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NMR processing:
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NMR assignment:
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Side-chains:
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NOEs:
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Structure from NMR restraints:
Ab initio:
GeNMR
Cyana
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Fragment-based:
BMRB CS-Rosetta
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Template-based:
GeNMR
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Refinement:
Amber
Structure from chemical shifts:
Fragment-based:
WeNMR CS-Rosetta
BMRB CS-Rosetta
Homology-based:
CS23D
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Torsion angles from chemical shifts:
Preditor
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Promega- Proline
Secondary structure from chemical shifts:
CSI (via RCI server)
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MICS caps, β-turns
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Flexibility from chemical shifts:
RCI
Interactions from chemical shifts:
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Chemical shifts re-referencing:
Shiftcor
UNIO Shiftinspector
LACS
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RefDB
NMR model quality:
NOEs, other restraints:
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RPF scores
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Chemical shifts:
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Vasco
iCing
RDCs:
DC
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Pseudocontact shifts:
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Protein geomtery:
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PROSESS
What-If
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PSVS
MolProbity
SAVES2 or SAVES4
Vadar
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ProQ
MetaMQAPII
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Eval123D
STAN
Ramachandran Plot
Rampage
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Verify_3D
Harmony
Quality Control Check
NMR spectrum prediction:
FANDAS
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V-NMR
Flexibility from structure:
Backbone S2
Methyl S2
B-factor
Molecular dynamics:
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Chemical shifts prediction:
From structure:
Shiftx2
Sparta+
Camshift
CH3shift- Methyl
ArShift- Aromatic
ShiftS
Proshift
PPM
CheShift-2- Cα
From sequence:
Shifty
Camcoil
Poulsen_rc_CS
Disordered proteins:
MAXOCC
Format conversion & validation:
CCPN
From NMR-STAR 3.1
Validate NMR-STAR 3.1
NMR sample preparation:
Protein disorder:
DisMeta
Protein solubility:
camLILA
ccSOL
Camfold
camGroEL
Zyggregator
Isotope labeling:
UPLABEL
Solid-state NMR:
sedNMR


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Unread 02-16-2011, 09:34 PM
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Default Re: problems in linear prediction for both indirect diemnsions in CC

Re: problems in linear prediction for both indirect diemnsions in CC

Ok, just as a check, be sure that an ordinary FT of your data looks good if you havent done this already. Inverse processing divides by the previously-applied

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