches are typically embedded in figures, tables or supplementary information in the primary published literature.
[ "11", "13" ]
170
1,856
0
false
Rather, the subnetwork models produced by automated approaches are typically embedded in figures, tables or supplementary information in the primary published literature.
[]
Rather, the subnetwork models produced by automated approaches are typically embedded in figures, tables or supplementary information in the primary published literature.
true
true
true
true
true
318
3
INTRODUCTION
1
11
[ "b11", "b13" ]
17,135,207
pmid-16496022|pmid-15763560
Although it is certainly possible to read about the models, there are several problems with this traditional method of dissemination.
[ "11", "13" ]
133
1,857
0
false
Although it is certainly possible to read about the models, there are several problems with this traditional method of dissemination.
[]
Although it is certainly possible to read about the models, there are several problems with this traditional method of dissemination.
true
true
true
true
true
318
3
INTRODUCTION
1
11
[ "b11", "b13" ]
17,135,207
pmid-16496022|pmid-15763560
First, the size and number of models from even a single publication can be overwhelming, making models relevant to a particular gene or function difficult to locate.
[ "11", "13" ]
165
1,858
0
false
First, the size and number of models from even a single publication can be overwhelming, making models relevant to a particular gene or function difficult to locate.
[]
First, the size and number of models from even a single publication can be overwhelming, making models relevant to a particular gene or function difficult to locate.
true
true
true
true
true
318
3
INTRODUCTION
1
11
[ "b11", "b13" ]
17,135,207
pmid-16496022|pmid-15763560
Second, in many cases, network modeling papers target bioinformatic, rather than biological or medical, audiences.
[ "11", "13" ]
114
1,859
0
false
Second, in many cases, network modeling papers target bioinformatic, rather than biological or medical, audiences.
[]
Second, in many cases, network modeling papers target bioinformatic, rather than biological or medical, audiences.
true
true
true
true
true
318
3
INTRODUCTION
1
11
[ "b11", "b13" ]
17,135,207
pmid-16496022|pmid-15763560
As a result, the models remain largely inaccessible to those who have the most knowledge to interpret them and the most to gain from their successful interpretation.
[ "11", "13" ]
165
1,860
0
false
As a result, the models remain largely inaccessible to those who have the most knowledge to interpret them and the most to gain from their successful interpretation.
[]
As a result, the models remain largely inaccessible to those who have the most knowledge to interpret them and the most to gain from their successful interpretation.
true
true
true
true
true
318
4
INTRODUCTION
1
25
[ "b25", "b26", "b27" ]
17,135,207
pmid-15287973|pmid-15024411|pmid-16381960
Recent opinion articles (25,26) have recognized a related problem for the case of protein functional predictions, calling for a clearinghouse of hypotheses generated by bioinformatics analyses and searchable by experimental biologists.
[ "25", "26", "27" ]
235
1,861
0
false
Recent opinion articles have recognized a related problem for the case of protein functional predictions, calling for a clearinghouse of hypotheses generated by bioinformatics analyses and searchable by experimental biologists.
[ "25,26" ]
Recent opinion articles have recognized a related problem for the case of protein functional predictions, calling for a clearinghouse of hypotheses generated by bioinformatics analyses and searchable by experimental biologists.
true
true
true
true
true
319
4
INTRODUCTION
1
27
[ "b25", "b26", "b27" ]
17,135,207
pmid-15287973|pmid-15024411|pmid-16381960
In the same vein, the BioModels Database (27) has recently been adopted as a working repository for simulations of kinetic quantitative systems based on ordinary differential equations.
[ "25", "26", "27" ]
185
1,862
1
false
In the same vein, the BioModels Database has recently been adopted as a working repository for simulations of kinetic quantitative systems based on ordinary differential equations.
[ "27" ]
In the same vein, the BioModels Database has recently been adopted as a working repository for simulations of kinetic quantitative systems based on ordinary differential equations.
true
true
true
true
true
319
4
INTRODUCTION
1
25
[ "b25", "b26", "b27" ]
17,135,207
pmid-15287973|pmid-15024411|pmid-16381960
Subnetworks inferred from genome-scale data, however, do not fall into this category.
[ "25", "26", "27" ]
85
1,863
0
false
Subnetworks inferred from genome-scale data, however, do not fall into this category.
[]
Subnetworks inferred from genome-scale data, however, do not fall into this category.
true
true
true
true
true
319
5
INTRODUCTION
0
null
null
17,135,207
null
Motivated by these considerations, we have designed CellCircuits as an open-access general repository of models distilled from protein networks.
null
144
1,864
0
false
null
null
Motivated by these considerations, we have designed CellCircuits as an open-access general repository of models distilled from protein networks.
true
true
true
true
true
320
5
INTRODUCTION
0
null
null
17,135,207
null
By aggregating models derived from many separate studies into a single resource, CellCircuits bridges the gap between databases of individual pairwise interactions and fully curated, biologically validated pathway models.
null
221
1,865
0
false
null
null
By aggregating models derived from many separate studies into a single resource, CellCircuits bridges the gap between databases of individual pairwise interactions and fully curated, biologically validated pathway models.
true
true
true
true
true
320
5
INTRODUCTION
0
null
null
17,135,207
null
The CellCircuits database enables experimentalists to readily access and cross-reference models across multiple publications.
null
125
1,866
0
false
null
null
The CellCircuits database enables experimentalists to readily access and cross-reference models across multiple publications.
true
true
true
true
true
320
5
INTRODUCTION
0
null
null
17,135,207
null
It also enables the meta-analysis of the entire set of models to reveal inter-model relationships and to answer global questions; for instance, which models overlap in terms of the genes and/or cellular processes represented?
null
225
1,867
0
false
null
null
It also enables the meta-analysis of the entire set of models to reveal inter-model relationships and to answer global questions; for instance, which models overlap in terms of the genes and/or cellular processes represented?
true
true
true
true
true
320
5
INTRODUCTION
0
null
null
17,135,207
null
How novel is a new result given the models that are already present in the database?
null
84
1,868
0
false
null
null
How novel is a new result given the models that are already present in the database?
true
true
true
true
true
320
0
DISCUSSION
0
null
null
17,135,207
pmid-15343339|pmid-16762047|pmid-16309778|pmid-12934013|pmid-15998455|pmid-14704708|pmid-12000970|pmid-14564010|pmid-15567862|pmid-16496022|pmid-15763560
In summary, CellCircuits version 1.0 provides a clearinghouse in which hypothetical pathway models derived from large-scale protein networks may be easily accessed, queried and exported for further study.
null
204
1,869
0
false
null
null
In summary, CellCircuits version 1.0 provides a clearinghouse in which hypothetical pathway models derived from large-scale protein networks may be easily accessed, queried and exported for further study.
true
true
true
true
true
321
0
DISCUSSION
0
null
null
17,135,207
pmid-15343339|pmid-16762047|pmid-16309778|pmid-12934013|pmid-15998455|pmid-14704708|pmid-12000970|pmid-14564010|pmid-15567862|pmid-16496022|pmid-15763560
The 11 publications included in this initial release were chosen to cover a broad range of network model types with a bias towards publications that provided models in both graphical and machine-readable format.
null
211
1,870
0
false
null
null
The 11 publications included in this initial release were chosen to cover a broad range of network model types with a bias towards publications that provided models in both graphical and machine-readable format.
true
true
true
true
true
321
0
DISCUSSION
0
null
null
17,135,207
pmid-15343339|pmid-16762047|pmid-16309778|pmid-12934013|pmid-15998455|pmid-14704708|pmid-12000970|pmid-14564010|pmid-15567862|pmid-16496022|pmid-15763560
Beyond this proof-of-principle, a significant question is whether, or to what extent, all past and future network models might be incorporated.
null
143
1,871
0
false
null
null
Beyond this proof-of-principle, a significant question is whether, or to what extent, all past and future network models might be incorporated.
true
true
true
true
true
321
1
DISCUSSION
1
45
[ "b45", "b44", "b27" ]
17,135,207
pmid-11752321|pmid-16381839|pmid-12519993|pmid-16381927|pmid-14681455|pmid-15608231|pmid-16381923|pmid-16381885|pmid-12048284|pmid-15608230|pmid-16381929|NA|pmid-12611808|pmid-16381960
On one hand, the field of network biology is still young such that the number of relevant previous publications is probably <50.
[ "45", "44", "27" ]
128
1,872
0
false
On one hand, the field of network biology is still young such that the number of relevant previous publications is probably <50.
[]
On one hand, the field of network biology is still young such that the number of relevant previous publications is probably <50.
true
true
true
true
true
322
1
DISCUSSION
1
45
[ "b45", "b44", "b27" ]
17,135,207
pmid-11752321|pmid-16381839|pmid-12519993|pmid-16381927|pmid-14681455|pmid-15608231|pmid-16381923|pmid-16381885|pmid-12048284|pmid-15608230|pmid-16381929|NA|pmid-12611808|pmid-16381960
On the other hand, the rapid adoption of systems and network approaches will make capturing information from all future works a daunting prospect if the models are not readily accessible.
[ "45", "44", "27" ]
187
1,873
0
false
On the other hand, the rapid adoption of systems and network approaches will make capturing information from all future works a daunting prospect if the models are not readily accessible.
[]
On the other hand, the rapid adoption of systems and network approaches will make capturing information from all future works a daunting prospect if the models are not readily accessible.
true
true
true
true
true
322
1
DISCUSSION
1
27
[ "b45", "b44", "b27" ]
17,135,207
pmid-11752321|pmid-16381839|pmid-12519993|pmid-16381927|pmid-14681455|pmid-15608231|pmid-16381923|pmid-16381885|pmid-12048284|pmid-15608230|pmid-16381929|NA|pmid-12611808|pmid-16381960
CellCircuits complements existing efforts that have begun to address this challenge, such as markup languages for describing models [BioPAX (45) and SBML (44)] and the BioModels Database of quantitative, kinetic models (27).
[ "45", "44", "27" ]
224
1,874
1
false
CellCircuits complements existing efforts that have begun to address this challenge, such as markup languages for describing models and the BioModels Database of quantitative, kinetic models.
[ "BioPAX (45) and SBML (44)", "27" ]
CellCircuits complements existing efforts that have begun to address this challenge, such as markup languages for describing models and the BioModels Database of quantitative, kinetic models.
true
true
true
true
true
322
1
DISCUSSION
1
45
[ "b45", "b44", "b27" ]
17,135,207
pmid-11752321|pmid-16381839|pmid-12519993|pmid-16381927|pmid-14681455|pmid-15608231|pmid-16381923|pmid-16381885|pmid-12048284|pmid-15608230|pmid-16381929|NA|pmid-12611808|pmid-16381960
Similar to biological sequence and microarray databases, we envision CellCircuits as a valuable resource for storing, accessing and updating network models across the wider biological research community.
[ "45", "44", "27" ]
203
1,875
0
false
Similar to biological sequence and microarray databases, we envision CellCircuits as a valuable resource for storing, accessing and updating network models across the wider biological research community.
[]
Similar to biological sequence and microarray databases, we envision CellCircuits as a valuable resource for storing, accessing and updating network models across the wider biological research community.
true
true
true
true
true
322
0
INTRODUCTION
1
1
[ "B1", "B2", "B3" ]
17,584,797
NA|NA|pmid-1315624
The structures of large and complex lipids are difficult to represent in drawings, which leads to the use of many custom formats that often generate more confusion than clarity among members of the lipid research community.
[ "1", "2", "3" ]
223
1,876
0
false
The structures of large and complex lipids are difficult to represent in drawings, which leads to the use of many custom formats that often generate more confusion than clarity among members of the lipid research community.
[]
The structures of large and complex lipids are difficult to represent in drawings, which leads to the use of many custom formats that often generate more confusion than clarity among members of the lipid research community.
true
true
true
true
true
323
0
INTRODUCTION
1
1
[ "B1", "B2", "B3" ]
17,584,797
NA|NA|pmid-1315624
For example, usage of the Simplified Molecular Line Entry Specification (SMILES) (1) (www.daylight.com/smiles/index.html) format to represent lipid structures, while being very compact and accurate in terms of bond connectivity, valence and chirality, causes problems when the structure is rendered.
[ "1", "2", "3" ]
299
1,877
1
false
For example, usage of the Simplified Molecular Line Entry Specification (SMILES) (www.daylight.com/smiles/index.html) format to represent lipid structures, while being very compact and accurate in terms of bond connectivity, valence and chirality, causes problems when the structure is rendered.
[ "1" ]
For example, usage of the Simplified Molecular Line Entry Specification (SMILES) (www.daylight.com/smiles/index.html) format to represent lipid structures, while being very compact and accurate in terms of bond connectivity, valence and chirality, causes problems when the structure is rendered.
true
true
true
true
true
323
0
INTRODUCTION
1
1
[ "B1", "B2", "B3" ]
17,584,797
NA|NA|pmid-1315624
This is due to the fact that the SMILES format does not include 2D coordinates and hence the orientation of the structure as drawn is quite arbitrary, making visual recognition and comparison of related structures difficult.
[ "1", "2", "3" ]
224
1,878
0
false
This is due to the fact that the SMILES format does not include 2D coordinates and hence the orientation of the structure as drawn is quite arbitrary, making visual recognition and comparison of related structures difficult.
[]
This is due to the fact that the SMILES format does not include 2D coordinates and hence the orientation of the structure as drawn is quite arbitrary, making visual recognition and comparison of related structures difficult.
true
true
true
true
true
323
0
INTRODUCTION
1
1
[ "B1", "B2", "B3" ]
17,584,797
NA|NA|pmid-1315624
Members of the lipid community currently draw structures based on their own individual preferences.
[ "1", "2", "3" ]
99
1,879
0
false
Members of the lipid community currently draw structures based on their own individual preferences.
[]
Members of the lipid community currently draw structures based on their own individual preferences.
true
true
true
true
true
323
0
INTRODUCTION
1
1
[ "B1", "B2", "B3" ]
17,584,797
NA|NA|pmid-1315624
A given lipid structure may appear quite differently in different lipid databases (2, 3).
[ "1", "2", "3" ]
89
1,880
0
false
A given lipid structure may appear quite differently in different lipid databases.
[ "2, 3" ]
A given lipid structure may appear quite differently in different lipid databases.
true
true
true
true
true
323
0
INTRODUCTION
1
1
[ "B1", "B2", "B3" ]
17,584,797
NA|NA|pmid-1315624
In summary, consistent structure-drawing tools for lipids are currently not available.
[ "1", "2", "3" ]
86
1,881
0
false
In summary, consistent structure-drawing tools for lipids are currently not available.
[]
In summary, consistent structure-drawing tools for lipids are currently not available.
true
true
true
true
true
323
1
INTRODUCTION
1
4
[ "B4", "B5" ]
17,584,797
pmid-15722563|pmid-17098933
The structure-drawing step is typically a most time-consuming process in creating molecular databases of lipids.
[ "4", "5" ]
112
1,882
0
false
The structure-drawing step is typically a most time-consuming process in creating molecular databases of lipids.
[]
The structure-drawing step is typically a most time-consuming process in creating molecular databases of lipids.
true
true
true
true
true
324
1
INTRODUCTION
1
4
[ "B4", "B5" ]
17,584,797
pmid-15722563|pmid-17098933
However, many classes of lipids lend themselves to automated structure-drawing paradigms, due to their consistent 2D layout.
[ "4", "5" ]
124
1,883
0
false
However, many classes of lipids lend themselves to automated structure-drawing paradigms, due to their consistent 2D layout.
[]
However, many classes of lipids lend themselves to automated structure-drawing paradigms, due to their consistent 2D layout.
true
true
true
true
true
324
1
INTRODUCTION
1
4
[ "B4", "B5" ]
17,584,797
pmid-15722563|pmid-17098933
The LIPID MAPS consortium has developed and deployed a suite of structure-drawing tools that greatly increase the efficiency of data entry into lipid structure databases and permit ‘on-demand’ structure generation in conjunction with a variety of MS prediction tools.
[ "4", "5" ]
267
1,884
0
false
The LIPID MAPS consortium has developed and deployed a suite of structure-drawing tools that greatly increase the efficiency of data entry into lipid structure databases and permit ‘on-demand’ structure generation in conjunction with a variety of MS prediction tools.
[]
The LIPID MAPS consortium has developed and deployed a suite of structure-drawing tools that greatly increase the efficiency of data entry into lipid structure databases and permit ‘on-demand’ structure generation in conjunction with a variety of MS prediction tools.
true
true
true
true
true
324
1
INTRODUCTION
1
4
[ "B4", "B5" ]
17,584,797
pmid-15722563|pmid-17098933
We have chosen a consistent format for representing lipid structures (4) where, in the simplest case of the fatty acid derivatives, the acid group (or equivalent) is drawn on the right and the hydrophobic hydrocarbon chain is on the left.
[ "4", "5" ]
238
1,885
1
false
We have chosen a consistent format for representing lipid structures where, in the simplest case of the fatty acid derivatives, the acid group (or equivalent) is drawn on the right and the hydrophobic hydrocarbon chain is on the left.
[ "4" ]
We have chosen a consistent format for representing lipid structures where, in the simplest case of the fatty acid derivatives, the acid group (or equivalent) is drawn on the right and the hydrophobic hydrocarbon chain is on the left.
true
true
true
true
true
324
1
INTRODUCTION
1
4
[ "B4", "B5" ]
17,584,797
pmid-15722563|pmid-17098933
Similarly for glycerolipids, glycerophospholipids and sphingolipids, the radyl hydrocarbon chains are drawn to the left and the headgoups are depicted on the right.
[ "4", "5" ]
164
1,886
0
false
Similarly for glycerolipids, glycerophospholipids and sphingolipids, the radyl hydrocarbon chains are drawn to the left and the headgoups are depicted on the right.
[]
Similarly for glycerolipids, glycerophospholipids and sphingolipids, the radyl hydrocarbon chains are drawn to the left and the headgoups are depicted on the right.
true
true
true
true
true
324
1
INTRODUCTION
1
5
[ "B4", "B5" ]
17,584,797
pmid-15722563|pmid-17098933
This approach enables a more consistent, error-free approach to drawing lipid structures and has been used extensively in populating the LIPID MAPS structure database (LMSD), which currently contains over 10 000 molecules (5).
[ "4", "5" ]
226
1,887
1
false
This approach enables a more consistent, error-free approach to drawing lipid structures and has been used extensively in populating the LIPID MAPS structure database (LMSD), which currently contains over 10 000 molecules.
[ "5" ]
This approach enables a more consistent, error-free approach to drawing lipid structures and has been used extensively in populating the LIPID MAPS structure database (LMSD), which currently contains over 10 000 molecules.
true
true
true
true
true
324
2
INTRODUCTION
0
null
null
17,584,797
null
We have adopted an approach where ‘core’ structures such as diacetyl glycerol (glycerolipids) and formic acid (fatty acyls) are represented as text-based MDL molfiles (described under section MDL CTfile Formats at www.mdli.com), and these molfiles are then manipulated to generate a variety of structures in MDL molfile and Structure Data Format (SDF) files containing that core (Figure 1).
null
390
1,888
0
false
null
null
We have adopted an approach where ‘core’ structures such as diacetyl glycerol (glycerolipids) and formic acid (fatty acyls) are represented as text-based MDL molfiles (described under section MDL CTfile Formats at www.mdli.com), and these molfiles are then manipulated to generate a variety of structures in MDL molfile and Structure Data Format (SDF) files containing that core (Figure 1).
true
true
true
true
true
325
2
INTRODUCTION
0
null
null
17,584,797
null
This manipulation is carried out by command-line or online programs written in the Perl programming language.
null
109
1,889
0
false
null
null
This manipulation is carried out by command-line or online programs written in the Perl programming language.
true
true
true
true
true
325
2
INTRODUCTION
0
null
null
17,584,797
null
Figure 1.Schematic demonstrating the principle of using molfile templates and a list of lipid abbreviations as input for structure-drawing tools.
null
145
1,890
0
false
null
null
Figure 1.Schematic demonstrating the principle of using molfile templates and a list of lipid abbreviations as input for structure-drawing tools.
true
true
true
true
true
325
3
INTRODUCTION
0
null
null
17,584,797
null
Schematic demonstrating the principle of using molfile templates and a list of lipid abbreviations as input for structure-drawing tools.
null
136
1,891
0
false
null
null
Schematic demonstrating the principle of using molfile templates and a list of lipid abbreviations as input for structure-drawing tools.
true
true
true
true
true
326
4
INTRODUCTION
0
null
null
17,584,797
null
The structural similarities of many lipid categories also make it feasible to predict structures from MS precursor ion and/or product ion data by creating a database composed of masses of all possible likely combinations of acyl side chains for a given lipid core.
null
264
1,892
0
false
null
null
The structural similarities of many lipid categories also make it feasible to predict structures from MS precursor ion and/or product ion data by creating a database composed of masses of all possible likely combinations of acyl side chains for a given lipid core.
true
true
true
true
true
327
4
INTRODUCTION
0
null
null
17,584,797
null
One can then use matching algorithms to display possible candidates for given precursor ion/product ion m/z values and then generate corresponding structures.
null
158
1,893
0
false
null
null
One can then use matching algorithms to display possible candidates for given precursor ion/product ion m/z values and then generate corresponding structures.
true
true
true
true
true
327
0
INTRODUCTION
1
1–5
[ "B1 B2 B3 B4 B5", "B6", "B7", "B8", "B9", "B10", "B11" ]
17,485,475
pmid-15993809|NA|pmid-11470599|pmid-15288245|pmid-11790605|NA|NA|NA|pmid-15667143|pmid-16845110|pmid-17170002
Drug discovery is a complex and expensive endeavor that has taken advantage of the recent years’ emergence of the ‘in silico’ biology.
[ "1–5", "6", "7", "8", "9", "10", "11" ]
134
1,894
0
false
Drug discovery is a complex and expensive endeavor that has taken advantage of the recent years’ emergence of the ‘in silico’ biology.
[]
Drug discovery is a complex and expensive endeavor that has taken advantage of the recent years’ emergence of the ‘in silico’ biology.
true
true
true
true
true
328
0
INTRODUCTION
1
1–5
[ "B1 B2 B3 B4 B5", "B6", "B7", "B8", "B9", "B10", "B11" ]
17,485,475
pmid-15993809|NA|pmid-11470599|pmid-15288245|pmid-11790605|NA|NA|NA|pmid-15667143|pmid-16845110|pmid-17170002
More specifically, virtual or in silico screening, based on the 3D structure of known ligands or of the targets is becoming a method of choice to facilitate lead compound identification, as seen in several recent studies [see for examples (1–5)].
[ "1–5", "6", "7", "8", "9", "10", "11" ]
246
1,895
0
false
More specifically, virtual or in silico screening, based on the 3D structure of known ligands or of the targets is becoming a method of choice to facilitate lead compound identification, as seen in several recent studies.
[ "see for examples (1–5)" ]
More specifically, virtual or in silico screening, based on the 3D structure of known ligands or of the targets is becoming a method of choice to facilitate lead compound identification, as seen in several recent studies.
true
true
true
true
true
328
0
INTRODUCTION
1
1–5
[ "B1 B2 B3 B4 B5", "B6", "B7", "B8", "B9", "B10", "B11" ]
17,485,475
pmid-15993809|NA|pmid-11470599|pmid-15288245|pmid-11790605|NA|NA|NA|pmid-15667143|pmid-16845110|pmid-17170002
In all situations, these in silico processes require a suitable compound collection as input.
[ "1–5", "6", "7", "8", "9", "10", "11" ]
93
1,896
0
false
In all situations, these in silico processes require a suitable compound collection as input.
[]
In all situations, these in silico processes require a suitable compound collection as input.
true
true
true
true
true
328
0
INTRODUCTION
1
1–5
[ "B1 B2 B3 B4 B5", "B6", "B7", "B8", "B9", "B10", "B11" ]
17,485,475
pmid-15993809|NA|pmid-11470599|pmid-15288245|pmid-11790605|NA|NA|NA|pmid-15667143|pmid-16845110|pmid-17170002
Usually, libraries have to be filtered (ADME/tox filtering) to remove compounds with unacceptable physico-chemical properties and disease-causing chemical functionalities.
[ "1–5", "6", "7", "8", "9", "10", "11" ]
171
1,897
0
false
Usually, libraries have to be filtered (ADME/tox filtering) to remove compounds with unacceptable physico-chemical properties and disease-causing chemical functionalities.
[]
Usually, libraries have to be filtered (ADME/tox filtering) to remove compounds with unacceptable physico-chemical properties and disease-causing chemical functionalities.
true
true
true
true
true
328
0
INTRODUCTION
1
6
[ "B1 B2 B3 B4 B5", "B6", "B7", "B8", "B9", "B10", "B11" ]
17,485,475
pmid-15993809|NA|pmid-11470599|pmid-15288245|pmid-11790605|NA|NA|NA|pmid-15667143|pmid-16845110|pmid-17170002
Then, the 3D structure of each compound has to be generated since, for the time being, academic or commercial compound collections are delivered in 1D SMILES (6) (simplified molecular input line entry system), CANSMILES (7) (canonical smiles) or in 2D SDF (8) (structure data file) formats.
[ "1–5", "6", "7", "8", "9", "10", "11" ]
290
1,898
1
false
Then, the 3D structure of each compound has to be generated since, for the time being, academic or commercial compound collections are delivered in 1D SMILES (simplified molecular input line entry system), CANSMILES (canonical smiles) or in 2D SDF (structure data file) formats.
[ "6", "7", "8" ]
Then, the 3D structure of each compound has to be generated since, for the time being, academic or commercial compound collections are delivered in 1D SMILES (simplified molecular input line entry system), CANSMILES (canonical smiles) or in 2D SDF (structure data file) formats.
true
true
true
true
true
328
0
INTRODUCTION
1
1–5
[ "B1 B2 B3 B4 B5", "B6", "B7", "B8", "B9", "B10", "B11" ]
17,485,475
pmid-15993809|NA|pmid-11470599|pmid-15288245|pmid-11790605|NA|NA|NA|pmid-15667143|pmid-16845110|pmid-17170002
In addition, for drug design programs that use rigid-body docking steps or for 3D ligand-based screening experiments, one single conformation per compound is not enough and one has to generate conformational isomers.
[ "1–5", "6", "7", "8", "9", "10", "11" ]
216
1,899
0
false
In addition, for drug design programs that use rigid-body docking steps or for 3D ligand-based screening experiments, one single conformation per compound is not enough and one has to generate conformational isomers.
[]
In addition, for drug design programs that use rigid-body docking steps or for 3D ligand-based screening experiments, one single conformation per compound is not enough and one has to generate conformational isomers.
true
true
true
true
true
328