Quantitative analysis of nucleic acid three-dimensional structures.

By Patrick Gendron, S. Lemieux, François Major. 2001

202 citations recorded by the source corpus.

Subfields: Materials Chemistry, Molecular Biology

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Materials Chemistry

In Molecular Biology

Citations in the corpus

An enumerative stepwise ansatz enables atomic-accuracy RNA loop modeling (2011, methodology): “For this analysis, extra-helical bulges were annotated by the program MC-annotate (24) (i.”
Automated 3D structure composition for large RNAs (2012, background): “The INF cbp and INF all parameter values (33,35) indicate that all canonical and non-canonical base pairing and stacking are well recovered in the predicted structures.”
FR3D: finding local and composite recurrent structural motifs in RNA 3D structures (2007, background): “Major and co–workers pioneered the combined geometric and symbolic approach to analyze RNA 3D structure [13,36].”
RNA-Puzzles: a CASP-like evaluation of RNA three-dimensional structure prediction. (2012, background): “In DMD simulations, the structural information of a given RNA, such as base pairs and distances between specific nucleotides, can be incorporated as constraints to guide RNA folding (Gherghe et al. 2009; Lavender et al. 2010).”
ClaRNA: a classifier of contacts in RNA 3D structures based on a comparative analysis of various classification schemes (2014, methodology): “The ModeRNA stacking detection algorithm uses a precise version of this criterion; however, the current versions of MC-Annotate (5) and FR3D (7) appear to use a more relaxed criteria, as we found that they report stacking for some other residue pairs (e.”
New metrics for comparing and assessing discrepancies between RNA 3D structures and models. (2009, methodology): “MC-Annotate also computes the base-stacking network (see Fig.”
New prediction categories in CASP15 (2023, unknown): “22 Further, we will work to improve measures comparing predictions to raw data to assess low-resolution targets.”
RNA-Puzzles toolkit: a computational resource of RNA 3D structure benchmark datasets, structure manipulation, and evaluation tools (2019, methodology): “The interactions of an RNA structure can be extracted by programs such as MC-Annotate (25) and 3DNA (64).”
iFoldRNA v2: folding RNA with constraints (2015, methodology): “Closer examination of the predicted structure using MC Annotate (Gendron et al., 2001) reveals that it has 39 out of 46 canonical base pairs (AU or CG) and 5 out of 6 non-canonical UG base pairs as compared to the crystal structure.”
Tools for the automatic identification and classification of RNA base pairs (2003, methodology): “The present set of programs is complementary to others (9,10) and the results of either can be used or compared using the RNAML files.”
Integrating end-to-end learning with deep geometrical potentials for ab initio RNA structure prediction (2022, unknown): “In Table S1, we summarize the base interaction network ﬁ delity (INF) 26,27 and deformation index (DI) 28 scores of the models generated by DRfold and the control methods, which were calculated using the RNA-Puzzles toolkit 29 In Table S2, we further list the mean of circular quantity (MCQ) 30 and H”