Advances in RNA secondary structure prediction and RNA modifications: Methods, data, and applications | Paper Citation Record

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This paper cites Probing the dynamic RNA structurome and its functions.

Advances in RNA secondary structure prediction and RNA modifications: Methods, data, and applications Probing the dynamic RNA structurome and its functions

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This paper cites Rock, scissors, paper: How RNA structure informs function.

Advances in RNA secondary structure prediction and RNA modifications: Methods, data, and applications Rock, scissors, paper: How RNA structure informs function

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Advances in RNA secondary structure prediction and RNA modifications: Methods, data, and applications The roles of structural dynamics in the cellular functions of RNAs

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This paper cites Riboswitches: small-molecule recognition by gene regulatory RNAs.

Advances in RNA secondary structure prediction and RNA modifications: Methods, data, and applications Riboswitches: small-molecule recognition by gene regulatory RNAs

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Advances in RNA secondary structure prediction and RNA modifications: Methods, data, and applications Non-coding RNA: a new frontier in regulatory biology

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This paper cites RNA-targeted therapeutics.

Advances in RNA secondary structure prediction and RNA modifications: Methods, data, and applications RNA-targeted therapeutics

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This paper cites RNA structure and stability.

Advances in RNA secondary structure prediction and RNA modifications: Methods, data, and applications RNA structure and stability

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This paper cites How RNA folds.

Advances in RNA secondary structure prediction and RNA modifications: Methods, data, and applications How RNA folds

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Advances in RNA secondary structure prediction and RNA modifications: Methods, data, and applications RNA quaternary structure and global symmetry

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This paper cites Folding and finding RNA secondary structure.

Advances in RNA secondary structure prediction and RNA modifications: Methods, data, and applications Folding and finding RNA secondary structure

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This paper cites Highly accurate protein structure prediction with AlphaFold.

Advances in RNA secondary structure prediction and RNA modifications: Methods, data, and applications Highly accurate protein structure prediction with AlphaFold

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This paper cites RNA secondary structure prediction using an ensemble of two-dimensional deep neural networks and transfer learning.

Advances in RNA secondary structure prediction and RNA modifications: Methods, data, and applications RNA secondary structure prediction using an ensemble of two-dimensional deep neural networks and transfer learning

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This paper cites UFold: fast and accurate RNA secondary structure prediction with deep learning.

Advances in RNA secondary structure prediction and RNA modifications: Methods, data, and applications UFold: fast and accurate RNA secondary structure prediction with deep learning

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This paper cites Interpretable RNA foundation model from unannotated data for highly accurate RNA structure and function predictions.

Advances in RNA secondary structure prediction and RNA modifications: Methods, data, and applications Interpretable RNA foundation model from unannotated data for highly accurate RNA structure and function predictions

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This paper cites Messenger RNA modifications: form, distribution, and function.

Advances in RNA secondary structure prediction and RNA modifications: Methods, data, and applications Messenger RNA modifications: form, distribution, and function

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This paper cites RNA modifications in structure prediction–Status quo and future challenges.

Advances in RNA secondary structure prediction and RNA modifications: Methods, data, and applications RNA modifications in structure prediction–Status quo and future challenges

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This paper cites MODOMICS: a database of RNA modifications and related information.

Advances in RNA secondary structure prediction and RNA modifications: Methods, data, and applications MODOMICS: a database of RNA modifications and related information

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This paper cites Secondary structure prediction for RNA sequences including N6-methyladenosine.

Advances in RNA secondary structure prediction and RNA modifications: Methods, data, and applications Secondary structure prediction for RNA sequences including N6-methyladenosine

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This paper cites RNA modifications and structures cooperate to guide RNA–protein interactions.

Advances in RNA secondary structure prediction and RNA modifications: Methods, data, and applications RNA modifications and structures cooperate to guide RNA–protein interactions

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This paper cites The emerging role of RNA modifications in the regulation of mRNA stability.

Advances in RNA secondary structure prediction and RNA modifications: Methods, data, and applications The emerging role of RNA modifications in the regulation of mRNA stability

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This paper cites Dynamic regulation and functions of mRNA m6A modification.

Advances in RNA secondary structure prediction and RNA modifications: Methods, data, and applications Dynamic regulation and functions of mRNA m6A modification

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This paper cites RNA modifications: importance in immune cell biology and related diseases.

Advances in RNA secondary structure prediction and RNA modifications: Methods, data, and applications RNA modifications: importance in immune cell biology and related diseases

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This paper cites RNA modifications in cellular metabolism: implications for metabolism-targeted therapy and immunotherapy.

Advances in RNA secondary structure prediction and RNA modifications: Methods, data, and applications RNA modifications in cellular metabolism: implications for metabolism-targeted therapy and immunotherapy

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Advances in RNA secondary structure prediction and RNA modifications: Methods, data, and applications RNA modifications: an overview of select web-based tools

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Advances in RNA secondary structure prediction and RNA modifications: Methods, data, and applications Attention-based multi-label neural networks for integrated prediction and interpretation of twelve widely occurring RNA modifications

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Advances in RNA secondary structure prediction and RNA modifications: Methods, data, and applications Towards retraining-free RNA modification prediction with incremental learning

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Advances in RNA secondary structure prediction and RNA modifications: Methods, data, and applications TransRNAm: identifying twelve types of RNA modifications by an interpretable multi-label deep learning model based on Transformer

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Advances in RNA secondary structure prediction and RNA modifications: Methods, data, and applications RMBase v3

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Advances in RNA secondary structure prediction and RNA modifications: Methods, data, and applications m7GHub V2

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Advances in RNA secondary structure prediction and RNA modifications: Methods, data, and applications H2Opred: a robust and efficient hybrid deep learning model for predicting 2’-O-methylation sites in human RNA

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Advances in RNA secondary structure prediction and RNA modifications: Methods, data, and applications Meta-2OM: a multi-classifier meta-model for the accurate prediction of RNA 2’-O-methylation sites in human RNA

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Advances in RNA secondary structure prediction and RNA modifications: Methods, data, and applications Nmix: a hybrid deep learning model for precise prediction of 2’-O-methylation sites based on multi-feature fusion and ensemble learning

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Advances in RNA secondary structure prediction and RNA modifications: Methods, data, and applications ac4C-AFL: A high-precision identification of human mRNA N4-acetylcytidine sites based on adaptive feature representation learning

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Advances in RNA secondary structure prediction and RNA modifications: Methods, data, and applications V oting-ac4C: Pre-trained large RNA language model enhances RNA N4- acetylcytidine site prediction

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Advances in RNA secondary structure prediction and RNA modifications: Methods, data, and applications iRNA-ac4C: a novel computational method for effectively detecting N4-acetylcytidine sites in human mRNA

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Advances in RNA secondary structure prediction and RNA modifications: Methods, data, and applications TransAC4C—a novel interpretable architecture for multi-species identification of N4- acetylcytidine sites in RNA with single-base resolution

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Advances in RNA secondary structure prediction and RNA modifications: Methods, data, and applications Deepm5C: a deep-learning-based hybrid framework for identifying human RNA N5-methylcytosine sites using a stacking strategy

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Advances in RNA secondary structure prediction and RNA modifications: Methods, data, and applications MLm5C: A high-precision human RNA 5-methylcytosine sites predictor based on a combination of hybrid machine learning models

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Advances in RNA secondary structure prediction and RNA modifications: Methods, data, and applications XGBoost framework with feature selection for the prediction of RNA N5-methylcytosine sites

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Advances in RNA secondary structure prediction and RNA modifications: Methods, data, and applications MST-m6A: A Novel Multi-Scale Transformer-based Framework for Accurate Prediction of m6A Modification Sites Across Diverse Cellular Contexts

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Advances in RNA secondary structure prediction and RNA modifications: Methods, data, and applications BLAM6A-Merge: Leveraging Attention Mechanisms and Feature Fusion Strategies to Improve the Identification of RNA N6-methyladenosine Sites

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Advances in RNA secondary structure prediction and RNA modifications: Methods, data, and applications Moss-m7G: A Motif-Based Interpretable Deep Learning Method for RNA N7- Methlguanosine Site Prediction

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Advances in RNA secondary structure prediction and RNA modifications: Methods, data, and applications THRONE: a new approach for accurate prediction of human RNA N7-methylguanosine sites

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Advances in RNA secondary structure prediction and RNA modifications: Methods, data, and applications Secondary structure prediction of long noncoding RNA: review and experimental comparison of existing approaches

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Advances in RNA secondary structure prediction and RNA modifications: Methods, data, and applications Recent trends in RNA informatics: a review of machine learning and deep learning for RNA secondary structure prediction and RNA drug discovery

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Advances in RNA secondary structure prediction and RNA modifications: Methods, data, and applications When will RNA get its AlphaFold moment? Nucleic Acids Research

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Advances in RNA secondary structure prediction and RNA modifications: Methods, data, and applications Machine learning modeling of RNA structures: methods, challenges and future perspectives

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Advances in RNA secondary structure prediction and RNA modifications: Methods, data, and applications Advances and opportunities in RNA structure experimental determination and computational modeling

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Advances in RNA secondary structure prediction and RNA modifications: Methods, data, and applications Forna (force-directed RNA): Simple and effective online RNA secondary structure diagrams

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Advances in RNA secondary structure prediction and RNA modifications: Methods, data, and applications Fast algorithm for predicting the secondary structure of single-stranded RNA

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Advances in RNA secondary structure prediction and RNA modifications: Methods, data, and applications Incorporating chemical modification constraints into a dynamic programming algorithm for prediction of RNA secondary structure

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Advances in RNA secondary structure prediction and RNA modifications: Methods, data, and applications Optical melting measurements of nucleic acid thermodynamics

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Advances in RNA secondary structure prediction and RNA modifications: Methods, data, and applications NNDB: the nearest neighbor parameter database for predicting stability of nucleic acid secondary structure

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Advances in RNA secondary structure prediction and RNA modifications: Methods, data, and applications Optimal computer folding of large RNA sequences using thermodynamics and auxiliary information

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Advances in RNA secondary structure prediction and RNA modifications: Methods, data, and applications Computational biology of RNA interactions

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Advances in RNA secondary structure prediction and RNA modifications: Methods, data, and applications ViennaRNA Package 2.0

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Advances in RNA secondary structure prediction and RNA modifications: Methods, data, and applications A dynamic programming algorithm for RNA structure prediction including pseudoknots

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Advances in RNA secondary structure prediction and RNA modifications: Methods, data, and applications Expanded sequence dependence of thermodynamic parameters provides improved prediction of RNA secondary structure

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This paper cites Biopolymers: Original Research on Biomolecules.

Advances in RNA secondary structure prediction and RNA modifications: Methods, data, and applications Biopolymers: Original Research on Biomolecules

Reference 59

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This paper cites RNAstructure: software for RNA secondary structure prediction and analysis.

Advances in RNA secondary structure prediction and RNA modifications: Methods, data, and applications RNAstructure: software for RNA secondary structure prediction and analysis

Reference 60

Resolution: unresolved; no resolver link, observed 2026-08-10T21:56:19.139949Z

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This paper cites RNA Secondary Structure Analysis Using RNAstructure.

Advances in RNA secondary structure prediction and RNA modifications: Methods, data, and applications RNA Secondary Structure Analysis Using RNAstructure

Reference 61

Resolution: unresolved; no resolver link, observed 2026-08-10T21:56:19.143603Z

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This paper cites Thermodynamic parameters for an expanded nearest-neighbor model for formation of RNA duplexes with Watson- Crick base pairs.

Advances in RNA secondary structure prediction and RNA modifications: Methods, data, and applications Thermodynamic parameters for an expanded nearest-neighbor model for formation of RNA duplexes with Watson- Crick base pairs

Reference 62

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This paper cites A set of nearest neighbor parameters for predicting the enthalpy change of RNA secondary structure formation.

Advances in RNA secondary structure prediction and RNA modifications: Methods, data, and applications A set of nearest neighbor parameters for predicting the enthalpy change of RNA secondary structure formation

Reference 63

Resolution: unresolved; no resolver link, observed 2026-08-10T21:56:19.151117Z

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Observation bb8d454c-b541-4b43-b838-51213dd3626e · outbound

This paper cites A range of complex probabilistic models for RNA secondary structure prediction that include the nearest neighbor model and more.

Advances in RNA secondary structure prediction and RNA modifications: Methods, data, and applications A range of complex probabilistic models for RNA secondary structure prediction that include the nearest neighbor model and more

Reference 64

Resolution: unresolved; no resolver link, observed 2026-08-10T21:56:19.154691Z

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This paper cites LinearFold: linear-time approximate RNA folding by 5’-to-3’dynamic programming and beam search.

Advances in RNA secondary structure prediction and RNA modifications: Methods, data, and applications LinearFold: linear-time approximate RNA folding by 5’-to-3’dynamic programming and beam search

Reference 65

Resolution: unresolved; no resolver link, observed 2026-08-10T21:56:19.158530Z

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This paper cites Algorithms for predicting the secondary structure of pairs and combinatorial sets of nucleic acid strands.

Advances in RNA secondary structure prediction and RNA modifications: Methods, data, and applications Algorithms for predicting the secondary structure of pairs and combinatorial sets of nucleic acid strands

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:56:20.412814Z

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Observation 4021ffdb-fd71-4ea0-884d-21afb3ddb8f7 · outbound

This paper cites Efficient parameter estimation for RNA secondary structure prediction.

Advances in RNA secondary structure prediction and RNA modifications: Methods, data, and applications Efficient parameter estimation for RNA secondary structure prediction

Reference 67

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:56:20.400177Z

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Observation 55590e58-f7c6-44a7-ab4a-71072c79dd0a · outbound

This paper cites PPfold 3.0: fast RNA secondary structure prediction using phylogeny and auxiliary data.

Advances in RNA secondary structure prediction and RNA modifications: Methods, data, and applications PPfold 3.0: fast RNA secondary structure prediction using phylogeny and auxiliary data

Reference 68

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:56:20.386543Z

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Observation 2a6e3837-5fec-44e8-b939-8716f5bf0f36 · outbound

This paper cites Multithreaded comparative RNA secondary structure prediction using stochastic context-free grammars.

Advances in RNA secondary structure prediction and RNA modifications: Methods, data, and applications Multithreaded comparative RNA secondary structure prediction using stochastic context-free grammars

Reference 69

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:56:20.373749Z

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Observation f9af0baf-074c-49bc-9a60-115e6943ec75 · outbound

This paper cites A comparative method for finding and folding RNA secondary structures within protein-coding regions.

Advances in RNA secondary structure prediction and RNA modifications: Methods, data, and applications A comparative method for finding and folding RNA secondary structures within protein-coding regions

Reference 70

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:56:20.360959Z

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Observation 564a085d-7f53-4128-aaf7-258c55effccb · outbound

This paper cites An evolutionary model for protein-coding regions with conserved RNA structure.

Advances in RNA secondary structure prediction and RNA modifications: Methods, data, and applications An evolutionary model for protein-coding regions with conserved RNA structure

Reference 71

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:56:20.349800Z

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Observation 5334de5c-93a8-4716-a81f-a91781622de5 · outbound

This paper cites RNA secondary structure prediction with convolutional neural networks.

Advances in RNA secondary structure prediction and RNA modifications: Methods, data, and applications RNA secondary structure prediction with convolutional neural networks

Reference 72

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:56:20.337809Z

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Observation c8eb54e8-cfb6-4726-b1b5-50862a239c28 · outbound

This paper cites CONTRAfold: RNA secondary structure prediction without physics-based models.

Advances in RNA secondary structure prediction and RNA modifications: Methods, data, and applications CONTRAfold: RNA secondary structure prediction without physics-based models

Reference 73

Resolution: verified exact; doi, observed 2026-08-10T21:56:19.497722Z

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Observation 2aa8c03e-28ae-4d44-b8c3-7bd3aac2283f · outbound

This paper cites RNA Secondary Structure Prediction By Learning Unrolled Algorithms.

Advances in RNA secondary structure prediction and RNA modifications: Methods, data, and applications RNA Secondary Structure Prediction By Learning Unrolled Algorithms

Reference 74

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:56:20.325949Z

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Observation 5a298162-e58e-4718-b496-c5fd39060f51 · outbound

This paper cites REDfold: accurate RNA secondary structure prediction using residual encoder-decoder network.

Advances in RNA secondary structure prediction and RNA modifications: Methods, data, and applications REDfold: accurate RNA secondary structure prediction using residual encoder-decoder network

Reference 75

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:56:20.314652Z

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No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 00e81ebe-a0c0-4b41-8484-edc015b53b17 · outbound

This paper cites Improved RNA secondary structure and tertiary base-pairing prediction using evolutionary profile, mutational coupling and two-dimensional transfer learning.

Advances in RNA secondary structure prediction and RNA modifications: Methods, data, and applications Improved RNA secondary structure and tertiary base-pairing prediction using evolutionary profile, mutational coupling and two-dimensional transfer learning

Reference 76

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:56:20.302366Z

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Observation 836b9222-c12e-4a72-8692-bf7a30893b9e · outbound

This paper cites A max-margin training of RNA secondary structure prediction integrated with the thermodynamic model.

Advances in RNA secondary structure prediction and RNA modifications: Methods, data, and applications A max-margin training of RNA secondary structure prediction integrated with the thermodynamic model

Reference 77

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:56:20.290800Z

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Observation 182b896b-870f-4fbb-b6a4-0994f1e301ef · outbound

This paper cites RNA secondary structure prediction using deep learning with thermodynamic integration.

Advances in RNA secondary structure prediction and RNA modifications: Methods, data, and applications RNA secondary structure prediction using deep learning with thermodynamic integration

Reference 78

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:56:20.279581Z

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Observation 3a5f57c6-f232-446b-852b-ae24029d4223 · outbound

This paper cites RNAalifold: improved consensus structure prediction for RNA alignments.

Advances in RNA secondary structure prediction and RNA modifications: Methods, data, and applications RNAalifold: improved consensus structure prediction for RNA alignments

Reference 79

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:56:20.267763Z

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Observation 86b6a002-19d7-4014-9bf6-d17e72fbf860 · outbound

This paper cites CENTROIDFOLD: a web server for RNA secondary structure prediction.

Advances in RNA secondary structure prediction and RNA modifications: Methods, data, and applications CENTROIDFOLD: a web server for RNA secondary structure prediction

Reference 80

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:56:20.256515Z

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Observation b88e5af4-acee-42b7-bbc6-48c26acb82a3 · outbound

This paper cites Multi-purpose RNA language modelling with motif-aware pretraining and type-guided fine-tuning.

Advances in RNA secondary structure prediction and RNA modifications: Methods, data, and applications Multi-purpose RNA language modelling with motif-aware pretraining and type-guided fine-tuning

Reference 81

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:56:20.244273Z

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Observation f70eb7a4-8475-49c3-a135-243bc62f7808 · outbound

This paper cites RNA secondary structure prediction using stochastic context-free grammars and evolutionary history.

Advances in RNA secondary structure prediction and RNA modifications: Methods, data, and applications RNA secondary structure prediction using stochastic context-free grammars and evolutionary history

Reference 82

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:56:20.232076Z

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Observation 5b268c27-a0bc-4d33-b525-bf7d0ad128c9 · outbound

This paper cites Pfold: RNA secondary structure prediction using stochastic context-free grammars.

Advances in RNA secondary structure prediction and RNA modifications: Methods, data, and applications Pfold: RNA secondary structure prediction using stochastic context-free grammars

Reference 83

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:56:20.221165Z

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Observation 0caff7cf-f645-4ddf-802d-9e3a58c8495e · outbound

This paper cites Evolutionary trees from DNA sequences: a maximum likelihood approach.

Advances in RNA secondary structure prediction and RNA modifications: Methods, data, and applications Evolutionary trees from DNA sequences: a maximum likelihood approach

Reference 84

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:56:20.209500Z

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Observation 78af2839-0c81-4d7b-afa2-83709e46f039 · outbound

This paper cites Syntax in universal translation.

Advances in RNA secondary structure prediction and RNA modifications: Methods, data, and applications Syntax in universal translation

Reference 85

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:56:20.196172Z

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Observation cb0c2794-82cd-4a35-9283-82cc2cf9030f · outbound

This paper cites Identity mappings in deep residual networks.

Advances in RNA secondary structure prediction and RNA modifications: Methods, data, and applications Identity mappings in deep residual networks

Reference 86

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:56:20.184837Z

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Observation 3112d38a-fc79-4cb5-9295-306df0b8fd41 · outbound

This paper cites Long Short-term Memory.

Advances in RNA secondary structure prediction and RNA modifications: Methods, data, and applications Long Short-term Memory

Reference 87

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:56:20.172030Z

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Observation 00b63268-e949-4018-b9e6-e87d54bb72e2 · outbound

This paper cites Bidirectional recurrent neural networks.

Advances in RNA secondary structure prediction and RNA modifications: Methods, data, and applications Bidirectional recurrent neural networks

Reference 88

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:56:20.160473Z

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Observation 342393bb-7354-4322-aad9-6280e4ef73f2 · outbound

This paper cites Multi-scale context aggregation by dilated convolutions.

Advances in RNA secondary structure prediction and RNA modifications: Methods, data, and applications Multi-scale context aggregation by dilated convolutions

Reference 89

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:56:20.147912Z

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Observation b46fb0ce-700c-449b-ac6a-7d84a6641d62 · outbound

This paper cites Accurate RNA 3D structure prediction using a language model-based deep learning approach.

Advances in RNA secondary structure prediction and RNA modifications: Methods, data, and applications Accurate RNA 3D structure prediction using a language model-based deep learning approach

Reference 90

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Observation f5080ca6-dc60-4fd9-98d0-ecefff0938ac · outbound

This paper cites U-net: Convolutional networks for biomedical image segmentation.

Advances in RNA secondary structure prediction and RNA modifications: Methods, data, and applications U-net: Convolutional networks for biomedical image segmentation

Reference 91

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:56:20.135539Z

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Observation f2e94261-e1fb-4b06-8e82-3a5f25e84c79 · outbound

This paper cites A New Method of RNA Secondary Structure Prediction Based on Convolutional Neural Network and Dynamic Programming.[J].

Advances in RNA secondary structure prediction and RNA modifications: Methods, data, and applications A New Method of RNA Secondary Structure Prediction Based on Convolutional Neural Network and Dynamic Programming.[J]

Reference 92

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:56:20.122647Z

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Observation 7d8c5684-5cff-4175-ac55-cccb1e4936af · outbound

This paper cites Deep residual learning for image recognition.

Advances in RNA secondary structure prediction and RNA modifications: Methods, data, and applications Deep residual learning for image recognition

Reference 93

Resolution: unresolved; no resolver link, observed 2026-08-10T21:56:19.263104Z

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This paper cites The one hundred layers tiramisu: Fully convolutional densenets for semantic segmentation.

Advances in RNA secondary structure prediction and RNA modifications: Methods, data, and applications The one hundred layers tiramisu: Fully convolutional densenets for semantic segmentation

Reference 94

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:56:20.103317Z

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Observation 1a6e1f8d-88d3-4619-bba6-9f43a491688c · outbound

This paper cites Prediction of RNA secondary structure using generalized centroid estimators.

Advances in RNA secondary structure prediction and RNA modifications: Methods, data, and applications Prediction of RNA secondary structure using generalized centroid estimators

Reference 95

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:56:20.091799Z

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No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 4f4e9790-1484-42b6-8dca-5567f35f653d · outbound

This paper cites Computational approaches for RNA energy parameter estimation.

Advances in RNA secondary structure prediction and RNA modifications: Methods, data, and applications Computational approaches for RNA energy parameter estimation

Reference 96

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:56:20.080426Z

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Observation 384ea90e-61d6-43e6-b196-0ee94e556f50 · outbound

This paper cites Interpretable prediction models for widespread m6A RNA modification across cell lines and tissues.

Advances in RNA secondary structure prediction and RNA modifications: Methods, data, and applications Interpretable prediction models for widespread m6A RNA modification across cell lines and tissues

Reference 97

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:56:20.069123Z

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Observation 5d44d835-660b-4c46-9279-91943d3b5c88 · outbound

This paper cites Interconnections between m6A RNA modification, RNA structure, and protein–RNA complex assembly.

Advances in RNA secondary structure prediction and RNA modifications: Methods, data, and applications Interconnections between m6A RNA modification, RNA structure, and protein–RNA complex assembly

Reference 98

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:56:20.058194Z

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Observation 601e7354-1a42-4154-8c07-c7261716b691 · outbound

This paper cites Machine learning applications in RNA modification sites prediction.

Advances in RNA secondary structure prediction and RNA modifications: Methods, data, and applications Machine learning applications in RNA modification sites prediction

Reference 99

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:56:20.046835Z

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Observation b1e3219d-86b7-4f7d-87ed-73c385155db0 · outbound

This paper cites RNAMethPre: a web server for the prediction and query of mRNA m6A sites.

Advances in RNA secondary structure prediction and RNA modifications: Methods, data, and applications RNAMethPre: a web server for the prediction and query of mRNA m6A sites

Reference 100

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:56:20.035782Z

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