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A constraint-based expert system for automating the analysis of backbone resonance assignments using triple resonance NMR spectra of small proteins. The AutoAssign web interface can submit jobs to the AutoAssign server. It can also submit jobs to PINE, another automated resonance assignment web server. The AutoAssign interface will immediately show the results from the AutoAssign server. Once the PINE results are available by e-mail, the user can also upload them into the AutoAssign web interface. The AutoAssign web interface will then show an interactive comparison chart where the user can easily find different resonance assignments between the two programs. This comparison chart can generally guide the user for further investigation of resonances assigned differently by the AutoAssign and PINE web servers. The resonances assigned by both programs generally have higher accuracy confidences.

NMR Constraints Analyser

Analyses the constraint distribution of biological molecules solved by nuclear magnetic resonance (NMR) spectroscopy. NMR Constraints Analyser is a webserver aimed at an automatic graphical analysis of the NMR experimental constraints distribution on biological macromolecules, including the analysis of the violated constraints and the distinction between ambiguous/non-ambiguous restraints. The web app performs a rapid analysis of the NMR experimental constraints from which the 3D structure of the biological macromolecule was determined.


Aids the process of protein resonance assignment in the field of Nuclear magnetic resonance (NMR). NvAssign is a software module written for use with NMRView. It provides a flexible interface to cluster data and interact with the existing assignment algorithms. Further, this software module is able to read the results of other algorithms so that the data can be easily verified by spectral analysis. This package is likely to be extremely useful as a verification tool for any of the various proteomics initiatives.


Analyses nuclear magnetic resonance (NMR) spectra from a multitude of spectrometers and scanners, ranging from 1 to 3 dimensions. iNMR can read foreign spectra directly, it does not translate them into another format. For each spectrum, iNMR interprets the native data and applies the necessary processing. This tool is able to (i) insert a chemical formula and other information into a spectra, (ii) generate ready to publish lists of chemical shifts and coupling constants, (iii) simulate 1-dimension of ½ spins including phenomena of chemical exchange, (iv) write scripts to add custom functions, (v) process hundreds of spectra with a single command, (vi) export data as ASCII tables or in widely recognized formats, and (vii) combine several spectra into a single picture or poster.


Accepts as input the sequence of the protein plus user-specified combinations of data corresponding to an extensive list of NMR experiments; it provides as output a probabilistic assignment of NMR signals (chemical shifts) to sequence-specific backbone and aliphatic side chain atoms plus a probabilistic determination of the protein secondary structure. PINE-NMR can accommodate prior information about assignments or stable isotope labeling schemes. As part of the analysis, PINE-NMR identifies, verifies, and rectifies problems related to chemical shift referencing or erroneous input data. PINE-NMR achieves robust and consistent results that have been shown to be effective in subsequent steps of NMR structure determination.

LACS / Linear Analysis of Chemical Shifts

Detects referencing errors and to recalibrate the 1H and 13C chemical shift scales if needed. The analysis requires only that the signals be identified with distinct residue types (intra-residue spin systems). LACS allows errors in calibration to be detected and corrected in advance of sequence-specific assignments and secondary structure determinations. Signals that do not fit the linear model (outliers) deserve scrutiny since they could represent errors in identifying signals with a particular residue, or interesting features such as a cis-peptide bond. LACS provides the basis for the automated detection of such features and for testing reassignment hypotheses. Early detection and correction of errors in referencing and spin system identifications can improve the speed and accuracy of chemical shift assignments and secondary structure determinations. The input format is NMRSTAR 2.1 (BMRB) format, and. the result will be returned via email in a couple of minutes.