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Machine learning for RNA secondary structure prediction: a review of current methods and challenges. [PDF]

RNA
Sacco G, Bussi G, Sanguinetti G.
europepmc   +1 more source

Zero-shot benchmarking of RNA language models in structural, functional, and evolutionary learning. [PDF]

Brief Bioinform
Wang H, Zhang Y, Chen J, Zhan J, Zhou Y.
europepmc   +1 more source

Improving the Reliability of Protein Folding Rate Predictions by Applying Guidelines for Validating QSAR/QSPR Models. [PDF]

Int J Mol Sci
Kraljević A, Batista J, Bojović V, Lučić B.   +3 more
europepmc   +1 more source

Trainable subnetworks reveal insights into structure knowledge organization in protein language models. [PDF]

PLoS Comput Biol
Vinod R, Amini AP, Crawford L, Yang KK.
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Integrated Computational Analysis Reveals Structurally Destabilizing Missense Variants in the <i>PDX1</i> Transcription Factor. [PDF]

Genes (Basel)
Ahmed EM.
europepmc   +1 more source

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Protein secondary structure prediction

Current Opinion in Structural Biology, 1995
The past year has seen a consolidation of protein secondary structure prediction methods. The advantages of prediction from an aligned family of proteins have been highlighted by several accurate predictions made 'blind', before any X-ray or NMR structure was known for the family.
S R, Krystek, W J, Metzler, J, Novotny
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Protein Secondary Structure Prediction with SPARROW

Journal of Chemical Information and Modeling, 2012
A first step toward predicting the structure of a protein is to determine its secondary structure. The secondary structure information is generally used as starting point to solve protein crystal structures. In the present study, a machine learning approach based on a complete set of two-class scoring functions was used.
Francesco, Bettella, Dawid, Rasinski, Ernst Walter, Knapp   +2 more
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Protein Secondary Structure Prediction

2009
While the prediction of a native protein structure from sequence continues to remain a challenging problem, over the past decades computational methods have become quite successful in exploiting the mechanisms behind secondary structure formation. The great effort expended in this area has resulted in the development of a vast number of secondary ...
Pirovano, W.A., Heringa, J.
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Parallelized protein secondary structure prediction

Proceedings of 2004 International Conference on Machine Learning and Cybernetics (IEEE Cat. No.04EX826), 2005
Functional characterization of a protein sequence is one of the most frequent problems in biology. Secondary structure prediction is a useful first step in understanding how the amino acid sequence of a protein determines the native state. There are many previous famous prediction methods available now, although most of them allow users to submit their
null Yu-Tao Qi, null Feng Lin
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