R value - Revision history

Eric Martz at 00:01, 10 September 2012

Eric Martz — Mon, 10 Sep 2012 00:01:09 GMT

←Older revision		Revision as of 00:01, 10 September 2012
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	As a rule of thumb, models with R values substantially exceeding (resolution/10) should be treated with caution. Thus, if the resolution of a model is 2.5 Å, that model's R value should not exceed 0.25. Completely erroneous models (e.g. random models) give R values of 0.40 to 0.60.		As a rule of thumb, models with R values substantially exceeding (resolution/10) should be treated with caution. Thus, if the resolution of a model is 2.5 Å, that model's R value should not exceed 0.25. Completely erroneous models (e.g. random models) give R values of 0.40 to 0.60.

-	However, R values themselves must be treated with caution. Unlike the [[Free R]], acceptable R values can be achieved despite serious errors in the model, as demonstrated unequivocally by Kleywegt & Brünger<ref>PMID: 8805582</ref>. In fact analysis has shown that this value is frequently underestimated so that a final model is not as good as it should be<ref name="Karplus">PMID: 22628654</ref><ref>PMID: 22628641</ref>. A different statistical value, CC*, has been proposed to assess model and data quality on the same scale and reveal data quality is limiting model improvement <ref name="Karplus" />.	+	However, R values themselves must be treated with caution. Unlike the [[Free R]], acceptable R values can be achieved despite serious errors in the model, as demonstrated unequivocally by Kleywegt & Brünger<ref>PMID: 8805582</ref>. In fact analysis has shown that this value is frequently underestimated so that a final model is not as good as it should be<ref name="Karplus">PMID: 22628654</ref><ref>PMID: 22628641</ref>. A different statistical value, CC*, has been proposed to assess model and data quality on the same scale and reveal when data quality is limiting model improvement <ref name="Karplus" />.

	One famous pitfall that can result in a misleading R value is the addition of substantially more than one water molecule per amino acid.		One famous pitfall that can result in a misleading R value is the addition of substantially more than one water molecule per amino acid.

Wayne Decatur at 17:02, 6 September 2012

Wayne Decatur — Thu, 06 Sep 2012 17:02:31 GMT

←Older revision		Revision as of 17:02, 6 September 2012
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	As a rule of thumb, models with R values substantially exceeding (resolution/10) should be treated with caution. Thus, if the resolution of a model is 2.5 Å, that model's R value should not exceed 0.25. Completely erroneous models (e.g. random models) give R values of 0.40 to 0.60.		As a rule of thumb, models with R values substantially exceeding (resolution/10) should be treated with caution. Thus, if the resolution of a model is 2.5 Å, that model's R value should not exceed 0.25. Completely erroneous models (e.g. random models) give R values of 0.40 to 0.60.

-	However, R values themselves must be treated with caution. Unlike the [[Free R]], acceptable R values can be achieved despite serious errors in the model, as demonstrated unequivocally by Kleywegt & Brünger<ref>PMID: 8805582</ref>. In fact analysis has shown that this value is frequently underestimated so that a final model is not as good as it should be<ref name='Karplus'>PMID: 22628654</ref><ref>PMID: 22628641</ref>. A different statistical value, CC*, has been proposed to assess model and data quality on the same scale and reveal data quality is limiting model improvement <ref name="Karplus />.	+	However, R values themselves must be treated with caution. Unlike the [[Free R]], acceptable R values can be achieved despite serious errors in the model, as demonstrated unequivocally by Kleywegt & Brünger<ref>PMID: 8805582</ref>. In fact analysis has shown that this value is frequently underestimated so that a final model is not as good as it should be<ref name="Karplus">PMID: 22628654</ref><ref>PMID: 22628641</ref>. A different statistical value, CC*, has been proposed to assess model and data quality on the same scale and reveal data quality is limiting model improvement <ref name="Karplus" />.

	One famous pitfall that can result in a misleading R value is the addition of substantially more than one water molecule per amino acid.		One famous pitfall that can result in a misleading R value is the addition of substantially more than one water molecule per amino acid.

Wayne Decatur at 17:02, 6 September 2012

Wayne Decatur — Thu, 06 Sep 2012 17:02:09 GMT

←Older revision		Revision as of 17:02, 6 September 2012
Line 3:		Line 3:
	As a rule of thumb, models with R values substantially exceeding (resolution/10) should be treated with caution. Thus, if the resolution of a model is 2.5 Å, that model's R value should not exceed 0.25. Completely erroneous models (e.g. random models) give R values of 0.40 to 0.60.		As a rule of thumb, models with R values substantially exceeding (resolution/10) should be treated with caution. Thus, if the resolution of a model is 2.5 Å, that model's R value should not exceed 0.25. Completely erroneous models (e.g. random models) give R values of 0.40 to 0.60.

-	However, R values themselves must be treated with caution. Unlike the [[Free R]], acceptable R values can be achieved despite serious errors in the model, as demonstrated unequivocally by Kleywegt & Brünger<ref>PMID: 8805582</ref>. In fact analysis has shown that this value is frequently underestimated so that a final model is not as good as it should be<ref>PMID: 22628654</ref><ref>PMID: 22628641</ref>. A different statistical value, CC*, has been proposed to assess model and data quality on the same scale and reveal data quality is limiting model improvement <ref~~>PMID: 22628654<~~/~~ref~~>.	+	However, R values themselves must be treated with caution. Unlike the [[Free R]], acceptable R values can be achieved despite serious errors in the model, as demonstrated unequivocally by Kleywegt & Brünger<ref>PMID: 8805582</ref>. In fact analysis has shown that this value is frequently underestimated so that a final model is not as good as it should be<ref name='Karplus'>PMID: 22628654</ref><ref>PMID: 22628641</ref>. A different statistical value, CC*, has been proposed to assess model and data quality on the same scale and reveal data quality is limiting model improvement <ref name="Karplus />.

	One famous pitfall that can result in a misleading R value is the addition of substantially more than one water molecule per amino acid.		One famous pitfall that can result in a misleading R value is the addition of substantially more than one water molecule per amino acid.

Wayne Decatur at 16:57, 6 September 2012

Wayne Decatur — Thu, 06 Sep 2012 16:57:57 GMT

←Older revision		Revision as of 16:57, 6 September 2012
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	As a rule of thumb, models with R values substantially exceeding (resolution/10) should be treated with caution. Thus, if the resolution of a model is 2.5 Å, that model's R value should not exceed 0.25. Completely erroneous models (e.g. random models) give R values of 0.40 to 0.60.		As a rule of thumb, models with R values substantially exceeding (resolution/10) should be treated with caution. Thus, if the resolution of a model is 2.5 Å, that model's R value should not exceed 0.25. Completely erroneous models (e.g. random models) give R values of 0.40 to 0.60.

-	However, R values themselves must be treated with caution. Unlike the [[Free R]], acceptable R values can be achieved despite serious errors in the model, as demonstrated unequivocally by Kleywegt & Brünger<ref>~~Kleywegt, GJ, AT Brünger~~. ~~1996. Checking your imagination: applications of the free R~~ value~~. Structure 4~~:~~897-904. [http~~:/~~/www.ncbi.nlm.nih.gov/pubmed/8805582 PubMed]~~.</ref>.	+	However, R values themselves must be treated with caution. Unlike the [[Free R]], acceptable R values can be achieved despite serious errors in the model, as demonstrated unequivocally by Kleywegt & Brünger<ref>PMID: 8805582</ref>. In fact analysis has shown that this value is frequently underestimated so that a final model is not as good as it should be<ref>PMID: 22628654</ref><ref>PMID: 22628641</ref>. A different statistical value, CC*, has been proposed to assess model and data quality on the same scale and reveal data quality is limiting model improvement <ref>PMID: 22628654</ref>.

	One famous pitfall that can result in a misleading R value is the addition of substantially more than one water molecule per amino acid.		One famous pitfall that can result in a misleading R value is the addition of substantially more than one water molecule per amino acid.
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	*[[Resolution]]		*[[Resolution]]
	*[[Temperature value]]		*[[Temperature value]]
		+	[[CC]]
	*[[Quality assessment for molecular models]]		*[[Quality assessment for molecular models]]

Eric Martz: adding content

Eric Martz — Thu, 26 Jun 2008 23:41:12 GMT

adding content

←Older revision		Revision as of 23:41, 26 June 2008
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-	The R value is used to assess progress in the refinement of a model from X-ray crystallographic data, and can be used as one factor in evaluating the quality of a model. R is a measure of error between the observed intensities from the diffraction pattern and the predicted intensities that are calculated from the model. R values of 0.20 or less are taken as evidence that the model is reliable.	+	The R value is used to assess progress in the refinement of a model from X-ray crystallographic data, and can be used as one factor in [[Quality assessment for molecular models\|evaluating the quality of a model]]. R is a measure of error between the observed intensities from the diffraction pattern and the predicted intensities that are calculated from the model. R values of 0.20 or less are taken as evidence that the model is reliable.

	As a rule of thumb, models with R values substantially exceeding (resolution/10) should be treated with caution. Thus, if the resolution of a model is 2.5 Å, that model's R value should not exceed 0.25. Completely erroneous models (e.g. random models) give R values of 0.40 to 0.60.		As a rule of thumb, models with R values substantially exceeding (resolution/10) should be treated with caution. Thus, if the resolution of a model is 2.5 Å, that model's R value should not exceed 0.25. Completely erroneous models (e.g. random models) give R values of 0.40 to 0.60.
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	One famous pitfall that can result in a misleading R value is the addition of substantially more than one water molecule per amino acid.		One famous pitfall that can result in a misleading R value is the addition of substantially more than one water molecule per amino acid.
		+
		+	==See Also==
		+
		+	*[[Free R]]
		+	*[[Resolution]]
		+	*[[Temperature value]]
		+	*[[Quality assessment for molecular models]]

	==Content Donors==		==Content Donors==

Eric Martz: polishing

Eric Martz — Thu, 26 Jun 2008 23:39:18 GMT

polishing

←Older revision		Revision as of 23:39, 26 June 2008
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-	The R value is used to assess progress in the refinement of a model from X-ray crystallographic data, and can be used as one factor in evaluating the quality of a model<ref>Laskowski, Roman A. 2003. Structural quality assurance. Chapter 14 in ''Structural Bioinformatics'' (2003) edited by Philip E. Bourne and Helge Weissig, Wiley-Liss, 649 pages. Complete contents at [http://www.structuralbioinformaticsbook.com structuralbioinformaticsbook.com].</ref><ref>Kleywegt, GJ. 2000. Validation of protein crystal structures. Acta. Crystallogr. D. Biol. Crystallogr. 56:249-265</ref>. R is a measure of error between the observed intensities from the diffraction pattern and the predicted intensities that are calculated from the model. R values of 0.20 or less are taken as evidence that the model is reliable.	+	The R value is used to assess progress in the refinement of a model from X-ray crystallographic data, and can be used as one factor in evaluating the quality of a model. R is a measure of error between the observed intensities from the diffraction pattern and the predicted intensities that are calculated from the model. R values of 0.20 or less are taken as evidence that the model is reliable.

	As a rule of thumb, models with R values substantially exceeding (resolution/10) should be treated with caution. Thus, if the resolution of a model is 2.5 Å, that model's R value should not exceed 0.25. Completely erroneous models (e.g. random models) give R values of 0.40 to 0.60.		As a rule of thumb, models with R values substantially exceeding (resolution/10) should be treated with caution. Thus, if the resolution of a model is 2.5 Å, that model's R value should not exceed 0.25. Completely erroneous models (e.g. random models) give R values of 0.40 to 0.60.

-	However, R values themselves must be treated with caution. Unlike the [[Free R]], acceptable R values can be achieved despite serious errors in the model, as demonstrated unequivocally by Kleywegt & Brünger<ref>Kleywegt, GJ, AT Brünger. 1996. Checking your imagination: applications of the free R value. Structure 4:897-904. [http://www.ncbi.nlm.nih.gov/pubmed/8805582 PubMed]</ref>.	+	However, R values themselves must be treated with caution. Unlike the [[Free R]], acceptable R values can be achieved despite serious errors in the model, as demonstrated unequivocally by Kleywegt & Brünger<ref>Kleywegt, GJ, AT Brünger. 1996. Checking your imagination: applications of the free R value. Structure 4:897-904. [http://www.ncbi.nlm.nih.gov/pubmed/8805582 PubMed].</ref>.

	One famous pitfall that can result in a misleading R value is the addition of substantially more than one water molecule per amino acid.		One famous pitfall that can result in a misleading R value is the addition of substantially more than one water molecule per amino acid.
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	==Content Donors==		==Content Donors==

-	~~This~~ page ~~was~~ adapted from the [http://proteinexplorer.org/igloss.htm Glossary of ProteinExplorer.Org], with the permission of the principal author, [[User:Eric Martz\|Eric Martz]].	+	Portions of this page were adapted from the [http://proteinexplorer.org/igloss.htm Glossary of ProteinExplorer.Org], with the permission of the principal author, [[User:Eric Martz\|Eric Martz]].

	==Literature==		==Literature==

	<references />		<references />

Eric Martz: polishing

Eric Martz — Thu, 26 Jun 2008 23:29:17 GMT

polishing

←Older revision		Revision as of 23:29, 26 June 2008
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	One famous pitfall that can result in a misleading R value is the addition of substantially more than one water molecule per amino acid.		One famous pitfall that can result in a misleading R value is the addition of substantially more than one water molecule per amino acid.
-
-	Laskowski

	==Content Donors==		==Content Donors==

Eric Martz: adding content

Eric Martz — Thu, 26 Jun 2008 22:53:46 GMT

adding content

←Older revision		Revision as of 22:53, 26 June 2008
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-	The R value is used to assess progress in the refinement of a model from X-ray crystallographic data, and can be used as one factor in evaluating the quality of a model<ref>Laskowski, Roman A. 2003. Structural quality assurance. Chapter 14 in ''Structural Bioinformatics'' (2003) edited by Philip E. Bourne and Helge Weissig, Wiley-Liss, 649 pages. Complete contents at [http://www.structuralbioinformaticsbook.com structuralbioinformaticsbook.com].</ref>. R is a measure of error between the observed intensities from the diffraction pattern and the predicted intensities that are calculated from the model. R values of 0.20 or less are taken as evidence that the model is reliable.	+	The R value is used to assess progress in the refinement of a model from X-ray crystallographic data, and can be used as one factor in evaluating the quality of a model<ref>Laskowski, Roman A. 2003. Structural quality assurance. Chapter 14 in ''Structural Bioinformatics'' (2003) edited by Philip E. Bourne and Helge Weissig, Wiley-Liss, 649 pages. Complete contents at [http://www.structuralbioinformaticsbook.com structuralbioinformaticsbook.com].</ref><ref>Kleywegt, GJ. 2000. Validation of protein crystal structures. Acta. Crystallogr. D. Biol. Crystallogr. 56:249-265</ref>. R is a measure of error between the observed intensities from the diffraction pattern and the predicted intensities that are calculated from the model. R values of 0.20 or less are taken as evidence that the model is reliable.

	As a rule of thumb, models with R values substantially exceeding (resolution/10) should be treated with caution. Thus, if the resolution of a model is 2.5 Å, that model's R value should not exceed 0.25. Completely erroneous models (e.g. random models) give R values of 0.40 to 0.60.		As a rule of thumb, models with R values substantially exceeding (resolution/10) should be treated with caution. Thus, if the resolution of a model is 2.5 Å, that model's R value should not exceed 0.25. Completely erroneous models (e.g. random models) give R values of 0.40 to 0.60.

Eric Martz: /* Content Donors */ polishing

Eric Martz — Thu, 26 Jun 2008 22:48:24 GMT

Content Donors - polishing

←Older revision		Revision as of 22:48, 26 June 2008
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	==Content Donors==		==Content Donors==

-	This page was adapted from the [http://proteinexplorer.org/igloss.htm Glossary of ProteinExplorer.Org], with the permission of the principal author, [[Eric Martz]].	+	This page was adapted from the [http://proteinexplorer.org/igloss.htm Glossary of ProteinExplorer.Org], with the permission of the principal author, [[User:Eric Martz\|Eric Martz]].

	==Literature==		==Literature==

	<references />		<references />

Eric Martz: created

Eric Martz — Thu, 26 Jun 2008 22:46:01 GMT

created

New page

The R value is used to assess progress in the refinement of a model from X-ray crystallographic data, and can be used as one factor in evaluating the quality of a model<ref>Laskowski, Roman A. 2003. Structural quality assurance. Chapter 14 in ''Structural Bioinformatics'' (2003) edited by Philip E. Bourne and Helge Weissig, Wiley-Liss, 649 pages. Complete contents at [http://www.structuralbioinformaticsbook.com structuralbioinformaticsbook.com].</ref>. R is a measure of error between the observed intensities from the diffraction pattern and the predicted intensities that are calculated from the model. R values of 0.20 or less are taken as evidence that the model is reliable.

As a rule of thumb, models with R values substantially exceeding (resolution/10) should be treated with caution. Thus, if the resolution of a model is 2.5 Å, that model's R value should not exceed 0.25. Completely erroneous models (e.g. random models) give R values of 0.40 to 0.60.

However, R values themselves must be treated with caution. Unlike the [[Free R]], acceptable R values can be achieved despite serious errors in the model, as demonstrated unequivocally by Kleywegt & Brünger<ref>Kleywegt, GJ, AT Brünger. 1996. Checking your imagination: applications of the free R value. Structure 4:897-904. [http://www.ncbi.nlm.nih.gov/pubmed/8805582 PubMed]</ref>.

One famous pitfall that can result in a misleading R value is the addition of substantially more than one water molecule per amino acid.

Laskowski

==Content Donors==

This page was adapted from the [http://proteinexplorer.org/igloss.htm Glossary of ProteinExplorer.Org], with the permission of the principal author, [[Eric Martz]].

==Literature==

<references />