ArticlePLoS computational biology2009
Probabilistic interaction network of evidence algorithm and its application to complete labeling of peak lists from protein NMR spectroscopy.
Article in PLoS computational biology, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 130 papers.
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130 citing papers in PubMed.
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- Time-optimized protein NMR assignment with an integrative deep learning approach using AlphaFold and chemical shift prediction.Science advances · 2023Article
- Biological Magnetic Resonance Data Bank.Nucleic acids research · 2023Article
- The Ni(II)-Binding Activity of the Intrinsically Disordered Region of Human NDRG1, a Protein Involved in Cancer Development.Biomolecules · 2022Article
- ssPINE: Probabilistic Algorithm for Automated Chemical Shift Assignment of Solid-State NMR Data from Complex Protein Systems.Membranes · 2022Article
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- NMR Assignment through Linear Programming.Journal of global optimization : an international journal dealing with theoretical and computational aspects of seeking global optima and their applications in science, management and engineering · 2022Article
- Structural Investigations on the SH3b Domains ofMolecules (Basel, Switzerland) · 2021Article
- Structural basis of P[II] rotavirus evolution and host ranges under selection of histo-blood group antigens.Proceedings of the National Academy of Sciences of the United States of America · 2021Article
- Toho-1 β-lactamase: backbone chemical shift assignments and changes in dynamics upon binding with avibactam.Journal of biomolecular NMR · 2021Article
- A common binding motif in the ET domain of BRD3 forms polymorphic structural interfaces with host and viral proteins.Structure (London, England : 1993) · 2021Article
- An "up" oriented methionine-aromatic structural motif in SUMO is critical for its stability and activity.The Journal of biological chemistry · 2021Article
- Definition of the immune evasion-replication interface of rabies virus P protein.PLoS pathogens · 2021Article
- Evaluation of Multi-Objective Optimization Algorithms for NMR Chemical Shift Assignment.Molecules (Basel, Switzerland) · 2021Article
- Intrinsically Disordered Bacterial Polar Organizing Protein Z, PopZ, Interacts with Protein Binding Partners Through an N-terminal Molecular Recognition Feature.Journal of molecular biology · 2020Article
70 more citing papers are in PubMed but not listed here.
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4 authors.
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Abstract
The process of assigning a finite set of tags or labels to a collection of observations, subject to side conditions, is notable for its computational complexity. This labeling paradigm is of theoretical and practical relevance to a wide range of biological applications, including the analysis of data from DNA microarrays, metabolomics experiments, and biomolecular nuclear magnetic resonance (NMR) spectroscopy. We present a novel algorithm, called Probabilistic Interaction Network of Evidence (PINE), that achieves robust, unsupervised probabilistic labeling of data. The computational core of PINE uses estimates of evidence derived from empirical distributions of previously observed data, along with consistency measures, to drive a fictitious system M with Hamiltonian H to a quasi-stationary state that produces probabilistic label assignments for relevant subsets of the data. We demonstrate the successful application of PINE to a key task in protein NMR spectroscopy: that of converting peak lists extracted from various NMR experiments into assignments associated with probabilities for their correctness. This application, called PINE-NMR, is available from a freely accessible computer server (http://pine.nmrfam.wisc.edu). The PINE-NMR server 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.
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